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Blog – Page 1778

Fly, goat, fly! A new AI agent from Google DeepMind can play different games, including ones it has never seen before such as Goat Simulator 3, a fun action game with exaggerated physics. Researchers were able to get it to follow text commands to play seven different games and move around in three different 3D research environments. It’s a step toward more generalized AI that can transfer skills across multiple environments.

Google DeepMind has had huge success developing game-playing AI systems. Its system AlphaGo, which beat top professional player Lee Sedol at the game Go in 2016, was a major milestone that showed the power of deep learning. But unlike earlier game-playing AI systems, which mastered only one game or could only follow single goals or commands, this new agent is able to play a variety of different games, including Valheim and No Man’s Sky. It’s called SIMA, an acronym for “scalable, instructable, multiworld agent.”

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Let’s be honest – we’re all getting sick of seeing AI plastered over every tech product. A trend that will not be slowing down any time soon. A recent victim of this trend is the PC market, as AMD, Intel, Microsoft, and Qualcomm have been talking about AI PCs for the last year or so. Microsoft will be hosting an event on March 21st that is titled The New Era of Work. AMD, Intel, and Qualcomm will have dueling keynotes for their respective CEOs at Computex in Taipei, Taiwan. Be prepared for a flood of AI PCs this year.

In all honesty, Tirias Research has been a promoter of AI processing as the next big wave of computing – using trained data to better process predictive models and user interfaces. The use of AI processing has made major improvements to such PC tasks as voice recognition, video upscaling, video call optimization, microphone noise reduction, and power/battery management. The role of Large Language Models (LLMs) to build AI that can generate novel material/content from text prompts (Generative AI or just GenAI) has unleased another level of applications for AI. With GenAI, some tasks such as image development, creative and business writing, chatbot assistants, and now even video creation are possible with minimal user input. But to date, GenAI has run in cloud datacenters with some limited client device examples. The processing requirements and the power requirements to run the ever-increasing demand for GenAI is threatening to break cloud data centers.

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DeepMind’s SIMA is groundbreaking because it doesn’t tap into a game’s internal structure or rule set. Instead, its knowledge base derives from extensive analysis of human gameplay footage paired with the explanations provided by data labelers.

What differentiates SIMA is its ‘generalist’ design. Google partnered with eight game developers to give SIMA access to a wide range of titles, ensuring the AI learns to grasp the core concepts of play within different virtual worlds. This exposure allows SIMA to follow instructions provided as simple text and interact with its environment as a human player might.

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Researchers at the US Southwest Research Institute (SwRI) have developed camera-based autonomous driving tools that can work without deploying technologies like LIDAR and RADAR.

The technology can potentially deliver stealth capabilities for the military while finding applications in space and agriculture.

Modern autonomous driving solutions rely extensively on light detection and ranging (LIDAR) sensors to visualize objects around the vehicle. A software solution then identifies the objects nearby and helps the vehicle’s computer decide whether to halt or slow down.

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