The European Union is enacting the most comprehensive guardrails on the fast-developing world of artificial intelligence after the bloc’s parliament passed the AI Act on Wednesday.
Category: robotics/AI – Page 781
More than 500 drones light up the sky at SXSW
The show on Tuesday night was an abstract light show partially designed with AI.
OpenAI CEO Sam Altman seeks as much as $7 trillion for new AI chip project: Report
OpenAI CEO Sam Altman is seeking trillions of dollars in investments to overhaul the global semiconductor industry, The Wall Street Journal reported.
Altman has long talked of the supply-and-demand problem with AI chips — many AI giants want them, but there aren’t enough to go around — and that it limits OpenAI’s growth. He’s considering a project that would increase global chip-building capacity, according to a Thursday evening report in The Wall Street Journal, and is reportedly in talks with different investors, including the government of the United Arab Emirates.
Altman could need to raise between $5 trillion and $7 trillion for the endeavor, The Wall Street Journal reported, citing one source. CNBC could not confirm the number. OpenAI did not respond to a request for comment.
First Metamaterial developed to Enable Real-time Shape and Property Control
Engineers have unveiled an encodable multifunctional material that can dynamically tune its shape and mechanical properties in real time. Inspired by the remarkable adaptability observed in biological organisms like the octopus, a breakthrough has been achieved in soft machines. A research team, led by Professor Jiyun Kim in the Department of Materials Science and Engineering at UNIST has successfully developed an encodable multifunctional material that can dynamically tune its shape and mechanical properties in real-time. This groundbreaking metamaterial surpasses the limitations of existing materials, opening up new possibilities for applications in robotics and other fields requiring adaptability.
Current soft machines lack the level of adaptability demonstrated by their biological counterparts, primarily due to limited real-time tunability and restricted reprogrammable space of properties and functionalities.
In order to bridge this gap, the research team introduced a novel approach utilizing graphical stiffness patterns.
Cognition launches Devin, a generative AI-powered coding engineer
A new generative artificial intelligence startup called Cognition AI Inc. is looking to disrupt coding with the launch of a new tool that can autonomously create code for entire engineering jobs, including its own AI models.
That tool’s name is Devin, and it takes the premise of GitHub Inc.’s and Microsoft Corp.’s Copilot developer tool much further, as it can carry out entire jobs on its own, rather than simply assist a human coder.
In a video (below) attached to a blog post announcing Devin, Cognition Chief Executive Scott Wu demonstrates how users can view the model in action. They can see its command line, code editor and workflow as it goes step-by-step, completing comprehensive coding projects and data research tasks assigned to it.
Blog: Company just developed an AI Software Engineer named: Devin
And setting a new state of the art on the SWE-bench coding benchmark
Meet Devin, the world’s first fully autonomous AI software engineer. Devin is a tireless, skilled teammate, equally ready to build alongside you or independently complete tasks for you to review.
With Devin, engineers can focus on more interesting problems and engineering teams can strive for more ambitious goals.
How do neural networks learn? A mathematical formula explains how they detect relevant patterns
Neural networks have been powering breakthroughs in artificial intelligence, including the large language models that are now being used in a wide range of applications, from finance, to human resources to health care. But these networks remain a black box whose inner workings engineers and scientists struggle to understand.
