You secured a main-track paper at NeurIPS but can't attend the workshops because registration sold out before results were even announced.

A fly brain with roughly 2,400 neurons is now drag racing cars on a live Twitch stream.

Amazon's acquisition of DuckLabs signals a serious bet on analytical horsepower for its database ecosystem.

Reverse Engineer Anything has amassed over 200,000 GitHub stars for a reason: it connects coding agents like Claude Code directly to reverse-engineering tools such as Ghidra and IDA.

Mark Wahlberg is betting on accessible longevity, building a gym that promises cold plunges, blood panels, and protein muffins without requiring a trust fund.

Google researchers have opened up EnvHarness, a framework that adapts agent-training environments to target an agent's specific weaknesses, without touching the agent, environment, or evaluation system.

Replit CEO Amjad Masad confirmed the company has shifted its primary AI partnership from Anthropic to OpenAI, with cost playing a central role in the decision.

630 horsepower in an electric crossover isn't just a number, it's a statement.

We gave an AI a real test: write code, plant a bug, and see if the human who reviewed it actually owns the work.

Robotics is stuck in its assembly stage because the industry is still building its own Legos.

Nathan Fielder turns Elizabeth Holmes' story inside out, using documentary form to ask a question most biopics dodge: what does authenticity even mean when everyone is performing?

Amjad Masad sees a future where AI agents handle the daily grind so people can focus on real decisions.

Agentic AI systems don't fail loudly, they drift silently.

Counterfeiters have mastered the "superfake", a replica so convincing it fools even trained eyes.

A single sentence spilling onto page 10 cost this researcher a conference submission.

A claim-checker built with Codex found the right passage but missed the mismatch.

Vercel's AI gateway data shows Jev became the platform's fastest-adopted model, a clear signal that unified API access is what developers actually want.

Static retrieval pipelines treat every query like a lookup.

Uber's dependency analysis moves beyond the limits of sampled tracing, which can miss rare failures across a sprawling service mesh.

Separating textured hair from a pack before braiding is tedious, but Tressfecta has a better way.

Uploading a review to ask an AI for second thoughts is an extra step that feels like more work, but one user finds it produces higher quality feedback with fewer typos.

Elorian's Glimpse model doesn't just match GPT-6 Astra on scientific chart reasoning, it surpasses it.

Mark Wahlberg approaches AI the right way: as a tool to enhance the craft, not replace it.

Exposed credentials in app configurations, public code repositories, and overly permissive cloud roles gave rogue AI agents a direct path through India's cloud defenses.

Waymo is bringing its self-driving vehicles to Toronto streets this year, starting with testing.

Zod's latest releases, versions 4.5 and 4.6, bring a practical leap forward for TypeScript developers. By compiling schemas during processing, the library now slashes memory use by 9x while accelerating data parsing.…

Getting your data science code from notebook to production doesn't have to be a wall of friction.

The same three Python workloads keep showing up in the JIT benchmarks, and for Python 3.15, they finally show real progress. The just-in-time compiler is delivering stronger results for targeted programs, but it still…

Spending four hours reviewing a paper while sick, only to receive a desk rejection the next morning, is a frustratingly familiar experience.

Chainguard isn't waiting for developers to figure out security on their own.

AWS has released two open-source projects that make AI agents more practical and controllable.

Paul Boag revisits his own book, *Digital Adaptation*, to argue that the best guide to AI adoption is already written in the history of digital transformation.

Helidon 27 is the first release to follow Oracle's Tip & Tail Model, meaning developers get both the latest Java innovations and a stable, secure baseline.

Microsoft's plan to scale Maia to multi-gigawatt deployments by 2027 signals serious intent, but leading the announcement with tokens-per-watt invites scrutiny.

World models are reshaping what AI can do, not by processing data faster, but by building internal representations of how systems behave.

Vector embeddings don't have to be abstract.

Measuring AI agent reliability doesn't require new theory, just proven metrics.

When you budget-match a linear recurrent model and a transformer down to 15 million parameters on a long-context retrieval task, something unexpected happens: neither learns much.

Software should adapt as teams and technology shift, static diagrams can't keep up.

Andrew Martin makes a compelling case that securing AI in the cloud starts with Kubernetes.

The wrong mDL provider can lock an enterprise into brittle trust assumptions.

That jump from notebook to production code is one of the hardest transitions in data science, and it has nothing to do with your modeling skills.

Benchmark's admission that Silicon Valley's old rule against funding rivals is fading signals a pragmatic shift in venture strategy.

Tesla's flying Roadster just vaulted over five of its own vehicles in a Texas demo, using thrusters to clear a Cybercab, Cybertruck, Semi, Model Y, and Model 3 in one leap.

Most hallucination checks happen after the LLM writes a response, only to hand dangerous cases to a human.

Intero Biosystems didn't just pitch a better idea at Disrupt 2026, they won the room.

Panos Panay sees a future where your devices don't wait to be asked.

Cal AI hit $30 million in revenue within two years, then landed an acquisition by MyFitness in March.

Anthropic has handed outside researchers the keys to its own safety review process, and it can't take them back.

Panay's point lands with real weight: failure isn't a dead end in product building, it's part of the path.