Category Archives: Artificial Intelligence

Former Premier League midfielder Matt Oakley, seen here in action for Southampton in 1999, is a key backer of the AI tool

This does not mean that the human touch and experience needed to make these decisions are totally redundant

Artificial Intelligence, also known as AI, is a subject that has been spoken about in the world a lot, these days. There have been quite a few doomsday predictions where it has been projected that the machines will totally take over the functions of human beings as well.

Be that as it may, AI is defined as the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.

The term AI may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.

Uses of AI

There are four types of Artificial Intelligence. They are (i) Reactive machines, (ii) Limited memory, (iii) Theory of mind, and (iv) Self-awareness.

AI enhances the speed, precision, and effectiveness of human efforts. In financial institutions, AI techniques can be used to identify which transactions are likely to be fraudulent, adopt fast, and accurate credit scoring, as well as automate manually intense data management tasks.

There has been wide speculation as to how this can be used in sports.

Take smarter decisions?

In an earlier column, this writer presented an article regarding the use of a vest for data collection of athletes.

And, if the data collected during these matches, can they be used to feed the machines. Then could AI be used to make smarter decisions regarding players, by the coaches, clubs, and national sports bodies.

This has been the question that has been discussed and is being discussed at all levels of sports in the more advanced countries.

The answer to that question seems to be yes, judging from the results of the use of AI in the England Premier League football during last season. But one successful prediction is not conclusive evidence in any circumstance. And the accuracy of its predictions still makes reads rather scary reading.

Real Analytics

Former Southampton midfielder Matt Oakley and Professor Ian McHale of the University of Liverpool are behind the recruitment tool, Real Analytics, that they believe will revolutionise the way in which clubs obtain and retain players. Oakley has a very impressive background in football after having played for a number of Premier League clubs in his playing days.

Oakley, who made nearly 700 senior appearances for the likes of Southampton and Leicester, says: From my perspective as a former player, seeing what Ian can do is so exciting. This is completely different, that ability to predict the impact of results on a specific team. But it also helps in knowing when to sell a player. The analysis gives an unbiased view, all based on what a player does on the pitch.

Scouts should use data and vice versa

But as Oakley says: There is a definite resistance from some Managers towards data. I have seen it, but we are striving to bridge the gap between data and football. We have data on 150 leagues and 40,000 players. It is about turning that into useful information. At the moment, we believe people arent using it to its full advantage. That is not to say the traditional scout should be made redundant. Scouts should use data and data should use scouts. For example, a man in the stand can tell you more about body language and when a players head drops. We know there is more to it than numbers.

Scarily correct predictions

Professor Ian McHale of the University of Liverpool who created the technology that tells you what will happen, not what has happened

They spoke then of how, last summer, they were asked to run a player impact report on Pierre Emerick Aubameyang, prior to Arsenal football clubs decision to award him a lucrative new contract, worth 55 million (Rs. 15 b) over three years.

After all, Aubameyang had been their leading scorer and talisman at the club. Oakley and Prof. McHale however warned how keeping the striker at the club was perhaps not a prudent move.

Their system, Real Analytics, predicted that Arsenal would finish in an average of eighth position in the Premier League with Aubameyang in the squad, and ninth without him. It also projected that they would score 55 goals with, and 50 without. Arsenal finished eighth, with a goals tally of 55.

How does it work?

So how does this work? As McHale explains, all the readings are in the data itself.

The numbers that go into it are called event data. Every match has around 2,000 events. A pass is not just recorded as a pass. We have the x-y co-ordinates of where the pass came from and where it went and who it went to.

Our AI engine learns the value of every action in terms of what it contributes to the likelihood of that possession ending in a goal. Every pass, every tackle, every interception, everything is given a positive or negative score.

Originally from gambling industry

Real Analytics claims to be the future of decision making in football

He further went onto say, It can be used for coaching to look at the moments where you have added value, or it can deem that you have taken value away. You can see how some players, who might be completing lots of passes, actually impact negatively on the team.

But when it comes to recruitment, it is no use knowing how good a player was last week. We need our tools to be predictive. We want to know how good he will be next year, or in five years time. It turns out things like pass completion percentage reveal little about a players future performances.

We have been working on these types of models for 20 years. They were originally built for the gambling industry and designed for forecasting the outcome of matches. We realised that all the tools we were building, we could use them for the football industry, with a few tweaks.

Conclusion

This is only one of the predictions of a number of others that came in correctly as predicted by Real Analytics. This does not mean that the human touch and experience needed to make these decisions are totally redundant.

But what it does mean is that Artificial Intelligence or AI can be made use of by the humans to make better-informed decisions.

Continued here:

Use of Artificial Intelligence (AI) in football - nation.lk - The Nation Newspaper

Corin Stone is a Scholar-in-Residence and Adjunct Professor at the Washington College of Law. Stone is on leave from the Office of the Director of National Intelligence (ODNI) where, until August 2020, she served as the Deputy Director of National Intelligence for Strategy & Engagement, leading Intelligence Community (IC) initiatives on artificial intelligence, among other key responsibilities. From 2014-2017, Ms. Stone served as the Executive Director of the National Security Agency (NSA).

(Editors Note: This article was first published by our friends at Just Security and is the second in aseriesthat is diving into the foundational barriers to the broad integration of AI in the IC culture, budget, acquisition, risk, and oversight.)

OPINION Several weeks ago, I wrote anarticlepraising the widespread, bipartisan support for the U.S. Innovation and Competition Act (USICA), which would dramatically expand federal government support for U.S. technological growth and innovation in the face of the global AI race.

In that article, I argued that for the Intelligence Community (IC) to take advantage of AI in this supportive environment, it must overcome several critical implementation challenges, and quickly. In particular, the IC must more rapidly and nimbly navigate U.S. government budget and acquisition processes, create a simple but effective risk assessment framework, and work with congressional overseers to streamline engagement and improve the partnership between Congress and the IC. Each of these areas is in dire need of radical re-imagining, without which any one of them could be the Achilles heel for AI in the IC. I will address each of these in my next few articles.

To successfully tackle any of these specific tasks, though, the IC must at the same time prioritize an issue much more intangible and nebulous its own culture. Culture is the ethos of an organization the beliefs, behaviors, values, and characteristics of a group that are learned and shared over many years. In the IC, there are several predominant cultures, all of which flow from the mission of the IC protecting the women and men on the front lines, defending U.S. national security, and delivering insights to policymakers at the speed of decision. This mission is a powerful and unifying force that naturally leads to important IC values and behaviors.

IC Culture Today

Intelligence operations uncovering foreign secrets and protecting assets, for example are inherently risky; they very often put people in harms way. If there is a leak of information related to an operation if the people involved, or the location or target of an operation, are exposed not only might the mission fail to collect the desired information, but someones life could also be in jeopardy. The extreme consequences of leaks are well understood, thanks to notorious spies likeRobert Hanssenand inside leakers likeEdward Snowden. But significant damage can also flow from what seem like merely small mistakes. If someone fails to make a connection between relevant information or forgets to check a database of known terrorists, for example, the results can be just as disastrous. Thus, the ICs high-stakes operations drive an enormous emphasis on security, preparation, and tradecraft, all of which help mitigate operational risk.

This same spirit manifests in enabling activities, like budget, acquisition, or human resources, through a focus on certainty of action and predictability of results. Enabling activities by some considered a negative term but one in which I take pride as a life-long enabler are somewhat removed from the pointy end of the spear but are no less critical to the ultimate success of the mission. Proper funding and resources, the right capabilities, skilled officers, legal approval, and the many other support activities are integral to successful operations.

In the field, risks are unavoidable operators cannot choose inaction to avoid those risks. Given that risks are inherent in what they do, they must accept the reality that risks are inevitable, and they must learn to manage those risks to get the huge payoff of successful operations. So, the focus is not on risk avoidance, it is on risk management what level of risk is acceptable for what level of intelligence gain?

The Cipher Brief hosts private briefings with the worlds most experienced national and global securityexperts. Become a member today.

Back home, where most enabling activities are handled, risks are not seen as inevitable certainly not big ones. They are seen as avoidable, and subject to being minimized and mitigated. And some believe the best way to do that is by staying with tried-and-true standard operating procedures rather than experimenting with new approaches. Innovation is inherently risky. It can and will fail. Innovation is not mandatory, it is entirely avoidable. Therefore, if the tendency is to avoid risks, in most cases innovation will be avoided.

In addition to this instinct, there are compounding issues that discourage innovative change in enabling activities. First, there are practical difficulties: change is hard, messy, and requires resources that most offices cant spare. These concerns alone are big hurdles to clear. Second, innovative change means uncertainty in execution, accountability, and success. And that uncertainty leads to the risk that projects may fail, resulting in loss of money, reputation, or even position. Thus, control, compliance, and trust are paramount, and there is a strong aversion to things not invented here. Innovation is not particularly welcome in this environment and introducing new ideas can be an uphill battle, discouraging creativity in areas where it is needed most.

When it comes to budget and acquisition processes in particular which are critical to the ICs ability to quickly harness the power of AI capabilities the ICs risk-averse culture is also drawn in part from its reliance on Department of Defense (DOD) processes. And while DOD processes have aligned to IC needs in the past, they are based on decades-old approaches used for major systems acquisitions, like airplanes, aircraft carriers, and satellites. These are big ticket items that require minimal risk and significant time, structure, and certainty to move forward, because any failure could have costly consequences. But using this same approach for emerging technology like AI hampers the ICs ability to promptly obtain and use it before the underlying technologies become obsolete. In these cases, the IC must have the ability to try new things quickly, adjust on the fly, and accept some level of loss and failure as it continues to grow new technologies and processes. The IC must embrace a more flexible, innovative approach for AI even as that approach introduces more uncertainty.

Opportunity Born from Crisis

It is difficult, if not impossible, to create major cultural change in the absence of a compelling real-world problem. As leading change management expertJohn Kotterexplains, a sense of urgency helps others see the need for change and the importance of acting immediately. For example, prior to the COVID-19 pandemic, telework in the IC was virtually unheard of. Over the past 18 months, however, the IC not only achieved telework for many roles, telework proved to be so productive that many IC elements have now also changed their standing policies to allow it in certain roles going forward. Using that crisis to create a blueprint for new long-term approaches was key to jump-starting a real transformation.

Another striking example occurred after the September 11, 2001 attacks (9/11). Prior to 9/11, the IC culture around sharing and protecting information was heavily weighted toward jealously guarding information within agency stovepipes. This was a result of many things including the genuine need to protect sources and methods but it evolved in the extreme because it is easier to protect sensitive information if fewer people have access to it and, importantly, knowledge is power. After 9/11, though, IC culture slowly started to evolve to one that acknowledged the need to connect the dots and proactively share information with critical partners, even while protecting it. The need to share information more freely within the IC had beendocumented for decadesand executive branch policy already allowed information to go to those who had a need to know, but it took the crisis of 9/11 to really start to break through the cultural barriers to information sharing.

Go beyond the headlines with expert perspectives on todays news with The Cipher BriefsDaily Open-Source Podcast.Listen hereor wherever you listen to podcasts.

Indeed, the IC now has created an entire information technology enterprise architecture groundbreaking for the U.S. government when the enterprise was started in 2011 founded on the concept that the IC agencies must work together and share information more easily than in the past. The IC Information Technology Enterprise (IC ITE) has been underway for a decade and is not yet complete, not solely due to its audacious technical goals but because it is breaking down cultural barriers, connecting the IC as never before, and pushing the IC together beyond its comfort level. Culture shifts slowly, and this one has had its detractors. But eventually over time there has become a general acceptance of and willingness to share information in ways that would previously have been unthinkable. The 9/11 crisis and subsequent terrorist attacks (and attempts) brought the responsibility to share information into immediate, sharp focus.

As I discussed in my previousarticle, one of the ICs crises today is the ubiquity of and access to AI around the globe. Sophisticated technology like AI is no longer available to only a handful of wealthy governments; it is now abundant and often easy to acquire, enabling smaller foreign governments and non-governmental actors alike to take advantage of it. If the IC does not modernize its approach to AI quickly, it is only the United States that will pay. The IC must turn this crisis into an opportunity to embrace a more flexible and innovative culture that supports the ICs ability to leverage AI tools at the speed of mission.

IC Leadership Action Required

Culture is driven from thetopthrough leadership actions, behaviors, and priorities that reverberate across every level of an organization. To grow an IC-wide culture of innovation, IC leaders must set the right vision and tone by affirmatively and publicly embracing outside-the-box thinking, articulating acceptable risk and expected failure rates, continuing to back innovators when projects go awry, and setting expectations for collaboration between innovators and practitioners in every area from budget to acquisition to operations.

In 2018, the Director of National Intelligence (DNI) made IC-wide innovation a top priority by creating an ODNIinnovation organizationto lead and support, among other things, cross-IC creativity and modernization to help pioneers find each other, to encourage the IC to leverage each others ideas, to provide advice to those hoping to contribute new ideas, and to train officers on innovation best practices. This organization also led the top IC strategic initiatives, including Augmenting Intelligence using Machines (AIM), which drove senior and subject-matter-expert coordination and collaboration across the IC on AI and machine learning activities to better align innovation, acquisition, and use of AI and emerging technology.

The AIM initiative was one of only six priorities the directors of every IC element very visibly embraced as imperative to the future of the IC. As a result, the AIM initiative had relative success in its first few years, bringing the community together and ensuring better coordination across the many AI initiatives. However, the innovation offices more foundational task of creating a broad IC culture that embraces innovation foundered. Chronic under-resourcing of those activities signaled that they were not, in fact, a priority, and subsequent changes in ODNI leadership and support resulted in minimal progress over the course of two years. That office was recently disbanded, leaving IC innovators to continue to fend for themselves and signaling a lack of strategic support and leadership for IC-wide innovation.

There are glimmers of hope, however. Innovation remains one of the ICs statedvalues, and despite the lack of coordinated approach, there are pockets of brilliant innovation across the IC where individual visionaries recognize that new ideas and technology can transform the world of intelligence. Many enterprising and energetic individuals expend herculean efforts to create new pathways, build out novel ideas, and find new solutions to old problems. They are willing to fail and accept the consequences because they believe so strongly in the importance of their work.

IC leaders must harness this grassroots energy and enthusiasm by actively supporting and connecting innovators, rewarding creativity even when a project fails, and empowering the workforce to effectively manage risk. The DNI should designate a senior leader to drive innovation across the IC, starting with a 90-day action plan that takes advantage of the AI crisis to kick-start activities that will help shape the IC culture toward one that embraces and supports innovation more broadly. Strong and steady leadership, clear prioritization, and a willingness to hold the organization accountable for achieving those goals are critical for creating and adapting a culture.

As with all organizations, some IC officers will embrace changes quickly. However, people with a long history in the IC often become attached to existing processes and mechanisms, mistaking them for the ethos of the IC. And because major culture change cannot leave all existing processes untouched, it can provoke skepticism and pushback from those folks. But dragging them along or leaving them behind is not an option officers with time and depth in the IC are critical; they make up the engine of the community, and they support and nurture employees throughout it. Actively engaging them as a part of the process and focusing on small wins that provide tangible benefit will help cultivate buy-in for larger, overarching goals. Proving out a few impactful ideas in pilot programs will show the IC can handle increased flexibility and speed without losing the security, rigor, and accountability required. This will, in turn, refresh the ICs culture while preserving and championing its strengths, and pave the way for innovation and AI adoption at scale.

Because no matter how many brilliant minds come together to create excellent recommendations to take advantage of AI and promote innovation, the IC will not successfully implement them without addressing the institutional resistance to new ways of doing business that acts as a self-sustaining barrier between the IC and widespread AI adoption. As Winston Churchill admonished, the IC must not let this crisis go to waste.

Read more expert-driven national security insight, perspective and analysis in The Cipher Brief

Follow this link:

Artificial Intelligence in the IC: Culture is Critical - The Cipher Brief

DUBLIN--(BUSINESS WIRE)--The "Global Artificial Intelligence (AI) Market in Agriculture Industry Market 2021-2025" report has been added to ResearchAndMarkets.com's offering.

The artificial intelligence (AI) market in the agriculture industry is poised to grow by $458.68 million during 2021-2025, progressing at a CAGR of over 23% during the forecast period.

The market is driven by maximizing profits in farm operations, higher adoption of robots in agriculture, and the development of deep-learning technology. This study also identifies the advances in AI technology as another prime reason driving industry growth during the next few years.

The artificial intelligence (AI) market in agriculture industry analysis includes the application segment and geographic landscape.

The report on artificial intelligence (AI) market in agriculture industry covers the following areas:

The robust vendor analysis is designed to help clients improve their market position, and in line with this, this report provides a detailed analysis of several leading artificial intelligence (AI) market in agriculture industry vendors that include Ag Leader Technology, aWhere Inc., Corteva Inc., Deere & Co., DTN LLC, GAMAYA, International Business Machines Corp., Microsoft Corp., Raven Industries Inc., and Trimble Inc. Also, the artificial intelligence (AI) market in agriculture industry analysis report includes information on upcoming trends and challenges that will influence market growth. This is to help companies strategize and leverage all forthcoming growth opportunities.

Key Topics Covered:

Executive Summary

Market Landscape

Market Sizing

Five Forces Analysis

Market Segmentation by Application

Customer landscape

Geographic Landscape

Vendor Landscape

Vendor Analysis

For more information about this report visit https://www.researchandmarkets.com/r/58dom9

About ResearchAndMarkets.com

ResearchAndMarkets.com is the world's leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.

Read the rest here:

The Role of Artificial Intelligence (AI) in the Global Agriculture Market 2021 - ResearchAndMarkets.com - Business Wire

Organizations that profit the most from Artificial Intelligence (AI) projects are more likely to believe in cognitive capabilities. Winning over the end-users of AI-enabled capabilities is just as crucial, if not more, than winning over the AI-enabled capabilities themselves.

CIOs and other IT leaders who want to scale their AI programs need to win support across the organization.

According to the 2020 Market Research Report from Fortune Business Insights, artificial intelligence had a market value of US$27.23 billion in 2019 and by 2027 this figure is expected to increase nearly tenfold in just eight years, with a Compound Annual Growth Rate (CAGR) of 33.2 percent.

Here are a few steps IT leaders can take to gain buy-in and sponsorship from C-suite executives and line-of-business colleagues:

Senior executives should contribute significantly to the success of the project. Executives should collaborate with their AI teams to verify that the AI systems input and output are consistent with the companys overall digital transformation strategy. Collaborative strategy sessions with executives and AI researchers can help raise awareness of Artificial Intelligence initiatives and keep AI research and development efforts focused on business objectives.

Also Read: 4 Strategies to Enable Asynchronous Collaboration in Hybrid Work

Its critical to connect and organize advisory councils with the organizations partners, suppliers, and employees when making changes like this to gather their ideas and perspectives on implementation. Businesses will be able to know where it is wanted and needed if they do so.

Businesses should understand that while IT can help with AI-enabled innovation, it has to be a collaborative effort. Organizations should remember to foster applied interest before deciding on their next course of action.

IT leaders and managers need to illustrate how AI will help employees in order to boost user adoption within a business. Present high-quality data that demonstrates how to enhance business operations. Incentivize usage by presenting a successful use case with senior leadership support and plainly recognizable statistics. IT executives and managers should properly communicate to team members why Artificial Intelligence is helpful, and the positive impact it will have on productivity and efficiency on a daily and long-term basis.

Maintaining a people-centered mindset will go a long way. Retaining staff that have the required skills and expertise working with AI systems can pay off.

Many functional leaders are afraid of losing their jobs or becoming outdated, which is one of the barriers to AI adoption. Line managers who dont completely understand the potential of AI and ML will be overwhelmed and become defensive about the human aspects of their employment if its positioned simply as a technical upgrade or cost-saving breakthrough.

Through spotlighting that AI enables teams to focus on the actions to take based on the insights generated by AI and ML solutions rather than spending time mining the data for patterns, it becomes apparent that AI does not eliminate the need for human decision-making, but rather facilitates a more effective and efficient path to accurate results.

Also Read: Three strategies for Maximizing SaaS Spend

Business leaders could be reluctant to accept Artificial Intelligence or machine learning models outputs seriously. Changing the corporate attitude requires instilling trust by engaging with business leaders to demystify AI solutions, how they function, and how the outcomes are generated.

When business leaders recognize the value of the outcomes provided by AI solutions, they are more likely to unearth disruptive insights and be willing to use them to drive desired business goals and have a major influence across the organization.

Check Out The NewEnterprisetalk Podcast.For more such updates follow us on Google News Enterprisetalk News.

Visit link:

Building Support and Addressing Concerns to Promote Artificial Intelligence in the Workplace - EnterpriseTalk

With the advancement in technology, life has become way simpler than it earlier used to be. On the technological front, Artificial intelligence has served to be no less than a savior. Right from controlling the traffic on roads, detecting frauds to assisting the doctors and surgeons in numerous medical procedures, AI has paved the way for all of this. Needless to say, how AI can be put into use to reduce the workload and to address the various issues of the organization is of utmost importance. However, what cannot be overlooked is having a fair idea about the political, social and ethical implications of artificial intelligence.

Now that AI has integrated into our lives like never before, it is high time that we ensure that the technology is employed ethically and that our politics remain democratic. Ensuring that our policies are well informed is equally important as well.

With both, Artificial intelligence and machine learning continue to dominate the world of technology, we have seen massive transformations over the years. Well, not just that. The possibility of this trend to continue for the years to come is high, without a doubt. Considering the fact that these powerful new technologies like AI and machine learning stand a chance of both, improving as well as disrupting human lives, these transformations will have a deep ethical impact. Artificial intelligence offers us, in amplified form, everything that humanity already is, both good and evil. It is therefore important that we pay utmost importance pertaining to how these transitions are made.

Talking about AI ethics, it is worth noting that it has turned a little problematic now. A few key reasons identified in this aspect are

When it comes to AI, one of the most commonly faced questions is whether the AI systems would work as they are promised or will they fail? Issues dont arise when the AI systems work as promised. But what if they fail? On failing, what would be the results of those failures? Is it possible to survive without them if these systems fail? Though paying significant attention to this is important, what is even more important is whether AI stands true to its main purpose to help people lead longer, more flourishing, more fulfilling lives. The fact that there are innumerable instances where AI has left a remarkable positive impact in society makes us believe how good of a technology it is.

On the flip side, there are cases where a perfectly well functioning technology, such as a nuclear weapon, can, when put to its intended use, cause immense evil. What can be concluded from here is that Artificial intelligence can be used maliciously, similar to how human intelligence can be used. So what could be the conclusion then? Well, the technology itself is neutral: only the way we decide to use it in society determines whether it has good or bad effects.

Share This ArticleDo the sharing thingy

About AuthorMore info about author

Read the rest here:

What are the Implications of Artificial Intelligence? Analytics Insight - Analytics Insight

Roadrunner, the Anthony Bourdain documentary from 20 Feet from Stardom Oscar winner Morgan Neville, takes a page from documentaries like Alex Gibneys Sinatra: All or Nothing at All in allowing the late chef and television personality to narrate his own story through the use of archival audio. Neville and his team culled through over a dozen hours of audio from Bourdains film, TV, audiobook, radio, and podcast appearances. But there are three instances in Roadrunner where Neville needed Bourdain narration that did not exist, so he turned to an artificial intelligence system that could recreate Bourdains voice.

As reported by The New Yorker in a recent interview with Neville: There is a moment at the end of the films second act when the artist David Choe, a friend of Bourdains, is reading aloud an e-mail Bourdain had sent him: Dude, this is a crazy thing to ask, but Im curious Choe begins reading, and then the voice fades into Bourdains own: . . . and my life is sort of shit now. You are successful, and I am successful, and Im wondering: Are you happy? I asked Neville how on earth hed found an audio recording of Bourdain reading his own e-mail.There were three quotes there I wanted his voice for that there were no recordings of, Neville explained. So he got in touch with a software company, gave it about a dozen hours of recordings, and, he said, I created an A.I. model of his voice.'

If you watch the film, other than that line you mentioned, you probably dont know what the other lines are that were spoken by the A.I., and youre not going to know, Neville added. We can have a documentary-ethics panel about it later.

In a separate interview with GQ magazine, Neville confirmed his team fed more than ten hours of Tonys voice into an AI model so that his voice could be recreated. The bigger the quantity, the better the result, the director added. We worked with four companies before settling on the best.

Neville continued, We also had to figure out the best tone of Tonys voice: His speaking voice versus his narrator voice, which itself changed dramatically over the years. The narrator voice got very performative and sing-songy in the No Reservation years. I checked, you know, with his widow and his literary executor, just to make sure people were cool with that. And they were like, Tony would have been cool with that. I wasnt putting words into his mouth. I was just trying to make them come alive.

The decision to use A.I. to recreate Bourdains speaking voice is already generating backlash on social media ahead of the documentarys release. As film critic Sean Burns posted, When I wrote my review I was not aware that the filmmakers had used an A.I. to deepfake Bourdains voice for portions of the narration. I feel like this tells you all you need to know about the ethics of the people behind this project.

Roadrunner opens in theaters July 16 from Focus Features.

Sign Up: Stay on top of the latest breaking film and TV news! Sign up for our Email Newsletters here.

Continue reading here:

Anthony Bourdain Doc Recreates His Voice Using Artificial Intelligence and 10-Plus Hours of Audio - IndieWire

The government's highly anticipated UFO report was released earlier this month, stopping short of confirming the existence of alien life. With no legitimate confirmation that extraterrestrials walk among us, believers continue to speculate. One of the most prominent of those speculators is Harvard professor Avi Loeb, an astrophysicist who previously hypothesized aliens could have visited Earth as recently as in 2017. Now, the theoretical physicist says we may need to continue fleshing out the planet's artificial intelligence technology should we stand a chance to speak with aliens if they eventually find themselves crashlanded on the planet.

In a new opinion piece shared on Scientific American, Loeb breaks down the steps he'd recommend governmental officials take in trying to communicate with alien life found on this planet. As the physicist explains, the use of artificial intelligence would decrease the chances of any human error during communication, hopefully removing any opportunity to send "mixed messages" to potential alien research vessels or probes.

"Humanity should avoid sending mixed messages to these probes, because that would confuse our interpretation of their response," Loeb writes in his piece.

In April, Loeb wrote a separate piece on the lack of an international structure that would deal with such an "invasion." In the latest piece in the journal, published July 12th, Loeb backs up his previous thoughts.

"Any decision on how to act must be coordinated by an international organization such as the United Nations and policed consistently by all governments on Earth," he adds. "In particular, it would be prudent to appoint a forum composed of our most accomplished experts in the areas of computing (to interpret the meaning of any signal we intercept), physics (to understand the physical characteristics of the systems with which we interact) and strategy (to coordinate the best policy for accomplishing our goals)."

That's when the physicist suggests our best bet would be to send our artificial intelligence to meet with that of the hypothetical alien craft, all in an attempt to minimize errors.

"Ultimately, we might need to employ our own AI in order to properly interpret the alien AI. The experience will be as humbling as relying on our kids to make sense of new content on the internet by admitting that their computer skills exceed ours," Loeb writes. "The quality of expertise and AI might be more important than physical strength or natural intelligence in determining the outcome of a technological battlefield."

You can read Loeb's entire piece here.

Cover photo by Marcos del Mazo/LightRocket via Getty Images

View post:

Harvard Astrophysicist Says We May Need Artificial Intelligence to Speak With Alien Life - ComicBook.com

The Report Lists the Key Companies in the Artificial Intelligence (AI) Chipsets Market: NVIDIA Corporation, Intel Corporation, Xilinx, Inc., Samsung Electronics Co., Ltd., Micron Technology, Inc., Kneron, Alibaba Group Holding Limited, Qualcomm Technologies, Inc., IBM, Alphabet Inc., Microsoft Corporation, Amazon Web Services (AWS), Advanced Micro Devices, Inc. (AMD), General Vision, Inc., Huawei Technologies Co., Ltd., Graphcore Limited, MediaTek Inc., Fujitsu Limited, Wave Computing, Inc., Mythic Inc., Koniku Inc, Tenstorrent Inc., SambaNova Systems Inc, Kalray Corporation, XMOS Limited, GreenWaves Technologies

Pune, India, July 16, 2021 (GLOBE NEWSWIRE) -- The global artificial intelligence (AI) chipsets market size is expected to reach USD 108.85 billion by 2027, exhibiting a CAGR of 38.9% during the forecast period. The increasing implementation of 3D technology along with neural networks & deep learning technologies will promote the healthy growth of the market during the forecast period, states Fortune Business Insights, in a report, titled Artificial Intelligence (AI) Chipsets Market Size, Share & COVID-19 Impact Analysis, By Chipset Type (Graphics Processing Unit (GPU), Field Programmable Gate Arrays (FPGAs), Application-specific Integrated Circuit (ASIC) and Others), By Application (Natural Language Processing (NLP), Robotic Process Automation (RPA), Machine Learning, Computer Vision and Others), By Computing Technology (Cloud Computing and Edge Computing), By Function (Training and Inference), By Industry (Consumer Electronics, Healthcare, BFSI, IT & Telecom, Manufacturing, Automotive, Retail, and Others), and Regional Forecast, 2020-2027. The market size stood at USD 8.14 billion in 2019.

The whole world is battling with the novel coronavirus, leaving numerous industries distraught. The authorities of several countries have initiated lockdown to prevent the spread of this deadly virus. Such plans have caused disturbances in the production and supply chain. But, with time and resolution, we will be able to combat this stern time and get back to normality. Our well-revised reports will help companies to receive in-depth information about the present scenario of every market so that you can adopt the necessary strategies accordingly.

Story continues

Request Sample PDF Brochure: https://www.fortunebusinessinsights.com/enquiry/request-sample-pdf/artificial-intelligence-ai-chipsets-market-104500

The report on AI Chipsets Market accentuates:

All-inclusive analysis of the AI Chipsets Market

Dynamic insights into the segments

Extensive data about dominant regions

Key information about prominent players

Latest developments

AI Chipsets Market drivers and restraints

COVID-19 Influence

Regional Analysis:

Emergence of Startup Companies to Propel Market in Asia Pacific

Asia Pacific is expected to dominate the global Artificial Intelligence (AI) Chipsets Market owing to the developing economies such as South Korea, India, China. The growing acceptance of AI-based solutions will foster healthy growth of the market in the region. The government of Singapore has created an AI Ethics Advisory Council as a part of its AI Strategy to deploy AI applications across various industries in 2018.

The strong startup ecosystem is expected to further drive the market in Asia Pacific. Europe is expected to hold the largest share in the global market owing to the presence of AI solution providers in the European countries. The growing focus on R&D investments coupled with the adoption of AI technologies will consequently bolster the growth of the market in Europe. The Middle East and Africa is expected to grow rapidly during the forecast period owing to the smart city initiatives in the region. Ask For Customization: https://www.fortunebusinessinsights.com/enquiry/customization/artificial-intelligence-ai-chipsets-market-104500

Popularity of AI-based Solutions to Boost Market During Coronavirus

The production of AI chipsets has been greatly affected by the coronavirus. According to the index of industrial production (IIP) data, in 2020, the manufacturing sector production registered a decline of 11.1% in July, as covid-19 lockdown slows down the manufacturing process.

However, the demand for such chipsets has improved immensely during the pandemic because of the adoption of AI among various industries. Various industries such as automotive, manufacturing, and others have implemented AI solutions to ease up processes. Besides, the focus on advanced AI-based solutions by prominent players will aid the market amid coronavirus. For instance, in May 2020, Nvidia Corporation expanded its EGX Edge AI platform by introducing new products called the EGX Jetson Xavier NX and EGX A100.

AI Chipset Market Report Scope and segmentation:

Report Coverage

Details

Forecast Period

2020 to 2027

Forecast Period 2021 to 2028 CAGR

38.9%

2027 Value Projection

USD 108.85 Billion

Base Year

2019

Market Size in 2019

USD 8.14 Billion

Historical Data for

2016 to 2018

No. of Pages

160

Segments covered

Chipset Type, Application, Computing technology, Function, Industry

Growth Drivers

Popularity of AI-based Solutions to Boost Market During Coronavirus

Rapid Digital Transformation to Drive CRM Market Growth

Emergence of Startup Companies to Propel Market in Asia Pacific

Pitfalls & Challenges

Lack of Skilled AI Workforce to Inhibiting the Market

Speak To Analyst: https://www.fortunebusinessinsights.com/enquiry/speak-to-analyst/artificial-intelligence-ai-chipsets-market-104500

Key Development:

July 2019: MediaTek Inc. announced the launch of its new AI chipset - "MTK i700" that is featured with high-speed edge AI computation for rapid image recognition, AR applications, smart homes, stores, and factories, etc.

The Report Lists the Key Companies in the Artificial Intelligence (AI) Chipsets Market:

NVIDIA Corporation (California, United States)

Intel Corporation (California, United States)

Xilinx, Inc. (California, United States)

Samsung Electronics Co., Ltd. (Suwon-si, South Korea)

Micron Technology, Inc. (Idaho, United States)

Kneron (California, United States)

Alibaba Group Holding Limited (Hangzhou, China)

Qualcomm Technologies, Inc. (California, United States)

International Business Machines Corporation (IBM) (New York, United States)

Alphabet Inc. (Google LLC) (California, United States)

Microsoft Corporation (Washington, United States)

Amazon Web Services (AWS) (Washington, United States)

Advanced Micro Devices, Inc. (AMD) (California, United States)

General Vision, Inc. (California, United States)

Huawei Technologies Co., Ltd. (Shenzhen, China)

Graphcore Limited (Bristol, United Kingdom)

MediaTek Inc. (Hsinchu, Taiwan)

Fujitsu Limited (Tokyo, Japan)

Wave Computing, Inc. (California, United States)

Mythic Inc. (Texas, United States)

Koniku Inc (California, United States)

Tenstorrent Inc. (Ontario, Canada)

SambaNova Systems Inc (California, United States)

Kalray Corporation (Isere, France)

XMOS Limited (Bristol, United Kingdom)

GreenWaves Technologies (Isere, France)

Quick Buy - Artificial Intelligence (AI) Chipsets Market

https://www.fortunebusinessinsights.com/checkout-page/104500

Table Of Content:

Introduction

Key Takeaways

Market Dynamics

Macro and Micro Economic Indicators

Drivers, Restraints, Opportunities and Trends

Impact of COVID-19

Short-term Impact

Long-term Impact

Competition Landscape

Business Strategies Adopted by Key Players

Consolidated SWOT Analysis of Key Players

Porters Five Force Analysis

Global Artificial Intelligence (AI) Chipsets Market Share Analysis and Matrix, 2019

Key Market Insights and Strategic Recommendations

Profiles of Key Players (Would be provided for 10 players only)

Overview

Key Management

Headquarters etc.

Offerings/Business Segments

Key Details (Key details are subjected to data availability in public domain and/or on paid databases)

Employee Size

Key Financials

Read more:

Artificial Intelligence (AI) Chipsets Market to Exhibit an Exceptional CAGR of 38.9% by 2027; Implementation of Risk Management Solutions to Intensify...

Mumbai: Five skills, including artificial intelligence and adaptability, can future-proof workforce in a post-pandemic world, according to a global study by Randstad RiseSmart.

Of these skills, which also include creativity, blockchain, and affiliate marketing, artificial intelligence has emerged as one of the hottest skills to have, according to the study which surveyed HR professionals and employees across several regions including India.

"AI's demand is only set to increase as technology adoption continues. Being a highly scientific field, employees seeking to upskill in this area have taken on a pragmatic approach that translates knowledge into real-world skills and helps them develop capabilities to create data sets, build machine learning models, and use Python and/or R programming to deliver measurable results," said Randstad RiseSmart in a statement.

According to the World Economic Forum, 50% of employees worldwide will need reskilling as technology adoption increases, and this need has likely only increased given the pandemic.

The survey findings add adaptability and creativity as the next best skill to have. Having the right know-how and being able to adapt to changing trends, destabilization, industry shifts can make all the difference to how business functions today, and hence will see strong demand from employers. "When the pandemic set in, businesses had to transform their operating models practically overnight. Being able to adapt to changing situations with ease, and in an efficient manner is a sign of a strong leader," Randstad RiseSmart revealed.

Among a global pool of 1,099 HR professionals and 1,142 employees, across eight countries and 20 industries, the survey took into consideration 152 HR professionals and 154 individual employees from India, representing businesses of all sizes.

Also, blockchain, which was initially designed to be a technology to support, Bitcoin has now evolved into a revolutionary means of handling data and doing business in a digital world. As the demand for blockchain technologies in daily operations increases, so has the demand for resources with a strong knowledge of the same. "Within this space, employers have laid emphasis on identifying and recruiting talent with a strong knowledge of understanding cryptography, distributed computing, security, and consensus algorithms," the survey added.

With large-scale unrest and uncertainty in the market, trust between consumers and brands is at an all-time low. In order to remedy this, affiliate marketing is emerging as an important skill today. Being an affiliate marketer involves constantly ideating to solve problems and bring in solutions that will restore customers faith in brands. From research and analytics to planning and executing well-crafted campaigns that deliver measurable results, affiliate marketing has a lot of potentials to change the face of the sales game.

Subscribe to Mint Newsletters

* Enter a valid email

* Thank you for subscribing to our newsletter.

Never miss a story! Stay connected and informed with Mint. Download our App Now!!

Read this article:

Artificial Intelligence the hottest skill to have in post-pandemic world: Survey - Mint

Can artificial intelligence be employed to understand the context of computer code and write its own? There have been impressive strides being made in this direction, promising to make the work of developers -- and non-developers working with low-code/no-code platforms -- more productive, and more focused on the business at hand.

Last year, Intel, in conjunction with Massachusetts Institute of Technology and Georgia Institute of Technology, announced the creation of an automated engine designed to learn what a piece of software intends to do by studying the structure of the code and analyzing syntactic differences of other code with similar behavior. The goal of the effort "is to democratize the creation of software," said Justin Gottschlich, principal scientist at Intel. "When fully realized, machine programming will enable everyone to create software by expressing their intention in whatever fashion that's best for them, whether that's code, natural language or something else."

OpenAIGPT-3(Generative Pre-trained Transformer) also can be employed to automatically generate computer code. A development manager could "start things off in the project using a tool with GPT-3 features to build the foundation of the application," writes Vincent Tabora in Becoming Human. "By this I mean the skeleton from which the rest of the application will be built upon. The manager can simply type their requirements and the tool will generate what the manager wants. This saves project requirements for additional staff who would otherwise be responsible for building the initial application. After the skeleton has been generated, more advanced developers can come in with the rest of the project requirements to complete the application."

Along with creating new applications, AI for coding may also smooth the way for moving applications and systems to modern platforms. In a recentinterview, Maja Vukovi, an IBM Fellow at the company's Watson Research Center, explained how a client was struggling with millions of lines of code, and her team was able to employ AI to assist in migrating the code to new platforms. "Their mission-critical application has ballooned to over 1.5 million lines of code," she relates. "Decades of adding migrating combining different systems. Moreover, this evolution of the code happened by multiple development teams, some of which moved out to different roles, or are not even in the organization anymore. And there may not be even any documentation left."

It took the company's IT team more than two years of struggling with the legacy code, with no results, Vukovi says. "And why is that? Well, we as humans were not built to go and look through 1.5 million lines of code and understand what business functions are buried in there."

Enter AI. "We built an AI model that helped us, in a very short amount of time, to comb through all the code in this application, she explains. "The AI model helped us to identify just which parts of the code are obsolete or no longer in use, which parts of code are redundant, and also which parts of code can be grouped in more manageable groups of code -- or rather, microservices."

Not only did AI help the IBM team recommend suitable business-function-driven microservices, "but we can also use AI to help generate code for target microservices, further simplifying the time, she continues. "It saves the time and effort for the developers. It can also tell you where the gaps are, what else needs to be done to make those microservices fully executable. This simplifies and accelerates the entire application refactoring process tremendously -- our clients have thousands of applications in their portfolio."

This demonstration project was for one application with 1.5 million lines of code that took two years to do manually, Vukovi emphasizes. "Imagine if you have to modernize thousands of applications. You want to compress that time from a multi-year effort to something that you can do in months, or weeks."

Along these lines, IBM launched an initiative called CodeNet intended to facilitate the application of AI to code snippets, she says. Her team is making more than 14 million samples of code available as part of the open source dataset available on GitHub. The project is intended to provide for code what ImageNet, with its database of 14 million images, provided developers and researchers with identified images. "Our team has extracted the most representative code samples that can help us or help AI train and better help developers write software. Our AI for code technology is going to fundamentally change how we think about coding," Vukovi predicts.

Link:

Artificial intelligence will soon be assisting your platform migrations - ZDNet