AI-TechSpace

  Armchair speed demons have a new nemesis. What’s new:  Peter Wurman and a team at Sony developed  Gran Turismo Sophy  (GT Sophy), a reinforcement learning model that defeated human champions of Gran Turismo Sport, a PlayStation game that simulates auto races right down to tire friction and air resistance. Key insight:  It’s okay to bump another car while racing (as in the video above), but there’s a thin and subjective line between innocuous impacts and those that would give the offender an advantage. In official Gran Turismo Sport competitions — as in real-world races — a human referee makes these calls and penalizes errant drivers. A reinforcement learning algorithm can model such judgments by assigning a cost to each collision, but it must be tuned to avoid an adverse effect on performance: Too high a penalty and drivers become timid, too low and they become dangerous. Penalizing common situations in which a driver typically would be judged at fault, such a...

The next killer AI application may be developed by someone who has never heard of gradient descent. What’s new:  A rising generation of software development platforms serves users who aren’t familiar with AI — and even programming.  The New York Times   surveyed  the scene. Robocoders:  Using no-code AI platform — an automated programming tool that either generates new code or customizes pre-existing code according to user input — generally requires access to a web browser and training data. From there, a user-friendly interface lets users train a prebuilt architecture.  · Teachable Machine  from Google (pictured above) and  Lobe  from Microsoft make building vision models a point-and-click process. Users supply training images.  · Power Platform  and  AI  Builder , both from Microsoft, are aimed at business users who want to process text in documents and images. · Juji  enables users...

Competitive programming is a popular and challenging activity; hundreds of thousands of programmers participate in coding competitions to gain experience and showcase their skills in fun and collaborative ways. During competitions, participants receive a series of long problem descriptions and a few hours to write programs to solve them. Typical problems include finding ways to place roads and buildings within certain constraints, or creating strategies to win custom board games. Participants are then ranked mainly based on how many problems they solve. Companies use these competitions as recruiting tools and similar types of problems are common in hiring processes for software engineers. Creating solutions to unforeseen problems is second nature in human intelligence – a result of critical thinking informed by experience. The machine learning community has made tremendous progress in generating and understanding textual data, but advances in problem solving remain limited to relativel...