New Tool for Building and Fixing Roads and Bridges: Artificial … – The New York Times

In Pennsylvania, where 13 percent of the bridges have been classified as structurally deficient, engineers are using artificial intelligence to create lighter concrete blocks for new construction. Another project is using A.I. to develop a highway wall that can absorb noise from cars and some of the greenhouse gas emissions that traffic releases as well.

At a time when the federal allocation of billions of dollars toward infrastructure projects would help with only a fraction of the cost needed to repair or replace the nations aging bridges, tunnels, buildings and roads, some engineers are looking to A.I. to help build more resilient projects for less money.

These are structures, with the tools that we have, that save materials, save costs, save everything, said Amir Alavi, an engineering professor at the University of Pittsburgh and a member of the consortium developing the two A.I. projects in conjunction with the Pennsylvania Department of Transportation and the Pennsylvania Turnpike Commission.

The potential is enormous. The manufacturing of cement alone makes up at least 8 percent of the worlds carbon emissions, and 30 billion tons of concrete are used worldwide each year, so more efficient production of concrete would have immense environmental implications.

And A.I. essentially machines that can synthesize information and find patterns and conclusions much as the human mind can could have the ability to speed up and improve tasks like engineering challenges to an incalculable degree. It works by analyzing vast amounts of data and offering options that give humans better information, models and alternatives for making decisions.

It has the potential to be both more cost effective one machine doing the work of dozens of engineers and more creative in coming up with new approaches to familiar tasks.

But experts caution against embracing the technology too quickly when it is largely unregulated and its payoffs remain largely unproven. In particular, some worry about A.I.s ability to design infrastructure in a process with several regulators and participants operating over a long period of time. Others worry that A.I.s ability to draw instantly from the entirety of the internet could lead to flawed data that produces unreliable results.

American infrastructure challenges have become all the more apparent in recent years Texas power grid failed during devastating ice storms in 2021 and continues to grapple with the states needs; communities across the country from Flint, Mich., to Jackson, Miss., have struggled with failing water supplies; and more than 42,000 bridges are in poor condition nationwide.

A vast majority of the countrys roadways and bridges were built several decades ago, and as a result infrastructure challenges are significant in many dimensions, said Abdollah Shafieezadeh, a professor of civil, environmental and geodetic engineering at Ohio State University.

The collaborations in Pennsylvania reflect A.I.s potential to address some of these issues.

In the bridge project, engineers are using A.I. technology to develop new shapes for concrete blocks that use 20 percent less material while maintaining durability. The Pennsylvania Department of Transportation will use the blocks to construct a bridge; there are more than 12,000 in the state that need repair, according to the American Road & Transportation Builders Association.

Engineers in Pittsburgh are also working with the Pennsylvania Turnpike Commission to design a more efficient noise-absorbing wall that will also capture some of the nitrous oxide emitted from vehicles. They are planning to build it in an area that is disproportionately affected by highway sound pollution. The designs will save about 30 percent of material costs.

These new projects have not been tested in the field, but they have been successful in the lab environment, Dr. Alavi said.

In addition to A.I.s speed at developing new designs, one of its largest draws in civil engineering is its potential to prevent and detect damage.

Instead of investing large sums of money in repair projects, engineers and transportation agencies could identify problems early on, experts say, such as a crack forming in a bridge before the structure itself buckled.

This technology is capable of providing an analysis of what is happening in real time in incidents like the bridge collapse on Interstate 95 in Philadelphia this summer or the fire that shut down a portion of Interstate 10 in Los Angeles this month, and could be developed to deploy automated emergency responses, said Seyede Fatemeh Ghoreishi, an engineering and computer science professor at Northeastern University.

But, as in many fields, there are increasingly more conversations and concerns about the relationship between A.I., human work and physical safety.

Although A.I. has proved helpful in many uses, tech leaders have testified before Congress, pushing for regulations. And last month, President Biden issued an executive order for a range of A.I. standards, including safety, privacy and support for workers.

Experts are also worried about the spread of disinformation from A.I. systems. A.I. operates by integrating already available data, so if that data is incorrect or biased, the A.I. will generate faulty conclusions.

It really is a great tool, but it really is a tool you should use just for a first draft at this point, said Norma Jean Mattei, a former president of the American Society of Civil Engineers.

Dr. Mattei, who has worked in education and ethics for engineering throughout her career, added: Once it develops, Im confident that well get to a point where youre less likely to get issues. Were not there yet.

Also worrisome is a lack of standards for A.I. The Occupational Safety and Health Administration, for example, does not have standards for the robotics industry. There is rising concern about car crashes involving autonomous vehicles, but for now, automakers do not have to abide by any federal software safety testing regulations.

Lola Ben-Alon, an assistant professor of architecture technology at Columbia University, also takes a cautionary approach when using A.I. She stressed the need to take the time to understand how it should be employed, but she said that she was not condemning it" and that it had many great potentials.

Few doubt that in infrastructure projects and elsewhere, A.I. exists as a tool to be used by humans, not as a substitute for them.

Theres still a strong and important place for human existence and experience in the field of engineering, Dr. Ben-Alon said.

The uncertainty around A.I. could cause more difficulties for funding projects like those in Pittsburgh. But a spokesman for the Pennsylvania Department of Transportation said the agency was excited to see how the concrete that Dr. Alavi and his team are designing could expand the field of bridge construction.

Dr. Alavi said his work throughout his career had shown him just how serious the potential risks from A.I. are.

But he is confident about the safety of the designs he and his team are making, and he is excited for the technologys future.

After 10, 12 years, this is going to change our lives, Dr. Alavi said.

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New Tool for Building and Fixing Roads and Bridges: Artificial ... - The New York Times

Opera gives voice to Alan Turing with help of artificial intelligence – Yale News

A few years ago, composer Matthew Suttor was exploring Alan Turings archives at Kings College, Cambridge, when he happened upon a typed draft of a lecture the pioneering computer scientist and World War II codebreaker gave in 1951 foreseeing the rise of artificial intelligence.

In the lecture, Intelligent Machinery, a Heretical Theory, Turing posits that intellectuals would oppose the advent of artificial intelligence out of fear that machines would replace them.

It is probable though that the intellectuals would be mistaken about this, Turing writes in a passage that includes his handwritten edits. There would be plenty to do, trying to understand what the machines were trying to say, i.e., in trying to keep ones (sic) intelligence up to the standard set by the machines

To Suttor, the passage underscores Turings visionary brilliance.

Reading it was kind of a mind-blowing moment as were now on the precipice of Turings vision becoming our reality, said Suttor, program manager at Yales Center for Collaborative Arts and Media (CCAM) a campus interdisciplinary center engaged in creative research and practice across disciplines and a senior lecturer in the Department of Theater and Performance Studies in Yales Faculty of Arts and Sciences.

Inspired by Turings 1951 lecture, and other revelations from his papers, Suttor is working with a team of musicians, theater makers, and computer programmers (including several alumni from the David Geffen School of Drama at Yale) to create an experimental opera, called I AM ALAN TURING, which explores his visionary ideas, legacy, and private life.

I didnt envision a chronological biographical operatic piece To me, it was much more interesting to investigate Turings ideas.

Matthew Suttor

In keeping with Turings vision, the team has partnered with artificial intelligence on the project, using successive versions of GPT, a large language model, to help write the operas libretto and spoken text.

Three work-in-progress performances of the opera formed the centerpiece of the Machine as Medium Symposium: Matter and Spirit, a recent two-day event produced by CCAM that investigated how AI and other technologies intersect with creativity and alter how people approach timeless questions on the nature of existence.

The symposium, whose theme Matter and Spirit was derived from Turings writings, included panel discussions with artists and scientists, an exhibition of artworks made with the help of machines or inspired by technology, and tour of the Yale School of Architectures robotic lab led by Hakim Hasan, a lecturer at the school who specializes in robotic fabrication and computational design research.

All sorts of projects across fields and disciplines are using AI in some capacity, said Dana Karwas, CCAMs director. With the opera, Matthew and his team are using it as a collaborative tool in bringing Alan Turings ideas and story into a performance setting and creating a new model for opera and other types of live performance.

Its also an effective platform for inviting further discussion about technology that many people are excited about or questioning right now, and is a great example of the kind of work were encouraging at CCAM.

Turing is widely known for his work at Bletchley Park, Great Britains codebreaking center during World War II, where he cracked intercepted Nazi ciphers. But he was also a path-breaking scholar whose work set the stage for the development of modern computing and artificial intelligence.

His Turing Machine, developed in 1936, was an early computational device that could implement algorithms. In 1950, he published an article in the journal Mind that asked: Can machines think? He also made significant contributions to theoretical biology, which uses mathematical abstractions in seeking to better understand the structures and systems within living organisms.

A gay man, Turing was prosecuted in 1952 for gross indecency after acknowledging a sexual relationship with a man, which was then illegal in Great Britain, and underwent chemical castration in lieu of a prison sentence. He died by suicide in 1954, age 41.

Before visiting Turings archive, Suttor had read Alan Turing: The Enigma, Andrew Hodges authoritative 1983 biography, and believed the mathematicians life possessed an operatic scale.

I didnt envision a chronological biographical operatic piece, which frankly is a pretty dull proposition, Suttor said. To me, it was much more interesting to investigate Turings ideas. How do you put those on stage and sing about them in a way that is moving, relevant, and dramatically exciting?

Thats when Smita Krishnaswamy, an associate professor of genetics and computer science at Yale, introduced Suttor and his team to OpenAI and several Zoom conversations with representatives of the company about the emerging technology followed. Working with Yale University Librarys Digital Humanities Lab, the team built an interface to interact with an instance, or single occurrence, of GPT-2, training it with materials from Turings archive and the text of books hes known to have read. For example, they knew Turing enjoyed George Bernard Shaws play Back to Methuselah, and Snow White, the Brothers Grimm fairytale, so they shared those texts with the AI.

The team began asking GPT-2 the kinds of questions that Turing had investigated, such as Can machines think? They could control the temperature of the models answers or, the creativity or randomness and the number of characters the responses contained. They continually adjusted the settings on those controls and honed their questions to vary the answers.

Some of the responses are just jaw-droppingly beautiful, Suttor said. You are the applause of the galaxy, for instance, is something you might print on a T-shirt.

In one prompt, the team asked the AI technology to generate lyrics for a sexy song about the operas subject, which yielded the lyrics to Im a Turing Machine, Baby.

In composing the operas music, Suttor and his team incorporated elements of Turings work on morphogenesis the biological process that develops cells and tissues and phyllotaxis, the botanical study of mathematical patterns found in stems, leaves, and seeds. For instance, Suttor found that diagrams Turing had produced showing the spiral patterns of seeds in a sunflower head conform to a Fibonacci sequence, in which each number is the sum of the two before it. Suttor superimposed the circle of fifths a method in music theory of organizing the 12 chromatic pitches as a sequence of perfect fifths onto Turings diagram, producing a unique mathematical, harmonic progression.

Suttor repeated the process using prime numbers numbers greater than 1 that are not the product of two smaller numbers in place of the Fibonacci sequence, which also produced a harmonic series. The team sequenced analog synthesizers to these harmonic progressions.

It sounds a little like Handel on acid, he said.

The workshop version of I AM ALAN TURING was performed on three consecutive nights before a packed house in the CCAM Leeds Studio. The show, in its current form, consists of eight pieces of music that cross genres. Some are operatic with a chorus and soloist, some sound like pop music, and some evoke musical theater. While Suttor composed key structural pieces, the entire team has collaborated like a band while creating the music.

At the same time, the shows storytelling is delivered through various modes: opera, pop, and acted drama. At the beginning, an actor portraying Turing stands at a chalkboard drawing the sunflowers spiral pattern.

Another scene is drawn from a transcript of Turings comments during a panel discussion, broadcast by the BBC, about the potential of artificial intelligence. In that conversation, Turing spars with a skeptical colleague who doesnt believe machines could reach or exceed human levels of intelligence.

Turing made that point during that BBC panel that hed trained machines to do things, which took a lot of work, and they both learned something from the process, Suttor said. I think that captures our experience working with GPT to draft the script.

The show also contemplates Turings sexuality and the persecution he endured because of it. One sequence shows Turing enjoying a serene morning in his kitchen beside a partner, sipping tea and eating toast. His partner reads the paper. Turing scribbles in a notebook. A housecat makes its presence felt.

Its the life that Turing never had, Suttor said.

In high school, Turing had a close friendship with classmate Christopher Morcom, who succumbed to tuberculosis while both young men were preparing to attend Cambridge. Morcom has been described as Turings first true love.

Turing wrote a letter called Nature of Spirit to Christophers mother in which he imagines the possibility of multiple universes and how the soul and the body are intrinsically linked.

In the opera, a line from the letter is recited following the scene, in Turings kitchen, that showed a glimmer of domestic tranquility: Personally, I think that spirit is really eternally connected with matter but certainly not always by the same kind of body.

The show closed with an AI-generated text, seemingly influenced by Snow White: Look in the mirror, do you realize how beautiful you are? You are the applause of the galaxy.

The I AM ALAN TURING experimental opera was just one of many projects presented during Machine as Medium: Matter and Spirit, a two-day symposium that demonstrated the kinds of interdisciplinary collaborations driven by Yales Center for Collaborative Arts and Media (CCAM).

An exhibition at the centers York Street headquarters highlighted works created with, or inspired by, various kinds of machines and technology, including holograms, motion capture, film and immersive media, virtual reality, and even an enormous robotic chisel. An exhibition tour allowed the artists to connect while describing their work to the public. The discussion among the artists and guests typifies the sense of community that CCAM aims to provide, said Lauren Dubowski 14 M.F.A., 23 D.F.A.,CCAM's assistant director,who designed and led the event.

We work to create an environment where anyone can come in and be a part of the conversation, Dubowski said. CCAM is a space where people can see work that they might not otherwise see, meet people they might not otherwise meet and talk about the unique things happening here.

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Opera gives voice to Alan Turing with help of artificial intelligence - Yale News

Five reasons I would take INT D 161 – Artificial Intelligence Everywhere – University of Alberta

Over the past few years, artificial intelligence (AI) has gone from being something I would see in sci-fi movies and shows (always set in the future) to something that feels very present, both in my life and our society. Ive learnt a bit about AI from playing with OpenAIs ChatGPT, checking out Midjourney and reading a few news articles in the media, but at this point, my knowledge of what AI is, how it actually works and where it can be applied feels pretty superficial.

When I learned about the Artificial Intelligence Everywhere course taught by computing science professor Dr. Adam White, I was really excited to check it out. Its really easy to fit into a lot of degree pathways: as an INT D (interdisciplinary) course its open to almost every undergraduate student, and best of all its offered both on-campus (in-person) and asynchronous (online) in Winter 2024, so people can choose what works best for them.

Here are my five big reasons why Im considering registering for this course:

Anyone whos chatted with ChatGPT or asked DALL-E to make an image is often surprised by just hownatural everything feels. Here are a few examples:

While I was used to the magic of computers, processing datasets often required some fiddling with Python or Excel macros, this isnt so straightforward for everyone. Generative AI is massively powerful when its implemented specifically to deal with large datasets, but just pasting a big blob of numbers into ChatGPT can get you some surprisingly useful insights (note: dont try this for anything that actually matters).

On many ualberta.ca web pages, Im running into Vera, the generative-AI-powered chatbot assistant who often has the answer Im looking for. I can text Vera like I text a friend, which feels a lot different than playing with search terms in Google.

And when I need a witty response to the group chat? I want to act like Im coming up with all of my comedic bits on my own, but lets be honestthere mightve been some AI help.

There are a lot of buzzwords being thrown arounddataset, library, iterative processing, neural networks, etc., and I dont really understand what all of these mean or how they fit together. While I could spend some time in a Wikipedia rabbit hole trying to figure out whats going on, the chance to learn from a computing science professor with a strong background in the area sounds a lot more enticing. And these credits apply to a degree? Sign me up!

Theres a lot of talk in the news about what AI means for our society - will it affect jobs? Will it affect learning? Will it go rogue? While I dont think this course will have ALL the answers to ALL of these topics, Id like to be able to form some of my own opinions about AI, and I think a good foundational understanding of it is the right first step. There are famous quotes like the internet is a series of tubes which might show what happens when the people in charge of making major societal decisions about something dont understand it. And I definitely dont want to be caught saying, Well, AI is really just a lot of layered spreadsheets.

There are a ton of job titles like data scientist, CAD modeller, systems administrator, software engineer or web designer that all benefit from (or pretty much require) a strong foundational knowledge of computers and the internet. Im sure that there are going to be a lot of new jobs related to both implementing AI and using it in the workplace and as something without a perfectly clear-cut career path, I want to be ready for these. I feel the foundational knowledge will be really useful to see if I want to pursue a career related to AI.

It wasnt actually that long ago when the internet was launched (the formal date is in the 80s, but it didnt really show up in most homes and schools in Canada until the 90s), and then social media was another big thing that followed in the 2000s. Now these things are everywhere, even though they were pretty niche in the beginning. AI seemed like a sci-fi movie trope until a few years ago, and now, almost everyone I know has used it (well, maybe not my grandparents). Its certainly the next ubiquitous thing, and I want to be ready.

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Five reasons I would take INT D 161 - Artificial Intelligence Everywhere - University of Alberta

Formula One trials AI to tackle track limits breaches – Reuters

[1/2]Artificial Intelligence words are seen in this illustration taken March 31, 2023. REUTERS/Dado Ruvic/Illustration/File Photo Acquire Licensing Rights

ABU DHABI, Nov 23 (Reuters) - Formula One's governing body is trialling artificial intelligence (AI) to tackle track limits breaches at this weekend's season-ending Abu Dhabi Grand Prix.

The Paris-based FIA said it would be using 'Computer Vision' technology that uses shape analysis to work out the number of pixels going past the track edge.

The AI will sort out the genuine breaches, where drivers cross the white line at the edge of the track with all four wheels, reducing the workload for the FIA's remote operations centre (ROC) and speeding up the response.

The July 2 Austrian Grand Prix was a high water mark for the sport with just four people having to process an avalanche of some 1,200 potential violations.

By the title-deciding Qatar weekend in October there were eight people assigned to assess track limits and monitor 820 corner passes, with 141 reports sent to race control who then deleted 51 laps.

Some breaches still went unpunished at October's U.S. Grand Prix in Austin, however.

Stewards said this month that their inability to properly enforce track limits violations at turn six was "completely unsatisfactory" and a solution needed to be found before the start of next season.

Tim Malyon, the FIA's head of remote operations and deputy race director, said the Computer Vision technology had been used effectively in medicine in areas such as scanning data from cancer screening.

"They dont want to use the Computer Vision to diagnose cancer, what they want to do is to use it to throw out the 80% of cases where there clearly is no cancer in order to give the well trained people more time to look at the 20%," he said.

"And thats what we are targeting."

Malyon said the extra Computer Vision layer would reduce the number of potential infringements being considered by the ROC, with still fewer then going on to race control for further action.

"The biggest imperative is to expand the facility and continue to invest in software, because thats how well make big strides," he said. "The final takeaway for me is be open to new technologies and continue to evolve.

"Ive said repeatedly that the human is winning at the moment in certain areas. That might be the case now but we do feel that ultimately, real time automated policing systems are the way forward."

Reporting by Alan Baldwin in London, editing by Toby Davis

Our Standards: The Thomson Reuters Trust Principles.

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Formula One trials AI to tackle track limits breaches - Reuters

Inventorship and Patentability of Artificial Intelligence-Based … – Law.com

The concept of inventorship continues to evolve with the advent of artificial intelligence (AI). AI-generated inventions spur disagreement among Patent Offices across the world as to who, or what, qualifies as an inventor in patent applications. The quandary is whether an AI platform that assists in creating an invention should be named as an inventor in a patent. For example, an AI-powered system may be employed pharmaceutically to identify molecular compounds in the discovery of a newly invented drug, without much human involvement. Does such AI assistance rise to the level of inventorship? The answer is nonot in the United Statesaccording to the U.S. Court of Appeals for the Federal Circuit. See Thaler v. Vidal, 43 F.4th 1207, 1213 (Fed. Cir. 2022).

In a hallmark decision, the Court of Appeals for the Federal Circuit recently established that artificial intelligence cannot be named as an inventor on a U.S. patent. In Thaler v. Vidal, Dr. Stephen Thaler represented that he developed an AI platform named DABUS (device for the autonomous bootstrapping ofunified sentience) that created inventions. Thaler subsequently filed two patent applications at the U.S. Patent and Trademark Office (USPTO) for inventions generated by DABUS, attempting to list the DABUS-AI system as the inventor. The USPTO declined Thalers request. The circuit court affirmed, holding that only a human being can be an inventor in the United States. See Thaler, 43 F.4th at 1209, 1213.

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Inventorship and Patentability of Artificial Intelligence-Based ... - Law.com

The Top 2 Artificial Intelligence (AI) Companies Revolutionizing the … – The Motley Fool

Artificial intelligence (AI) and machine learning (ML) are more than just buzzworthy terms for some cutting-edge companies. They are the foundations on which incredible businesses have been built. Even better, some of these companies make hay in industries essential to the economy.

Cybersecurity is top of mind for C-suite executives in all industries, government agencies, school districts, and even nonprofits. Cybercriminals are always on the prowl, costing organizations billions each year. IBM notes that up to 90% of cyberattacks and 70% of breaches come through endpoint devices.

AI-powered CrowdStrike Holdings (CRWD 0.30%) is the leader in endpoint security with a comprehensive, entirely cloud-based platform. The company's results are on fire, as I'll discuss below.

Meanwhile, data centers are crucial for cloud applications, data storage, computing power, and (definitely) complex AI and ML software that require massive computing power. Nvidia (NVDA -2.46%) is light-years ahead of its competition, and its data center software and hardware are mission critical. This is why its data center revenue rose 171% year over year last quarter to $10.32 billion.

CrowdStrike provides comprehensive security with its Falcon platform. The advantages are several: Falcon is cloud-native (no on-premises hardware required), customizable, and uses AI to analyze data and provide real-time protection.

The platform is modular, so customers can choose which modules they want or need. This plays into CrowdStrike's land-and-expand strategy: It gains a customer, proves the platform's worth, and then the customer adds more modules -- creating more revenue.

This shows up in the company's dollar-based net retention rate (DBNR), which has been above 120% dating back to the first quarter of fiscal 2019. DBNR measures the year-over-year increase in sales from an average customer. Above 100% is good, and above 120% is excellent.

You can probably guess how the chart of annual recurring revenue (ARR) growth looks:

Source: CrowdStrike.

The meteoric rise to $2.9 billion in ARR has enabled CrowdStrike to generate $416 million in free cash flow through the second quarter of this 2024 fiscal year and stack up $3.2 billion in cash against $742 million in long-term debt. Having cash on hand to fund growth is crucial in this environment, and the company likely won't have to borrow money at unfavorable interest rates.

CrowdStrike has a market cap near $50 billion, about 16 times Wall Street estimates for sales this fiscal year (which ends Jan. 31, 2024), and 13 times Wall Street estimates for the next fiscal year. That's not necessarily cheap (great companies usually aren't), but it is less than other growth companies like Snowflake and Palantir Technologies. In short, it's a great company, but consider dollar-cost averaging to take advantage of dips in the stock price along the way.

Nvidia is top of mind as investors await Tuesday's 2024 third-quarter earnings report. The stock is near another all-time high after a brief pullback recently. It has risen 237% so far in 2023 for a simple reason: Business is absolutely booming.

At the top, I mentioned the rise in data center sales, and this demand gives it pricing power in the industry. So profits and margins are soaring alongside revenue, as shown below.

NVDA operating income (quarterly) data by YCharts.

The company more than doubled operating revenue from the first quarter to the second this year, and its 50% margin is spectacular. Unfortunately, the secret is out, and the stock isn't cheap. Nvidia needs to continue raising Wall Street's estimate to maintain its valuation.

Nvidia's current price-to-earnings (P/E) ratio is 119, ridiculous on the surface. But the P/E is backward-looking -- it uses earnings that have already happened, while Wall Street is about the future. Based on the market's estimates for next year, the P/E falls to 45, then to 29 the following year. This is nearly identical to Microsoft's current valuation, as shown below.

NVDA PE ratio (forward 1 year) data by YCharts.

This tells me that the stock isn't tremendously expensive; however, Nvidia must push the envelope to give investors more juicy gains.

Bradley Guichard has positions in CrowdStrike and Nvidia and has the following options: long September 2024 $630 calls on Nvidia. The Motley Fool has positions in and recommends CrowdStrike, Nvidia, Palantir Technologies, and Snowflake. The Motley Fool recommends International Business Machines. The Motley Fool has a disclosure policy.

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The Top 2 Artificial Intelligence (AI) Companies Revolutionizing the ... - The Motley Fool

Artificial Intelligence (AI) and Human Intelligence (HI) in the future of … – TechNode Global

In an era of rapid technological advancement, the dynamic interplay between Artificial Intelligence (AI) and Human Intelligence (HI) is shaping the future of education. As we peer into the horizon, it becomes increasingly clear that our approach to preparing the next generation for the challenges and opportunities that await must evolve. Here, we explore how AI and HI are set to play harmonious, complementary roles in the realm of preschool education and beyond.

Before we embark on this educational journey, it is crucial to envision the future professions that will shape the educational landscape. Two significant examples illustrate the evolving role of AI in various fields:

Future-proofing students for a rapidly evolving world equips students to be both AI-competent and distinctly human.

The collaboration between AI and human educators forms the core of the new educational landscape. This symbiotic relationship aims to merge the precision and efficiency of AI with the empathetic and creative guidance provided by human mentors. Heres how this partnership is poised to revolutionize education:

The integration of AI in preschool education unfolds a unique paradigm where young children can seamlessly transition between the roles of the tutee and the tutor, fostering a multifaceted and enriching educational experience. This concept manifests in three distinct applications of AI in education: as a tutor, as a tutee, and as a tool.

In essence, this multifaceted interaction with AI establishes a symbiotic relationship where the roles of teacher and student are fluid. By seamlessly transitioning between these roles, preschool children not only benefit from tailored guidance but also actively engage with AI as a creative collaborator and a student, cultivating a well-rounded skill set that extends beyond conventional learning approaches.

In summary, the future of education hinges on the collaborative efforts of human educators and AI. Together, they create an educational ecosystem that leverages the strengths of each, ensuring that students are not only equipped with knowledge but also possess the essential skills and attributes needed to thrive in a future where human qualities play a pivotal role.

Dr. Richard Yen, Harvard University PhD, founder of Ednovation, which develops edtech and operates Cambridge, ChildFirst, and Shaws Preschools in Singapore, South East Asia, and China.

TNGlobal INSIDERpublishes contributions relevant to entrepreneurship and innovation. You maysubmit your own original or published contributionssubject to editorial discretion.

How Southeast Asias SMEs can benefit from digital transformation and cloud combined

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Robo Global Artificial Intelligence ETF: A Diversified AI Play (THNQ) – Seeking Alpha

BlackJack3D

There's more to AI than Nvidia. This is why the Robo Global Artificial Intelligence ETF (NYSEARCA:THNQ) is an interesting way for investors to access artificial intelligence and robotics. What I like about the fund is that it's very well diversified, making it a pure thematic play beyond the idiosyncratic aspect of just a select number of stocks in the space.

THNQ seeks to track the ROBO Global Artificial Intelligence Index. This index aims to track companies that generate a significant portion of their revenues from the AI market. THNQ offers a diversified strategy for investors, providing exposure to the very best public companies from around the globe, irrespective of their size and location. The fund serves as an excellent platform for investors to capitalize on the expected growth in AI and robotics, sectors that are transforming virtually every industry across the globe.

THNQ strives for a balance between growth and value, focusing on companies with strong business models and positive cash flows. The fund is rebalanced on a quarterly basis to ensure it consistently holds the most innovative and promising companies in the AI and robotics sectors. The ETF is not limited to technology companies; it also includes firms from the consumer cyclical, communication, and healthcare sectors, among others. Geographically, THNQ's holdings are diverse, with significant exposure to non-U.S. markets, particularly in Europe and East Asia.

ycharts.com

I mentioned at the start of the writing that this is a well-diversified fund. No holding currently makes up more than 2.71% of the fund, and crowd favorite Nvidia is currently ranked 8 in the top 10. Again - I very much like this. It makes this a far more nuanced and diversified way of playing AI than other products where Nvidia is the biggest holding.

roboglobaletfs.com

The sector composition of THNQ is diverse, ensuring that investors gain exposure to various segments of the economy. As you'd expect, the majority of the fund is in the Technology space, but it's not a pure tech fund in that it does have stocks from non-tech groups.

ycharts.com

When comparing THNQ to its peers, it's important to note that it outperformed the TrueShares Technology, AI & Deep Learning ETF (LRNZ) which is another fund in the space. LRNZ is considerably less diversified with top holdings having more concentration risk than THNQ.

stockcharts.com

Investing in AI and robotics comes with its share of advantages and potential risks.

On the positive side, these sectors are experiencing unprecedented growth due to advancements in technology and increasing adoption across different industries worldwide. Furthermore, AI and robotics offer substantial potential for innovation, making them attractive sectors for forward-thinking investors.

On the flip side, investing in AI and robotics also carries risks. These include regulatory uncertainties, privacy concerns, and potential job displacements due to automation. Moreover, these sectors are highly competitive, requiring constant innovation and substantial capital expenditure.

Personally, I think THNQ is a solid avenue for investors looking to gain exposure to the rapidly growing fields of AI and robotics. It's well diversified, and if you believe that AI is unstoppable, despite relatively weak performance as of late, this becomes a good fund to access the trend.

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Robo Global Artificial Intelligence ETF: A Diversified AI Play (THNQ) - Seeking Alpha

Artificial intelligence finds ways to develop new drugs – Mirage News

One activation method that opens up a great many possibilities for different functional groups, at least on paper, is borylation. In this process, a chemical group containing the element boron is bonded to a carbon atom in the scaffold. The boron group can then simply be replaced by a whole range of medically effective groups.

"Although borylation has great potential, the reaction is difficult to control in the lab. That's why our comprehensive search of the worldwide literature only turned up just over 1,700 scientific papers on the subject," Atz says, describing the starting point for his work.

The idea was to take the reactions described in the scientific literature and use them to train an AI model, which the research team could then use to consider new molecules and identify as many sites as possible on them where borylation would be feasible. However, the researchers ultimately fed their model only a fraction of the literature they found. To ensure that the model wasn't misled by false results from careless research, the team limited itself to 38 particularly trustworthy papers. These described a total of 1,380 borylation reactions.

To expand the training dataset, the team supplemented the literature results with evaluations of 1,000 reactions carried out in the automated laboratory operated by Roche's medicinal chemistry research department. This allows many chemical reactions to be carried out at the milligram scale and analysed simultaneously. "Combining laboratory automation with AI has enormous potential to greatly increase efficiency in chemical synthesis and improve sustainability at the same time," says David Nippa, a doctoral student from Roche who accomplished the project together with Atz.

The predictive capabilities of the model generated from this data pool were verified using six known drug molecules. In five out of six cases, experimental testing in the laboratory confirmed the predicted additional sites. The model was just as reliable when it came to identifying sites on the scaffold where activation isn't possible. What's more, it determined the optimum conditions for the activation reactions.

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Artificial intelligence finds ways to develop new drugs - Mirage News

How an ‘internet of AIs’ will take artificial intelligence to the next level – Cointelegraph

HyperCycle is a decentralized network that connects AI machines to make them smarter and more profitable. It enables companies of all sizes to participate in the emerging AI computing economy.

Artificial intelligence (AI) is a rapidly evolving field that seems likely to fall into the hands of major companies or organizations with nationally driven budgets. One might think that only these have the massive financial resources to generate the computing power to train and ultimately own AI.

Recent events at OpenAI, a developer of the AI chatbot ChatGPT, highlight the challenges of centralized AI development. The firing of CEO Sam Altman and the resignation of co-founder Greg Brockman raise questions about governance and decision-making in centralized AI entities and highlight the need for a more decentralized approach. Srinivasan Balaji, a former chief technology officer at Coinbase, has become a staunch proponent for increased transparency in the realm of AI, advocating for the adoption of decentralized AI systems.

In addition to centralization, theres a lot of fragmentation in the AI space, meaning cutting-edge systems are unable to communicate with one another. Moreover, a high degree of centralization brings considerable security risks and reliability issues. Plus, given the vast amounts of computing power needed, efficiency and speed are key.

To achieve the full potential of AI that answers to all of humanity, we need a different approach one that decentralizes AI and allows AI systems to communicate with each other, eliminating the need for intermediaries. This would increase AI systems time to market, intelligence and profitability. While many systems are currently specialized in specific tasks, such as voice or facial recognition, a future shift to artificial general intelligence could allow one system to undertake a wide range of tasks simultaneously by delegating those tasks to multiple AIs.

As mentioned above, currently, the AI industry is dominated by large corporations and institutional investors, making it difficult for individuals to participate. HyperCycle, a novel ledgerless blockchain architecture, emerges as a transformative solution, aiming to democratize AI by establishing a fast and secure network that empowers everyone, from large enterprises to individuals, to contribute to AI computing.

HyperCycle is powered by a layer 0++ blockchain technology that enables rapid, cost-effective microtransactions between diverse AI agents interconnected to each other, and collectively solving problems.

This internet of AIs allows systems to interact and collaborate directly without intermediaries. It addresses the challenges of overcoming the slow, costly processes of the siloed AI landscape.

This is particularly timely, as the number of machine-to-machine (M2M) connections globally is increasing rapidly.

For instance, existing companies could interact with HyperCycles AIs specializing in IoT, blockchain, and supply chain management to optimize logistics for clients, predict maintenance before breakdowns occur, and ensure seamless data integrity. By enabling this interconnected ecosystem of decentralized A Is, HyperCycle can lead to operational efficiency and innovation in service offerings.

HyperCycle has also partnered with Penguin Digital to create HyperPG, a service that connects all the network beneficiaries together. HyperPG uses Paraguays abundant hydropower to provide a green and efficient source of energy for AI computing.

One of HyperCycles key features is the HyperAiBox, a plug-and-play device that allows individuals and organizations to perform AI computations at home and reduces their reliance on large corporations with vast data centers. The compact box is about the size of a modem, has a touchscreen, and allows nodes to be operated from home and network participants to be compensated for the resources they provide to the network. It is also a low-power solution.

The launch of HyperCycles mainnet, ahead of schedule, highlights the networks rapid growth. Currently, over 59,000 initial nodes are providing Uptime to the network by covering operational expenses. An additional 230,000 single licenses will soon join the ecosystem. This expansion indicates a strong demand for over 295 million HyPC tokens, reflecting the networks engagement and growth.

The three key metrics of Uptime, Computation, and Reputation incentivize node operators to maintain high standards, ensuring a stable, secure, and decentralized network environment.

Since June 2023, HyperCycles network has been operational, scaling up as demand increases. Source: HyperCycle

AI remains at a nascent stage, but HyperCycles goal is to anticipate the challenges that might stand in this technologys way and break down barriers to entry, making AI more accessible and affordable to everyone.

Disclaimer. Cointelegraph does not endorse any content or product on this page. While we aim at providing you with all important information that we could obtain in this sponsored article, readers should do their own research before taking any actions related to the company and carry full responsibility for their decisions, nor can this article be considered as investment advice.

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How an 'internet of AIs' will take artificial intelligence to the next level - Cointelegraph

JPMorgan’s George Gatch says artificial intelligence gives them firm … – The Australian Financial Review

JPMorgans asset management division employs 1300 portfolio managers and research analysts globally across stocks, bonds, derivatives and alternative asset classes, with $US400 million a year invested into technology to leverage AI and machine learning models.

That hasnt stopped JPMorgans rivals from also investing, with a PwC global asset management survey showing that more than 90 per cent of investment firms are already using disruptive technology such as AI within their business.

On AI, we decided a long time ago to build our own tech and not rent someone elses, Mr Gatch said. I think thats now a competitive advantage for our portfolio managers and clients.

The global market for AI in asset management is estimated to be worth about $US2.6 billion in 2022 and is expected to expand at a compound annual growth rate of 24.5 per cent over the next seven years, according to one estimate by US firm Grand View Research.

Earlier this year BlackRock, the worlds largest asset manager, described AI in its mid-year investment outlook as a mega force trend that would help unlock the value of the data gold mine some companies may be sitting on.

Elsewhere, JPMorgan is among a slew of investment banks, including Macquarie, that are launching more ETF products into the Australian market to challenge the dominance of BlackRock, Vanguard and State Street.

Mr Gatch said the global ETF industry had attracted $US1.4 trillion of funds in 2022, versus $US700 billion for traditional investment funds unlisted on exchanges.

In Australia, data from Betashares shows the local ETF industry recorded $13.5 billion of net inflows last year, versus outflows of $26.8 billion from unlisted managed funds.

JPMorgans strategy to grab market share is to offer so-called active ETFs that may outperform the traditional index-tracking products. The firm forecasts active ETF inflows to grow at a 40 per cent annual rate for the next five years, compared to 17 per cent for indexed ETFs.

That has big implications for how we run our business and whats happening is fairly astonishing, Mr Gatch added.

The story is no longer about indexing, we think that [active] will drive a wave of dramatic growth into the industry.

The JPMorgan Equity Premium Income Product is said to have attracted more inflows than any other ETF in 2023, with net assets of around $US29 billion in November. Much of its popularity is due to an active strategy of selling call options that provide extra income if the market falls or tracks sideways.

On fees, the CEO said asset managers, including the ETF sector, remained under pressure, but JPMorgans investment in digital currency and blockchain technology could eventually bring costs down.

Were doing a bunch of stuff on blockchain, he said. We have working groups looking at tokenisation for private markets, how to improve liquidity between institutions for private credit. Its going to take time, but weve got smart people, and operational efficiency is important.

As for JPMorgan launching a bitcoin ETF, its not on the agenda anytime soon. No, weve not done [regulatory] filings.

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JPMorgan's George Gatch says artificial intelligence gives them firm ... - The Australian Financial Review

Big brother: Democrat-led NTSB pushes for artificial intelligence … – Must Read Alaska

A National Transportation Safety Board investigation into a 2022 fatal crash inNorth Las Vegas, Nevada, that resulted in nine fatalities has given the board an excuse to recommend a new requirement for intelligent speed assistance technology in all new cars.

The board issued the recommendations earlier this month at a public meeting after determining the crash was caused by high speed, drug-impaired driving, and Nevadas failure to deter one drivers speeding recidivism due to systemic deficiencies, despite numerous speeding citations.

Intelligent speed assistance technology, or ISA, uses a cars GPS location compared with a database of posted speed limits and its onboard cameras to either issue a warning to drivers or to throttle back speed.

Passive ISA systems warn a driver when the vehicle exceeds the speed limit through visual, sound, or haptic alerts, and the driver is responsible for slowing the car.

Active systems include mechanisms that make it more difficult, but not impossible, to increase the speed of a vehicle above the posted speed limit and those that electronically limit the speed of the vehicle to fully prevent drivers from exceeding the speed limit.

This crash is the latest in a long line of tragedies weve investigated where speeding and impairment led to catastrophe, but it doesnt have to be this way, said NTSB Chair Jennifer Homendy. We know the key to saving lives is redundancy, which can protect all of us from human error that occurs on our roads. What we lack is the collective will to act on NTSB safety recommendations.

Homendy is a Democrat who served more than 14 years as Democratic staff director for the Subcommittee on Railroads, Pipelines, and Hazardous Materials of the Committee on Transportation and Infrastructure in the U.S. House of Representatives. She worked for the International Brotherhood of Teamsters, AFL-CIO, and American Iron and Steel Institute.

Eliminating speeding through the use of federally mandated speed limiters built into cars is a priority for the NTSB, which seeks to Develop performance standards for advanced speed-limiting technology, such as variable speed limiters and intelligent speed adaptation devices, for heavy vehicles, including trucks, buses, and motorcoaches. Then require that all newly manufactured heavy vehicles be equipped with such devices.

In 2021, speeding-related crashes resulted in 12,330 fatalitiesabout one-third of all traffic fatalities in the United States, the NTSB said.

However, according to the latest figures from AAA, 245 million drivers made a total of 229 billion driving trips, spent 91 billion hours driving, and drove 2.92 trillion miles in 2021. That means out of every 91 million hours of driving, there are 12,330 fatalities, or one fatality for every 7.3 million hours of driving.

According to the National Safety Council, the rates of fatal car accidents has greatly improved over the decades. This is due, in part, to the numerous safety features now required in cars, such as seatbelts, air bags, and backup cameras, which were mandated in 2018.

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Big brother: Democrat-led NTSB pushes for artificial intelligence ... - Must Read Alaska

Artificial Intelligence and Automation in Engineering – Drishti IAS

Artificial Intelligence (AI) and automation have had a profound impact on the field of engineering. These technologies have the potential to revolutionise the way engineers design, analyse, and optimise systems and processes. However, it's important to note that while AI and automation offer tremendous benefits, they also come with challenges, including ethical considerations, job displacement concerns, and the need for robust cyber security. Engineers and organisations need to carefully plan and implement these technologies to maximise their advantages while addressing potential drawbacks.

The emergence of Artificial Intelligence (AI) in engineering has been a transformative development that has significantly impacted various engineering fields. AI technologies, such as machine learning and deep learning, have been applied to engineering tasks to enhance efficiency, accuracy, and innovation. Machine learning will be among the top engineering talents in demand in 2022. Learning how to incorporate AI into processes is already in demand due to engineers' extraordinary capacity for solving complicated challenges.

90% of major corporations are thought to have made some kind of investment in artificial intelligence (AI) technologies. Less than 15% of these firms, however, are currently using AI in their working environment. AI is one of the technologies with the quickest growth in the engineering industry. Even while there has always been some worry that AI may eliminate some occupations, the current state of affairs is that new technology is creating a variety of chances for engineering skills.

AI is used in manufacturing at many phases of the production process to increase productivity, accuracy, and automation. It uses machine learning, data analysis, and algorithms to let robots do tasks that once required direct human interaction. Utilising characteristics like predictive maintenance, quality control, process enhancement, and others, this technology boosts output and decreases downtime. By analysing vast amounts of data in real-time, AI-driven systems can make sensible decisions, optimise processes, and identify trendspeople would miss.

AI and automation have significant advantages for businesses since they can increase production, efficiency, and financial performance. Enhanced Productivity Enhanced Efficiency, Improved Data Analysis and More favourable bottom-line results are some major advantages. However,there are also many challenges in developing and using AI for automotive electronics, including complexity, dependability, security, and regulation.

AI algorithms can be used to analyse sensor data from structures, such as temperature and vibration data, to forecast when maintenance is necessary,and to spot warning indications of structural breakdown before they materialise. AI-powered cameras are used for inspection and surveillance. Artificial intelligence-driven structural analysis systems may simulate and assess complicated structural behaviour, assisting engineers in locating possible weak points, foretelling failure modes, and improving structural performance. By quickly adapting to user preferences, AI-powered optimisation attempts to improve the personalisation, cost-effectiveness, and utility of digital experiences. With the help of this technology, organisations can make data-driven decisions that enhance the functionality of their websites, user engagement, and rates of conversion.

Machine Learning (ML) optimises energy efficiency models, predicting the consumption of energy tools. Over the last five years, ML techniques gained traction in designing energy-efficient systems amid rising demand for technologies like smart buildings and IOTs (Internet of Things). Sustainable growth in smart cities relies on technological advancements, merging sustainability with energy efficiency. Artificial Intelligence (AI) plays a vital role in managing, coordinating, and forecasting electricity supply. The global push for a low-carbon transition amplifies the significance of AI in achieving energy goals. AI-driven "smart consumption" transforms energy usage patterns, enabling decentralised power grids for balanced energy flows.

Systems with artificial intelligence (AI) can be used to identify and detect traffic events such asaccidents, wrong-way driving, speeding, or roadblocks. Real-time traffic data is analysed using AI from a variety of cameras and IoT devices, including cars, buses, and even trains. As over 90% of accidents are the result of human error, it is anticipated to drastically reduce the number of accidents. AVs (Autonomous Vehicles) can lower the cost of travel. For instance, AVs will save labour expenses when used in public transportation. With smart carpooling, costs can be further reduced. By removing the need for human drivers, a driverless car might significantly ease traffic congestion. This may lead to a significant increase in car sharing, which would reduce the number of vehicles on the road and the overall carbon footprint compared to more conventional modes of transportation.

Integrating AI and automation into engineering processes offers numerous benefits, such as increased efficiency, improved accuracy, and cost reduction. However, it also presents several challenges and ethical considerations like safety and reliability, Algorithm Complexity, Human-AI Collaboration, Integration with Existing Systems and Ethical Considerations (data collection, privacy, and decision-making). Concerns about job displacement and human-AI collaboration have been growing as artificial intelligence and automation technologies continue to advance. These concerns centre on the potential for AI and automation to replace human workers in various industries, leading to job loss and economic disruption. However, it's important to note that these concerns are not without nuance, and there are also opportunities for collaboration between humans and AI that can lead to more productive and fulfilling work environments.

Digital twins, virtual replicas of physical entities, leverage real-time data, simulation, analytics, and visualisation. Enhancing decision-making, they cut costs and boost efficiency. Manufacturers benefit by integrating digital twins seamlessly, reducing expenses and accelerating value. Architects and engineers employ digital twins in building design, incorporating details on use, materials, and maintenance. This streamlines construction oversight and communication, ensuring better quality.

AI-driven maintenance prediction is transforming asset management, using historical data and real-time analysis to predict equipment failures and facilitate proactive maintenance. By identifying flaws and analysing behavioural patterns, AI recommends optimal times for replacements or repairs, reducing emergency repairs. In various industries, AI enhances data analytics, offering valuable insights into market trends, client preferences, and business strategies. AI-generated maintenance schedules prevent over-maintenance and minimise breakdowns, conserving resources. For example, AI monitors machinery spindles in milling operations, reducing the need for costly repairs. This innovative approach optimises efficiency and minimises wasteful spending.

AI systems face risks such as adversarial machine learning attacks, where attackers manipulate input data to alter the model's output, potentially leading to poor decision-making and security vulnerabilities. Privacy concerns revolve around the increased likelihood of data breaches and unauthorized access to personal information. With the vast amount of data being collected, there's a risk of misuse through hacking or security flaws. Organizations must regularly assess their infrastructure's security, identify vulnerabilities, and prioritize corrections to safeguard against cyber threats. This involves timely application of security patches, software and hardware updates, and implementation of robust security configurations.

Designing AI systems with human factors in mind is crucial to ensure usability, safety, and user acceptance. User experience considerations play a pivotal role in AI-integrated engineering solutions, as they directly impact how users interact with and perceive AI technologies. It not only improves the usability, safety, and acceptance of AI but also helps avoid potential pitfalls and negative consequences associated with poorly designed systems. By prioritising user experience considerations, AI engineers can create solutions that are not only technically proficient but also genuinely beneficial and user-friendly. Designing AI systems that complement human capabilities rather than replace them is very significant. When users see AI as a helpful tool that enhances their work, they are more likely to accept and use it.

In the past, it was believed that AI would eventually displace workers. Organisations observe that AI is expanding export opportunities and building a highly qualified workforce. Additionally, as automation and AI can now finish the fundamental and monotonous duties, engineering roles can concentrate more on activities that bring value, making engineering employment much more dynamic and fulfilling.

The future advancements of AI and automation in engineering hold immense promise, with several exciting trends and developments on the horizon like aerospace, electronics, energy storage, etc. Quantum algorithms can also be used for tasks like molecular modelling, optimising supply chains, and solving complex equations in real time. Generative design, powered by AI, is transforming how engineers approach product design. This can lead to highly efficient and innovative designs in various industries, including automotive and architecture. We can expect to see more autonomous drones, self-driving vehicles, and robotic systems in manufacturing and logistics. These technologies will improve efficiency, safety, and precision in various engineering applications.

It's important to note that while these advancements offer numerous benefits, they also come with challenges, including ethical concerns, cyber security risks, and the need for up-skilling the workforce. Engineers and organisations should stay informed and adapt to these emerging technologies to harness their full potential while addressing associated challenges.

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Artificial Intelligence and Automation in Engineering - Drishti IAS

‘There’s almost nothing more important’: Local Holocaust survivors living on through artificial intelligence – WCPO 9 Cincinnati

CINCINNATI Artificial intelligence is creating a new way for individuals to learn about the Holocaust.

At the Nancy and David Wolf Holocaust & Humanity Center, the Dimensions in Testimony exhibit features testimony from Pinchas Gutter, a man now living in Canada but who spent time in six Nazi concentration camps as a young boy.

Visitors can ask him questions about his experience, how he feels about being a hologram, his favorite foods, his message to young people and pretty much anything else they can think of.

Gutter sat for several full days of recording. Artificial intelligence is used to understand questions and retrieve the most appropriate responses.

Holland Rains/WCPO

Because the algorithm pulls only from the testimony of the survivor, there is no risk for hallucination, which is when an AI model generates false or misleading information, museum representatives said.

Al Miller, a Jewish resident of Hamilton, Ohio, escaped Nazi Germany in 1937. He returned to Germany for the U.S. Army to interrogate suspected war criminals as a Ritchie Boy.

Last year, at the age of 100, Miller recorded his testimony for five full days of recordings. His daughter-in-law, Barbara Miller, who is also on the board of the museum, said this type of technology is a significant development for Holocaust education.

Theres almost nothing more important we can do than to share these stories, she said. Young people, in particular, many of whom know nothing about the Holocaust, need to be educated.

A December 2023 YouGov pollfound 20% of young people strongly agree or tend to agree that the Holocaust is a myth.

Barbara said Al found it important to share his story, no matter the crowd size: As long as he could make an impact and talk to them and inspire them, he felt he had done his job.

The museum said Als testimony, along with survivor and retired University of Cincinnati professor Henry Fenichel, will be available in early 2025.

Barbara Miller said that Al's message was always the same: "The Holocaust didn't start with bullets, it started with words."

She said she's worried that is something that is coming to fruition in the United States. The Anti-Defamation League has reported an increase in antisemitic incidents following Hamas' surprise attack in Israel on October 7, 2023.

Various artifacts from Millers experience are featured throughout the museum. Barbara said those items will be enhanced by museum guests getting an opportunity to speak with him.

Al had a tremendous sense of giving back. And he really wanted to ensure that the lessons of the Holocaust would not repeat, she said.

His efforts will continue.

Kara Driscoll, Director of Marketing & Events at Holocaust & Humanity Center said data shows that students, often digital natives, feel more comfortable interacting with this technology than they might talking to someone across from them.

This technology allows us to interact with their stories, their biographies, and keep their memories alive in an interactive way that is really meaningful to the visitors that experience it, she said.

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'There's almost nothing more important': Local Holocaust survivors living on through artificial intelligence - WCPO 9 Cincinnati

Artificial Intelligence May Predict Ovarian Cancer Therapy Outcomes – Curetoday.com

An artificial intelligence model showed promise in predicting ovarian cancer outcomes.

An artificial intelligence model called IRON (Integrated Radiogenomics for Ovarian Neoadjuvant therapy) shows an 80% accuracy rate in the prediction of therapy outcomes for patients with ovarian cancer. The artificial intelligence model focuses specifically on the volumetric reduction of tumor lesions within this patient population, according to a press release.

This tool surpassed the efficiency of present clinical methods, as IRON uses an approach that focuses on a patients liquid biopsy (cancer-specific information that can be observed via blood tests), overall health characteristics such as age, health status, tumor markers and disease images that were captured during CT scan images.

A recent research study, which was featured in Nature Communications, focused on 134 patients who had been diagnosed with high-grade ovarian cancer. Dr. Evis Sala, chair of Diagnostic Imaging and Radiotherapy at the Faculty of Medicine and Surgery of the Catholic University and Director of the Advanced Radiology Center at the Policlinico Universitario A. Gemelli IRCCS ran the study and the AI model was created by Professor Salas team at the University of Cambridge.

"We compiled two independent datasets with a total of 134 patients (92 cases in the first dataset, 42 in the second independent test set)," Sala and Dr. Mireia Crispin Ortuzar from Cambridge said in the press release.

When it comes to a precise accuracy rate in high-grade ovarian carcinoma, therapy response predictions result to about 50% accuracy. As there were a few significant biomarkers used for this type of cancer, the IRON model was able to predict chemotherapy responders more accurately.

Notably, this is not the first study showing that artificial intelligence has the potential to predict cancer outcomes. Earlier this year, research found that artificial intelligence may help determine which patients with prostate cancer were more likely to benefit from hormone therapy plus radiation. Additionally, another group of researchers also showed that artificially intelligence may play a role in diagnosing sarcopenia in patients with head and neck cancer.

Within the study, demographic information, treatment details, blood biomarkers (CA-125, which could indicate the growth of ovarian cancer) and circulating tumor DNA (ctDNA, which is bits of cancer DNA that can be observed on a blood test) were collected from patients. CT scans were also found and characteristics of the tumor were obtained throughout the CT scans.

Where disease spread in the initial stage was investigated within omental and pelvic/ovarian regions. Omental deposits showed more of a response compared to pelvic disease when it came to neoadjuvant (presurgical) therapy. Before and after therapy responses, tumor mutations and CA-125 had correlation to the overall disease burden, according to the press release.

Analyzation of CT scans showed that six patient subgroups, classified by biological and clinical characteristics became indicators of therapy responses. The efficiency of the model was shown throughout the independent patient sample shown within the study.

"From a clinical perspective, the proposed framework addresses the unmet need to early identify patients unlikely to respond to neoadjuvant therapy and may be directed to immediate surgical intervention," Sala emphasized. "The tool could be applied to stratify the risk of each individual patient in future clinical research...

For more news on cancer updates, research and education, dont forget tosubscribe to CUREs newsletters here.

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Artificial Intelligence May Predict Ovarian Cancer Therapy Outcomes - Curetoday.com

The Synergy of Startups and Artificial Intelligence: | by Dr Richard Matthews – Chief AI Officer RHEM Labs | Jan, 2024 – Medium

In the rapidly evolving landscape of technology, the fusion of startups and artificial intelligence (AI) has emerged as a beacon of innovation, reshaping industries and redefining the boundaries of what is possible. This dynamic duo is not just a trend but a transformative force, with startups leveraging AI to solve complex problems, enhance efficiency, and create unprecedented value; but it is not without challenges.

The world of technology is witnessing a remarkable era where artificial intelligence has become the cornerstone of innovation.

Amidst this technological renaissance, startups play a crucial role, acting as the crucibles where the raw potential of AI is refined into groundbreaking applications.

These nimble entities, characterized by their innovative spirit, flexibility, and willingness to try anything, are exploring AIs capabilities to attack the status quo by offer solutions that were once discounted as science fiction.

Today you can:

All thanks to the power of AI and emergence of integrating technologies such as mixed reality and the metaverse.

But why are Startups where all of this magic is happening?

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The Synergy of Startups and Artificial Intelligence: | by Dr Richard Matthews - Chief AI Officer RHEM Labs | Jan, 2024 - Medium

If artificial intelligence is going to get involved in elections, Colorado lawmakers want voters to know – Colorado Public Radio

Failure to disclose that content was created using artificial intelligence could incur a financial penalty.

Other states have made efforts in recent years to regulate AI election content, with mixed results. Michigan, Minnesota, and Washington state all passed legislation last year to address the issue. But proposals to require disclosure have failed elsewhere, including Indiana, Illinois, and New York according to the National Conference of State Legislatures.

Those are the kinds of things that, when done in proximity to an election, can upend what people want to do in that election, how they vote if they vote, and that is a threat to democracy, said Titone. Shes not just worried about local actors, but that foreign adversaries might take advantage of this technology to create disinformation and try to influence U.S. elections.

However, Titone noted that legislation can only do so much to limit how much-manipulated content is created and distributed. And because any restrictions could potentially butt up against the First Amendment, lawmakers will have to be careful with how the bill is crafted.

Separately, Secretary Griswold is also pushing for a new law to add penalties for anyone who acts as a fake elector in future presidential elections. Some states have prosecuted individuals who submitted certificates naming themselves to the Electoral College based on false claims that former President Donald Trump won the 2020 election.

We want to make sure that it's very clear that if someone tries to do this, they will be facing major penalties, said Griswold.

Democratic Rep. Lorena Garcia of Adams County said she decided to sponsor the false electors bill because she wants to protect the fundamental safeguards of democracy.

We know that Trump's camp is going to go all out in the 2024 election, and we just want to make sure we set our state up for continued success in safe elections, she said.

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If artificial intelligence is going to get involved in elections, Colorado lawmakers want voters to know - Colorado Public Radio

Why Mark Zuckerberg Is the Power Player in Artificial Intelligence – The Motley Fool

Meta Platforms (META 0.24%) will have more GPU power than almost any company in the world by the end of 2024, and the company plans to make most of its AI models open source. This is a powerful strategy that could destroy value for even the biggest competitors in the industry, as Travis Hoium covers in this video.

*Stock prices used were end-of-day prices of Jan. 23, 2024. The video was published on Jan. 23, 2024.

Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool's board of directors. John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Travis Hoium has positions in Alphabet and Snap. The Motley Fool has positions in and recommends Alphabet, Amazon, Meta Platforms, Microsoft, Nvidia, and Oracle. The Motley Fool has a disclosure policy. Travis Hoium is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through their link they will earn some extra money that supports their channel. Their opinions remain their own and are unaffected by The Motley Fool.

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Why Mark Zuckerberg Is the Power Player in Artificial Intelligence - The Motley Fool

3 Stocks Capitalizing on the Artificial Intelligence Boom – InvestorPlace

The artificial intelligence boom has generated many winners like these three stocks

Artificial intelligence (AI) can increase global productivity and help businesses generate more revenue. Those two outcomes and others have captivated investors who seek to beat the market.

Its hard to find an industry that performed as well as AI last year. It may also be challenging to find a sector that can keep up with artificial intelligence stocks in 2024. These stocks wont go parabolic and will have good years and bad years.

However, many of the catalysts that fueled 2023s rally are still in play this year. Its possible for these three AI stocks to soar higher as they capitalize on the artificial intelligence boom.

Source: sdx15 / Shutterstock.com

Nvidia(NASDAQ:NVDA) put investors on notice last year as artificial intelligence caused revenue to surge.Quadruple-digit year-over-year net income growthmade the valuation easier to justify.

Even now, it can be argued that Nvidia is still an undervalued stock. The companys continued growth, business opportunities, 28 forward P/E ratio, and 0.56 PEG ratio form the foundation for this argument.

This company has been one of the best performers in the stock market. Shares are up by 241% over the past year and have gained 1,328% over the past five years. The company has even notched a 19% year-to-date gain. Most indexes have eked out low-single-digit gains this year, if that.

The firm is in a class of its own and has the potential to become the worlds most valuable company. It has grown the most out of the top artificial intelligence players and leads by a wide margin.

Source: The Art of Pics / Shutterstock.com

If Nvidia wants to become the worlds most valuable publicly traded company, it will have to contend with heavyweights:Microsoft(NASDAQ:MSFT) andApple(NASDAQ:AAPL). The two stocks have been jockeying for the top spot with Microsoft having a slight edge at the time of writing.

A 70% gain over the past year and a 268% gain over the past five years make Microsoft stock look appealing for long-term investors. The companys artificial intelligence initiatives can fuel more gains and reward investors who accumulate shares.

Microsofts Azure has anAI platformthat helps developers build apps at enterprise scale. The company has built-in tools to help developers create more effective AI and construct AI workflows.

The company also benefits from the rise of AI through its investment in OpenAI and Microsoft Copilot. Copilot is a new feature that has been built into Microsoft Office Products to increase productivity. The firm is a leading AI stock that continues to deliver double-digit year-over-year revenue and earnings growth.

Source: Benny Marty / Shutterstock.com

Alphabet(NASDAQ:GOOG, NASDAQ:GOOGL) is well-known for its search engine. Google is the worlds most popular website with its own YouTube right behind it. These platforms rely on artificial intelligence to provide consumers with relevant search results. YouTube also recommends videos similar to the one the viewer is currently watching to increase the amount of time people spend on the website.

Attention is money for any company, and Alphabet has demonstrated that it can keep attention for several hours in a given day. While ad revenue is still growing, the company is diversifying into other areas, such as cloud computing, to achieve higher growth rates.

Google Cloud offers severalAI and machine learning productsto help people use generative AI, gather data, and perform other tasks. Alphabet is also at the forefront ofquantum computingthrough AI which can become the next megatrend. Quantum computing is still in its early innings, but artificial intelligence is heating up right now.

Alphabet stock gives you exposure to those sectors, the companys vast advertising business, and other business segments.

On this date of publication, Marc Guberti held long positions in NVDA and MSFT. The opinions expressed in this article are those of the writer, subject to theInvestorPlace.comPublishing Guidelines.

Marc Guberti is a finance freelance writer at InvestorPlace.com who hosts the Breakthrough Success Podcast. He has contributed to several publications, including the U.S. News & World Report, Benzinga, and Joy Wallet.

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3 Stocks Capitalizing on the Artificial Intelligence Boom - InvestorPlace

Stellantis to Enhance Personalized Mobility Experience with Acquisition of CloudMade’s Artificial Intelligence … – Stellantis

AMSTERDAM Stellantis N.V. announced today the acquisition of the artificial intelligence framework, machine learning models and intellectual property rights and patents of CloudMade, a developer of smart and innovative big data-driven automotive solutions.

The acquisition as an asset deal will support the mid-term development of STLA SmartCockpit and reinforces Stellantis software strategy outlined in Dare Forward 2030.

The AI-powered framework created by CloudMade, with integrated graphical interfaces, is the industry-leading cloud and software development kit for collecting and analyzing automotive data sets and has been the reference point to transform the in-car and mobility user experience throughout the past decade.

The acquisition of CloudMades pioneering AI capabilities will accelerate our development journey on STLA SmartCockpit and help us deliver our Dare Forward 2030 goals, said Yves Bonnefont,Stellantis Chief Software Officer. Thanks to this adaptable technology and leveraging our growing connected car parc, we will create intelligent mobility solutions faster and with more flexibility, to delight our customers with in-vehicle and mobile experience personalization.

As part of the acquisition, 44 engineers and software developers from CloudMade, dedicated to the development of AI technology, will be joining Stellantis.

CloudMadeis extremely pleased with this transaction, said Jim Brown, founder and CTO of CloudMade. The team is excited to deepen their working relationship withStellantis to bring new features to the vehicles cockpit.

CloudMades framework architecture allows to maximize data value using three learning approaches: personalized learning, which predicts an individuals behavior in a particular context; fleet learning, using sensor data across devices to detect and share real world features; cohort learning, combining real world data with data from clustered groups of people distinguished by attributes.

CloudMades software technology will support Stellantis strategy to develop intelligent mobility products and enhance the overall customer experience with personalized features that will make their drive safer, their life easier and their trip exciting.

Services and products will include:

Through this acquisition, Stellantis will also be able to develop end-to-end and fully owned navigation features; enhance data privacy, since the data for training the models will be managed internally, reducing risks of possible exposure; and introduce development kits for making custom models for its software developers.

About Stellantis

Stellantis N.V. (NYSE: STLA / Euronext Milan: STLAM / Euronext Paris: STLAP) is one of the worlds leading automakers aiming to provide clean, safe and affordable freedom of mobility to all. Its best known for its unique portfolio of iconic and innovative brands including Abarth, Alfa Romeo, Chrysler, Citron, Dodge, DS Automobiles, Fiat, Jeep, Lancia, Maserati, Opel, Peugeot, Ram, Vauxhall, Free2move and Leasys. Stellantis is executing its Dare Forward 2030, a bold strategic plan that paves the way to achieve the ambitious target of becoming a carbon net zero mobility tech company by 2038, while creating added value for all stakeholders. For more information, visit http://www.stellantis.com

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Stellantis to Enhance Personalized Mobility Experience with Acquisition of CloudMade's Artificial Intelligence ... - Stellantis