One step closer to the Matrix: AI defeats human champion in Street Fighter with a revolutionary type of memory it used makes it even more powerful

Date:
Sun, 15 Oct 2023 17:13:05 +0000

Description:
The AI system, powered by phase-change memory and reinforcement learning, was trained for just two days.

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Researchers from the Singapore University of Technology and Design (SUTD) created a new software centered around reinforcement learning and
phase-change memory thats designed to understand complicated movement design.

Previous work has applied this kind of deep learning to other games like
Chess or Go, but they decided instead to expose the D-PPO algorithm to the rigors of Street Fighter Champion Edition II. The SUTD researchers trained
its SF-R2 AI player on two days of consecutive play against the computer, before letting it loose on a human participant who the AI-powered system
beat comfortably.

The work has implications for movement science more broadly, according to the research paper , and can possibly be fed into improving robotics and autonomous vehicles, for example. It paves the way for broadly applicable training in fields where machines may observe human norms and attempt to replicate and outperform them. Ready Pl-AI-yer One

One of the major milestones that AI researchers have used to measure the effectiveness of the systems theyve built is by letting them compete with human players in different kinds of games. This has been happening for some time.

In 2017, an Alpha Go AI built by DeepMind beat the number-one human Go player in the world for the second time, following the first victory over Fan Hui
the previous year. Microsofts AI, in June, achieved the worlds first perfect Ms. Pac-Man score, and in August we saw an OpenAI engine beating the best
Dota 2 players of the time.

This latest milestone besting a Street Fighter champion was made possible due to reinforcement learning as well as phase-change memory. First developed by HP, this is a form of nonvolatile memory achieved by using electrical charges to change areas on chalcogenide glass. Its much faster than commonly used Flash memory.

"Our approach is unique because we use reinforcement learning to solve the problem of creating movements that outperform those of top human players,
said principal investigator Desmond Loke to TechXplore . This was simply not possible using prior approaches, and it has the potential to transform the types of moves we can create. More from TechRadar Pro These are the best AI tools around AI is going to ruin humanity just not in the way you might expect What is AI capable of, really?



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Link to news story: https://www.techradar.com/pro/one-step-closer-to-the-matrix-ai-defeats-human-c hampion-in-street-fighter-with-a-revolutionary-type-of-memory-it-used-makes-it -even-more-powerful


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