If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Pluribus is the first AI bot capable of beating human experts in six-player no-limit Hold'em, the most widely played poker format in the world. This is the first time an AI bot has beaten top human players in a complex game with more than two players or two teams. We tested Pluribus against professional poker players, including two winners of the World Series of Poker Main Event. Pluribus succeeds because it can very efficiently handle the challenges of a game with both hidden information and more than two players. It uses self-play to teach itself how to win, with no examples or guidance on strategy. Pluribus uses far fewer computing resources than the bots that have defeated humans in other games. The bot's success will advance AI research, because many important AI challenges involve many players and hidden information. For decades, poker has been a difficult and important grand challenge problem for the field of AI.
IBM has been tweaking the AI-powered highlight picking algorithm it deploys during the Wimbledon tennis championships this year to take into account a wider array of factors to better find and personalise the best points to share with fans around the world. Big Blue is celebrating a 30-year technology partnership with the famous grass court tennis tournament, and in 2017 it unveiled an AI-powered system for picking the best points to insert into a highlights package, with the aim of delivering highlights "better than an international media organisation" as Sam Sneddon, IBM sports and entertainment lead, told Computerworld UK during a tour of its technology bunker on-site at the Championships this year. Whether it was Novak Djokovic and Roger Federer's five-hour epic mens' final, or Simona Halep's swift dismantling of Serena Williams in the ladies' final, IBM was working in the background to map and collect every second of footage before feeding it through a set of machine learning and deep learning algorithms which decide the points that would make for the best 5-10 minute highlight package. The Watson system analyses 39 factors, like player gestures and crowd reactions, from live footage and assigns an'excitement score'. For an idea of scale, IBM collects 4.5 million tennis data points per tournament.
Elon Musk's Neuralink projects have been somewhat secretive since the company was first established. To that effect, all that's been known about the firm was that it was working on machine-brain interfaces. Well, the company has finally gone public with its first project and it turns out that it's an AI that can be inserted into a person's brain to allow them to connect to phones and computers. Machine/brain interface devices have been on the market in some form for over a decade, with people suffering from paralysis seeing many of the benefits of using these kinds of devices. For example, back in 2006, Matthew Nagle, who suffered from a spinal cord injury, was able to play Pong aided by the devices.
Artificial intelligence poses both a blessing and a curse to businesses, customers, and cybercriminals alike. AI technology is what provides us with speech recognition technology (think Siri), Google's search engine, and Facebook's facial recognition software. Some credit card companies are now using AI to help financial institutions prevent billions of dollars in fraud annually. Is artificial intelligence an advantage or a threat to your company's digital security? On one hand, artificial intelligence in cyber security is beneficial because it improves how security experts analyze, study, and understand cybercrime.
"The solution to the Rubik's Cube involves more symbolic, mathematical and abstract thinking, so a deep learning machine that can crack such a puzzle is getting closer to becoming a system that can think, reason, plan and make decisions." An expert system designed for a narrow task, such as only solving a Rubik's Cube will forever be limited to that domain. But a system like DeepCubeA, boasting an adaptable neural net, can be used for other tasks, such as solving complex scientific, mathematical, and engineering problems. Stephen McAleer, a co-author of the new paper, told Gizmodo how this system "is a small step toward creating agents that are able to learn how to think and plan for themselves in new environments." Reinforcement learning works the way it sounds.
Not many robotics companies can boast legions of fans online, but not many robotics companies make robots quite like Boston Dynamics. Each time the firm shares new footage of its machines, they cause a sensation. Whether it's a pack of robot dogs towing a truck or a human-like bot leaping nimbly up a set of boxes, Boston Dynamics' bots are uniquely thrilling. And when a parody video circulated last month showing a CGI "Bosstown Dynamics" robot turning on its creators, many mistook it for the real thing -- a testament to how far the company has pushed what seems technologically possible. But for all its engineering prowess, Boston Dynamics now faces its biggest challenge yet: turning its stable of robots into an actual business.
Artificial Intelligence (AI) and machine learning is no more an unheard concept. AI is everywhere now and is slowly taking over routine jobs from human beings. Digital marketers and businesses are implementing AI to improve their rankings, increase sales revenue, and cut operational costs at the same time. AI is placing itself in almost every aspect of our life. Back in the 2000s, who would have thought of controlling their home appliances using Amazon Echo or Google Home?
As companies increasingly invest in business intelligence and analytical tools, organisations are increasingly unable to derive critical benefits from them. In most cases, this results because of the inflection shift caused by the new oil, Data. Data has transformed how businesses look at their processes and operations. It has changed perspectives and introduced new sources of revenues, insights and competencies. With AI being on the rise, companies are digitally transforming their organisations at a scale never seen before.
Artificial intelligence is transforming a variety of banking functions and allowing tech startups to compete with some of the largest banks for market share of key services, including lending and wealth management. Business news and media sites have been heralding the downfall of the banking industry as we know it because fintech companies are going to feel comfortable leveraging AI long before banks. That said, the future of banking has yet to be decided, and banks still have many advantages over fintech companies they can leverage to survive in the next decade. We spoke with four experts on the state of AI in banking about how banks can use artificial intelligence and machine learning to both retain their market share and win new customers over their competitors, including millennials who are used to online banking. Wilson, Smallwood, and Chandra also all served as research advisors for our AI in Banking Vendor Landscape and Capability Map report.
Advancements in artificial intelligence software in the commercial space have gained traction in recent years. From Watson assisting with diagnoses in doctors' offices to the computer programs running risk analysis for banks making lending decisions, AI has permeated many facets of our lives. However, the federal government's use of AI has received far less attention, despite directly impacting most citizens across the country. The term "artificial intelligence" has been co-opted for a wide array of applications. The definition often includes everything from marginally automated systems to advanced machine learning programs that make decisions independently of a human operator.