БЛОГ

Archive for the ‘robotics/AI’ category: Page 8

Jul 17, 2019

Eight Ways AI Could Impact the Future of Electronic Gaming and Online Gambling

Posted by in category: robotics/AI

How might the application of artificial intelligence enhance the experience and reach of electronic gaming and gambling?

Over the next few years, the internet gaming business could be transformed completely as artificial intelligence (AI) enters the scene. At its core, AI is a type software or hardware that learns—and it could be programmed to learn mostly about us, its users and those insights could drive the developments of new, hyper-personalised gaming and internet betting experiences. The technology is being applied to learn our habits, our likes, and our relationship patterns. Just as Netflix uses an algorithm to suggest films you might watch, the concept of personalisation is extending to the idea of “Lifestyle AI” applications that could help choose your entertainment, gaming choices, wardrobe, your next meal, your job, and romantic partner. Take this one natural step further, and we enter the domain of mass tailoring of gaming and betting experiences.

While it all sounds a bit like science fiction, the capabilities of AI tools and the range of applications are growing exponentially. Indeed, by 2020 AI could be present in some form in everything we do, and by 2030, AI is likely to have infiltrated our lives in much the same way as smartphones, the internet, and global travel are now taken for granted. So how might AI change our recreational habits and day-to-day existence in a way that might affect e-gaming? Here are eight novel ways internet betting could be different in future as a result of AI.

  • Trend Betting – Individuals could bet on the word, phrase, issue, or concept that will be mentioned most across a range of sites on the web during a fixed period, and then AI web crawlers would determine the actual count. Machine learning would be used to profile these trends and patterns over time, predict the likelihood and frequency of occurrence of key terms, and then determine the odds accordingly. Users could volunteer their own terms alongside those which the gambling sites suggest. To determine the initial odds for new terms, machine learning would compare the new term to others it has already analysed, and search the internet to see how frequently it is mentioned. The algorithm would then set the initial odds and refine them over time in response to actual betting patterns and payouts.
  • Campaign Betting – Companies could hedge the costs of their marketing campaigns by betting on their success. Machine learning algorithms could evaluate a campaign, compare keywords and phrases in the material against past campaigns, and then determine the odds accordingly. The company placing the wager could then bet on achieving or not achieving a certain target number of hits.
  • Next Generation Sports Betting – A combination of wearables and implantables tracking vital signs could be worn by sportspeople. Bets could then be placed on the aggregate performance of a team in a game—average heart rate, total calorie consumption, median oxygen intake, etc. The AI system would crunch the numbers in real time and generate minute by minute predictions of the likely outcomes for the rest of the event. Gamblers would be able to jump in at any time to bet on the likely outcome. The odds would be generated by applying machine learning algorithms to analyse the vast amounts of data generated from previous games.
  • Betting on Your Life – With AI, any scenario could turn into a betting opportunity. What are the chances that you would run into a friend at the grocery store? Find a lucky penny? Get a call from your parents? Enjoy your date? Go and see a movie? Be fired by your boss tomorrow? In a form of crowdsourced betting system, if you find enough people to bet on your life events then you could give it a go. Even individuals’ lives could be ranked according to their predictability or spontaneity. The algorithm would do a detailed comparison of your social media profiles and other web postings and data against its databank to determine the odds and change them dynamically as the bets roll in.
  • Beat the Bookies ­– With the analytical capability of AI, an independently developed ‘Beat the Bookie’ app could look at all the variables associated with a sports event. The app might factor in player performance statistics, player behaviour information, weather, previous fixtures, key match events, and create a ‘best bet’ opportunity for the gambler from across all available betting sites. An interesting question arises over how long it would be before the bookmakers develop a counter to the app or a more sophisticated basis for gambling.

Jul 17, 2019

Could artificial intelligence be the future of cancer diagnosis?

Posted by in categories: biotech/medical, robotics/AI

The authors of a recent paper believe that in the future, artificial intelligence might be able to tell benign from malignant lesions without a biopsy.

Jul 16, 2019

Elon Musk unveils Neuralink’s plans for brain-reading ‘threads’ and a robot to insert them

Posted by in categories: biotech/medical, Elon Musk, mobile phones, robotics/AI

Elon Musk’s Neuralink, the secretive company developing brain-machine interfaces, showed off some of the technology it has been developing to the public for the first time. The goal is to eventually begin implanting devices in paralyzed humans, allowing them to control phones or computers.

Jul 16, 2019

AI solves Rubik’s Cube in one second

Posted by in category: robotics/AI

An AI system teaches itself to solve the Rubik’s Cube more quickly than any human.

Jul 16, 2019

Intel’s neuromorphic system surfs next wave in brain-inspired research

Posted by in categories: biological, robotics/AI

A neuromorphic computer that can simulate 8 million neurons is in the news. The term “neuromorphic” suggests a design that can mimic the human brain. And neuromorphic computing? It is described as using very large scale integration systems with electric analog circuits imitating neuro-biological architectures in our system.

This is where Intel steps in, and significantly so. The Loihi chip applies the principles found in biological brains to computer architectures. The payoff for users is that they can process information up to 1,000 times faster and 10,000 times more efficiently than CPUs for specialized applications, e.g., sparse coding, graph search and constraint-satisfaction problems.

Its news release on Monday read “Intel’s Pohoiki Beach, a 64-Chip Neuromorphic System, Delivers Breakthrough Results in Research Tests.” Pohoiki Beach is Intel’s latest neuromorphic system.

Jul 16, 2019

Artificial intelligence designs metamaterials used in the invisibility cloak

Posted by in categories: engineering, particle physics, robotics/AI

Metamaterials are artificial materials engineered to have properties not found in naturally occurring materials, and they are best known as materials for invisibility cloaks often featured in sci-fi novels or games. By precisely designing artificial atoms smaller than the wavelength of light, and by controlling the polarization and spin of light, researchers achieve new optical properties that are not found in nature. However, the current process requires much trial and error to find the right material. Such efforts are time-consuming and inefficient; artificial intelligence (AI) could provide a solution for this problem.

The research group of Prof. Junsuk Rho, Sunae So and Jungho Mun of Department of Mechanical Engineering and Department of Chemical Engineering at POSTECH have developed a design with a higher degree of freedom that allows researchers to choose materials and design photonic structures arbitrarily by using deep learning. Their findings are published in several journals including Applied Materials and Interfaces, Nanophotonics, Microsystems & Nanoengineering, Optics Express, and Scientific Reports.

AI can be trained with a vast amount of data, and it can learn designs of various and the correlation between photonic structures and their optical properties. Using this training process, it can provide a that makes a photonic structure with desired optical properties. Once trained, it can provide a desired design promptly and efficiently. This has already been researched at various institutions in the U.S. such as MIT, Stanford University and Georgia Institute of Technology. However, the previous studies require inputs of materials and structural parameters beforehand, and adjusting photonic structures afterwards.

Jul 16, 2019

Facebook and CMU’s ‘superhuman’ poker AI beats human pros

Posted by in category: robotics/AI

It can bluff better than any human.

Jul 16, 2019

AI Drug Hunters Could Give Big Pharma a Run for Its Money

Posted by in categories: biotech/medical, economics, health, robotics/AI

But a less-noticed win for DeepMind, the artificial-intelligence arm of Google’s parent Alphabet Inc., at a biennial biology conference could upend how drugmakers find and develop new medicines. It could also dial up pressure on the world’s largest pharmaceutical companies to prepare for a technological arms race. Already, a new breed of upstarts are jumping into the fray.


Alphabet’s DeepMind cracked a problem that long vexed biologists, heating up a technological arms race in health care.

Jul 15, 2019

Britain makes Alan Turing, the father of AI, the face of its 50-pound note

Posted by in categories: government, robotics/AI

Decades after his chemical castration by the British government and subsequent suicide, Alan Turing, the wartime codebreaker, pioneering computer scientist, and founder of artificial intelligence, will appear on the nation’s 50 pound note.

Jul 15, 2019

Game-theory research better allocates military resources, fight cancer

Posted by in categories: biotech/medical, cybercrime/malcode, military, robotics/AI

U.S. Army game-theory research using artificial intelligence may help treat cancer and other diseases, improve cybersecurity, deploy Soldiers and assets more efficiently and even win a poker game.

New research, published in Science, and conducted by scientists at Carnegie Mellon University, developed an artificial intelligence program called Pluribus that defeated leading professionals in six-player no-limit Texas hold’em poker.

The Army and National Science Foundation funded the mathematics modeling portion of the research, while funding from Facebook was specific to the poker.

Page 8 of 620First56789101112Last