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Google DeepMind has released four new vision-capable Apache 2.0-licensed reasoning models sized at 2B, 4B, and 31B, plus a 26B-A4B Mixture-of-Experts. The models are multi-modal beyond just images and can process video at variable resolutions. The two smaller models feature native audio input for speech recognition and understanding. API access to the two larger models is available through Google's AI Studio.
OpenAI has acquired TBPN, an online talk show with by-the-minute analysis of technology news and executive interviews. The show averages around 70,000 viewers per episode across various platforms. It has become popular among Silicon Valley power players, who view it as more supportive of the tech industry than traditional news outlets. The show generated around $5 million in revenue from advertising last year and was on track to make more than $30 million in revenue in 2026.
Sanctuary AI recently released a video showing the company's hydraulic hand autonomously manipulating a lettered cube, achieving target orientation 10 consecutive times without dropping the cube. The manipulation took place entirely at the fingertips without the support of the palm. The demonstration showcases a successful instance of zero-shot transfer. The video is available in the article.
Three Americans and one Canadian launched into orbit on the Space Launch System rocket from NASA's Kennedy Space Center on Wednesday. The Artemis II mission is testing the transportation system NASA plans to use to get astronauts to the Moon and then return crews home at the end of their mission. If the mission is successful, the astronauts will go further than anyone has ever traveled in space. They will see parts of the far side of the Moon never before seen with human eyes. The crew is scheduled to return on April 10.
Simon Willison is an independent software developer, blogger, and one of the most visible and trusted voices on the impact AI is having on builders. Willison made the leap from traditional software engineering to AI-native development more fully and visibly than almost anyone, documenting everything he learned in real time on his blog. This article features highlights from a recent interview with Willison, where he shares why November 2025 was an inflection point for AI coding agents, how he writes 95% of his code from his phone now, why mid-career engineers (not juniors) are most at risk right now, and more. A video of the full 1 hour and 40 minute-long interview is available.
Cursor 3 brings clarity to the work that agents produce, pulling users up to a higher level of abstraction. It is faster, cleaner, and more powerful. The new interface is inherently multi-workspace, so users can work with agents across different repositories. The company plans to continue making interface changes as more powerful coding models unlock new interaction patterns.
Medvi, a telehealth provider of GLP-1 weight-loss drugs, took two months and around $20,000 to build. Its founder, Matthew Gallagher, used AI tools to write the code that powers the company, produce website copy, generate media for ads, handle customer service, and analyze business performance. He outsourced the other stuff he couldn't do himself and hired one employee, his younger brother. The startup is on track to do $1.8 billion in sales this year.
Amazon's success has done a great deal of harm to a lot of companies. Jeff Bezos is a generational entrepreneur who came from a hedge fund. He made a very calculated decision to lose money in the short term to make more in the long term. He took every detail into consideration to make his plan work. Amazon is a bad example of why it is okay to burn loads of cash during growth. The strategy doesn't always work out, especially if it is not executed correctly.
We need better cache policies and architectures to address the impact of AI bot traffic on cloud infrastructure, which is only going to continue to grow.
People will start using agents to attack old problems with modern tooling, resulting in new versions of software tools that people rely on but don't like.
Microsoft lost its largest customer, OpenAI, and the trust of the US government, in one of the silliest, most preventable, and most costly mishaps of the 21st century.
Every AI tool today is powerful, but useless without context. It doesn't know your projects, your priorities, or the conversation you had an hour ago. So you copy, paste, re-explain, and start over. Every time.Littlebird is what AI should have been from the start. It observes your screen and meetings, building a private memory that grows with you. No setup. No catching it up. Just an AI that finally knows what you're working on.This is what AI was supposed to feel like.
SpaceX has confidentially filed IPO paperwork with the Securities and Exchange Commission. The company is aiming to raise between $40 billion and $80 billion. The filing puts it on track to potentially list shares by July. The confidential filing means most investors will have to wait until closer to the IPO to see the company's financial performance.
OpenAI shares have dropped in value on the secondary market as investors pivot to Anthropic. Investors are, in some cases, unable to sell their shares. Meanwhile, buyers have indicated that they have $2 billion in cash ready to deploy to Anthropic. Anthropic and OpenAI don't allow investors to trade shares on secondary markets without permission, but access is still available on many platforms through mechanisms such as special-purpose vehicles.
Economists and AI experts predict major AI progress, but there will be no dramatic break from economic trends. GDP growth rates will remain similar to today's despite a moderate decline in labor force participation. There will be significant economic impacts by 2050. It is predicted that by 2050, the labor force participation rate will be 55%, and 80% of wealth will be held by the top 10%, the highest disparity since 1939.
Google Quantum AI recently dropped a whitepaper with a headline finding that the cryptography that secures Bitcoin and most of the crypto ecosystem can be broken using fewer than half a million physical qubits on a superconducting architecture in about nine minutes. The company withheld the specific quantum circuit used in the name of responsible disclosure, but the paper constrains the search space so tightly that reproducing comparable circuits is well within reach for any serious quantum algorithms group. The qubit counts that make these cryptographic attacks feasible are roughly the same number of qubits required to make quantum-enhanced AI feasible. This suggests that the threat and capability of quantum computing will arrive roughly on the same timescale.
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The most dangerous failure mode in agent-driven systems is silent drift - code that compiles and passes every test, but quietly violates the architectural assumptions that were thought safe. While humans can catch these mistakes through intuition, agents can't, so they need deterministic, immediate signals. This means tightening the feedback loop by shrinking the gap between a wrong change and a clear failure signal. Focus on feedback rather than chasing clever prompts.
Spec-driven development means writing durable intent down before implementation, using it to plan, build, check, and revise the work. The goal is to reduce execution freedom. Specs should be declarative, layered, and cheap to revise. When a rule can be enforced mechanically, move it out of the spec and into lint, schemas, tests, or the harness. Specs matter, but they're just one layer. The winning model puts a narrow interface between human intent and machine execution.
Amy Hood, Microsoft's longtime chief financial officer, has one of the hardest jobs in tech. The decision of how much to invest in AI without starving out other parts of the company or spooking investors with bottomless spending is a tough call, especially as projects about AI are educated guesses at best. While the industry consensus is to open the spigot for fear of missing out, Hood has kept a lid on costs, and Wall Street loves her for it. Huge AI investments have forced other companies to start burning cash, but Microsoft's margins have been largely stable.
The people who get hired are the ones who can tell a clear story about their work and capabilities and make the interviewer think, 'I want to work with that person'. This is a skill, and like any skill, it can get better with practice. Most people never practice because they don't think it is something they can prepare for. A little preparation here goes further than almost anything else you can do for your career.
AI is accelerating development, but it's not creating 10x engineers out of thin air. New data by Gitkraken shows rising duplication, shifting quality, and widening gaps between teams. Read the research
M2.7 is MiniMax's latest model, the first to deeply participate in its own training, handling complex multi-step agentic tasks and on par with Sonnet 4.6 on OpenClaw at a fraction of the cost. Its M2.5 was the first open-weight model in Notion's Custom Agents lineup, alongside Claude and GPT, and became the most-used model on OpenClaw within a month of release. → Try M2.7MiniMax is also open-sourcing their Office Skills library(MIT): 4 production-grade Skills for Word, Excel, PDF & PPT that generate actually deliverable files. Works with Claude Code, Cursor, Codex & OpenCode. → Check out the open source Skills library [Github]New: MiniMax launches the world's first subscription supporting all modalities: M2.7, video, voice, music and image, with no surprise bills. → Subscribe to the new Token Plan
Anthropic recently published a version of the Claude Code npm package that included a source map file that could be used to access the entirety of Claude Code's source code. More than 512,000 lines of code were leaked on a public GitHub repository, which has since been forked tens of thousands of times. Developers are already analyzing the code to find out how Claude Code works. Anthropic has publicly acknowledged the mistake.
Apple is testing a feature in Siri that will let it process multiple requests in a single query. Siri currently requires users to make requests individually. The new feature will allow users to combine requests, for example, ask Siri to check the weather, create a calendar appointment, and send a message, all within a single prompt. The new Siri is expected to be released at Apple's Worldwide Developers Conference on June 8.
Microbubbles are tiny gas-filled bubbles with a protective outer shell that are capable of carrying drugs or genetic material to cells in the body. They are too large to leave the bloodstream, so they deliver drugs by bursting on command, briefly forcing open biological barriers to allow treatments to pass through. The force of their bursts can be used to break apart kidney stones. These bubbles can be steered, so they can carry therapies through the bloodstream to release precisely where they're needed.
Two independently written whitepapers have come to the same conclusion that building a utility-scale quantum computer that can crack elliptic curves requires far fewer resources than anticipated. The papers are the latest sign that cryptographically relevant quantum computing at utility-scale is making meaningful progress. The advances are being driven by new quantum architectures that operate correctly even in the presence of errors, and ever more efficient algorithms. Neither of the papers has yet been peer reviewed.
As the first engineer on TLDR's new Applied AI team, you'll build AI agents to automate end-to-end workflows and lead our context engineering project to allow non-technical teammates create their own AI workflows. Learn more.
Claude Code CLI's source code was recently leaked on GitHub. This post breaks down how the system works, where Anthropic made clever engineering choices, and where Anthropic's approach diverges from OpenAI's Codex. Claude Code is about 500,000 lines of TypeScript, with the actual API call comprising maybe 200 of them. Everything else in the harness.
Inference is when a model takes an input and generates an output, one token at a time. Inference engineering is becoming more widespread as open models become more capable. With closed models, inference engineering is only done by the AI engineers who build the model, but anyone can tinker with open models. This post discusses what inference engineering is and some interesting approaches to inference engineering worth knowing about.
Google decided to restructure itself in 2015, spinning out chunks of its operation as semi-independent bets and creating a holding company called Alphabet to preside over them. DeepMind used the opportunity to regain its independence. It planned to create a new DeepMind with a board comprising three people from DeepMind, three people from Alphabet, and three independent members. The ensuing governance talks were dubbed by DeepMind's leaders as 'Project Mario'.
JustPaid, a California-based startup, used a combination of OpenClaw and Claude Code to create a team of seven AI agents to grind out code 24/7. The agents have built 10 major features in a month, each of which would have taken a team of human developers a month or more to build. JustPaid plans to eventually replace all its employees with AI. The company currently has nine employees - its latest human hire was trained almost entirely by the AI agent engineers.
Your AI agents are fast but flying blind. mirrord connects them to real API responses, database state, and queue payloads so every change gets tested against actual staging. See how monday.com cut dev cycle time by 70%.
Businesses are using AI under the assumption that the technology will eventually improve to the point that it will easily solve all of the technical debt currently accruing, but this might not be true.
Malicious versions of popular open source software development tool, Axios, were published on Monday, putting millions of developers at risk of being compromised.