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A study in a virtual reality environment found that action video game players have better implicit temporal skills than non-gamers. They are better at preparing to time their reactions in tasks that require quick reactions and they do it automatically, without consciously working on it. The paper was published in Communications Biology.

Many research studies have shown that playing video games enhances cognition. These include increased ability to learn on the fly and improved control of attention. The extent of these improvements is unclear and it also depends on gameplay.

Success in action video games depends on the players’ skill in making precise responses at just the right time. Players benefit from practice during which they refine their time-related expectations of in-game developments, even when they are unaware of it. This largely unconscious process of processing time and preparing to react in a timely manner based on expectations of how the situation the person is in will develop is called incidental temporal processing.

An artificial intelligence (AI) agent named CICERO has mastered the online board game of Diplomacy. This is according to a new study by the Meta Fundamental AI Research Diplomacy Team (FAIR) that will be published today (November 22) in the journal Science.

AI has already been successful at playing competitive games like chess and Go which can be learned using only self-play training. However, games like Diplomacy, which require natural language negotiation, cooperation, and competition between multiple players, have been challenging.

The new agent developed by FAIR is not only capable of imitating natural language, but more importantly, it also analyzes some of the goals, beliefs, and intentions of its human partners in the game. It uses that information to figure out a plan of action that accounts for aligned and competing interests, and to communicate that plan in natural language, the researchers say.

Deep Learning AI Specialization: https://imp.i384100.net/GET-STARTED
Nvidia unveils its new artificial intelligence 3D model maker for game design uses text or photo input to output a 3D mesh and can also edit and adjust 3D models with text descriptions. New video style transfer from Nvidia uses CLIP to convert the style of 3D models and photos. New differential equation-based neural network machine learning AI from MIT solves brain dynamics.

AI News Timestamps:
0:00 Nvidia AI Turns Text To 3D Model Better Than Google.
2:03 Nvidia 3D Object Style Transfer AI
4:56 New Machine Learning AI From MIT

#nvidia #ai #3D

Human behaviour is remarkably complex. Even a simple request like, “Put the ball close to the box” still requires deep understanding of situated intent and language. The meaning of a word like ‘close’ can be difficult to pin down – placing the ball inside the box might technically be the closest, but it’s likely the speaker wants the ball placed next to the box. For a person to correctly act on the request, they must be able to understand and judge the situation and surrounding context.

Most artificial intelligence (AI) researchers now believe that writing computer code which can capture the nuances of situated interactions is impossible. Alternatively, modern machine learning (ML) researchers have focused on learning about these types of interactions from data. To explore these learning-based approaches and quickly build agents that can make sense of human instructions and safely perform actions in open-ended conditions, we created a research framework within a video game environment.

Continue reading “Building interactive agents in video game worlds” »

A study of physiological responses of college-age Overwatch players found that many skilled players tend to start the game with elevated physiological stress responses, adjusting them during gameplay. The physiological stress responses of low skill players, in contrast, tend to increase as the game progresses. The study was published in the Journal of Strength and Conditioning Research.

Competitive electronic gaming or eSport is gaining traction as a recognized sport. The rise of eSports into a multi-billion dollar industry has been attributed to the emergence of streaming platforms and advertisement revenues and high-values sponsorships that came with them. eSports are one of the 24 competitive sports included in the 2022 Asian games held in Hangzhou, China.

Following their rise in popularity, scientists have become interested in studying eSports athletes to understand the stress related to participating in eSports both in competitive and noncompetitive settings. First studies focused on health concerns, given the sedentary nature of eSports, and primarily studied players of League of Legends (LOL) as one of the most popular eSports games at the time.

Circa 2016 😗

Last month, Google’s AI division, DeepMind, announced that its computer had defeated Europe’s Go champion in five straight games. Go, a strategy game played on a 19×19 grid, is exponentially more difficult for a computer to master than chess—there are 20 possible moves to choose from at the start of a chess game compared to 361 moves in Go—and the announcement was lauded as another landmark moment in the evolution of artificial intelligence.

Or, at least, living neurons. His startup, Koniku, which just completed a stint at the biotech accelerator IndieBio, touts itself as “the first and only company on the planet building chips with biological neurons.” Rather than simply mimic brain function with chips, Agabi hopes to flip the script and borrow the actual material of human brains to create the chips.

A tool for estimating the local entropy production rate of a system enables the visualization and quantification of the out-of-equilibrium regions of an active-matter system.

A movie of a molecule jostling around in a fluid at equilibrium looks the same when played forward and backward. Such a movie has an “entropy production rate”—the parameter used to quantify this symmetry—of zero; most other movies have a nonzero value, meaning the visualized systems are out of equilibrium. Researchers know how to compute the entropy production rate of simple model systems. But measuring this parameter in experiments is an open problem. Now Sungham Ro of the Technion-Israel Institute of Technology, Buming Guo of New York University, and colleagues have devised a method for making local measurements of the entropy production rate [1]. They demonstrate the technique using simulations and bacteria observations (Fig. 1).

What is extended mind? How does the mind work? It’s not obvious. Where does the mind stop and the rest of the world begin? What is extended mind? What is embodied mind? Featuring interviews with David Chalmers, Andy Clark, and Raymond Tallis.

Season 18, Episode 11 — #CloserToTruth.

Continue reading “What is Extended Mind? | Episode 1811 | Closer To Truth” »

To show how computer chips are improving a bit, my first computer, an Apple II+ based on the 6,502 chip, had 7 bytes of memory on the chip. Nvidia’s H100 chip has 85,986,377,728 bytes of memory on it!

The 6,502 was a very successful chip and is still made today, with over 6 billion units sold!

Continue reading “MOS Technology 6502” »