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Navigating new compliance requirements can be a daunting task, but with the right automation tools, it doesn't have to be. Whether you're a fast-growing startup or an established security team, Vanta can help you achieve continuous compliance [4] (and more).
Gemini Robotics is a vision-language-action (VLA) model by Google DeepMind that aims to bring Gemini and AI to the physical world. It was created to make general purpose robots that can perform a wider range of real-world tasks than ever before. The VLA is built on Gemini 2.0 and has physical actions as an additional output modality for the purpose of directly controlling robots. Google built its robotic AI model to be able to understand and respond quickly to instructions or changes in the environment, capable of the kinds of things people can generally do with their hands and fingers, and adept with dealing with new objects, diverse instructions, and new environments. A video showing some of the model's capabilities is available in the article.
Lip-Bu Tan will become the CEO of Intel on March 18. Former CEO Pat Gelsinger was booted from the position on December 2 after several quarters of losses, rounds of layoffs, and canceled or spun-off side projects. Tan was previously on Intel's board from 2022 to 2024 and has been a board member for several other technology and chip manufacturing companies. Intel reported a loss of $18.76 billion in 2024, its first annual loss since 1986.
Google installed 100 million lithium-ion cells across its data centers to provide backup power to its servers. The lithium-ion cells hold twice the power and take up half as much space as the lead-acid batteries they replaced, allowing the company to cut the number of cells required by three-quarters - more space for servers. Batteries are driving change in a myriad parts of the economy. Panasonic has shipped over 10 billion cells from its Nevada plant since it opened in 2015.
Canadian startup General Fusion has created plasma inside its prototype reactor, a major milestone in proving its technology. The company uses technology that dates back to the 1970s - details are available in the article. The prototype is now forming plasmas daily - the next step is to compress the plasmas with a lithium liner to create fusion and heating from compression. The company hopes it will achieve scientific break-even equivalent by 2026.
This post discusses how to make the Cursor experience as good as possible. It covers what to put inside the .cursorrules file, how to get the best output, and more. One of the biggest factors in a developer's experience with coding with AI is going to be what they are coding and which tech stack they are using. One of the best things about AI is that it can help developers tackle problems that would normally be outside of their reach.
The DuckDB team and MotherDuck have released a local UI for DuckDB as part of the ui extension. The DuckDB UI uses interactive notebooks to define SQL scripts and show the results of queries. It can show databases, table summaries, notebooks, column insights, and more.
It was clear when Apple announced Apple Intelligence that some of its features were more ambitious than others. Apple hinted strongly that the various features wouldn't all ship at the same time - the more trivial features would ship first. Its more ambitious features have been delayed until sometime 'in the coming year'. Apple appears to have pitched a story that wasn't true and set a course based on that.
The excitement around AI's potential contributions to mathematics doesn't always come with a nuanced understanding of what mathematics truly is and isn't. This post attempts to articulate these differences and hopefully build a bridge for better collaboration. Most mathematicians are not interested in AI creating new mathematics, but in processing and organizing existing knowledge. Even if AI was able to produce a proof of a major conjecture, it would fail to deliver the deeper understanding that mathematicians truly seek.
The latest Gemma model is aimed at developers who need to create AI to run in various environments.
FilePizza enables peer-to-peer file transfers inside the browser.
Manus uses Browser Use to execute various tasks like clicking through site menus and filling out forms.
Inference is a far more diverse workload compared to training - performance is predominantly determined by memory capacity, memory bandwidth, and compute - which of these is prioritized is heavily dependent on a model's architecture, parameter count, hosting location, and target audience.
You should only train a model on outputs, not on an analysis of its outputs or on the technique used to analyze its outputs.
The real value of generative AI will come from agents that can do things for users directly.