TLDR AI 2026-04-01

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PrismML has developed an extreme form of compression that allows AI to run locally on edge devices. Its 1-bit technology model has a radically compressed size without compromised performance. The same efficiency gains that enable local deployment will also allow data centers to operate more efficiently. The mathematics for the process are proprietary, with Caltech owning the intellectual property and PrismML being the sole exclusive licensee.

OpenAI announced $122 billion in new funding at an $852 billion valuation, highlighting rapid revenue growth, large-scale adoption, and a strategy centered on compute, APIs, and enterprise AI systems.

Mercor, an AI recruiting startup, has confirmed a security incident linked to a supply chain attack involving LiteLLM. A recent compromise of LiteLLM's project, linked to a hacking group called TeamPCP, has affected thousands of companies. Lapsus$, an extortion hacking group, claims it has access to the stolen data, though it is unclear how it was obtained. The incident has prompted LiteLLM to shift from Delve to Vanta for compliance certifications.

Anthropic has accidentally leaked the inner workings of Claude Code to the public. The codebase has now been mirrored and analyzed by thousands of developers. The most significant discovery seems to be how Anthropic solved context entropy by using a three-layer memory architecture. This post looks at other interesting parts of the code and the implications of the leak.

Claude Code's performance stems from a sophisticated software harness rather than just the underlying model, utilizing dedicated tools like Grep, Glob, and LSP for superior repository navigation. The system minimizes context bloat through file-read deduplication and structured session memory, while using forked subagents to parallelize tasks like background analysis without contaminating the main execution loop.

The semi layer still captures around 70% of all AI revenues. Infra is currently the only competitive layer. The most profitable strategy in AI is still selling the shovels.

Opus 4.5 was a major breakthrough that was achieved because Anthropic more than doubled its capacity. This got Anthropic close to OpenAI's total capacity, and probably much higher effective capacity available for new model runs. OpenAI will pull away in terms of compute available in the second half of this year, but 2027 will be close. OpenAI so far has much higher planned capacity for future years, but it is unlikely that Anthropic will not push as hard as possible for more compute.

Scroll.ai's knowledge agents provide accuracy and speed that other agents can't touch. Your users will feel the difference from the very first message. Thousands of teams use Scroll for employee enablement, customer education, business insights, and more.

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Agents can generate outdated Gemini API code due to outdated training data. Google has introduced the Gemini API Docs MCP and the Gemini API Developer Skills to fix this. The tools are designed to ensure coding agents have access to the most up-to-date APIs and code using best practices. Combined, they lead to a 96.3% pass rate on Google's eval set.

Google introduced Veo 3.1 Lite, a lower-cost video generation model available via the Gemini API, offering the same speed as Veo 3.1 Fast at under half the cost for high-volume applications.

Aurora is an RL-based framework that learns directly from live inference traces and continuously updates the speculator without interrupting serving. It enables real-time adaptation across shifting traffic domains and a 1.25x additional speedup over a well-trained static speculator. The framework shows how online training from scratch can outperform a carefully pretrained static baseline.

AI capability has been running ahead of AI accessibility. Models have been smart enough to do a lot of things for a while now, but access to them has been mostly limited to chatbots. A lot of the 'AI disappointment' people express comes from the interfaces being wrong. As interfaces improve, many more people will be able to see what AI is capable of.

AI startups now command higher seed valuations, with rounds reaching $10 million at $40-45 million post-money, as investors focus on AI-driven growth potential. Early traction and the allure of proven AI talent, particularly from ex-OpenAI, propel these valuations, with Y Combinator Demo Day highlighting rising prices. The shift to pre-seed investments reflects a need to invest earlier, as VCs now expect quick growth and substantial traction, with less tolerance for missteps.

You were promised AI that understands your work. Littlebird actually delivers. It observes your screen and meetings, building a private memory that grows with you. Try it free.

Anthropic introduced computer use in Claude Code, enabling agents to interact with apps, navigate interfaces, and iteratively test and fix code through a closed-loop workflow.

Meta launched prescription-first Blayzer and Scriber styles starting at $499, expanding the Ray-Ban and Oakley lineups with specialized Prizm and Transitions lenses.

Agent Lightning is a trainer that can turn any agent into an optimizable beast with zero code change.