'This was a fun project that I put together on the weekend that I knew would be a really good fit for AI and where we're going,' she told TechCrunch, adding that she wanted to give it 'to the masses.' Tank OS is geared toward power users looking to run OpenClaw on their own computers and toward IT pros managing fleets of corporate OpenClaw agents. It makes OpenClaw safer and easier to maintain en masse. Countless people, companies, and startups are already inventing better ways to work with OpenClaw ' the open source project that installs an AI agent on a local computer. There is also a growing number of startups building competing claw alternatives that they say are safer (like NanoClaw). What makes O'Malley's project notable is that she is an OpenClaw maintainer. That means she's among the select software engineers working with creator Peter Steinberger to decide which features and bugs get worked on. In her case, she focuses on making OpenClaw work better in enterprise use cases, and with Red Hat's various flavors of the Linux operating system. (While Steinberger was hired by OpenAI, he still leads the independent open source OpenClaw project.)...

Machine-learning systems such as large language models (LLMs), which turn prompts into text, images and video, are becoming increasingly sophisticated and continue to make astonishing progress, including in science. But such 'generative AI' tools also have limitations. The approach does not always make accurate predictions about the physical world, and could fail at modelling correctly what would happen if a car were to go off the edge of a cliff, for example. This would have implications for developing effective and safe AI-powered robots and self-driving vehicles. Some researchers, including the computer scientist and AI pioneer Yann LeCun, who founded the firm Advanced Machine Intelligence (AMI) Labs in Paris, have turned their attention to a different type of AI tool, developing systems known as 'world models' that are trained on real-world data and can embody virtual, interactive and 3D environments. The approach is attracting huge investment and business interest. AMI Labs ' which is taking a radical approach to world models ' has raised more than US$1 billion, a record initial infusion of money for a European company. Technology giants such as Google and Nvidia are also developing world models, as are several other start-up companies....

By showing individual cells absorbing drugs in real-time, this technology could help scientists test whether new drugs for neurodegenerative disease like Alzheimer's or ALS reach their targets in the brain, with greater speed and resolution. 'The common belief in the field is that if you crank up the power in this type of laser, the light will inevitably become chaotic. But we proved that this is not the case. We followed the evidence, embraced the uncertainty, and found a way to let the light organize itself into a novel solution for bioimaging,' says Sixian You, assistant professor in the MIT Department of Electrical Engineering and Computer Science (EECS), a member of the Research Laboratory for Electronics, and senior author of a paper on this imaging technique. She is joined on the paper by lead author Honghao Cao, an EECS graduate student; EECS graduate students Li-Yu Yu and Kunzan Liu; postdocs Sarah Spitz, Francesca Michela Pramotton, and Federico Presutti; Zhengyu Zhang PhD '24; Subhash Kulkarni, an assistant professor at Harvard University and the Beth Israel Deaconess Medical Center; and Roger Kamm, the Cecil and Ida Green Distinguished Professor of Biological and Mechanical Engineering at MIT. The paper appears today in Nature Methods....

Ineffable Intelligence, a British AI lab founded a mere few months ago by former DeepMind researcher David Silver, has raised $1.1 billion in funding at a valuation of $5.1 billion to join the race for novel AI models that could outperform large language models. According to its newly launched site, Ineffable aims to create a 'superlearner' capable of discovering knowledge and skills without relying on human data by leveraging reinforcement learning ' a technique in which AI systems learn through trial and error rather than studying human-generated examples. This is Silver's area of expertise. A professor at University College London, Silver was until recently leading the reinforcement learning team at Google-owned DeepMind, where he spent more than a decade before leaving to found this new venture. While at DeepMind, Silver was involved in developing programs that beat professional players at chess and the board game Go games by learning purely from experience, without being fed human strategies or game records ' defeating the world's top computer programs in each game. The most notable of these was AlphaZero. Similarly, Ineffable Intelligence hopes that its superlearner will discover all knowledge from its own experience....