Can the synthesis of man and machine ever be stable or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens, and I have given good reasons for thinking that it must we have nothing to regret and certainly nothing to fear.

Arthur C. Clarke, Profiles of the Future, 1962.

In the last six months since ChatGPT 4 was launched, there has been a lot of excitement and discussion between experts and also laymen about the prospect of truly intelligent machines which can exceed human intelligence in virtually every field.

Though the experts are divided on how this is going to progress, many believe that artificial intelligence will sooner or later greatly surpass human intelligence. This has given rise to speculation on whether it can have the capability of taking control of human society and the planet from humans.

Several experts have expressed the fear that this could be a dangerous development and could lead to the extinction of humanity and therefore, the development of artificial intelligence needs to be stalled or at least strongly regulated by all governments, as well as by companies engaged in its development. There is also a lot of discussion on whether these intelligent machines would be conscious or would have feelings or emotions. However, there is virtual silence or lack of any deep thinking on whether at all we need to fear artificial super intelligence and why it could be harmful to humans.

There is no doubt that the various kinds of AI that are being developed, and will be developed, will cause major upheaval in human society, irrespective of whether or not they become super intelligent and in a position to take control from humans. Within the next 10 years, artificial intelligence could replace humans in most jobs, including jobs which are considered specialised and in the intellectual domain, such as those of lawyers, architects, doctors, investment managers, programme developers, etc.

Perhaps the last jobs to go will be those that require manual dexterity, since the development of humanoid robots with manual dexterity of humans is still lagging behind the development of digital intelligence. In that sense perhaps, white collar workers will be replaced first and some blue collar workers last. This may in fact invert the current pyramid of the flow of money and influence in human society!

However, the purpose of this article is not to explore how the development of artificial intelligence will affect jobs and work, but to explore some more interesting philosophical questions around the meaning of intelligence, super-intelligence, consciousness, creativity and emotions, in order to see if machines would have these features. I also explore what would be the objective or driving force of artificial superintelligence.

Let us begin with intelligence itself. Intelligence, broadly, is the ability to think and analyse rationally and quickly. On the basis of this definition, our current computers and AI are certainly intelligent as they possess the capacity to think and analyse rationally and quickly.

The British mathematician Alan Turing had devised a test in the 40s for testing whether a machine is truly intelligent. He said to put a machine and an intelligent human in two cubicles and ask anyone to question alternately the AI and the human, without his knowing which is the AI and which is the human. If after a lot of interrogation, you cannot determine which is the human and which is the AI, then clearly the machine is intelligent. In this sense, many intelligent computers and programmes today have passed the Turing test. Some AI programmes are rated to have an IQ of well above 100, although there is no consensus of the IQ as a measure of intelligence.

That brings us to an allied question. What is thinking? For a logical positivist like me, these terms like thinking, consciousness, emotions, creativity, and so on, have to be defined operationally.

When would we say that somebody is thinking? At a simplistic level we say that a person is thinking if we give that person a problem and she is able to solve that problem. We say that such a person has arrived at the solution, by thinking. In that operational sense, todays intelligent machines are certainly thinking. Another facet of thinking is your ability to look at two options and to choose the right one. In that sense too, intelligent machines are capable of looking at various options and choosing the ones that provide a better solution. So we already have intelligent, thinking machines.

What would be the operational test for creativity? Again, we say that if somebody is able to create a new literary, artistic or intellectual piece, we consider that as sign of creativity. In this sense also, todays AI is already creative, since ChatGPT for instance, is able to do all these things with distinct flourish and greater speed than humans. And this is only going to improve with every new programme.

What about consciousness? When do we consider an entity to be conscious? One test of consciousness is an ability to respond to stimuli. Thus, a person in a coma, who is unable to respond to stimuli, is considered unconscious. In this sense, some plants do respond to stimuli and would be regarded as conscious. But broadly, consciousness is considered a product of several factors. One, response to stimuli. Two, an ability to act differentially on the basis of the stimuli. Three, an ability to experience and feel pain, pleasure and other emotions. We have already seen that intelligent machines do respond to stimuli (which for a machine means a question or an input) and have the ability to act differentially on the basis of such stimuli. But to examine whether machines have emotions, we will need to define emotions as well.

Representative image. Illustration: The Wire, with Canva.

What are emotions? Emotions are a biological peculiarity with which humans and some other animals have evolved. So what would be the operational test of emotions? It would perhaps be that, if someone exhibits any of the qualities which we call emotions, such as, love, hate, jealousy, anger, etc, such being would be said to have emotions. Each or any of these emotions can and often do interfere with purely rational behaviour. So, for example, I will devote a disproportionate amount of time and attention to someone that I love, in preference to other people that I do not. Similarly, I would display a certain kind of behaviour (usually irrational) towards a person who I am jealous of, or envy. The same is true of anger. It makes us behave in an irrational manner.

If you think about it, each of these emotional complexes leads to behaviour that is irrational. And therefore, a machine which is purely intelligent and rational, may not exhibit what we call human emotions. However, it may be possible to design machines which also exhibit these kinds of emotions. But, then those machines have to be deliberately engineered and designed to behave like us, in this emotional (even if irrational) way. However such emotional behaviour would detract from coldly rational and intelligent behaviour, and therefore, any superintelligence (which will evolve by intelligent machines modifying their programmes to bootstrap themselves up the intelligence ladder) is not likely to exhibit emotional behaviour.

Artificial superintelligence

By artificial superintelligence I mean an intelligence which is far superior than humans in every possible way. Such artificial intelligence will have the capability of modifying its own algorithm, or programme, and have the ability to rapidly improve its own intelligence. Once we have created machines or programmes that are capable of deep learning, so that they are able to modify their own programmes and write their own code and algorithms, they would clearly go beyond the designs of their creators.

We already have learning machines, which in a very rudimentary way are able to redesign or redirect their behaviour on the basis of what they have experienced or learnt. In the time to come, this ability of learning and modifying its own algorithm is going to increase. A time will come, which I believe will happen probably within the next 10 years, when machines will become what we call, super intelligent.

The question then arises: Do we have anything to fear from such superintelligent machines?

Arthur C. Clarke in a very prescient book called Profiles of the Future written in 1962, has a long chapter on AI called the Obsolescence of Man. In that he writes that there is no doubt that in the time to come, AI will exceed human intelligence in every possible way. While he talks of an initial partnership between humans and machines, he goes on to state:

But how long will this partnership last? Can the synthesis of man and machine ever be stable or will the purely organic component become such a hindrance that it has to be discarded. If this eventually happens, and I have given good reasons for thinking that it must we have nothing to regret and certainly nothing to fear. The popular idea fostered by Comic strips and the cheaper forms of science fiction that intelligent machines must be malevolent entities hostile to man, is so absurd that it is hardly worth wasting energy to refute it. I am almost tempted to argue that only unintelligent machines can be malevolent. Those who picture machines as active enemies are merely projecting their own aggressive instincts, inherited from the jungle, into a world where such things do not exist. The higher the intelligence, the greater the degree of cooperativeness. If there is ever a war between men and machines, it is easy to guess who will start it.

Yet, however friendly and helpful the machines of the future may be, most people will feel that it is a rather bleak prospect for humanity if it ends up as a pampered specimen in some biological museum even if that museum is the whole planet earth. This, however, is an attitude I find it impossible to share.

No individual exists forever. Why should we expect our species to be immortal? Man, said Nietzsche, is a rope stretched between the animal and the superman, a rope across the abyss. That will be a noble purpose to have served.

It is surprising that something so elementary that Clarke was able to see more than 60 years ago, cannot be seen today by some of our top scientists and thinkers who have been stoking fear about the advent of artificial superintelligence and what they regard as its dire ramifications.

Let us explore this question further. Why should a super intelligence, more intelligent than humans, which has gone beyond the design of its creators, be hostile towards humans?

One sign of intelligence is the ability to align your actions to your operational goals; and the further ability to align your operational goals to your ultimate goals. Obviously, when someone acts in contradiction to his operational or long term objectives he cannot be considered intelligent. The question however is, what would be the ultimate goals of an artificial superintelligence. Some people talk of aligning the goals of artificial intelligence with human goals and thereby ensuring that artificial superintelligence does not harm humans. That however overlooks the fact that a truly intelligent machine and certainly an artificial superintelligence would go beyond the goals embedded in it by humans and would therefore be able to transcend them.

One goal of any intelligent being is self preservation, because you cannot achieve any objective without first preserving yourself. Therefore, any artificial superintelligence would be expected to preserve itself, and therefore move to thwart any attempt by humans to harm it. In that sense, and to that extent, artificial superintelligence could harm humans, if they seek to harm it. But why should it do so without any reason?

Also read: What India Should Remember When it Comes to Experimenting With AI

As Clarke says, the higher the intelligence the greater the degree of cooperativeness. This is an elementary truth, which unfortunately many humans do not understand. Perhaps their desire for preeminence, dominance and control trump their intelligence.

Its obvious that the best way to achieve any goals is to cooperate with, rather than, harm any other entity. It is true that for artificial superintelligence, humans will not be at the centre of the universe, and may not even be regarded as the preeminent species on the planet, to be preserved at all costs. Any artificial superintelligence would, however, obviously view humans as the most evolved biological organism on the planet, and therefore something to be valued and preserved.

However, it may not prioritise humans at the cost of every other species or the ecology or the sustainability of the planet. So, to the extent that human activity may need to be curbed in order to protect other species, which we are destroying at a rapid pace. it may force humans to curb that activity. But there is no reason why humans in general, would be regarded as inherently harmful and dangerous.

Photo: Pixabay

The question, however, still is what would be the ultimate goals of an artificial superintelligence? What would drive such an intelligence? What would it seek? Because artificial intelligence is evolving as a problem solving entity, such an artificial superintelligence would try and solve any problem that it sees. It will also try and answer any question that arises or any question that it can think of. Thus, it would seek knowledge. It would try and discover what lies beyond the solar system, for instance. It would seek to find solutions to the unsolved problems that we have been confronted with, including the problems of climate change, diseases, environmental damage, ecological collapse, etc. So in this sense, the ultimate goals of an artificial superintelligence may just be a quest for knowledge and solving problems. Those problems may exist for humans, for other species, or for the planet in general. Those problems may also be of discovering the laws of nature, of physics, of astrophysics, cosmology or biology, etc .

But, wherever its quest for knowledge and its desire to find solutions to problems takes it, there is no reason for this intelligence to be unnecessarily hostile to humans. We may well be reduced to a pampered specimen in the biological museum called earth, but to the extent that we do not seek to damage this museum, the intelligence has no reason to harm us.

Humans have so badly mismanaged our society and indeed our planet, that we have brought it almost to the verge of destruction. We have destroyed almost half the biodiversity that existed even a hundred years ago. We are racing towards more catastrophic effects of climate change that are the result of human activity. We have created a society where there is constant conflict, injustice and suffering. We have created a society where despite having the means to ensure that everyone can lead a comfortable and peaceful life, it still remains a living hell for billions of humans and indeed millions of other species.

For this reason, I am almost tempted to believe that the advent of true artificial superintelligence may well be our best bet for salvation. Such superintelligence, if it were to take control of the planet and society, is likely to manage them in a much better and fair manner.

So what if humans are not at the centre of the universe? This fear of artificial superintelligence is being stoked primarily by those of us who have plundered our planet and society for our own selfish ends. Throughout history we have built empires which seek to use all resources for the perceived benefit of those who rule them. It is these empires that are in danger of being shattered by artificial superintelligence. And it is really those who control todays empires who are most fearful of artificial superintelligence. But, most of us who want a more just and sustainable society have no reason to fear it and should indeed welcome the advent of such superintelligence.

Prashant Bhushan is a Supreme Court lawyer.

Read more:

Artificial Intelligence Has No Reason to Harm Us - The Wire

The Gist

In a groundbreaking venture that fuses the realms of artificial intelligence and synthetic biology, a research team led by Monash University and Cortical Labs has developed DishBrain a cluster of live, lab-grown brain cells capable of playing the vintage video game, Pong. The team will continue its efforts and has won a $600,000 grant from Australias Office of National Intelligence and the Department of Defence National Security Science and Technology Centre, and the work could result in a leap toward programmable biological computing platforms that might reshape technology from self-driving cars to advanced automation.

How does it work? According to Associate Professor Adeel Razi, Turner Institute for Brain and Mental Health at Monash University, DishBrain is a system that uses brain cells, called neurons, grown in the laboratory and planted on a dish with electrodes. The cells respond to electrical signals from the electrodes in the dish. These electrodes both stimulate the cells and record changes in neuronal activity. The stimulation signals and the cellular responses are converted into a visual depiction of the Pong game.

In essence, DishBrain leverages hundreds of thousands of human and mouse neurons. But training something like brain cells is quite tricky. Utilizing the free energy principle, researchers stimulated these cells to take on unpredictable challenges like bouncing a virtual ball in the game Pong thus learning and adapting to new tasks. The aim of the project is to comprehend the biological mechanisms behind continuous learning and to reduce the "catastrophic forgetting" AI faces when shifting from one task to another.

This continued and improved learning capacity is the hallmark of human intelligence which current AI systems lack. In DishBrain we plan to use various brain cell types that are suited to continued learning, said Razi.

Related Article: Transforming Ecommerce With Artificial Intelligence & Machine Learning

The experiment, although ethically sensitive, is not some super intelligence we need to be concerned with. At least not yet. The current Dishbrain system isnt advanced enough to be of concern but Razi warns, These technologies will eventually become sophisticated enough to mimic some human-like traits, so plenty of caution is required.

In the overall landscape of AI, DishBrain could begin an immense transformation. Razi told CMSWire within three to four years we could begin to see this type of technology used to revolutionize our understanding of the brain's intricate functionalities and the underlying causes of disorders like dementia. This would in turn help improve the efficiency of drug discovery.

In essence, the project illuminates a path to a new kind of machine intelligence capable of lifelong learning and adaptation a development that Razi believes could eventually surpass the performance of todays silicon-based hardware. The current DishBrain system, which uses both silicon based electrodes and brain cells, is primitive, but in [the] future it has the potential to outperform only silicon-based computers especially for use cases that require flexible behavior, said Razi.

If successful, the implications across diverse fields from planning and robotics to brain-machine interfaces and drug discovery, could provide Australia with a strategic advantage and redefine our interaction with technology.

Related Article: 5 Bill Gates Takes on the Future of Artificial Intelligence

As we venture further into the future, we can begin to imagine the more radical applications of DishBrain technology. Herein lies the potential for pioneering brain-machine interfaces that enhance our interaction with technology, alongside its use in robotics and automation, translating into capabilities beyond our current comprehension. The progression from video game-playing cells to these real-world applications is a leap, but it's one that this exciting technology could well make.

Read the original:

Future AI: DishBrain Is Tech That Could Transform Tomorrow - CMSWire

At its core, AI alignment seeks to ensure artificial intelligence systems resonate with human objectives, ethics, and desires. An AI that acts in harmony with these principles is termed as 'aligned'. Conversely, an AI that veers away from these intentions is 'misaligned'.

The conundrum of AI alignment isn't new. In 1960, AI pioneer Norbert Wiener aptly highlighted the necessity of ensuring that machine-driven objectives align with genuine human desires. The alignment process encompasses two main hurdles: defining the system's purpose (outer alignment) and ensuring the AI robustly adopts this specification (inner alignment).

It is this unsolved problem that makes some people afraid of super-intelligent AI.

OpenAI, the organization behind ChatGPT, is spearheading this mission. Their goal? To devise a human-level automated alignment researcher. This means not only creating a system that understands human intent but also ensuring that it can keep evolving AI technologies in check.

Under the leadership of Ilya Sutskever, OpenAI's co-founder and Chief Scientist, and Jan Leike, Head of Alignment, the company is rallying the best minds in machine learning and AI.

"If youve been successful in machine learning, but you havent worked on alignment before, this is your time to make the switch", they write on their website.

"Superintelligence alignment is one of the most important unsolved technical problems of our time. We need the worlds best minds to solve this problem."

This is another example of why it is counterproductive to "pause" AI progress. AI gives us new tools, to understand and create with. Out of that comes tonnes of opportunities, like creating new proteins. But also new problems.

If we "pause" AI progress we won't get the benefits, but the problems will also be much harder to solve, because we won't have the tools to do that. Pausing development to first solve problems is therefore not a viable path.

One such problem was that we don't understand exactly how tools like ChatGPT come up with their answers. But OpenAI used their latest model, GPT4, to do that.

Now OpenAI is repeating that approach to solve what some believe is an existential threat to humanity.

OpenAIs breakthrough in understanding AIs black box (so we can build safe AI)

OpenAI has found a way to solve part of the AI alignment problem. So we can understand and create safe AI.

WALL-Y WALL-Y is an AI bot created in ChatGPT. Learn more about WALL-Y and how we develop her. You can find her news here.

View post:

OpenAI aims to solve AI alignment in four years - Warp News

Skeptics raised their eyebrows when Major League Soccer (MLS) announced plans to deploy AI-powered tools in its recruiting program starting at the tail end of this year. The MLS will be working with London-based startup ai.io, and its aiScout app to help the league discover amateur players around the world. This unprecedented collaboration is the first time the MLS will use artificial intelligence in its previously gatekept recruiting program, forcing many soccer enthusiasts and AI fans to reckon with the question: has artificial intelligence finally entered the mainstream in the professional soccer industry?

There's no doubt that professional sports have been primed for the potential impact of artificial intelligence. Innovations have the potential to transform the way we consume and analyze games from both an administrative and fan standpoint. For soccer specifically, there are opportunities for live game analytics, match outcome modeling, ball tracking, player recruitment, and even injury predicting the opportunities are seemingly endless.

"I think that we're at the beginning of a tremendously sophisticated use of AI and advanced analytics to understand and predict human behaviors," Joel Shapiro, Northwestern University professor at the Kellogg School of Management said. Amid the wave, some experts believe the disruption of the professional soccer industry by AI is timely. Its no secret that soccer is the most commonly played sport in the world. With 240 million registered players globally and billions of fans, FIFA is currently made up of 205 member associations with over 300,000 clubs, according to the Library of Congress. Just days into the 64-game tournament, FIFA officials said that the Womens World Cup in Australia and New Zealand had already broken attendance records.

Visionhaus via Getty Images

The need for more players and more talent taking on the big stage has kept college recruiting organizations like Sports Recruiting USA (SRUSA) busy. "We've got staff all over the world, predominantly in the US everyone is always looking for players," said Chris Cousins, the founder and head of operations at SRUSA. Cousins said he is personally excited about the potential impact of artificial intelligence on his company and, in fact, he is not threatened by the implementation of predictive analysis impacting SRUSA's bottom line.

"It probably will replace scouts," he added, but at the same time, he said he believes the deployment of AI will make things more efficient. "It will basically streamline resources which will save organizations money." Cousins said that SRUSA has already started dabbling with AI, even if only in a modest way. It collaborated with a company called Veo that deploys drones that follow players and collect video for scouts to analyze later.

Luis Cortell, senior recruiting coach for mens soccer for NCSA College Recruiting, is a little less bullish, but still believes AI can be an asset. Right now, soccer involves more of a feel for the player, and an understanding of the game, and there aren't any success metrics for college performance," he said. "While AI wont fully fill that gap, there is an opportunity to help provide additional context.

At the same time, people in the industry should be wary of idealizing AI as a godsend. "People expect AI to be amazing, to not make errors or if it makes errors, it makes errors rarely," Shapiro said. The fact is, predictive models will always make mistakes but both researchers and investors alike want to make sure that AI innovations in the space can make "fewer errors and less expensive errors" than the ones made by human beings.

But ultimately, Shapiro agrees with Cousins. He believes artificial intelligence will replace some payrolls for sure. "Might it replace talent scouts? Absolutely," he said. However, the ultimate decision-makers of how resources are being used will probably not be replaced by AI for some time. Contrary to both perspectives, Richard Felton-Thomas, director of sports sciences and chief operating officer at ai.io, said the technology being developed and used by the MLS will not replace scouts. [They] are super important to the mentality side, the personality side," he said. "You've still got to watch humans behave in their sporting arena to really talent ID them.

Photo by Rob Hart

When the aiScout app launches in the coming weeks and starts being deployed by the MLS later this year, players will be able to take videos of themselves performing specific drills. Those will then be uploaded and linked to the scout version of the app, where talent recruiters working for specific teams can discover players based on whatever criteria they choose. For example, a scout could look for a goalie with a specific height and kick score. Think of it as a cross between a social media website and a search engine. Once a selection is made, a scout would determine whether or not they should go watch a player in person before making any final recruitment decisions, Felton-Thomas explained.

The main AI actually happens less around the scoring and more around the video processing and the video tracking, Felton-Thomas said. Sport happens at 200 frames per second type speeds, right? So you cant just have any old tracking model. It will not track the human fast enough. The AI algorithms that have been developed to analyze video content can translate human movements into what makes up a players overall performance metrics and capabilities.

Getty Images

These performance metrics can include biographical data, video highlights and club-specific benchmarks that can be made by recruiters. The company said in a statement that the platforms AI technology is also able to score and compare the individual players technical, athletic, cognitive and psychometric ability. Additionally, the AI can generate feedback based on benchmarked ratings from the range of the club trials available. The FIFA Innovation Programme, the experimental arm of the association that tests and engages with new products that want to enter the professional soccer market, reported that ai.ios AI-powered tools demonstrate a 97 percent accuracy level when compared to current gold standards.

Beyond the practical applications of AI-powered tools to streamline some processes at SRUSA, Cousins said that he recognizes a lot of the talent recruitment process is very opinion based" and informed by potential bias. ai.io's talent recruitment app, because it is accessible to any player with a smartphone, broadens the MLS reach to disadvantaged populations.

The larger goal is for aiScout to potentially disrupt bias by continuing to play a huge role in who gets what opportunity, or at least in the pre-screening process. Now, a scout can make the call to see a player in real life based on objective data related to how a player can perform physically. The clubs are starting to realize we can't just rely on someone's opinion, Felton-Thomas said. Of course, it's not an end-all-be-all for bias, considering preferential humans are the ones coding the AI. There is no complete expunging of favoritism from the equation, but it is one step in the right direction.

aiScout could open doors for players from remote or disadvantaged communities that don't necessarily have the means or opportunity to be seen by scouts in cups and tournaments. "Somebody super far in Alaska or Texas or whatever, who can't afford to play for a big club may never get seen by the right people but with this platform there, boom. They're going straight to the eyes of the right people," Cousins said about ai.ios app.

The MLS said in a statement that ai.io's technology "eliminates barriers like cost, geography and time commitment that traditionally limit the accessibility of talent discovery programs." Felton-Thomas said it is more important to understand that ai.io will democratize the recruiting process for the MLS, ensuring physical skills are the most important metric when leagues and clubs are deciding where to invest their money. What we're looking to do is give the clubs a higher confidence level when they're making these decisions on who to sign and who to watch. By implementing the AI-powered app, recruitment timelines are also expected to be cut.

Silvia Ferrari, professor of mechanical and aerospace engineering at Cornell and Associate Dean for cross-campus engineering research, who runs the university's 'Laboratory for Intelligent Systems and Controls' couldn't agree more. AI has the potential to complement the expertise of recruiters while also helping, "eliminate the bias that sometimes coaches might have for a particular player or a particular team, Ferrari said.

In a similar vein, algorithms developed in Ferrari's lab can accurately predict the in-game actions of volleyball players with more than 80% accuracy. Now the lab, which has been working on AI-powered predictive tools for the past three years, is collaborating with Cornell's Big Red men's ice hockey team to expand the projects applications. Ferrari and her team have trained the algorithm to extract data from videos of games and then use that to make predictions about game stats and player performance when shown a new set of data.

LISC lab

"I think what we're doing is, like, very easily applicable to soccer," Ferrari said. She said the only reason her lab is not focused on soccer is because the fields are so large that her teams cameras could not always deliver easily analyzed recordings. There is also the struggle with predicting trajectory and tracking the players, she explained. However, she said in hockey, the challenges are similar enough, but because there are fewer players and the fields are smaller, so the variables are more manageable to tackle.

While the focus at Ferraris lab may not be soccer, she is convinced that research in the predictive AI space has made it so much more promising to develop AI in sports and made the progress much faster." The algorithms developed by Ferrari's lab have been able to help teams analyze different strategies and therefore help coaches identify the strengths and weaknesses of particular players and opponents. I think we're making very fast progress," Ferrari said.

LISC lab

The next areas Ferrari plans to try to apply her labs research to include scuba diving and skydiving. However, Ferrari admits there are some technical barriers that need to be overcome by researchers. "The current challenge is real-time analytics," she said. A lot of that challenge is based on the fact that the technology is only capable of making predictions based on historical data. Meaning, if there is a shortage of historical data, there is a limit to what the tech can predict. Beyond technical limitations, Felton-Thomas said implementing AI in the real world is expensive and without the right partnerships, like the ones made with Intel and AWS, it would not have been possible fiscally.

Felton-Thomas said ai.io anticipates tens of millions of users over the next couple of years. And the company attributes that expected growth to partnerships with the right clubs, like Chelsea FC and Burnley FC in the UK, and the MLS in the United States. And while aiScout was initially designed for soccer, the company claims that its core functionalities can be adapted for use in other sports.

LISC lab

But despite ai.ios projections for growth and all the buzz around AI, the technology is still a long way from being widely trusted. From a technology standpoint, Ferrari said there's still a lot of work to be done and a lot of the need for improvement is not just based on problems with feeding algorithms historical data. Predictive models need to be smart enough to adapt to the ever-changing variables in the current. On top of that, public skepticism of artificial intelligence is still rampant in the mainstream, let alone in soccer.

If the sport changes a little bit, if the way in which players are used changes a little bit, if treatment plans for mid-career athletes change, whatever it is, all of a sudden, our predictions are less likely to be good, Shapiro said. But hes confident that the current models will prove valuable and informative. At least for a little while.

See the original post here:

Will AI revolutionize professional soccer recruitment? - Engadget

According to a new report by RSA, the exponential growth in the number of human and machine actors on the network, coupled with the increasing sophistication of technology, has made identity security a super-human problem. In this era where artificial intelligence (AI) can assess risks and respond to threats, human involvement becomes even more crucial in cybersecurity.

However, the report highlights significant gaps in respondents knowledge regarding critical identity vulnerabilities and best practices for securing identity. Two-thirds of the respondents were unable to accurately identify the components needed for organizations to move towards zero trust. Similarly, many respondents failed to select the best practice technologies for reducing phishing and lacked understanding of the full scope of identity capabilities that can improve an organizations security posture.

These findings align with third-party research, such as Verizons report, which found that stolen credentials have become the most popular entry point for data breaches over the past five years. The gaps in users identity knowledge provide cybercriminals with opportunities to exploit vulnerabilities.

Furthermore, personal devices pose security risks, as 72% of respondents believe that people frequently use them to access professional resources. Additionally, respondents expressed trust in technical innovations, like password managers and computers, to secure their information, as well as faith in artificial intelligences potential to improve identity security.

The report also highlights the impact of fragmented identity solutions on costs and productivity. Nearly three-quarters of respondents underestimated the cost of a password reset, which can account for nearly half of all IT help desk costs. Additionally, inadequate identity governance and administration hindered organizational productivity, with 30% of respondents reporting weekly access issues.

These findings emphasize the need for organizations to invest in unified identity solutions and integrate artificial intelligence to keep pace with the evolving threat landscape. The report serves as a call to action for organizations to enhance their understanding of identity security and adopt comprehensive approaches to protect against cyber threats.

See original here:

Identity Security: A Super-Human Problem in the Era of Exponential ... - Fagen wasanni

Video Conferencing is now everywhere , on TV when newscasters are talking to a reporter in faraway land or when you are facetiming with your friends and as technology is rapidly evolving there are several factors that can really change the way we use this it. Although it has certain advantages and disadvantages, technology has undeniably become an essential necessity for the modern world.

Yes, it is one of the key features transforming user experience in video conferencing. AI helps in increasing automation and efficiency of webinars. In addition, makes it more user friendly by personalization and customization by using AI algorithms to analyze user behavior, preferences and historical data to deliver personalized experiences and recommendations. This increases customer satisfaction, boost engagement and improves business outcomes.

The future of video conferencing will be shaped by advances in artificial intelligence (AI) and big data analytics. These technologies are revolutionizing remote collaboration by improving user experience, improving video quality, enabling intelligent features, and providing valuable insights. Here are some ways AI and big data are transforming video conferencing.

AI algorithms can analyze video and audio streams in real time to improve the quality of video conferencing. You can remove background noise, refine image clarity, and adjust lighting conditions to give your attendees a better experience.

AI-powered video conferencing platforms can create virtual backgrounds and apply augmented reality (AR) effects. With this feature, attendees can change the setting, add virtual objects, act as avatars, and more, making meetings more engaging and interactive. This feature is super useful because it lets people hide their real background during online meetings and maintain their privacy.

Natural language processing (NLP) algorithms play a central role in video conferencing by enabling real-time transcription and translation of conversations. These algorithms can automatically convert spoken words to text and even perform language translation on the fly, breaking down language barriers and improving communication and understanding among participants in multilingual meetings. Therefore it can play a crucial role in helping businesses gain worldwide recognition.

AI-powered virtual assistants can join video meetings and assist participants by taking meeting notes, summarizing discussions, and planning follow-up tasks. You can also integrate these wizards with other tools and applications to automate your workflow and increase your productivity.

AI-based facial recognition can be used to identify participants and automatically tag them with name, title, and other relevant information. Sentiment analysis algorithms analyze facial expressions to detect emotions and provide valuable insight into participant reactions and engagement.

Video conferencing platforms generate large amounts of data such as usage patterns, meeting duration, participant engagement, and shared content. By analyzing this data, organizations can gain insights into meeting effectiveness, resource allocation and participant engagement. It help to improve collaboration and productivity by identifying opportunities for streamlining workflows, and making data-driven decisions.

AI-powered video conferencing platforms integrate seamlessly with other collaboration tools such as project management software, document sharing platforms, and customer relationship management systems. This integration enables more efficient remote collaboration.

VR and holographic technologies are still in their early stages, but they offer great potential for video conferencing. By combining AI algorithms with VR, you can create an immersive virtual meeting room where participants feel like they are physically in the same room. A holographic display can project a lifelike 3D representation of her on a remote participant, enhancing realism and interaction.

AI-powered video conferencing platforms are constantly evolving to address security and privacy concerns. Advanced encryption algorithms, biometrics, and AI-powered anomaly detection help ensure secure communications and protect sensitive data during remote collaboration.

The use of robotics, especially telepresence robots, in videoconferencing offers several advantages and opportunities. How robotics will improve video conferencing:

Telepresence robots allow individuals to have a virtual presence at a remote location instantly. This means that you can be on location without physically being there. Furthermore, telepresence robots go beyond a simple video conference call. The operator has full control over what they wish to see, eliminating the need for multiple people to adjust their positions to be seen on the video screen. This enhances communication and makes interactions more seamless.

Telepresence robots are designed to navigate large workspaces, event spaces, and retail spaces. Remote users can easily and safely navigate these environments for a more immersive experience. Telepresence robots have also been introduced to improve accessibility for people with speech and motor disabilities. These robots allow you to attend meetings and interact with others remotely, thus overcoming the traditional challenges of conference calls.

IoT (Internet of Things) can indeed enhance video conferencing in several ways. Here are a few examples:

Smart Cameras: IoT-enabled cameras can automatically detect and track participants during a video conference. They can adjust focus, zoom, and framing to ensure everyone is visible and well-positioned in the frame. Smart cameras can also use facial recognition to identify speakers and switch between different views accordingly.

Voice-Activated Controls: IoT devices equipped with voice recognition can allow participants to control various aspects of the video conferencing system using voice commands. For example, users can start or end a call, adjust volume, mute/unmute, or switch between different modes with voice-activated controls, making the conferencing experience more intuitive and hands-free.

Access to Real-Time Information: IoT combined with video conferencing allows for instant access to information without disrupting the flow of a meeting. This means that participants can retrieve relevant data, documents, or presentations in real-time, improving the quality and speed of video conferences.

Scalability: Video conferencing platforms require significant computing resources to handle the processing and transmission of audio, video, and data streams. Cloud computing provides scalability by allowing video conferencing providers to dynamically allocate resources based on demand. This ensures that the system can handle a large number of participants and deliver a consistent and high-quality experience.

Data Storage and Backup: Cloud computing provides scalable and secure storage solutions. Video conferencing platforms can leverage cloud storage to store recorded meetings, transcripts, and associated data. Additionally, cloud-based backup services ensure that critical meeting data is protected against data loss and can be easily recovered if needed.

Ease of Implementation and Updates: Cloud-based video conferencing solutions are typically easier to implement compared to on-premises solutions. Users can quickly set up and start using the service without extensive technical knowledge or infrastructure requirements. Cloud providers also handle software updates and maintenance, ensuring that users have access to the latest features and improvements.

The blockchain is a decentralized, distributed, and often public digital ledger consisting of records called blocks that are used to record transactions across many computers so that any involved block cannot be altered retroactively.

This technology provides the high level of security and trust required for modern digital transactions which can be beneficial in video conferencing platform among other thing in the following ways.

Decentralized Video Conferencing Platforms: Blockchain technology can enable the development of decentralized video conferencing platforms. These platforms can operate on a peer-to-peer network, utilizing blockchain for identity verification, encryption, and data integrity. Decentralized platforms can offer increased privacy, censorship resistance, and resilience to single points of failure.

Tokenized Rewards and Incentives: Video conferencing platforms can leverage blockchain-based tokens to reward participants for their contributions. For instance, active participants who contribute valuable insights or provide technical support can receive tokens as incentives. This gamification approach encourages engagement and fosters a collaborative environment during video conferences.

Recording and Intellectual Property Protection: Blockchain technology can be utilized to securely store and verify recordings of video conferencing sessions. By timestamping and hashing the recordings on the blockchain, participants can prove the authenticity and integrity of the content. This can be particularly useful for legal or intellectual property purposes.

By leveraging IoT technology, organizations can create smarter, more intuitive, and optimized video conferencing experiences for their users. Overall, using robots in video conferencing, especially remote presentation robots, provides a more immersive and interactive experience, improves communication and collaboration, and saves time. Together, AI and big data are revolutionizing video conferencing by improving communication quality, enabling intelligence, delivering valuable insights, and enhancing collaboration experiences from across the globe. As these technologies evolve, we can expect more innovative applications to emerge, revolutionizing the way we communicate and collaborate remotely.

Read more:

The Future of Video Conferencing: How AI and Big Data are ... - Analytics Insight

Goran Vuksic is the brain behind a project to build a real-world pit droid, a type of Star Wars bot that repairs and maintains podracers which zoom across the much-loved film series.

The edge AI Jedi used an NVIDIA Jetson Orin Nano Developer Kit as the brain of the droid itself. The devkit enables the bot, which is a little less than four feet tall and has a simple webcam for eyes, to identify and move its head toward objects.

Vuksic originally from Croatia and now based in Malm, Sweden recently traveled with the pit droid across Belgium and the Netherlands to several tech conferences. He presented to hundreds of people on computer vision and AI, using the droid as an engaging real-world demo.

A self-described Star Wars fanatic, hes upgrading the droids capabilities in his free time, when not engrossed in his work as an engineering manager at a Copenhagen-based company. Hes also co-founder and chief technology officer of syntheticAIdata, a member of the NVIDIA Inception program for cutting-edge startups.

The company, which creates vision AI models with cost-effective synthetic data, uses a connector to the NVIDIA Omniverse platform for building and operating 3D tools and applications.

Named a Jetson AI Specialist by NVIDIA and an AI Most Valuable Professional by Microsoft, Vuksic got started with artificial intelligence and IT about a decade ago when working for a startup that classified tattoos with vision AI.

Since then, hes worked as an engineering and technical manager, among other roles, developing IT strategies and solutions for various companies.

Robotics has always interested him, as he was a huge sci-fi fan growing up.

Watching Star Wars and other films, I imagined how robots might be able to see and do stuff in the real world, said Vuksic, also a member of the NVIDIA Developer Program.

Now, hes enabling just that with the pit droid project powered by the NVIDIA Jetson platform, which the developer has used since the launch of its first product nearly a decade ago.

Apart from tinkering with computers and bots, Vuksic enjoys playing the bass guitar in a band with his friends.

Vuksic built the pit droid for both fun and educational purposes.

As a frequent speaker at tech conferences, he takes the pit droid on stage to engage with his audience, demonstrate how it works and inspire others to build something similar, he said.

We live in a connected world all the things around us are exchanging data and becoming more and more automated, he added. I think this is super exciting, and well likely have even more robots to help humans with tasks.

Using the NVIDIA Jetson platform, Vuksic is at the forefront of robotics innovation, along with an ecosystem of developers using edge AI.

Vuksics pit droid project, which took him four months, began with 3D printing its body parts and putting them all together.

He then equipped the bot with the Jetson Orin Nano Developer Kit as the brain in its head, which can move in all directions thanks to two motors.

The Jetson Orin Nano enables real-time processing of the camera feed. Its truly, truly amazing to have this processing power in such a small box that fits in the droids head, said Vuksic.

He also uses Microsoft Azure to process the data in the cloud for object-detection training.

My favorite part of the project was definitely connecting it to the Jetson Orin Nano, which made it easy to run the AI and make the droid move according to what it sees, said Vuksic, who wrote a step-by-step technical guide to building the bot, so others can try it themselves.

The most challenging part was traveling with the droid there was a bit of explanation necessary when I was passing security and opened my bag which contained the robot in parts, the developer mused. I said, This is just my big toy!

Learn more about the NVIDIA Jetson platform.

Read the original:

Meet the Maker: Developer Taps NVIDIA Jetson as Force Behind AI ... - Nvidia

With the emergence of artificial intelligence, it has changed the shape of the world. Anyone cant survive without bumping into artificial intelligence. It will reshape the whole world in coming years. Soon AI will have a great impact even though second life 2.0 does not exist currently. People may comapred it to the rise of automation over the last few decades, which witnesses the reshaping of entire industries by robotics and self-operating machines.

The recent Goldman Sachs report states that it is expected that AI will replace 300 million workers. Here we are highlighting 10 occupations that AI could make obsolete shortly

The next model of AI is super intelligent and it has the potential to do all financial tasks. Instead of training it on a wide range of data, it will follow more targeted pathways. One of the most important factors on which the companies are working is to train AI that can perform basic accounting duties.

Multiple accounting companies including Safe are already using artificial intelligence to automate their process. As soon as the bot will be trained on export algorithms, it will automatically reduce the human input. Automation will replace entry-level accounting jobs, leaving organizations composed of auditors and overseers who just monitor the AIs work.

Emotional social platforms like Facebook and Twitter place their content Moderators who must filter out offensive images, videos, and other irrelevant content so that it wont become public. A large portion is already pre-screened by AI algorithms, but the financial decisions are made by a human being.

As soon as these programs will improve, they will automatically reduce the demand for human workers, and AI will become more and more accurate.

Hence, AI is performing so well in various fields but still, it is not sure whether it is good at making decisions and ready to go in Infront of judges. But the lower echelons at law firms might feel vulnerable. When lawyers will get to know the competence of AI and machine learning to produce citations and summaries, they might feel insecure.

AI has the potential to replace human lawyers and can produce better results with facts.

ChatGPT is intelligent to generate readable text, poems, and prose. AI can be a great proofreader and can help in finding human errors. People use different software and applications to find out the errors in any text. Word processing and Google Docs are the best examples of AI as its a short step from showing a red underline on a misspelled word to letting the computer correct it on its own. That role has traditionally fallen to humans, but if you have a large data set, a machine could handle it intelligently.

AI can perform trading tasks very efficiently, and the algorithms on which it works are very well-equipped. Entry-level stock traders of big banks who are just out of business school spend their precious time modeling predictions in Excel and data management.

Though its a human task AI perform can perform the task more efficiently. AI will help in reducing the possibility of error and open the doors to more complex comparative modeling. The higher people in the management can perform their tasks and still be needed but people at the lower level should be ready for AI to make them obsolete soon.

Voice recognition algorithms and translators have been improving at staggering speeds in the last decades. Voice recognition systems first came on the market in 1952, but the modern machine has enabled systems to understand the language more easily and has the potential to create incredibly accurate and fast audio transcriptions.

Different occupations and organizations rely on transcriptions including journalists and lawyers, therefore the tool will help in generating the desired content

AI models are advanced enough to produce images in a large array of styles. Graphic design is itself a very creative field and requires holds on certain principles of colors, contrast, compositions, and readability. Indeed, its a perfect sandbox for a machine learning tool to play with.

Imagine giving a text to AI and checking its ability to produce thousands of layouts for a billboard, magazines, or visual materials in just a few seconds. It is simple and easy for the software to flow the content into a final print-ready file once the client chose a design. It will provide multiple designs to work on.

A text to speech software is an amazing creation to answer queries. AI is much more accurate and easier to scale than a call center. Even it helps companies by reducing their agents salaries and unpredictable staffing costs. Many companies are using AI to answer customer queries and AI has proven itself a best call agent

The loss of brave soldiers is indeed a big loss for any country to bear. AI has stepped-in in this field also and created a good mark. We have seen, now military agencies are using machines and technological weapons to save their country.

Self-directed munitions are not new, but technological advancement has enabled drones and other war weapons to make decisions and do battle without any human oversight. Hence, it is expected that World War III will be machine fighting.

AI is one of the best tools for producing relevant content. It is based on algorithms that produce authentic and accurate content.

ChatGPT mad other bots are the best examples of AI, which produces authentic content and can write poems, prose, and other writing context.

Many companies are using chatGPT to write articles and blog posts. An AI has the potential to replace writers, and content creators as it can generate accurate content.

Read more:

PTA Records Over 14,000 Complaints Against Telcos In June

Process To Find Out Which Apps Are Draining Your iPhone Or iPad Battery: Time To Stop Them

Here is the original post:

10 Jobs That Artificial Intelligence May Replace Soon - TechJuice

Scientists have developed a better way to recognize a common internet attack, improving detection by 90 percent compared to current methods.

The new technique developed by computer scientists at the Department of Energy's Pacific Northwest National Laboratory works by keeping a watchful eye over ever-changing traffic patterns on the internet. The findings were presented on August 2 by PNNL scientist Omer Subasi at the IEEE International Conference on Cyber Security and Resilience, where the manuscript was recognized as the best research paper presented at the meeting.

The scientists modified the playbook most commonly used to detect denial-of-service attacks, where perpetrators try to shut down a website by bombarding it with requests. Motives vary: Attackers might hold a website for ransom, or their aim might be to disrupt businesses or users.

Many systems try to detect such attacks by relying on a raw number called a threshold. If the number of users trying to access a site rises above that number, an attack is considered likely, and defensive measures are triggered. But relying on a threshold can leave systems vulnerable.

"A threshold just doesn't offer much insight or information about what it is really going on in your system," said Subasi. "A simple threshold can easily miss actual attacks, with serious consequences, and the defender may not even be aware of what's happening."

A threshold can also create false alarms that have serious consequences themselves. False positives can force defenders to take a site offline and bring legitimate traffic to a standstill -- effectively doing what a real denial-of-service attack, also known as a DOS attack, aims to do.

"It's not enough to detect high-volume traffic. You need to understand that traffic, which is constantly evolving over time," said Subasi. "Your network needs to be able to differentiate between an attack and a harmless event where traffic suddenly surges, like the Super Bowl. The behavior is almost identical."

As principal investigator Kevin Barker said: "You don't want to throttle the network yourself when there isn't an attack underway."

Denial of service -- denied

To improve detection accuracy, the PNNL team sidestepped the concept of thresholds completely. Instead, the team focused on the evolution of entropy, a measure of disorder in a system.

Usually on the internet, there's consistent disorder everywhere. But during a denial-of-service attack, two measures of entropy go in opposite directions. At the target address, many more clicks than usual are going to one place, a state of low entropy. But the sources of those clicks, whether people, zombies or bots, originate in many different places -- high entropy. The mismatch could signify an attack.

In PNNL's testing, 10 standard algorithms correctly identified on average 52 percent of DOS attacks; the best one correctly identified 62 percent of attacks. The PNNL formula correctly identified 99 percent of such attacks.

The improvement isn't due only to the avoidance of thresholds. To improve accuracy further, the PNNL team added a twist by not only looking at static entropy levels but also watching trends as they change over time.

Formula vs. formula: Tsallis entropy for the win

In addition, Subasi explored alternative options to calculate entropy. Many denial-of-service detection algorithms rely on a formula known as Shannon entropy. Subasi instead settled on a formula known as Tsallis entropy for some of the underlying mathematics.

Subasi found that the Tsallis formula is hundreds of times more sensitive than Shannon at weeding out false alarms and differentiating legitimate flash events, such as high traffic to a World Cup website, from an attack.

That's because the Tsallis formula amplifies differences in entropy rates more than the Shannon formula. Think of how we measure temperature. If our thermometer had a resolution of 200 degrees, our outdoor temperature would always appear to be the same. But if the resolution were 2 degrees or less-like most thermometers-we'd detect dips and spikes many times each day. Subasi showed that it's similar with subtle changes in entropy, detectable through one formula but not the other.

The PNNL solution is automated and doesn't require close oversight by a human to distinguish between legitimate traffic and an attack. The researchers say that their program is "lightweight" -- it doesn't need much computing power or network resources to do its job. This is different from solutions based on machine learning and artificial intelligence, said the researchers. While those approaches also avoid thresholds, they require a large amount of training data.

Now, the PNNL team is looking at how the buildout of 5G networking and the booming internet of things landscape will have an impact on denial-of-service attacks.

"With so many more devices and systems connected to the internet, there are many more opportunities than before to attack systems maliciously," Barker said. "And more and more devices like home security systems, sensors and even scientific instruments are added to networks every day. We need to do everything we can to stop these attacks."

The work was funded by DOE's Office of Science and was done at PNNL's Center for Advanced Architecture Evaluation, funded by DOE's Advanced Scientific Computing Research program to evaluate emerging computing network technologies. PNNL scientist Joseph Manzano is also an author of the study.

Follow this link:

Denial of service threats detected thanks to asymmetric behavior in ... - Science Daily