Fidget poppers are an example of “bistability,” as the popped circles rest in one of two stable states. Purdue University researchers have taken this idea to its extreme, building robots that can be preprogrammed and controlled using just the physical properties of these fidget poppers.Fidget poppers are an example of “bistability,” as the popped circles rest in one of two stable states. Purdue University researchers have taken this idea to its extreme, building robots that can be preprogrammed and controlled using just the physical properties of these fidget poppers.[#item_full_content]
A year after filing to IPO, still-private Cerebras Systems raises $1.1B
Cerebras initially filed to go public in September 2024 but ran into several regulatory delays due to foreign investments.Cerebras initially filed to go public in September 2024 but ran into several regulatory delays due to foreign investments.[#item_full_content]
Whoop opens blood-testing service to what it says is a 350,000-person waitlist
Whoop Advanced Labs marries subscription blood tests with its fitness device monitoring for tech-powered wellness advice.Whoop Advanced Labs marries subscription blood tests with its fitness device monitoring for tech-powered wellness advice.[#item_full_content]
California Governor Gavin Newsom has signed into law groundbreaking legislation requiring the world’s largest artificial intelligence companies to publicly disclose their safety protocols and report critical incidents, state lawmakers announced Monday.California Governor Gavin Newsom has signed into law groundbreaking legislation requiring the world’s largest artificial intelligence companies to publicly disclose their safety protocols and report critical incidents, state lawmakers announced Monday.Internet[#item_full_content]
US startup Anthropic on Monday announced the launch of its new generative artificial intelligence model, Claude Sonnet 4.5, which it says is the world’s best for computer programming.US startup Anthropic on Monday announced the launch of its new generative artificial intelligence model, Claude Sonnet 4.5, which it says is the world’s best for computer programming.Machine learning & AI[#item_full_content]
AI recruiter Alex raises $17M to automate initial job interviews
The Y Combinator startup, raised a Series A led by Peak XV Partners.The Y Combinator startup, raised a Series A led by Peak XV Partners.[#item_full_content]
A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as variational autoencoders with infinitely many latent variables, reducing computational costs and preventing overfitting. By appropriately interrupting the training of the encoder, this approach enabled development of more efficient generative AI, with broad applicability beyond standard diffusion models.A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as variational autoencoders with infinitely many latent variables, reducing computational costs and preventing overfitting. By appropriately interrupting the training of the encoder, this approach enabled development of more efficient generative AI, with broad applicability beyond standard diffusion models.[#item_full_content]
A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as variational autoencoders with infinitely many latent variables, reducing computational costs and preventing overfitting. By appropriately interrupting the training of the encoder, this approach enabled development of more efficient generative AI, with broad applicability beyond standard diffusion models.A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as variational autoencoders with infinitely many latent variables, reducing computational costs and preventing overfitting. By appropriately interrupting the training of the encoder, this approach enabled development of more efficient generative AI, with broad applicability beyond standard diffusion models.Computer Sciences[#item_full_content]
Bar-Ilan University announced today that a team from its Department of Computer Science has developed a breakthrough in video processing that significantly simplifies the separation of foreground objects from their backgrounds, without the need for extensive training or optimization. The new method, called OmnimatteZero, was developed by Dr. Dvir Samuel and Prof. Gal Chechik, who also serves as a senior director of AI research at NVIDIA. The paper is published on the arXiv preprint server.Bar-Ilan University announced today that a team from its Department of Computer Science has developed a breakthrough in video processing that significantly simplifies the separation of foreground objects from their backgrounds, without the need for extensive training or optimization. The new method, called OmnimatteZero, was developed by Dr. Dvir Samuel and Prof. Gal Chechik, who also serves as a senior director of AI research at NVIDIA. The paper is published on the arXiv preprint server.[#item_full_content]
Bar-Ilan University announced today that a team from its Department of Computer Science has developed a breakthrough in video processing that significantly simplifies the separation of foreground objects from their backgrounds, without the need for extensive training or optimization. The new method, called OmnimatteZero, was developed by Dr. Dvir Samuel and Prof. Gal Chechik, who also serves as a senior director of AI research at NVIDIA. The paper is published on the arXiv preprint server.Bar-Ilan University announced today that a team from its Department of Computer Science has developed a breakthrough in video processing that significantly simplifies the separation of foreground objects from their backgrounds, without the need for extensive training or optimization. The new method, called OmnimatteZero, was developed by Dr. Dvir Samuel and Prof. Gal Chechik, who also serves as a senior director of AI research at NVIDIA. The paper is published on the arXiv preprint server.Computer Sciences[#item_full_content]
