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<pre style='white-space:pre-wrap;width:81ex'>fix: expose OpenAI image quality and moderation CLI options (#94156) Merged via squash. Prepared head SHA: 7f6d39610e49917a3119d041842be0bb46aefe79 Co-authored-by: lastguru-net <1543525+lastguru-net@users.noreply.github.com> Co-authored-by: fuller-stack-dev <263060202+fuller-stack-dev@users.noreply.github.com> Reviewed-by: @fuller-stack-dev</pre>

Noam Shazeer, co-author of the landmark "Attention Is All You Need" paper and former co-lead of Google's Gemini models, is joining OpenAI. He only returned to Google from Character.AI in 2024 as part of a $2.7 billion deal. After Karpathy's move to Anthropic, it's the second major AI hiring shake-up this year. The article Google's Gemini co-lead Noam Shazeer joins OpenAI after two-year return stint appeared first on The Decoder .

Hey all! I'm the maintainer of mistral.rs. I just landed support for OpenAI-compatible Agent Skills via a /v1/skills endpoint, and it works with local open models. Until now Skills have basically been locked to closed models, and with the ability to have private, local intelligence becoming increasingly important, but this feature allows you to do XYZ with local models. It's fully compatible with OpenAI's /v1/skills API, so you can drop mistral.rs into your existing code with minimal difficulty.

Is AI search making your SEO strategy harder to scale? Meet MozCon NYC 2026’s final speakers and learn AI, content, local SEO, and agent-ready frameworks you can use now.

Chrome DevTools for agents introduces third-party developer tools, which lets frameworks and applications share rich, runtime context with AI coding assistants.

Midjourney has announced its first hardware project, and it can do more than make cute AI pet photos.

Article URL: https://openai.com/index/deployment-simulation/ Comments URL: https://news.ycombinator.com/item?id=48581468 Points: 1 # Comments: 0

<p> AI tab manager that suspends background RAM hogs </p> <p> <a href="https://www.producthunt.com/products/tabnxt?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1174907?app_id=339">Link</a> </p>

A year ago at NVIDIA GTC Paris at VivaTech, France laid out plans to advance local AI — from new AI factories and national compute capacity to open frontier models and industrial platforms. Now, that AI infrastructure is coming online. AI agents are running in production, startups are deploying applications and the French AI ecosystem […]

<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1u8xxyh/multivariate_probability_models_in_machine/"> <img src="https://preview.redd.it/oe61t3vpcz7h1.jpg?width=140&height=79&auto=webp&s=b81382abced1a5fd05c0db147b1cf0dc1d07e6d3" alt="Multivariate Probability Models in Machine Learning [D]" title="Multivariate Probability Models in Machine Learning [D]" /> </a> </td><td> <!-- SC_OFF --><div class="md"><p>Hello Folks, we start our discussion on Lecture 10 of Probabilisti

Article URL: https://juileebhosale.substack.com/p/the-ai-debate-is-really-about-free Comments URL: https://news.ycombinator.com/item?id=48581285 Points: 2 # Comments: 0

Article URL: https://github.com/las7/memharness Comments URL: https://news.ycombinator.com/item?id=48581267 Points: 1 # Comments: 1

Ever since the dawn of agentic AI I transitioned more from writing code to reading what AI is doing and monitoring it. Naturally going from 1 session to at times 3 or 4 has increased the amount of AI produced words I consume. Recently I've started to notice more and more how I have unconciously adapted the subtle quirks of AI generated responses and have begun to sometimes have a double take if what I've just written is AI. I've also started to incoorperate language and other words that I have n

Article URL: https://github.com/iliatankelevich/maslul Comments URL: https://news.ycombinator.com/item?id=48581123 Points: 2 # Comments: 0

<pre style='white-space:pre-wrap;width:81ex'>refactor(gateway): dedupe agent id listing</pre>

<p> Securely execute AI-generated & untrusted code </p> <p> <a href="https://www.producthunt.com/products/vela-7?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1174875?app_id=339">Link</a> </p>

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Comments URL: https://news.ycombinator.com/item?id=48580995 Points: 5 # Comments: 3

<h1> API Testing in the AI Era: A Practical Workflow That Actually Holds Up </h1> <p>API testing hasn't fundamentally changed in the last few years. What has changed is how much of the grunt work can be handed off — and how much new grunt work AI-generated code has created in the process. If you're integrating systems for a living, you've probably noticed both sides of that trade.</p> <p>Here's a workflow that reflects where things actually stand right now, not the marketing version.</p> <h2> St

<pre style='white-space:pre-wrap;width:81ex'>refactor(agents): dedupe cli assistant deltas</pre>

Article URL: https://github.com/mr-gl00m/sigil Comments URL: https://news.ycombinator.com/item?id=48580907 Points: 2 # Comments: 0

Article URL: https://insinuator.net/2026/06/vulnerability-disclosure-stealing-emails-via-firefoxs-ai-features/ Comments URL: https://news.ycombinator.com/item?id=48580886 Points: 5 # Comments: 1

<pre style='white-space:pre-wrap;width:81ex'>refactor(agents): dedupe code mode json serialization</pre>

<p> Make your website work better for people and AI </p> <p> <a href="https://www.producthunt.com/products/nyman-media-signals?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1174859?app_id=339">Link</a> </p>

Article URL: https://github.com/Infodatamatrix/AIKafkaPipelineDemo Comments URL: https://news.ycombinator.com/item?id=48580864 Points: 1 # Comments: 0

<p>Most people treat Claude Projects like a folder with a label on it.</p> <p>They create a project. They give it a name. Maybe they write a sentence or two in the system prompt. Maybe they upload a file. Then they start chatting and wonder why the output feels the same as regular Claude.</p> <p><strong>That is not a project. That is a labeled chatbox.</strong></p> <p>The people getting insane results from Claude Projects are building something completely different. They are building <strong>cus

<pre style='white-space:pre-wrap;width:81ex'>refactor(agents): dedupe model catalog entries</pre>

Agents are designed to do almost any kind of work, from answering support tickets to writing code. No matter how complex the workload, how long it runs, or how many turns it takes to complete, every agent needs three core capabilities to operate: Agents need to connect to models and route between them Agents need to run workflows across many steps Agents need to connect to the systems that make them useful and the platforms people use to interact with them Implementing these capabilities to buil

Article URL: https://simonwillison.net/2026/Jun/17/glm-52/ Comments URL: https://news.ycombinator.com/item?id=48580759 Points: 8 # Comments: 0

Article URL: https://www.google.com/search?q=nvm Comments URL: https://news.ycombinator.com/item?id=48580726 Points: 2 # Comments: 2

<p> Agentic reports your clients want to read </p> <p> <a href="https://www.producthunt.com/products/layerproof-social-content-generation?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1174843?app_id=339">Link</a> </p>

arXiv:2606.17514v1 Announce Type: cross Abstract: Large Language Models have shown remarkable capabilities in code generation. However, most existing evaluations focus only on single-attempt accuracy and overlook the iterative refinement process that is central to real-world programming. This study presents a systematic investigation of LLMs' ability to rectify their own code through execution feedback. Using real-world programming problems across four models and two major programming languages,

arXiv:2606.17536v1 Announce Type: cross Abstract: Generative world models for autonomous driving face two unresolved tensions: heterogeneous control injection, where free-form language, HD-maps, trajectories, and camera poses reside in incompatible representational spaces, and post-hoc cross-view fusion, where per-camera latents fail to encode global 3-D geometry. We trace both to a single root cause: the absence of a shared symbolic interlingua aligning language, geometry, and pixels at the lat

arXiv:2606.17539v1 Announce Type: cross Abstract: Spatial VLMs have made substantial progress in geometric perception, yet complex spatial reasoning requiring multi-step inference over depth, distance, and scene relations remains challenging. Moreover, different spatial queries call for fundamentally different strategies: some are best addressed through purely linguistic, step-by-step deduction, while others require explicit 3D grounding before quantitative inference. We present Dual-Path Spatia

arXiv:2606.17555v1 Announce Type: cross Abstract: Banks simultaneously face signature-based fraud (card-not-present attacks, account takeover, ATM cloning) and behavioural financial crime (structuring, layering, mule networks, business email compromise) -- two threat families with fundamentally different detection requirements. Static rule engines that reliably catch brute-force and high-velocity events are structurally blind to business-email-compromise (BEC) payment redirection, session hijack

arXiv:2606.17564v1 Announce Type: cross Abstract: Standardized evaluation protocols are indispensable for robust benchmarking in remote sensing, particularly as foundation features are increasingly transferred across diverse sensors and complex imaging geometries. In satellite multi-view reconstruction, conventional evaluations relying on unconstrained 2D global matching are often misleading. The Rational Function Model (RFM) and its Rational Polynomial Coefficients (RPC) dictate a curved, heigh

arXiv:2606.17581v1 Announce Type: cross Abstract: We present a dependent-type-based prover designed around the way LLMs (and humans) tend to write mathematics, complementing existing systems such as Lean and Rocq. Its core design choices are a surface that imitates mathematical natural language and a rule-driven automation layer that closes the routine steps a textbook would omit, so that an accepted proof can be re-emitted as a checked Lean file. Early experiments suggest that, even without any

arXiv:2606.17588v1 Announce Type: cross Abstract: Several studies have examined the use of large language models (LLMs) for title-abstract screening in systematic reviews (SRs), reporting mixed accuracy. However, questions of reliability remain largely unaddressed. In this study, we go beyond quantitative LLM-human agreement metrics and qualitatively investigate how and why LLMs fail. We also propose actionable recommendations. We analyzed disagreements between LLMs and researchers across six so

arXiv:2606.17615v1 Announce Type: cross Abstract: Estimating human proficiency from video is a key challenge for automated skill assessment, with applications in sports coaching, music pedagogy, surgical training, and workplace learning. Existing approaches often focus on individual scenarios or rely on shared multi-view aggregation, limiting their ability to adapt to heterogeneous camera viewpoints and activity domains. We introduce SkillMoV, a unified, parameter-efficient framework for multi-s

arXiv:2606.17627v1 Announce Type: cross Abstract: Fine-grained action recognition in egocentric video is challenging for Vision-Language Models (VLMs): actions often differ only in small visual cues, and a single model tends to be biased toward a subset of these cues. We propose Divide, Deliberate, Decide, a fully-local, zero-shot multi-agent framework in which (i) a VLM orchestrator chunks the video and proposes a top-k candidate label list per segment, (ii) an ensemble of heterogeneous VLM spe