‘Love Machina’ Review: Artificial Intelligence Doc Fails to Ask the Interesting Questions – IndieWire

Bina48, the central figure of the documentary Love Machina, is among the most terrifying film characters of the year. A disembodied head resembling a middle-aged Black woman and powered by artificial intelligence, Bina48 combines a realistic face, dead emotionless eyes, jerky and mechanical head movements, and speech that resembles a voicemail chatbot more than a living being to create an uncanny valley nightmare. But to basically everyone on screen, Bina48 is a dream, a sign of a world where to quote the motto of her makers at the Terasem Movement Life is purposeful. Death is optional. God is technological. Love is essential.

Whether Love Machina agrees with its subjects views about Bina48, and the larger ongoing debates about the ethics of artificial intelligence, is a bit of a mystery even by the time its credits roll. In taking us into the story of the AI, director Peter Sillen opts for a fairly neutral approach that acknowledges some counterarguments and complications, enough that the film cant be called full-throttle AI propaganda. But the failure to take a strong stance either way makes for a boringly ambivalent film, one that fails to either enchant with promises of the future or terrify with warnings of whats to come.

As the title suggests, Love Machina fashions itself as a story of a marriage, though it doesnt dig particularly deeply into the relationship between its central characters. Bina48 is modeled after Bina Rothblatt, the wife of massively successful lawyer, satellite technology and biotechnology entrepreneur, and SiriusXM founder Martine Rothblatt. Married for over 40 years, Martine and Bina are almost oppressively in love (they even give themselves their own ship name, MarBina), and their pet project the Terasem Movement is intended as a gigantic tribute to their bond. Based on (the Rothblatts interpretations of) beloved sci-fi author Octavia Butlers works, the Terasem Movement seeks to find a way to upload peoples consciousness into artificial intelligence, to cheat death and live forever. Bina is essentially the guinea pig for the organizations efforts, her robot doppelganger powered by an algorithm based on her mind file, a virtual upload of the real womans personality and experiences based on a series of rigorous interviews.

The Terasem Movement and its goals raise a lot of obvious philosophical questions, but Love Machina doesnt try to ask them. The Rothblatts and the majority of the people interviewed in the film among them Terasem managing director Bruce Duncan, the Hanson Robotics engineers that developed Bina48, two of the couples children, and a gaggle of assorted artificial intelligence experts dont reveal any negative or contradictory feelings about the rise of AI or undercut the Rothblatts unwavering vision for the future in any way. Fascinating discussions about deaths role in human life, the nature of human consciousness, and the religious implications of living forever beg to be had about Terasems work, but the film doesnt want to start them.

The movie does tip its toes into the most uncomfortable element of the Bina48 story, the fact that a replica of a Black woman was created by a team of (seemingly) all-white people. Love Machina doesnt ignore it, including scenes where the team that created her discuss the difficulties that came from sculpting Black skin after previously making exclusively white male robots. The only person willing to probe deeper into the subject that we see in the film is Stephanie Dinkins, a professor and artist known for her series of videos in which she converses with Bina48. Dinkins, a Black woman who specializes in art exploring artificial intelligence, isnt necessarily anti-AI, but she reveals her discomfort with Bina48 as a representative of a Black woman, one whose code falls short of grasping the social context of her race. Its easily the most interesting discussion that the film has, but one that gets siloed off into a short section rather than meaningfully incorporated into the films discussions of AI at large.

Thats not the only angle of the film that goes unexamined. Frequently, Love Machina comes across as two films in one: a film about a marriage, and a film about the broader world of artificial intelligence. Rather than complement each other, both stories only flatten when paired together. The refusal to take a particularly strong approach to the question of artificial intelligence means theres very little interesting discussion about the topic to be had, and the film runs out of anything to say about Bina48 and its role in the advancement of AI very early on. In the final few minutes of the film, Sillen loses any semblance of focus and takes detours into the worlds of cryogenics and conversations with AI experts unrelated to Bina48, with little sense of how to meaningfully incorporate them into the broader film. All this is presented in a competent but thoroughly visual and editing style, that a few slightly creepy shots of Bina48 aside is content to just float from talking head to coverage without a real sense of style.

The Rothblatts story, presented via archival photos and video interviews done during the process of creating Binas mind file, is a potentially richer text that gets similarly diluted. For a film ostensibly about marriage, the recounting of their love story is painfully surface-level; you never actually know what draws the two into their passionate relationship. There are interesting threads about Martines gender transition and life as a prominent and powerful trans woman and the interracial nature of their family that the movie approaches timidly and fluffily, never adding dimension beyond the basic facts.

Late in the film, its revealed that part of the couples obsession with preventing death comes from the horrifying experience of witnessing one of their children go through a bout of childhood illness. Because the documentary doesnt tell us much about any of these people, the revelation doesnt particularly invite an emotional response. Like a lot of AI art, Love Machina is too fixated on technological advancement to leave any room for real, interesting human feelings.

Love Machina premiered at the 2024 Sundance Film Festival. It is currently seeking distribution.

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'Love Machina' Review: Artificial Intelligence Doc Fails to Ask the Interesting Questions - IndieWire

Making Money with AI: Unleashing the Potential of Artificial Intelligence – Medium

Artificial Intelligence (AI) is not just revolutionizing technology; its also opening up new avenues for making money. This article delves into the ways individuals can leverage AI to create income streams, offering insights and expert advice for those looking to capitalize on this rapidly evolving field.

Explore the diverse ways in which AI can be harnessed for generating income. From automation to data analysis, understand the broad spectrum of opportunities that AI presents for individuals seeking financial success.

Delve into specific niches within the AI landscape that offer lucrative income potential. Whether its AI-driven content creation, virtual assistance, or machine learning applications, discover where your skills and interests align.

Learn about the essential skills required to make money with AI. From programming languages to understanding algorithms, discover how individuals can prepare themselves for the evolving demands of the AI-driven job market.

Explore the world of freelancing in AI. Discover platforms and opportunities where individuals can offer their AI expertise to businesses and individuals in need of AI-driven solutions.

Uncover the potential of developing AI products. From AI-powered applications to specialized software, learn how to create and market products that leverage the capabilities of artificial intelligence.

Explore the role of AI in content creation. From automated writing tools to AI-generated visuals, discover how individuals can monetize their AI-enhanced content creation skills in various industries.

Understand the demand for AI solutions in the business world. Explore how individuals can create tailored AI solutions to address specific business needs, offering consulting or development services.

Delve into the world of AI competitions. Platforms like Kaggle offer opportunities for individuals to showcase their AI prowess and win cash prizes, providing a unique avenue for making money with AI skills.

Uncover the potential of creating educational content around AI. Whether through online courses, tutorials, or webinars, individuals can monetize their AI knowledge by sharing it with aspiring learners.

Q: Do I need a technical background to make money with AI? While a technical background is beneficial, there are opportunities for individuals with varying levels of expertise. Non-technical roles, such as AI consulting or content creation, also exist.

Q: Can I make money with AI without a formal education in the field? Yes, practical experience and skills often carry significant weight in the AI industry. Self-learning, certifications, and real-world projects can contribute to your success.

Q: Are there ethical considerations in AI income opportunities? Yes, ethical considerations are crucial in AI. Individuals should be mindful of the responsible use of AI and stay updated on ethical guidelines in the industry.

Q: How can I stay updated on the latest developments in AI? Engage with online communities, attend webinars, and follow reputable sources in the AI field. Continuous learning is key to staying informed and competitive.

Q: What are the potential risks of monetizing AI knowledge? Potential risks include ethical concerns, ensuring the security of AI solutions, and staying compliant with relevant regulations. Understanding and mitigating these risks is essential for success.

Q: Can I make money with AI as a side hustle? Yes, many AI opportunities can be pursued as a side hustle. Freelancing, content creation, and participating in competitions are examples of flexible AI income avenues.

Embark on the exciting journey of making money with AI, leveraging its transformative capabilities to create income streams. With strategic insights and a commitment to continuous learning, individuals can position themselves for success in the dynamic and lucrative world of AI-driven income.

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Making Money with AI: Unleashing the Potential of Artificial Intelligence - Medium

TV channels are using AI-generated presenters to read the news. The question is, will we trust them? – BBC.com

By Chris Stokel-WalkerFeatures correspondent

A start-up is developing a news service presented by anchors created by artificial intelligence. Will it upend decades of parasocial relationships between television audiences and the people they watch on screen?

The footage wouldn't look out of place on many of the world's news channels.

For 22 minutes, a variety of polished news anchors stand in front of the camera and run down the day's news in a video posted on social media . But none of them are real. Instead, the anchors are generated by artificial intelligence (AI).

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The video is produced by Los Angeles-based Channel 1, a start-up created by entrepreneurs Adam Mosam and Scott Zabielski, who plan to roll out AI-generated news on a streaming TV channel later this year. "There seemed to be a very interesting opportunity to level up the user experience of news," says Mosam, by using AI to tailor content to individuals.

AI technology can also help translate scripts and interviews from one language to another capabilities that Channel 1 demonstrated in a promotional video, which was shared in December.

Channel 1 is the latest demonstration of AI-powered news presenters around the world. In Kuwait, an AI persona by the name of Fedha ran through the headlines for Kuwait News. Hermes presented the news in May 2023 for Greek state broadcaster ERT. South Korean broadcaster SBShanded over the duties of news presenting to Zae-In, an AI-generated deepfake, for five months this year. There are others in India and Taiwan, too all created by AI.

But there's one key question still to be answered: will viewers trust news delivered by AI, rather than humans?

Trust in the humans presenting the news has dropped to an all-time low, according to a survey by public opinion polling firm Ipsos. Just 42% of people in the UK trust TV newsreaders, down 16 percentage points in a year. The scepticism around news presenters as independent arbiters of truth is an unusual modern phenomenon, with many choosing to get their news instead from individual creators or influencers.

Those social media stars leverage a connection with their audience called parasocial influence. First coined in the 1950s by academics at the University of Chicago, parasocial relationships were defined as the belief that viewers of nightly news programmes of the time had that the anchor behind the desk was talking through the camera directly to them. News presenters became more than just journalists telling you the news; they were friends, welcomed into your living rooms night after night.

Social media influencers have co-opted that same direct to camera format and perceived personal connection to great success. "It's interesting how the 'parasocial' label has evolved from describing the affinity that individuals might feel with remote newscasters to something way broader," says Christine H Tran, who studies digital platforms and labour at the University of Toronto. "You can be in a parasocial relationship with a reporter or news Twitch streamer," she says, referring to the livestreaming video service. "But you can also apparently be in a parasocial relationship with a YouTuber, a singer, and an Instagram power couple."

But whether AI can replicate the personal connection is less certain. "You'll never have the same connection with an AI that you do with another human being," admits Mosam. However, he argues that people are no longer looking for impartiality. "We're not doing this because we think a robot does a better job than a human that's ridiculous."

The idea of journalists not reading the news isn't all that unusual, even if the idea that they're computer-generated is. "When I started in journalism, you had actors reading the news," says Nic Newman, senior research associate at the Reuters Institute for the Study of Journalism at the University of Oxford, and a former editor at the BBC. "People were kind of fine with that."

The fact that journalists haven't always read the news means that this trial could well succeed with limitations, reckons Newman. It'll only be useful for short news bulletins, but he's less certain that viewers will embrace a parasocial relationship with an AI anchor. "For delivering news programmes, I think the humanity is going to remain really important," he says.

It's an unknown that Tran is also uncertain about. "Will AI personalities inspire the same parasociality if their broadcasts are accurately labelled as 'AI content' and the viewers know there's no personal life outside the screen?" they ask. "That depends on if the platforms hosting AI presenters will be expected to label their content as AI like some platforms such as Instagram have considered moving towards."

Channel 1 and NewsGPT , which claims to be the world's first news channel generated entirely by AI, may have another question to answer: is it possible to totally remove the human from the loop?

At present, Channel 1 has nearly a dozen staff members working on checking AI-generated scripts and selecting stories that ought to be covered. Mosan says there's a 13-step process that Channel 1 goes through for every story before it is aired to ensure some of the issues around generative AI don't make it onto air. These include hallucination, where AI tools make up content, which is obviously a no-no in journalism. The company behind it is looking to hire an editor-in-chief early next year.

Being able to actually find newsworthy events and report on them is another element that AI may struggle with, agree Mosan and Newman. The Channel 1 test episode relied heavily on stories unearthed and footage filmed by human journalists. "Without those sources, if they get cut off, I don't really see how they can do it," says Newman. "If that raw material is not there, then the AI has absolutely nothing to work on."

Mosan believes that there are some elements of the reporting process that can be carried out by AI, but others that can't. "You'll never be able to gather intelligence person-to-person, and interview person-to-person, effectively," he says. "But I could fly a drone and analyse what I'm looking at." Newsgathering solely by AI, without humans in the loop, isn't in Channel 1's current set of plans.

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TV channels are using AI-generated presenters to read the news. The question is, will we trust them? - BBC.com

The 3 Most Promising Artificial Intelligence Stocks in 2024, According to Grok AI – InvestorPlace

AI stock picks, courtesy of an AI trained to keep an eye on current trends.

Source: shutterstock.com/Victor Runov

With the steady rise of artificial intelligence, we asked Grok AI for its thoughts on the future of the market. Grok AI, or just Grok, provides a new take on the original ChatGPT format of large language modeling. We then asked it to help identify the top artificial intelligence stocks.

Founded by Elon Musk in March of 2023, xAI aims to integrate the Grok chatbot with X, formerly Twitter. Groks take on AI chatting features more wit and humor than the competition while claiming to seek only truth. With these defining features, Grok provides more up-to-date and pertinent information with the ability to evaluate current events.

This might make it the best AI to ask about the stock market. Through its ability to search the web for news and data, Groks conclusions differ from the standard chatbot. So, how do its stock picks measure up? These three AI stock picks by Grok AI provide some details to consider when using AI to research stocks.

Source: Below the Sky / Shutterstock.com

Nvidia (NASDAQ:NVDA) makes the computers responsible for training AI, so no wonder Grok considers them a good pick. While other AI companies specialize in optimizing software for training their chatbots, Nvidia controls the whole process.

By designing the most efficient graphics processing units (GPUs) on the market, Nvidia maximizes the amount of math its machines perform. Through using GPUs, Nvidias AI training software completes thousands of calculations per second in parallel. This results in blazing-fast speeds for training the chatbot to interpret data and respond with information.

With this unique advantage, Nvidia rapidly transforms its AI applications to respond to industry trends. Groks developers even use Nvidia GPUs to train the bot, which speaks volumes about the critical role of the technology. A lack of serious competition in the GPU space and stellar performance have made Nvidia a strong buy option. It also helps that its one of the AI stock picks by Grok AI.

Source: The Art of Pics / Shutterstock.com

Another solid pick by Grok, Microsofts (NASDAQ:MSFT) position in the AI race comes from its ubiquitous software. Almost every tech user in the world interacts with a Microsoft application in some form or another.

Furthermore, Microsoft now integrates AI in nearly every live service they develop. When a company researching AI has access to this level of data, it results in rapid product development. Add on the fact that Microsofts value continues increasing and this stock continues to be a strong buy. Microsofts investments in OpenAI and ChatGPT also put the company in a diversified position when it comes to research.

Its focus on pioneering new chatbot technologies makes it a direct competitor to Musks Grok project. This makes Grok seem even more trustworthy, as it openly recommends the stock of one of its competing models. Though Microsofts Copilot AI may not be the stuff of headlines yet, its projects show promise.

Source: Tada Images / Shutterstock.com

The last, but certainly not least of AI stock picks by Grok AI is Amazon (NASDAQ:AMZN). While investors focus on Amazons endless retail selection and shipping speeds, the company has an AI ace up its sleeve. By leveraging its Amazon Web Services suites, Amazon possesses endless business data to train AI for practical applications.

Since machine learning serves as the focus of Amazons AI projects, the company currently enables corporations to become more efficient. This unique approach to AI services and Amazons high potential stock make for a strong buy position. With this third pick, Groks preferences for stocks reflect an AI that focuses on strong historical performance and ideal positions.

These types of stocks serve as a benchmark for their industry and tend towards stability. Interestingly enough, an AI programmed to tap into current events and seek truth seems genuinely risk averse. If you are looking for high-value artificial intelligence stocks, start here.

On the date of publication, Viktor Zarevdid not have (either directly or indirectly) any positions in the securities mentioned in this article.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

Viktor Zarev is a scientist, researcher, and writer specializing in explaining the complex world of technology stocks through dedication to accuracy and understanding.

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The 3 Most Promising Artificial Intelligence Stocks in 2024, According to Grok AI - InvestorPlace

Misinformation And Irresponsible AI: Experts Forecast How Technology May Shape Our Near Future – Eurasia Review

From misinformation and invisible cyber attacks, to irresponsible AI that could cause events involving multiple deaths, expert futurists have forecast how rapid technology changes may shape our world by 2040.

As the pace of computer technology advances surges ahead, and systems become increasingly interlinked, it is vital to know how these fast technology advances could impact the world in order to take steps to prevent the worst outcomes.

Using a Delphi study, a well known technique for forecasting, a team of cyber security researchers led by academics from Lancaster University interviewed 12 experts in the future of technologies.

The experts, ranged from chief technology officers in businesses, consultant futurists and a technology journalist to academic researchers. They were asked how particular technologies may develop and change our world over the next 15 years by 2040, what risks they might pose, and how to address the challenges that may arise.

Most of the experts forecasted exponential growth in Artificial Intelligence (AI) over the next 15 years, and many also expressed concern that corners could be cut in the development of safe AI. They felt that this corner cutting could be driven by nation states seeking competitive advantage. Several of the experts even considered it possible that poorly implemented AI could lead to incidents involving many deaths, although other experts disagreed with this view.

Dr Charles Weir, Lecturer at Lancaster Universitys School of Computing and Communications and lead researcher of the study, said: Technology advances have brought, and will continue to bring, great benefits. We also know there are risks around some of these technologies, including AI, and where their development may goeveryones been discussing thembut the possible magnitude of some of the risks forecast by some of the experts was staggering.

But by forecasting what potential risks lie just beyond the horizon we can take steps to avoid major problems.

Another significant concern held by most of the experts involved in the study was that technology advances will make it easier for misinformation to spread. This has the potential to make it harder for people to tell the difference between truth and fiction with ramifications for democracies.

Dr Weir said: We are already seeing misinformation on social media networks, and used by some nation states. The experts are forecasting that advances in technologies will make it much easier for people and bad actors to continue spreading misleading material by 2040.

Other technologies were forecast to not have as big as impact by 2040, including quantum computing which experts see as having impacts over a much longer timeframe, and Blockchain which was dismissed by most of the experts as being a source of major change.

The experts forecast that:

By 2040, competition between nation states and big tech companies will lead to corners being cut in the development of safe AI

Quantum computing will have limited impact by 2040

By 2040 there will be ownership of public web assets. These will be identified and traded through digital tokens

By 2040 it will be harder to distinguish truth from fiction because widely accessible AI can massively generate doubtful content

By 2040 there will be less ability to distinguish accidents from criminal incidents due to the decentralised nature and complexity of systems

The forecasters also offered some suggested solutions to help mitigate against some of the concerns raised. Their suggestions included governments introducing AI purchasing safety principles, new laws to regulate AI safety. In addition, universities could be vital by introducing courses combining technical skills and legislation.

These forecasts will help policy makers and technology professionals make strategic decisions around developing and deploying novel computing technologies. They are outlined in the paper Interlinked Computing in 2040: Safety, Truth, Ownership and Accountability which has been published by the peer-reviewed journalIEEE Computer.

The papers authors are: Charles Weir and Anna Dyson of Lancaster University; Olamide Jogunola and Katie Paxton-Fear of Manchester Metropolitan University; and Louise Dennis of Manchester University.

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Misinformation And Irresponsible AI: Experts Forecast How Technology May Shape Our Near Future - Eurasia Review

3 Magnificent Artificial Intelligence (AI) Semiconductor Stocks to Buy in 2024 – The Motley Fool

In this video, I will talk about three AI semiconductor companies that will greatly benefit from the AI revolution. These companies aren't talked about as much as Nvidia, AMD, or Intel, but they play an increasingly important role in the industry.

*Stock prices used were from the trading day of Jan. 22, 2024. The video was published on Jan. 23, 2024.

Neil Rozenbaum has positions in Intel. The Motley Fool has positions in and recommends Advanced Micro Devices, Nvidia, and Qualcomm. The Motley Fool recommends Intel and Super Micro Computer and recommends the following options: long January 2023 $57.50 calls on Intel, long January 2025 $45 calls on Intel, and short February 2024 $47 calls on Intel. The Motley Fool has a disclosure policy. Neil is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through his link, he will earn some extra money that supports his channel. His opinions remain his own and are unaffected by The Motley Fool.

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3 Magnificent Artificial Intelligence (AI) Semiconductor Stocks to Buy in 2024 - The Motley Fool

HDR uses artificial intelligence tools to help design a vital health … – Building Design + Construction

Paul Howard Harrison has had a longstanding fascination with machine learning and performance optimization. Over the past five years, artificial intelligence (AI) has been augmenting some of the design work done by HDR, where Harrison is a computational design lead. He also lectures on AI and machine learning at the University of Toronto in Canada, where he earned his Masters of Architecture.

Harrisons interest in computational research and data-driven design contributed to the development of an 8,500-sf healthcare clinic and courtyard at Baruipur, in West Bengal, India. This was Harrisons first project with Design 4 Others (D4O), a philanthropic initiative that operates out of HDRs architecture practice through which architects volunteer their services to make positive impacts on underserved communities.

India has fewer than one doctor per 1,000 people. (By comparison, the ratio in the U.S. is more than 2.5 per 1,000.) The client for the Baruipur clinic is iKure, a technology and social enterprise that delivers healthcare through a hub-and-spoke model, where clinics (hubs) extend their reach to where patients live through local healthcare workers (the spokes), who are trained to monitor, track, and collect data from patients. The hubs and spokes are connected by a proprietary platform called the Wireless Health Incident Monitoring System. According to iKures website, there are 20 hubs of varying sizes serving nine million people in 10 Indian states. iKures goal is to eventually operate 125 hubs and expand its concept to 10 Asian and African countries.

D4O and iKure became aware of each other in 2019 through Construction for Change, a Seattle-based nonprofit construction management firm. Prior to the Baruipur hub project, D4O and Construction for Change had worked on more than a dozen projects together, starting with a healthcare clinic in northwest Uganda, according to the August 11, 2020, episode of HDRs podcast Speaking of Design.

Harrisonwhom BD+C interviewed with Megan Gallagher, a health planner at HDR and a D4O volunteer on the Baruipur projectacknowledges that all design outputs come with inherent biases. But by training AI on smaller models, the datasets and biases can be controlled, he posits.

Initially, HDR found AI useful for design optimization; more recently, the firm has been using AI for early-stage ideation. Harrison points specifically to the design for a hospital in Kingston, Ontario, where HDR used AI as an ideation tool. AI is better at coming up with what I like than I am, he laughs.

The firm has also used AI as a means of engagement to get different client constituencies on the same page about a projects mission.

During the interview, Harrison several times referred to DALL-E, an open AI system used to create realistic images. DALL-E favors a diffusion model, a random-field approach to produce generative models that are similar to data on which the AI has been trained.

Where most project designs start with a facilitys programming, the iKure clinic was different in that it needed to support the hub-and-spoke delivery method. The client also wanted a design that could add a second floor, as needed.

To help design the iKure hub, Harrison wrote a machine-learning program that focused on the buildings gross floor area, the amount of shade the building would provide (as some patients need relief after traveling long distances to receive care), and the size of the buildings modules. (Gallagher notes that each room is 125 sf.)

By optimizing for shade, the algorithm consistently came up with a courtyard design. The end result looked similar to a courtyard house in Kolkata, observes Gallagher. The computer program also came up with the best positioning for circulation aisles within a building that would not be air conditioned.

Treatment rooms were moved to the back of the building, which has four strategically located shading areas. Air is circulated up and out of the building through chimneys whose design takes its cue from local brick kilns.

The last piece of the hubs design will be its screening for security and ventilation. Harrison says that HDR has been training AI on a dataset of different screen designs that could be made from brick. (This area of India is known for its brickmaking, he explains.)

Gallagher says shes curious to see how AI will progress as a design tool. Harrison concedes that while AI is quicker for ideation, it will take some time to perfect the tool for larger projects.

As for the iKure hub, Harrison observed in HDRs 2020 podcast that you dont need to have a high-architecture project to have a high-tech approach.

When its completed, the Baruipur clinic will offer eye and dental care, X-rays, maternal and pediatric care, and telemedicine. The hub will serve about a half-dozen spokes as well as multiple villages that include remote islands in the Sundarbans Delta, where diagnostics will be accessible through portable handheld devices, says Jason-Emery Gron, Vice President and Design Director for HDRs Kingston office.

Gron says that HDR focuses on projects that are most likely to have a significant impact on their communities, and have the best chance of getting built. And D4O has been in discussions with iKure about helping with its expansion plans.

But hes also realistic about the unpredictability of project delays in underdeveloped markets. The iKure hub was scheduled for completion in 2021, but might not be ready until 2024. Gron explains the construction has taken longer than anticipated because the client wanted D4O to review land options before it settled on the original site, the pandemics impact on labor and materials availability, and longer-than expected monsoon seasons.

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HDR uses artificial intelligence tools to help design a vital health ... - Building Design + Construction

Artificial Intelligence Is Here to Stay, so We Should Think more about … – GW Today

On Friday morning, George Washington University Provost Christopher Alan Bracey disseminated a document on the use of generative artificial intelligence to guide faculty members on how they might (or might not) allow the use of AI by their students. At the same moment, a daylong symposium titled I Am Not a Robot: The Entangled Futures of AI and the Humanities kicked off with remarks by its principal organizer, Katrin Schultheiss, associate professor of history in the Columbian College of Arts and Sciences.

In late 2022, said Schultheiss, the launch of ChatGPT presented educators with a significant moment of technological change.

Here was a toolavailable, at least temporarily, for free, Schultheiss said, that would answer almost any question in grammatically correct, informative, plausible-sounding paragraphs of text.

In response, people expressed the fear that jobs would be eliminated, the ability to write would atrophy and misinformation would flourish, with some invoking dystopias where humans became so dependent on machines that they can no longer think or do anything for themselves.

But that wasnt even the worst of the fears expressed. At the very far end, Schultheiss said, they conjured up a future when AI-equipped robots would break free of their human trainers and take over the world.

On the other hand, she noted, proponents of the new technology argued that ChatGPT will lead to more creative teaching and increase productivity.

The pace at which new AI tools are being developed is astonishing, Schultheiss said. Its nearly impossible to keep up with the new capabilities and the new concerns that they raise.

For that reason, she added, some observers (including members of Congress) are advocating for a slowdown or even a pause in the deployment of these tools until various ethical and regulatory issues can be addressed.

With this in mind, she said, a group of GW faculty from various humanities departments saw a need to expand the discourse beyond the discussion of new tools and applications, beyond questions of regulation and potential abuses of A.I., adding that the symposium is one of the fruits of those discussions.

Maybe we should spend some more time thinking about exactly what we are doing as we stride forward boldly into the AI-infused future, Schultheiss said.

Four panel discussions followed, the first one featuring philosophers. Tadeusz Zawidzki, associate professor and chair of philosophy, located ChatGPT in the larger philosophical tradition, beginning with the Turing test.

That test was proposed by English scientist Alan Turing, who asked: Could a normal human subject tell the difference between another human and a computer by reading the text of their conversation? If not, Turing said, that machine counts as intelligent.

Some philosophers, such as John Searle, objected, saying a digitally simulated mind does not really think or understand. But Zawidzki said ChatGPT passes the test.

Theres no doubt in my mind that ChatGPT passes the Turing test, he said. So, by Turings criteria, it is a mind. But its not like a human mind, which can interact with the world around it in ways currently unavailable to ChatGPT.

Marianna B. Ganapini, assistant professor at Union College and a visiting scholar at the Center for Bioethics at New York University, began by asking if we can learn from ChatGPT and if we can trust it.

As a spoiler alert, Ganapini said, Im going to answer no to the second questionits the easy questionand maybe to the first.

Ganapini said the question of whether ChatGPT can be trusted is unfair, in a sense, because no one trusts people to know absolutely everything.

A panel on the moral status of AI featured Robert M. Geraci, professor of religious studies at Manhattan College, and Eyal Aviv, assistant professor of religion atGW.

In thinking about the future of AI and of humanity, Geraci said, we must evaluate whether the new technology has been brought into alignment with human values and the degree to which it reflects our biases.

A fair number of scholars and advocates fear that our progress in value alignment is too slow, Geraci said. They worry that we will build powerful machines that lack our values and are a danger to humanity as a result. I worry that in fact our value alignment is near perfect.

Unfortunately, he said, our daily values are not in fact aligned with our aspirations for a better world. One way to counteract this is through storytelling, he added, creating models for reflection on ourselves and the future.

A story told by the late Stephen Hawking set the stage for remarks by Aviv, an expert on Buddhism, who recalled an interview with Hawking from Last Week Tonight with John Oliver posted to YouTube in 2014.

Theres a story that scientists built an intelligent computer, Hawking said. The first question they asked it was, Is there a God? The computer replied, There is now, and a bolt of lightning struck the plug so it couldnt be turned off.

Aviv presented the equally grim vision of Jaron Lanier, considered by many to be father of virtual reality, who said the danger isnt that AI will destroy us, but that it will drive us insane.

For most of us, Aviv said, its pretty clear that AI will produce unforeseen consequences.

One of the most important concepts in Buddhist ethics, Aviv said, is ahimsa, or doing no harm. From its inception, he added, AI has been funded primarily by the military, placing it on complex moral terrain from the start.

Many experts call for regulation to keep AI safer, Aviv said, but will we heed such calls? He pointed to signs posted in casinos that urge guests to play responsibly. But such venues are designed precisely to keep guests from doing so.

The third panel featured Neda Atanasoski of the University of Maryland, College Park, and Despina Kakoudaki of American University.

Atanasoski spoke about basic technologies found in the home, assisting us with cleaning, shopping, eldercare and childcare. Such technologies become creepy, she said, when they reduce users to data points and invade their privacy.

Tech companies have increasingly begun to market privacy as a commodity that can be bought, she said.

How do you ban it if its everywhere?

Pop culture has had an impact on how we understand new technology, Kakoudaki said, noting that very young children can draw a robot, typically in an anthropomorphic form.

After suggesting the historical roots of the idea of the mechanical body, in the creation of Pandora and, later, Frankenstein, for example, Kakoudaki showed how such narratives reverse the elements of natural birth, with mechanical beings born as adults and undergoing a trajectory from death to birth.

The fourth panel, delving further into the history of AI and meditating on its future, featured Jamie Cohen-Cole, associate professor of American Studies, and Ryan Watkins, professor and director of the Educational Technology Leadership Program in the Graduate School of Education and Human Development.

Will we come to rely on statements from ChatGPT? Maybe, Cohen-Cole said, though he noted that human biases will likely continue to be built into the technology.

Watkins said he thinks we will learn to live with the duality presented by AI, enjoying its convenience while remaining aware of its fundamental untrustworthiness. It is difficult for most people to adjust in real time to rapid technological change, he said, encouraging listeners to play with the technology and see how they might use it, adding that he has used it to help one of his children do biology homework. Chatbot technology is being integrated into MS Word, email platforms and smartphones, to name a few places the average person will soon encounter it.

How do you ban it if its everywhere? he asked.

The symposium, part of the CCAS Engaged Liberal Arts Series, was sponsored by the CCAS Departments of American Studies, English, History, Philosophy, Religion and Department of Romance, German and Slavic Languages and Literatures. Each session concluded with questions for panelists from the audience. The sessions were moderated, respectively, by Eric Saidel, from the philosophy department; Irene Oh, from the religion department; Alexa Alice Joubin, from the English Department; and Eric Arnesen, from the history department.

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Artificial Intelligence Is Here to Stay, so We Should Think more about ... - GW Today

For the First-Time Ever, Miller Lite Teaches Artificial Intelligence What Beer Tastes Like – Food Industry Executive

Miller Lite kicks off new global campaign by showing Sophia the robot the feeling behind real-life beer moments

CHICAGO April 19, 2023 Artificial intelligence has had a busy year answering our questions, generating headshots, and even making aging actors look younger, but despite all of these advances in technology, theres one thing AI still cant do enjoy the great taste of beer. But thats all about to change thanks to Miller Liteseriously. For the first time ever, the brand is teaching AI the taste, feeling and human emotion behind enjoying a beer, starting with Sophia, an advanced humanoid robot from Hanson Robotics.

Miller Lite and AIreally? Yes, and for good reason too. Miller Lite is all about great beer taste and celebrating Miller Time so in its new global campaign, Tastes like Miller Time, the brand is demonstrating that the taste of beer is so much more than what we literally taste. And Miller Lite is making sure everyone, including AI, knows what the experience of cracking open a great beer like Miller Lite truly feels like.

The taste of beer is so much more than barley, malt, and hops its the real moments at neighborhood bars, tailgates and backyards spent over a Miller Lite, says Sofia Colucci, Chief Marketing Officer at Molson Coors Beverage Company (not to be confused with Sophia the robot). Our new campaign pays tribute to those unforgettable experiences that just taste better with a Miller Lite in hand. Were bringing this notion to life in fresh and unexpected ways from our new TV spots to even teaching AI what beer actually tastes like.

Miller Lite worked with Hanson Robotics to analyze social media and identify humanitys most cherished beer drinking moments, translating them to something Sophia could finally experience. Watch here to learn more:https://youtu.be/5OkB6s9hsPc.

When Miller Lite approached us about teaching Sophia what beer tasted like, we were intrigued because it was something AI has never experienced before, says Kath Yeung, Chief Operations Coordinator of Hanson Robotics.

Our teams scrolled social media and assessed our findings to gather the feelings and emotions humans get when tasting beer and translated that data into something Sophia could experience for the first time, says CEO David Hanson PhD. We were excited to see Sophia was making new friends, learning and analyzing the human experience.

So, what did Sophia think of her first beer? To see her reaction and have the chance to ask Sophia questions in real time, tune-in to the Miller Lite Instagram Live on Friday, April 21st at 5pm CDT.

To further AIs education on the true joy and experience of beer, Miller Lite is asking everyone to share the moments that taste better with beer. Follow @MillerLite on Instagram, share a photo of your Tastes Like Miller Time Moment in an Instagram story or post, and tag @MillerLite. Then use the hashtag #BeerforAI and #Sweepstakes for a chance to win free beer.* These moments will be added to the data set so Miller Lite can continue to teach AI what the human experience of beer is.

The new Tastes like Miller Time campaign will appear across all touchpoints in the United States, Canada, and Latin America. It includes retail, out of home, advertising, social media, partnerships, localization, and brand new video spots, which you can viewhere.

Miller Lites new campaign aims to fuel continued growth and positive trajectory for the brand. Year to date in the U.S., Miller Lite is growing dollar share of total beer dollar according to April 2023 Circana multi-source and convenience data.

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For the First-Time Ever, Miller Lite Teaches Artificial Intelligence What Beer Tastes Like - Food Industry Executive

Artificial intelligence helps people be productive in these ways – CBS News

Artificial intelligence is becoming increasingly commonin the workplace, but it's also starting to assist with tasks at home.

Insider tech reporter Lakshmi Varanasi told CBS News she uses OpenAI's GPT4 technology to help her plan and prep meals, while parents are using it to generate bedtime stories to read to their children. Really committed parents can even use it to create their own books with corresponding images, also using AI tools, like image generator DALL-E.

In this way, AI can be tremendously helpful in sating kids' appetites for constant entertainment, Varanasi added.

click to expand

Something to beware of when reading AI-generated text to children: AI tools like ChatGPT are known to occasionally make errors or inappropriate statements. "There needs to be fact-checking involved whenever you use an AI tool," Varanasi said.

To be sure, AI doesn't have the same level of judgment and insight that humans do, and may not be able to respond helpfully to personal questions.

"It's really good for the broad strokes of navigating life." Varanasi said.

Other useful applications of sophisticated AI include asking it for help generating emails, or general inspiration for creating any type of content. Travel company Expedia is even betting that it will be helpful for people planning trips.

Computer programmers and coders have found AI useful as well. One worker used GPT4 as a coding assistant while building a video game.

"He'd type in command he wanted, the tool gave him code," Varanasi said. When a digital spaceship that was part of the game wouldn't move, AI stepped in and "helped get it moving."

A coder might have ordinarily spent hours on trial and error, but AI sped up the process.

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Artificial intelligence helps people be productive in these ways - CBS News

Global Artificial Intelligence (AI) Platform Market to Reach $120.7 Billion by 2030 – Yahoo Finance

ReportLinker

The global economy is at a critical crossroads with a number of interlocking challenges and crises running in parallel. The uncertainty around how Russia`s war on Ukraine will play out this year and the war`s role in creating global instability means that the trouble on the inflation front is not over yet.

New York, April 19, 2023 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence (AI) Platform Industry" - https://www.reportlinker.com/p06030752/?utm_source=GNW Food and fuel inflation will remain a persistent economic problem. Higher retail inflation will impact consumer confidence and spending. As governments combat inflation by raising interest rates, new job creation will slowdown and impact economic activity and growth. Lower capital expenditure is in the offing as companies go slow on investments, held back by inflation worries and weaker demand. With slower growth and high inflation, developed markets seem primed to enter into a recession. Fears of new COVID outbreaks and Chinas already uncertain post-pandemic path poses a real risk of the world experiencing more acute supply chain pain and manufacturing disruptions this year. Volatile financial markets, growing trade tensions, stricter regulatory environment and pressure to mainstream climate change into economic decisions will compound the complexity of challenges faced. Year 2023 is expected to be tough year for most markets, investors and consumers. Nevertheless, there is always opportunity for businesses and their leaders who can chart a path forward with resilience and adaptability.

Global Artificial Intelligence (AI) Platform Market to Reach $120.7 Billion by 2030

In the changed post COVID-19 business landscape, the global market for Artificial Intelligence (AI) Platform estimated at US$17.8 Billion in the year 2022, is projected to reach a revised size of US$120.7 Billion by 2030, growing at aCAGR of 27.1% over the period 2022-2030. Cloud, one of the segments analyzed in the report, is projected to record 28.8% CAGR and reach US$84 Billion by the end of the analysis period. Taking into account the ongoing post pandemic recovery, growth in the On-Premise segment is readjusted to a revised 23.8% CAGR for the next 8-year period.

The U.S. Market is Estimated at $5.3 Billion, While China is Forecast to Grow at 25.8% CAGR

The Artificial Intelligence (AI) Platform market in the U.S. is estimated at US$5.3 Billion in the year 2022. China, the world`s second largest economy, is forecast to reach a projected market size of US$20 Billion by the year 2030 trailing a CAGR of 25.8% over the analysis period 2022 to 2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 23.3% and 21.9% respectively over the 2022-2030 period. Within Europe, Germany is forecast to grow at approximately 16.8% CAGR.

Select Competitors (Total 240 Featured)- Absolutdata- Amazon Web Services- Apple inc.- Ayasdi- Enlitic, inc.- Facebook inc.- General Electric- General vision, inc.- Google LLC- Hewlett Packard Enterprise Development LP- IBM Corporation- icarbonX- Infosys- Intel Corporation- Micro Technology inc.- Microsoft Corporation- Next It Corporation- Qualcomm Technologies- Salesforce.com, inc.- SAMSUNG- SAP- Siemens AG- Wipro

Read the full report: https://www.reportlinker.com/p06030752/?utm_source=GNW

I. METHODOLOGY

II. EXECUTIVE SUMMARY

1. MARKET OVERVIEWInfluencer Market InsightsWorld Market TrajectoriesImpact of Covid-19 and a Looming Global RecessionArtificial Intelligence (AI) Platform - Global Key CompetitorsPercentage Market Share in 2022 (E)Competitive Market Presence - Strong/Active/Niche/Trivial forPlayers Worldwide in 2022 (E)

2. FOCUS ON SELECT PLAYERS

3. MARKET TRENDS & DRIVERS

4. GLOBAL MARKET PERSPECTIVETable 1: World Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Geographic Region -USA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld Markets - Independent Analysis of Annual Sales in US$Million for Years 2022 through 2030 and % CAGR

Table 2: World 8-Year Perspective for Artificial Intelligence(AI) Platform by Geographic Region - Percentage Breakdown ofValue Sales for USA, Canada, Japan, China, Europe, Asia-Pacificand Rest of World Markets for Years 2023 & 2030

Table 3: World Recent Past, Current & Future Analysis for Cloudby Geographic Region - USA, Canada, Japan, China, Europe,Asia-Pacific and Rest of World Markets - Independent Analysisof Annual Sales in US$ Million for Years 2022 through 2030 and% CAGR

Table 4: World 8-Year Perspective for Cloud by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 5: World Recent Past, Current & Future Analysis forOn-Premise by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 6: World 8-Year Perspective for On-Premise by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 7: World Recent Past, Current & Future Analysis forHealthcare by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 8: World 8-Year Perspective for Healthcare by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 9: World Recent Past, Current & Future Analysis forResearch & Academia by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 10: World 8-Year Perspective for Research & Academia byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 11: World Recent Past, Current & Future Analysis forTransportation by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 12: World 8-Year Perspective for Transportation byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 13: World Recent Past, Current & Future Analysis forRetail & eCommerce by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 14: World 8-Year Perspective for Retail & eCommerce byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 15: World Recent Past, Current & Future Analysis forOther End-Uses by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 16: World 8-Year Perspective for Other End-Uses byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 17: World Recent Past, Current & Future Analysis for BFSIby Geographic Region - USA, Canada, Japan, China, Europe,Asia-Pacific and Rest of World Markets - Independent Analysisof Annual Sales in US$ Million for Years 2022 through 2030 and% CAGR

Table 18: World 8-Year Perspective for BFSI by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 19: World Recent Past, Current & Future Analysis forManufacturing by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 20: World 8-Year Perspective for Manufacturing byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 21: World Recent Past, Current & Future Analysis forForecasts & Prescriptive Models by Geographic Region - USA,Canada, Japan, China, Europe, Asia-Pacific and Rest of WorldMarkets - Independent Analysis of Annual Sales in US$ Millionfor Years 2022 through 2030 and % CAGR

Table 22: World 8-Year Perspective for Forecasts & PrescriptiveModels by Geographic Region - Percentage Breakdown of ValueSales for USA, Canada, Japan, China, Europe, Asia-Pacific andRest of World for Years 2023 & 2030

Table 23: World Recent Past, Current & Future Analysis forChatbots by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 24: World 8-Year Perspective for Chatbots by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 25: World Recent Past, Current & Future Analysis forSpeech Recognition by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 26: World 8-Year Perspective for Speech Recognition byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 27: World Recent Past, Current & Future Analysis for TextRecognition by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 28: World 8-Year Perspective for Text Recognition byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 29: World Recent Past, Current & Future Analysis forOther Applications by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 30: World 8-Year Perspective for Other Applications byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 31: World Artificial Intelligence (AI) Platform MarketAnalysis of Annual Sales in US$ Million for Years 2014 through2030

III. MARKET ANALYSIS

UNITED STATESArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in the United Statesfor 2023 (E)Table 32: USA Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 33: USA 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 34: USA Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 35: USA 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 36: USA Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 37: USA 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

CANADATable 38: Canada Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 39: Canada 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 40: Canada Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 41: Canada 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 42: Canada Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 43: Canada 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

JAPANArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in Japan for 2023 (E)Table 44: Japan Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 45: Japan 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 46: Japan Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 47: Japan 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 48: Japan Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 49: Japan 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

CHINAArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in China for 2023 (E)Table 50: China Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 51: China 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 52: China Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 53: China 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 54: China Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 55: China 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

EUROPEArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in Europe for 2023 (E)Table 56: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Geographic Region -France, Germany, Italy, UK and Rest of Europe Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 57: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by Geographic Region - Percentage Breakdown ofValue Sales for France, Germany, Italy, UK and Rest of EuropeMarkets for Years 2023 & 2030

Table 58: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 59: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 60: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 61: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 62: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 63: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

FRANCEArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in France for 2023 (E)Table 64: France Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 65: France 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 66: France Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 67: France 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 68: France Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 69: France 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

GERMANYArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in Germany for 2023(E)Table 70: Germany Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 71: Germany 8-Year Perspective for ArtificialIntelligence (AI) Platform by Deployment - Percentage Breakdownof Value Sales for Cloud and On-Premise for the Years 2023 &2030

Table 72: Germany Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 73: Germany 8-Year Perspective for ArtificialIntelligence (AI) Platform by End-Use - Percentage Breakdown ofValue Sales for Healthcare, Research & Academia,Transportation, Retail & eCommerce, Other End-Uses, BFSI andManufacturing for the Years 2023 & 2030

Table 74: Germany Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 75: Germany 8-Year Perspective for ArtificialIntelligence (AI) Platform by Application - PercentageBreakdown of Value Sales for Forecasts & Prescriptive Models,Chatbots, Speech Recognition, Text Recognition and OtherApplications for the Years 2023 & 2030

ITALYTable 76: Italy Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 77: Italy 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 78: Italy Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 79: Italy 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 80: Italy Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 81: Italy 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

UNITED KINGDOMArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in the United Kingdomfor 2023 (E)Table 82: UK Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 83: UK 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 84: UK Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 85: UK 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

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Global Artificial Intelligence (AI) Platform Market to Reach $120.7 Billion by 2030 - Yahoo Finance

Council Post: Exploring Pros and Cons of Artificial Intelligence in … – Analytics India Magazine

In a report by MIT, a student explains what AI is. He says, its kind of like a baby or a human brain because it has to learn, and it stores and uses that information to figure things out.

For a 10 yr old to give such an explanation on a vast phenomenon like AI, means that we have come a long way. AI has always been there and whether we know it or not we use it everyday. The place of artificial intelligence (AI) in the future of education is the subject of intense discussion. Fans of the technology argue that schools must adopt it and use it to deliver a more effective educational experience, while critics fear that its adoption will have a number of negative side consequences.

There is no clear consensus regarding which point of view is correct. AI does not have to be a one-size-fits-all solution. As with most technologies, implementing it safely and successfully necessitates a complete comprehension of the advantages and disadvantages. To give us more insights on this we had our monthly Roundtable session.

The session was moderated by Rathnakumar Udayakumar, Product Lead Cloud and AI at Netradyne along with our experienced panelists, Chiranjiv Roy, Vice President Industry 4.0, Applied AI at Course5i, Deepika Kaushal, Deputy Vice President at Piramal Capital & Housing Finance, Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion, Parikshit Nag, Head of Data & Analytics at Indus OS and Anand K Sundaram, Head Retail Analytics at IDFC First Bank.

AI has been here since the machine was invented. Nothing has changed. The fundamentals have never been changed and it will never be changed in itself. The challenge is that the academic body, especially in emerging countries like India, never paced up with AI, because the last 25 years has always been about software development. Because everybody was focusing on Java. Now, everything can be done by generative AI or ChatGPT.

Thats when you require logic and require data. Thats where the premise comes into picture. The economic institutions, especially in emerging countries, had never been ready to do it. We see a lot of things where academics and corporate need to be together. But it actually has never been due to the diversity we have today. We are the largest, biggest population in India. We dont even know how deep and diverse the number of people who are passing out are.

Chiranjiv Roy, Vice President Industry 4.0, Applied AI at Course5i

Its fantastic how far we have moved, from the information being restricted to the elite part of the society. This relates to whether we will have information based education or transformational education. We are used to having information based education which is generated by 10% of the society, the rest 90% of that information is replicated, duplicated and consumed. But now we are entering into the transformation way of learning things.

The section of society, which was restricted from getting exposed to the new way of learning new things and new trends, is easily accessible now. I dont see any boundaries or any socio economic conditions. Some people may not have access to some quality education, because we do get an education, but the quality of education also matters and the networking matters, exposure matters. But theres a different set of challenges to deal with.

Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion

Any transformation does not come easy. And its not done on an immediate basis, it takes a certain time to establish. In recent years there is too much excitement in the institutes and academies. Kids learn mobile apps at the age of eight but know nothing. Its a transformation stage. And sometimes in transformation, it takes a while to get the right things in place. For every person its like a dual ceiling.

Anand K Sundaram, Head Retail Analytics at IDFC First Bank

Analytics is all about predictive modeling. Everybody is fencing that some models will run and theyll change the world but Analytics is a mix of business plus math plus statistics. These are the basic combinations a person needs to know. From an academy perspective, I think they need to blend all of it together. In case they want to keep a pace, the first thing is to get your basics right for every kid who you are coaching.

Online courses are a little boring, because many times, you dont have a live instructor. Its more of a recorded session and if I have a question, I dont have anybody to talk to. Similarly, it goes with Academia right now in India, its not really a knowledge gaining kind of institution. Analytics is an upcoming area, if you get certified you get a job, and people come to the job and they struggle. We dont really look at knowledge, we dont really teach people how to survive in our environment. Especially when you have to deliver outcomes, because we are in the business of doing so.

Deepika Kaushal, Deputy Vice President at Piramal Capital & Housing Finance

Companies come in and tell you that if you learn to code, as a six year old, you will become the next Steve Jobs, but you probably wont. And even if you do become the next Steve Jobs, its probably not going to be because he picked up a course as a six year old. The rate at which AI is evolving, I think for any student who actually has exposure to all of these three subjects(math, stats and business) to begin with, and formed a strong base there is way more critical as compared to learning about NLP or large language model, some course or learning about decision trees and fitting them in the Titanic data set.

Institutions use some of the open source datasets which are available, and that doesnt make sense because they come back and talk about what they have done. But if you ask them how the decision tree works, theyll just falter. If you think about putting AI as a course right now, its evolving very fast. Standardising it into the curriculum doesnt make sense at this point in time. One thing, which we tremendously lack in India, is industry exposure. And there is a gap on both sides. If you look at Academia, they dont have enough industrial projects going for them.

In the real world scenario, if you look at most of the corporations, they dont have a strong AI or r&d division, which basically only focuses on research. Most of the AI teams, in corporates, have some business goals, which they need to achieve. And they need to deliver on that within a particular timeline. Because AI is expensive. I think that gap needs to be bridged really fast.

Parikshit Nag, Head of Data & Analytics at Indus OS

There are two aspects to it, one is the creation of it, and then governing it. Education is not just about technology itself. I dont think we are there yet. None of the institutes are really wrapping their heads around. What do we teach our kids? How do you make it easily accessible and easily comprehensible by our school kids or college kids? More than creation, the biggest challenge, the academy still needs to think about, is to educate or create awareness about how we govern this.

Some people refer to it as the curse of magic. So technology is not something that happened yesterday, it is just that awareness is exploding. So the technology itself is not really that complicated. We can train our people, we can put them through and grind them out. But how do we harness the power that needs to be educated along with creation of it? None of the institutes are ready for it yet.

Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion

There is no standardized framework, yet in India, or even globally, per se, but it has started to seep into the ecosystem. These kinds of regulations are quite exhausted and have started seeping into the culture of individuals and institutes as well. The second thing is around data literacy. Why do we actually need to classify data? The thing is, its very easy to store data somewhere in a data lake and make it accessible to everyone.

But should the data thats available be accessible? Or should everyone be able to access, is a very critical question. The point is around data classification, ensuring that PII data is masked and kept separately, its not accessible to everyone, people who actually have permission, and its all time bound to ensure that they delete the data after a certain point in time. Its a good practice, but it will take time to actually standardize this into a particular bill. I think it will take some time for it to standardize, but I think it will come out more around ethical AI.

Its going to be more of an individual responsibility to say that lets not breach privacy, lets ensure that were doing things and it will be the responsibility of organizations and institutes who actually inculcate this kind of thinking.

Parikshit Nag, Head of Data & Analytics at Indus OS

Its exciting to see how the two industries can combine and what opportunities they bring out.

To conclude, the only thing better than learning from your own mistakes is asking a machine learning algorithm to do it for you. Rathnakumar Udayakumar, Product Lead Cloud and AI at Netradyne

This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the formhere

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Council Post: Exploring Pros and Cons of Artificial Intelligence in ... - Analytics India Magazine

Experts Demand ‘Pause’ on Spread of Artificial Intelligence Until … – Common Dreams

"Until meaningful government safeguards are in place to protect the public from the harms of generative AI, we need a pause."

So says a report on the dangers of artificial intelligence (AI) published Tuesday by Public Citizen. Titled Sorry in Advance! Rapid Rush to Deploy Generative AI Risks a Wide Array of Automated Harms, the analysis by researchers Rick Claypool and Cheyenne Hunt aims to "reframe the conversation around generative AI to ensure that the public and policymakers have a say in how these new technologies might upend our lives."

Following the November release of OpenAI's ChatGPT, generative AI tools have been receiving "a huge amount of buzzespecially among the Big Tech corporations best positioned to profit from them," the report notes. "The most enthusiastic boosters say AI will change the world in ways that make everyone richand some detractors say it could kill us all. Separate from frightening threats that may materialize as the technology evolves are real-world harms the rush to release and monetize these tools can causeand, in many cases, is already causing."

Claypool and Hunt categorized these harms into "five broad areas of concern":

In a statement, Public Citizen warned that "businesses are deploying potentially dangerous AI tools faster than their harms can be understood or mitigated."

"History offers no reason to believe that corporations can self-regulate away the known risksespecially since many of these risks are as much a part of generative AI as they are of corporate greed," the statement continues. "Businesses rushing to introduce these new technologies are gambling with peoples' lives and livelihoods, and arguably with the very foundations of a free society and livable world."

On Thursday, April 27, Public Citizen is hosting a hybrid in-person/Zoom conference in Washington, D.C., during which U.S. Rep. Ted Lieu (D-Calif.) and 10 other panelists will discuss the threats posed by AI and how to rein in the rapidly growing yet virtually unregulated industry. People interested in participating must register by this Friday.

"Businesses rushing to introduce these new technologies are gambling with peoples' lives and livelihoods, and arguably with the very foundations of a free society and livable world."

Demands to regulate AI are mounting. Last month, Geoffrey Hinton, considered the "godfather of artificial intelligence," compared the quickly advancing technology's potential impacts to "the Industrial Revolution, or electricity, or maybe the wheel."

Asked by CBS News' Brook Silva-Braga about the possibility of the technology "wiping out humanity," Hinton warned that "it's not inconceivable."

That frightening potential doesn't necessarily lie with existing AI tools such as ChatGPT, but rather with what is called "artificial general intelligence" (AGI), through which computers develop and act on their own ideas.

"Until quite recently, I thought it was going to be like 20 to 50 years before we have general-purpose AI," Hinton told CBS News. "Now I think it may be 20 years or less." Eventually, Hinton admitted that he wouldn't rule out the possibility of AGI arriving within five yearsa major departure from a few years ago when he "would have said, 'No way.'"

"We have to think hard about how to control that," said Hinton. Asked by Silva-Braga if that's possible, Hinton said, "We don't know, we haven't been there yet, but we can try."

The AI pioneer is far from alone. In February, OpenAI CEO Sam Altman wrote in a company blog post: "The risks could be extraordinary. A misaligned superintelligent AGI could cause grievous harm to the world."

More than 26,000 people have signed a recently published open letter that calls for a six-month moratorium on training AI systems beyond the level of OpenAI's latest chatbot, GPT-4, although Altman is not among them.

"Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable," says the letter.

While AGI may still be a few years away, Public Citizen's new report makes clear that existing AI toolsincluding chatbots spewing lies, face-swapping apps generating fake videos, and cloned voices committing fraudare already causing or threatening to cause serious harm, including intensifying inequality, undermining democracy, displacing workers, preying on consumers, and exacerbating the climate crisis.

These threats "are all very real and highly likely to occur if corporations are permitted to deploy generative AI without enforceable guardrails," Claypool and Hunt wrote. "But there is nothing inevitable about them."

They continued:

Amid "growing regulatory interest" in an AI "accountability mechanism," the Biden administration announced last week that it is seeking public input on measures that could be implemented to ensure that "AI systems are legal, effective, ethical, safe, and otherwise trustworthy."

According toAxios, Senate Majority Leader Chuck Schumer (D-N.Y.) is "taking early steps toward legislation to regulate artificial intelligence technology."

In the words of Claypool and Hunt: "We need strong safeguards and government regulationand we need them in place before corporations disseminate AI technology widely. Until then, we need a pause."

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Experts Demand 'Pause' on Spread of Artificial Intelligence Until ... - Common Dreams

Smart Ways to Invest in Artificial Intelligence – Yahoo Finance

invest in ai

Artificial intelligence has become one of the most talked about technologies over the past few years. Many see AI with large dollar signs in their eyes. However, every new technology has a lag between invention and commodification and just as every new technology has the risk that it wont pan out. For investors, this poses a challenge. While the risks are real so, too, are the opportunities. So, for a technology that is still effective in the drumroll phase, how can you invest? Here are a few ideas. For more personalized investment advice, consider working with a financial advisor.

Artificial Intelligence Industry

Artificial intelligence has not yet been truly monetized. Now, theres a lot to unpack in that statement. For starters, tech companies have been integrating AI into their software for a generation and making tons of money off it. From autocorrect to playlists to the monsters in World of Warcraft, companies have been profiting off software decision-making for a long time.

The new AI, however, is a different thing entirely. The news-making artificial intelligence has come in the form of predictive algorithms like ChatGPTs chatbot software and DALL-Es image generator. These tools remain experimental. They are inventions and innovations but, at the time of writing, not yet products. Part of that is because engineers still arent quite sure what they are yet.

Advocates say that current AI software represents a fundamentally new tool, one that will change the way we interact with information and each other. Critics argue that they are just high-volume autocorrects, machines best suited for reorganizing existing work at best and stealing it at worst, but incapable of creating new value.

In both cases, monetization is a challenge. If tools like ChatGPT represent a true leap forward, then companies will need some time to figure out their commercial use. If, instead, they fundamentally rely on copying and pasting the work of others, then they may be more novelty than revolution.

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However, that doesnt mean that there arent opportunities to invest and profit yourself. Here are some of the best ways you can benefit financially from the early stages of AI development.

If youre ready to be matched with local advisors that can help you achieve your financial goals, get started now.

Invest In Individual Stocks Like Google and Microsoft

Alphabet (GOOG), or Google, and Microsoft (MSFT), which kept its maiden name, are some of the earliest companies racing for commercial AI applications. In both cases, their goal is to search. Both companies want to turn their search engines into a conversational source of inquiry, analysis and advice.

Instead of searching for information by a string of keywords, you would just ask the search engine questions and it would pop out the answer based on whats out there on the web. In this way, AIs best and worst qualities align with the business model of search. The goal is to paraphrase articles like this onto Google/Microsoft sites, so those companies can collect the ad revenue without having to pay for the work.

Googles Bard AI remains experimental and, true to the products core design, Bings AI search remains underwhelming. However, both companies hope to make this a major product at some point in the future.

This is a theme that applies broadly: Invest in companies that are will use AI in their products. As currently designed, AI will most likely be a backend feature in an enormous range of technology products. So, for example, while your phone is the front-end product, meaning the product you directly interact with, AI will become part of the back-end, meaning one of the many moving pieces that make your phone work.

Look for companies that can use AI in their products. Invest in them directly, so that you can collect their gains from this new technology.

Use Robo-Traders

invest in ai

Robo-traders have emerged as a major section of the market and for a good reason.

A robo-trader is a company that offers algorithmically managed portfolios. In essence, you invest your money according to a series of goals or conditions that you establish, then the brokerage manages that portfolio based on its own software model. These have shown particularly good results for investors because they tend to seek long-term investments, which tend to outperform short-term and high-volume trading.

Artificial intelligence has the potential to improve this further. Investors are already experimenting with AI-built portfolios and investment strategies. This trend will only continue to grow and the companies that build their portfolios with AI from the ground up will stand to benefit significantly.

Invest In AI Funds

As with all industries, an excellent way to invest in AI is through relevant funds. In fact, theres something of a gold rush on artificial intelligence ETFs right now. The market is filled with companies that are looking to capitalize on companies that operate in or around this technology.

For an investor, this is both an opportunity and a problem. The opportunities are out there, but how do you identify good investments? One good approach is to start by deciding how you want to invest in AI. There are ETFs, for example, such as Global X Robotics & Artificial Intelligence ETF (BOTZ) and ROBO Global Robotics and Automation Index ETF (ROBO), among others that let you invest in this market.

These funds invest in stocks and assets that support AI, such as companies that make the chips and hardware that AI companies depend on. Other funds will try to invest directly, buying into companies that are developing AI software itself, while others will invest in the companies that will use AI in their own products.

The best place to start with an AI-related fund is to look at how it invests. That will help you figure out if this is something youre interested in.

The Bottom Line

invest in ai

Artificial intelligence could very well be the next big boom. However, it can be difficult to determine the right areas that could make strong investments. Both directly and indirectly, AI might present plenty of opportunities that you can profit from. Finding the right one for you will depend on a number of factors including your expectation of risk.

Technology Investment Tips

Investing in any new technology is a risk. When it pays off, it can pay off big, but there are no guarantees. A financial advisor can help you determine the best investment plan for you when it comes to AI. Finding a financial advisor doesnt have to be hard.SmartAssets free tool matches you with up to three vetted financial advisors who serve your area, and you can interview your advisor matches at no cost to decide which one is right for you. If youre ready to find an advisor who can help you achieve your financial goals, get started now.

Finance and technology go hand-in-hand and the industry dedicated to that idea is called fintech. Its important to fully understand how the industry operates if youre wanting to invest.

Photo credit: iStock.com/Thai Liang Lim, iStock.com/Laurence Dutton, iStock.com/imaginima

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Smart Ways to Invest in Artificial Intelligence - Yahoo Finance

Reminder For Illinois (And Other) Employers: Restrictions Apply … – JD Supra

SUMMARY

Illinois and other jurisdictions have adopted, or are considering, laws establishing parameters for employer use of AI during the hiring process.

The current attention being given to ChatGPT and other technologies using artificial intelligence (AI) is prompting companies to consider (or take another look) at how AI can and/or should play a role in their operations. From an employment law perspective, employers in Illinois and elsewhere should be aware of existing laws and guidance, and also should keep an eye out for the additional restrictions that will undoubtedly come as the use of AI becomes more prevalent.

In 2020, Illinois adopted the Artificial Intelligence Video Interview Act (820 ILCS 42/1), which establishes parameters for employer use of AI during the hiring process. If an employer intends to ask applicants to record video interviews so that it can use an AI analysis of such videos as part of the evaluation process, the employer must:

Sharing of such videos is limited to those with the expertise or technology necessary to evaluate the applicants fitness for a position. The videos (including all copies) must be destroyed within 30 days of a request by the applicant. These restrictions presumably apply to both new hires and employees who are seeking new positions within a company.

Illinois is not the only jurisdiction with AI restrictions on the books or under consideration. Bryan Cave Leighton Paisners Data Privacy group has prepared a summary of current and pending AI legislation around the United States.

California is among the jurisdictions currently reviewing proposed laws and regulations on the subject of the use of AI when making employment decisions, while Maryland enacted a law similar to Illinois in 2020, placing restrictions on the use of facial recognition services during pre-employment interviews until the applicant provides consent.

A more extensive law will be enforced in New York City beginning July 5, 2023: The New York City Automated Employment Decision Tools Law (AEDTL) which, among other things, requires employers to (a) conduct an audit for potential bias before using any artificial intelligence tools that screen candidates for hire or promotion, (b) give advance notice to candidates concerning the use of such tools, and (c) provide information on their websites about the tools and data collected. More information on the AEDTL is available here.

The potential for bias in the use of artificial intelligence tools is a key concern of the federal Equal Employment Opportunity Commission (EEOC) as well. The EEOC launched an agency-wide initiative on the subject in 2021, with a goal of ensuring that, the use of software, including artificial intelligence (AI), machine learning, and other emerging technologies used in hiring and other employment decisions comply with the federal civil rights laws that the EEOC enforces.

In May 2022, the EEOC issued guidance on the subject of, The Americans with Disabilities Act and the Use of Software, Algorithms, and Artificial Intelligence to Assess Job Applicants and Employees. This guidance provides definitions of key terms and explains how the use of algorithmic decision-making tools may violate the Americans with Disabilities Act (ADA), and notes that the use of a third-party vendor to develop and/or administer such a tool is not likely to insulate the employer from liability in connection with the results of using that tool. The EEOC held a public hearing on the issue of employment discrimination and the use of AI in January 2023, and is likely to continue its focus on this developing area.

As the use of AI in the hiring and selection process continues to evolve, employers should: (1) become familiar with artificial intelligence concepts; (2) examine, understand, be able to explain, and monitor their automated recruiting tools and practices; and (3) take steps to avoid bias and comply with applicable law.

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Reminder For Illinois (And Other) Employers: Restrictions Apply ... - JD Supra

DFPI Launches Sweep of Investment Fraud Claiming Ties to … – California Department of Financial Protection and Innovation

Download this press release (PDF)

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SACRAMENTO The California Department of Financial Protection and Innovation (DFPI) announced today it has issued desist and refrain orders against five entities to stop fraudulent investment schemes tied to artificial intelligence (AI).

Todays enforcement actions continue the DFPIs crack down on investor fraud. Scammers are taking advantage of the recent buzz around artificial intelligence to entice investors into bogus schemes, said DFPI Commissioner Clothilde Hewlett. We will continue our efforts to protect California consumers and investors by going after these unscrupulous actors.

The orders find that the named entities and individuals violated California securities laws by offering and selling unqualified securities and making material misrepresentations and omissions to investors. The entities solicited funds from investors by claiming to offer high yield investment programs (HYIP) that generate incredible returns by using AI to trade crypto assets. As part of their solicitations, they used multi-level marketing schemes that reward investors for recruiting new investors.

The subjects of todays desist and refrain orders are the following entities and individuals:

The Anatomy of the Scams

Taking advantage of the hype around AI, these entities claimed to use AI to conduct the purported crypto trading. The pitch was simple: investors were told that if they invested funds, these entities would use their knowledge, skill, experience, and AI to trade crypto assets and generate incredible profits for investors. In each case, these claims are false.

Each of these entities went to great lengths to appear as if they were legitimate businesses. They created professional websites, maintained social media accounts, and were promoted on social media by influencers and investors that shared stories of the money they were supposedly making.

For investors, these schemes may seem as if they are operating as promised for a certain amount of time. For weeks, months, or even years, investors see their account balances steadily increase. In the early stages, HYIPs will process investors withdrawal requests to gain investors trust and encourage them to recruit others. However, a time will come when the scheme stops processing withdrawals and then the website goes dark, leaving investors without a way to access their funds. By then its too late and the scammers have disappeared with investors money.

DFPIs Crackdown on High Yield Investment Programs

These orders continue the DFPIs crackdown on HYIPs. These programs use social media and influencers to quickly raise hype about the promised returns and low risk of the investment, then the operators quickly disappear leaving investors with no recourse to retrieve their money. Learn more about HYIPs:

The DFPI expects any person offering securities, lending, or other financial services in California to comply with our financial laws. Investors may file a complaint directly with the DFPI if they suspect a company of using unlawful, unfair, deceptive, or abusive practice online (dfpi.ca.gov/file-a-complaint) or call toll-free at (866) 275-2677.

About DFPI

The DFPI protects consumers, regulates financial services, and fosters responsible innovation. The DFPI protects consumers by establishing and enforcing financial regulations that promote transparency and accountability. We empower all Californians to access a fair and equitable financial marketplace through education and preventing potential risks, fraud, and abuse. Learn more atdfpi.ca.gov.

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DFPI Launches Sweep of Investment Fraud Claiming Ties to ... - California Department of Financial Protection and Innovation

How is artificial intelligence used in cricket? – Rebellion Research

How is artificial intelligence used in cricket?

Cricket is a bat-and-ball game that originated in England in the 16th century additionally, has since become a popular sport around the world. While there is no direct connection between the sport of cricket and artificial intelligence, there have been some notable applications of AI in the sport in recent years.

Cricket has a long and rich history, with the first recorded game taking place in the 16th century. Over time, the game evolved and became more formalized, with the first international match played in the mid-19th century. Today, cricket becomes played at both the professional and amateur levels. Moreover, with international tournaments such as the Cricket World Cup and the Ashes attracting millions of viewers around the world.

One area where AI has become used is in player analysis, where data from matches and training sessions analyze with machine learning algorithms to identify patterns and trends. Thus this can help coaches and players identify areas for improvement and develop more effective training programs.

Another area where AI has become applied in cricket is in the use of virtual reality training simulations. By using VR headsets and controllers, players can practice and refine their skills in a simulated environment, which can be especially useful for training when outdoor facilities are not available.

AI has also become used in cricket umpiring. Where machine learning algorithms help umpires make more accurate decisions. However, this technology is still in its early stages, but has the potential to revolutionize the sport by reducing errors and improving the overall accuracy of umpiring decisions.

In conclusion, while there is no direct connection between the sport of cricket and artificial intelligence, there have been some notable applications of AI in the sport in recent years. Furthermoe, from player analysis and virtual reality training simulations to umpiring technology. Lastly, AI has the potential to transform the way the sport becomes played and officiated. In addition could help take cricket to new heights of popularity and success in the years to come.

Cricket + Artificial Intelligence SV4U Blog (siliconvalley4u.com)

How AI is helping to improve Cricket (analyticsinsight.net)

used in the IPL? (indiaai.gov.in)

Cricket? Mad About Sports

Artificial Intelligence in Cricket (thinkml.ai)

AI IN CRICKET. -BATTING ITS WAY OUT!!!! | by Asthajha | Student Technical CommunityVIT Vellore | Medium

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How is artificial intelligence used in cricket? - Rebellion Research

Global Artificial Intelligence in Healthcare Market Report 2023: Ability of AI to Improve Patient Outcomes and Growing Importance of AI-assisted Robot…

DUBLIN, April 18, 2023 /PRNewswire/ -- The "Artificial Intelligence in Healthcare Market - Growth, Trends, COVID-19 Impact, and Forecasts (2023-2028)" report has been added to ResearchAndMarkets.com's offering.

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The artificial intelligence in the healthcare market is expected to register a CAGR of 42.2% during the forecast period.

Companies Mentioned

Key Market Trends

Medical Imaging & Diagnostics To Hold Significant Share in the Market

In diagnostics, AI enables healthcare providers to make the most appropriate treatment decisions for their patients. AI can be used to identify cancer, triage crucial discoveries in medical imaging, flag acute abnormalities, assist radiologists in prioritizing life-threatening patients, diagnose cardiac arrhythmias, forecast stroke outcomes, and assist with chronic disease management.

The rise in the prevalence of chronic diseases, along with product launches by market players, drives the segment. For instance, the Cancer Facts and Figures 2022, published in January 2022 by the American Cancer Society, predicted approximately 1.9 million new cancer cases in 2022, estimating 186,670 prostate cancer cases, followed by 169,870 cases of lung cancer and 144,490 cases of female breast cancer.

The increased prevalence of cancer and the high burden of other chronic diseases are, in turn, increasing the demand for accurate diagnosis and treatment. This is likely to increase the adoption of AI for early diagnosis purposes, ultimately boosting the market growth.

Incorporating AI into imaging devices may improve diagnosis, which is expected to aid market growth during the forecast period. For instance, in December 2021, Roche introduced three artificial intelligence (AI) based, deep learning image analysis Research Use Only (RUO) algorithms developed for breast cancer.

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Additionally, in April 2022, Arterys, the vendor-neutral AI platform, launched several new modules to its robust Cardio AI clinical application and an additional (eighth) Food and Drug Administration (FDA) AI clearance based on deep learning.

Additionally, various strategies adopted by the market players are expected to propel the segment's growth. For instance, in November 2021, LifeVoxel, based in San Diego, raised USD 5 million in a seed round to improve the data intelligence of its AI diagnostic visualization platform for faster and more accurate prognosis. Healthcare facilities employ the Software-as-a-Service (SaaS) platform for remote diagnostics in various medical specialties, including radiology, cardiology, and orthopedics.

Thus, all the aforementioned factors, such as the growing prevalence of chronic diseases and key strategies adopted by market players, are expected to boost the segment's growth over the forecast period.

North America Expected to Hold a Significant Market Share

The use of artificial intelligence in the North American healthcare market is being driven by the increasing use of advanced technology in healthcare systems, the growth in funding of AI-based startups, the rising burden of chronic diseases in the country, the growing need to reduce healthcare costs, and the implementation of big data in healthcare.

The increased adoption of big data in healthcare in the region is expected to propel the market's growth. For instance, in August 2022, the Children's Hospital of Philadelphia (CHOP) and the University of Pennsylvania School of Medicine (Penn Medicine) launched the big data-driven Penn-CHOP Kidney Innovation Center, which will support research to improve patient care for adults and children with kidney disease.

Moreover, the Association of American Medical Colleges reported in August 2022 that the United States spends USD 4 trillion per year on health care. Thus, the region is facing the need to minimize healthcare costs, which can be accomplished by applying AI in healthcare, thereby enhancing market growth.

Furthermore, introducing technologically advanced products into the market is expected to propel the market's growth. For instance, in December 2021, Crawford & Company introduced Crawford Intelligent Fraud Detection.

It combined human expertise and forensic analysis, joining DXC Luxoft's Financial Crimes Intelligence platform with IBM, improvising how it recognizes and manages fraudulent claims for its clients. Additionally, in June 2022, My Intelligent Machines (MIMs) launched software with artificial intelligence that has the potential to transform the way organizations prepare for oncology clinical trials or drug development.

Strategic activities of the market players are also expected to support the market's expansion. For instance, in June 2022, Insilico Medicine opened a fully automated, artificial intelligence-driven robotics lab for drug research.

Thus, all the factors mentioned above, such as the growing demand for big data in healthcare and technologically advanced product launches, are expected to boost the market over the forecast period.

Key Topics Covered:

1 INTRODUCTION

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS4.1 Market Overview4.2 Market Drivers4.2.1 Growing Need to Reduce Increasing Healthcare Costs4.2.2 Big Data in Healthcare4.2.3 Ability of AI to Improve Patient Outcomes and Growing Importance of AI-assisted Robot Surgery4.3 Market Restraints4.3.1 Reluctance Among Traditional Practitioners to Adopt AI-based Technologies4.4 Industry Attractiveness - Porter's Five Forces Analysis

5 MARKET SEGMENTATION (Market Size by Value - USD million)5.1 By Technology5.1.1 Natural Language Processing (NLP)5.1.2 Deep Learning5.1.3 Context Aware Processing5.1.4 Querying Method5.1.5 Other Technology Types5.2 By Application5.2.1 Robot-assisted Surgery5.2.2 Virtual Nursing Assistants5.2.3 Fraud Detection5.2.4 Drug Discovery and Research5.2.5 Dosage Error Reduction5.2.6 Medical Imaging and Diagnostics5.2.7 Wearables5.2.8 Other Application Types5.3 By Offering5.3.1 Hardware5.3.2 Software5.3.3 Services5.4 By End-user5.4.1 Healthcare Payers5.4.2 Healthcare Providers5.4.3 Pharmaceutical and Biotechnology Companies5.4.4 Patients5.4.5 Other End-user Types5.5 By Geography

6 COMPETITIVE LANDSCAPE6.1 Company Profiles

7 MARKET OPPORTUNITIES AND FUTURE TRENDS

For more information about this report visit https://www.researchandmarkets.com/r/z2i953

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Global Artificial Intelligence in Healthcare Market Report 2023: Ability of AI to Improve Patient Outcomes and Growing Importance of AI-assisted Robot...

SAVVY SENIORS: Artificial Intelligence will be a genuine game … – Peace Arch News

Hi there! Im TaxGPT, a friendly AI tax adviser.

Well, thanks anyway, but I had a human file my tax return for me this year.

But of course, we know the world is changing as Artificial Intelligence or AI dominates the planet.

AI is now a hot topic as almost 77 per cent of devices today use AI technology. There are more AI assistants today, a figure which will eventually surpass the number of people on this Earth.

According to carbon60global.com the AI market is expected to reach $407 billion by 2027. By 2057, robots could replace or displace 2.7 million jobs in construction and engineering alone.

How many times have you said, Hey Google, where is the nearest Italian restaurant?

Hey Siri, what is the population of Nunavut?

Alexa, play me my favourite Lionel Richie songs from the 80s.

AI is software meant to mimic a human mind and model human intelligence.

According to Reference.com, the general benefit of AI is that it replicates decisions and actions of humans without human shortcomings such as fatigue, emotion and limited time.

I am thinking of adding a shortcoming such as stupidity to the list, which would mean we could replace the average politician with artificial intelligence.

Machines driven by AI technology are being used to replace humans as they are able to perform consistent repetitious actions without getting tired.

They dont need work breaks or work-life balance or time off due to sickness. They are available 24/7 and reduce the need for human personnel.

Theres a reduction in human error.

Those are some of the advantages.

However, currently, the disadvantages are that machines are neither flexible nor creative, as robots cant think outside the box. It stifles critical thinking as AI cant be improved with experience like we can. Costs are high and it leads to unemployment and the risk of making humans lazy.

Is Artificial Intelligence improving the lives of seniors today?

Absolutely.

During the pandemic, research studies were done in Sweden and the U.K. where a chatbot, an interactive computer program using AI voice technology, was used to interact with isolated seniors.

The researchers used a chatbot called ChatGPT (Generative Pre-Trained Transformer) as a cure for loneliness. It replicated human conversation, covering a wide array of topics. It can create human-like responses when prompted.

As visitors werent allowed to visit their elderly loved ones during the lockdown, ChatGPT could also help the isolated seniors answer questions, problem-solve as well as compose letters to their family.

Thats a good thing, but on the downside, chatbots could easily replace human interactions with all of their emotional baggage and drama.

At Drexel University in Pennsylvania, (drexel.edu) researchers say that using similar voice technology helps with early detection of dementia and Alzheimers disease. The chatbox program used was 80 per cent accurate in predicting early signs of dementia because language impairment affects between 60 and 80 per cent of dementia patients. The program can detect subtle clues such as grammar and pronunciation mistakes, hesitation and forgetting the meaning of words.

As the AI creators strive to produce a machine with a humans intellectual capacities, its billionaire executives such as Sam Altman fear that superhuman machine intelligence is probably the greatest threat to the continuous existence of humanity. Even Elon Musk is asking for a six-month moratorium on the development of advanced AI systems, including the latest version of ChatGPT.

But fellas, before you take a hiatus, could you develop me an interactive chatbot, who well call George, to be at my beck and call?

Hey George, rub my tired feet. While youre at it, peel me a grape!

April Lewis writes monthly on seniors issues for Peace Arch News.

AI technologyColumnSeniors

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Nvidia’s $329 Billion Surge Helped By Artificial Intelligence … – Baker City Herald

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