SEO TIP: UPDATE YOUR BRAND PAGES (PRICING, HOW IT WORKS, HOMEPAGE, COMPETITOR COMPARISONS)
Updating a pricing page with clearer messaging, design, and keyword-rich title and headings resulted in a 46% increase in organic traffic.
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Updating a pricing page with clearer messaging, design, and keyword-rich title and headings resulted in a 46% increase in organic traffic.
YouTube now auto-detects positive comments and lets creators quickly like them with a single option.
After 12 tons of KitKat candy bars were stolen, Nestlé launched a website to track the missing bars.
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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
MiniMax 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 &
New: MiniMax launches the world's first subscription supporting all modalities: M2.7, video, voice, music and image, with no surprise
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 [12].
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.
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Malicious versions of popular open source software development tool, Axios, were published on Monday, putting millions of developers at risk of being compromised.
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.
Gmail users can now create new account names without losing access to their old addresses.
The band will integrate with an AI-powered personal health coach inside the newly redesigned Fitbit app.
OpenAI has raised $122 billion in a round that values the company at $852 billion.
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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.
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.
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.
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.
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.
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.
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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.
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.
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.
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.
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actually delivers. It observes your screen and meetings, building a
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.
Figma has expanded its AI image tools — Expand, Erase, and Isolate — to FigJam, Slides, and Buzz (beta), with Vectorize also available in Slides and Buzz. These tools allow users to refine visuals across the entire workflow, from brainstorming to presentation to promotion. Access is available to Dev, Collab, and View seats (Buzz only) on Professional, Organization, and Enterprise plans with AI enabled.
Apple Music's updated design in iOS 26.4 adapts interface colors to match album art, which many users like visually, but it creates a problem for dark mode users—light-colored artwork can suddenly make the screen very bright at night (“flash bang” effect). This has led to widespread complaints, especially from users who rely on dark mode for comfort in low-light conditions. A proper solution would require Apple to refine how adaptive colors behave in dark mode—either by limiting brightness or offering a dedicated setting. In the meantime, users can enable the Increase Contrast accessibility option (globally or just for Apple Music), which keeps the track list in a darker theme and reduces the intensity of the effect, though it doesn't fully eliminate bright elements.
Adobe's Firefly custom models, now in public beta, let creatives train AI on their own work to generate consistent, on-brand visuals—addressing a major limitation of generative AI: maintaining style across outputs. This enables faster workflows, reduces repetitive tweaks, and helps teams scale content production while preserving creative identity, with early enterprise use showing significant efficiency gains across industries like retail and media. Alongside this, Adobe envisions conversational AI (via Project Moonlight) becoming a core part of creative workflows, combining natural language interaction with precise editing to enhance, not replace, human creativity.
Internal website search often fails because it requires users to guess exact keywords rather than understanding search intent, leading them to abandon the site for Google searches. This "Site-Search Paradox" occurs when users prefer using Google with "site:" commands to find content on local websites rather than using the site's own search function. Google succeeds not just through raw computing power, but by understanding context and user intent rather than demanding exact keyword matches.