- Anthropic is donating another $20 million to Public First Action
anthropic-news· 21-jul
Jul 21, 2026Announcements
- Ask Claude about the Anthropic Economic Index
anthropic-news· 22-jul
Jul 22, 2026Product
- A research agenda for the Economic Futures Research Fund
anthropic-news· 22-jul
Jul 22, 2026Economic Research
- JAXBench: Benchmarking Autonomous TPU Kernel Optimization
arxiv-ai· 24-jul
arXiv:2607.20466v1 Announce Type: new Abstract: Rigorous benchmarks have driven progress in autonomous GPU kernel performance optimization by establishing a shared target to hillclimb on, but no equivalent exists for TPUs. We present JAXBench, a TPU-native benchmark suite for AI-generated kernel optimization on Google Cloud TPUs. JAXBench comprises 50 JAX workloads that are both relevant and provide headroom for optimization. We extract 17 production ML operators from architectures in the public MaxText library such as Llama-3.1, DeepSeek-V3, Mixtral, Mamba-2, and AlphaFold2, and translate 33 operators from KernelBench that are validated for correctness and set with new problem sizes that achieve high TPU v6e MXU utilization. Eight of the 17 production operators ship with hand-optimized P…
- DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding
arxiv-ai· 24-jul
arXiv:2607.20467v1 Announce Type: new Abstract: While parallel decoding is central to the efficiency of Diffusion Large Language Models (dLLMs), current strategies are often hindered by overly conservative confidence thresholds. These thresholds, necessitated by the Joint Probability Dependence Error (JPDE), result in redundant denoising iterations and suboptimal inference speeds. To overcome this, we propose DC-Leap, a training-free framework that enables reliable acceleration of dLLMs in the moderate-confidence regime. DC-Leap introduces a Dynamic Contiguous Verification strategy that integrates strictly-ordered causal constraints into the parallel decoding process. By progressively validating token dependencies, this mechanism effectively neutralizes the JPDE, enabling reliable acceler…
- InferenceBench: A Benchmark for Open-Ended LLM Inference Optimization by AI Agents
arxiv-ai· 24-jul
arXiv:2607.20468v1 Announce Type: new Abstract: AI agents are increasingly used to automate research and development tasks, yet existing benchmarks typically evaluate them on prescribed workflows or narrow action spaces. Even nominally open-ended tasks can often be solved by retrieving a well-known recipe and tuning a few hyperparameters, making it unclear whether strong results reflect genuine optimization or memorized solutions. We introduce InferenceBench, where an agent must deploy an OpenAI-compatible inference server and optimize the speed of LLM inference. Each agent receives a target LLM, one H100 GPU, an optimization scenario, and a wall-clock time budget of two hours. Three optimization scenarios isolate distinct bottlenecks of inference (prefill latency, decode latency, and con…
- DecodeShare: Tracing the Shared Subspace of LLM Decode-Time Decisions
arxiv-ai· 24-jul
arXiv:2607.20469v1 Announce Type: new Abstract: Large language models (LLMs) handle many tasks with one set of parameters, but under KV-cached inference it is unclear what task-general structure, if any, is used at decode time rather than during prefill. We propose DecodeShare, a protocol that identifies a low-dimensional subspace consistently shared across tasks in decode-time hidden states, and then tests its causal role by removing that subspace only during decoding. In our experiments, disturbing the discovered shared subspace degrades decision performance far more than disturbing either a prefill-derived or random subspace under the same intervention budget. We further show this decode-shared subspace has practical consequences for activation steering: common steering directions can …
- PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMs
arxiv-ai· 24-jul
arXiv:2607.20470v1 Announce Type: new Abstract: Enhancing the task-specific capabilities of Large Language Models (LLMs) primarily requires substantial instruction-tuning datasets. However, the sheer volume of such data imposes a considerable annotation cost, and a lack of optimization methods for tailoring LLMs to specific tasks. To address the above issues, we propose a \textbf{Plan}ning framework for constructing \textbf{E}xtractive-based LLMs called \textbf{PlanE}, which includes data decomposition, instruction tuning, and prompt inference. Additionally, we introduce a Data-Tuning-Inference (DTI) planner, aimed at selecting the optimal base-LLM and its DTI combinations for specific datasets to improve construction efficiency. The experimental results demonstrate the effectiveness of o…
- Benchmarking the Personalization Capabilities of Large Language Models
arxiv-ai· 24-jul
arXiv:2607.20471v1 Announce Type: new Abstract: Personalization, the act of varying a message to induce action from a specific receiver while keeping sender, channel, and time fixed, has a long tradition in psychology and marketing as a two-party problem in which sender and receiver have independent objectives. Large language models remove the bounded-inventory constraint of classical retrieval-and-ranking approaches by generating a continuum of message variants conditioned on inferred receiver state, raising the question of how well current models perform personalization in the classical sense. Existing LLM personalization benchmarks measure sender-side adaptation, in which the receiver is the same user the model is serving. The two-party question, whether a generated message induces its…
- AINTMA: Agentic AI Architecture for Autonomous Test Management with Generative Intelligence, Secure Cloud Communication and Adaptive Quality Analytics
arxiv-ai· 24-jul
arXiv:2607.20452v1 Announce Type: new Abstract: Modern software quality assurance demands intelligent, autonomous systems capable of adaptive decision-making across distributed cloud environments. This paper presents AINTMA (Agentic Intelligent Test Management Architecture), a multi-agent agentic AI system that transforms traditional test management into an autonomous quality intelligence ecosystem. AINTMA deploys six specialized AI agents (Test Discovery, Risk Assessment, Reinforcement Learning Prioritization, Execution Orchestration, Generative Quality Intelligence, and Cloud Security Monitor) coordinated through a secure multi-agent communication framework over a cloud-native microservices infrastructure. The Generative Quality Intelligence agent employs large language models to produc…
- ClickGuard: Detecting and Spoiling Clickbait News with Informativeness Measures and Large Language Models
arxiv-ai· 24-jul
arXiv:2607.20463v1 Announce Type: new Abstract: This paper presents an AI-driven browser extension that identifies clickbait to help users avoid misleading Internet articles. Moving beyond traditional detection, the application employs a hybrid machine learning architecture that combines transformer-based embeddings with linguistically motivated features and a custom "baitness" score. After evaluating various natural language processing techniques -- from classic vectorizers to large language model (LLM) embeddings -- an XGBoost-based model was developed that achieves an F1-score of 91% on the open combined dataset. Most importantly, the tool can warn users before and after they access a clickbait article. After opening an article, the user receives a percentage score indicating the likel…
- Stochastic Sampling is Epistemically Shallow: The Dimensionality Gap Between Temperature Variation and Model Diversity in LLMs
arxiv-ai· 24-jul
arXiv:2607.20464v1 Announce Type: new Abstract: When a language model gives different answers on repeated runs, does that variation reveal what it does not know? Self-consistency turns the variation into a per-question uncertainty estimate via majority voting. But does the same variation reveal cross-question structure -- related questions flipping together, the way a diverse ensemble does? We compare two regimes on the same questions: one model run $100$ times at $\tau=1$ versus an ensemble of $24$ LLMs run once each at $\tau=0$. A Marchenko--Pastur random-matrix test separates signal from sampling noise on both sides. Within any single model, at most one dimension rises above noise across five families and three benchmarks (MMLU, HellaSwag, GSM8K). Across the ensemble, four eigenvalues …
- Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts
arxiv-ai· 24-jul
arXiv:2607.20462v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into clinical workflows, stressing the need for reliable traceability of model-generated output with watermarking. Yet, most watermarks are evaluated on general-purpose benchmarks, leaving domains like medicine, where small token-level perturbations can result in significant semantic changes, underexplored. In this work, we present the first rigorous study of how LLM watermarks affect medical performance, benchmarking 5 watermarking schemes across 11 LLMs and 7 VLMs on various tasks spanning unimodal and multimodal clinical reasoning. Importantly, we complement existing evaluations by introducing a human-expert-validated pipeline for systematically auditing medical reasoning quality, t…
- Inside Roblox’s Bet on World Models
bytebytego· 21-jul
We sat down with Anupam Singh, senior vice president of engineering at Roblox, to hear from him about the world model that Roblox is using to make its…Jul 21 • ByteByteGo30237
- MCP vs A2A vs ACP: How AI Agents Actually Talk to Each Other
bytebytego· 18-jul
Agents are capable on their own. Combined with tools and other agents, their capabilities compound.Jul 18 • ByteByteGo347520
- A Beginner’s Guide to Clocks, Causality, and Ordering in Distributed Systems
bytebytego· 23-jul
Why does something as simple as reading the time become a hard problem for distributed systems?14 hrs ago • ByteByteGo1243
- Best Practices for Building AI Agents That Work in Production
bytebytego· 22-jul
In this article, we try to explore the collective thinking into a smaller set of practices and explain the reasoning behind each one, rather than asking…Jul 22 • ByteByteGo296112
- Introducing Cache Response Rules
cloudflare· 23-jul
Perhaps you’ve seen something that should sail out of cache get dragged back to the origin by a stray Set-Cookie or Cache-Control, headers that can be difficult to change on the origin itself. Cache Response Rules is the fix, applied at the right time.
- Cloudflare WAF protects WordPress applications from two high-severity vulnerabilities
cloudflare· 17-jul
Cloudflare has deployed two WAF rules in response to high-severity vulnerabilities disclosed to us by the WordPress security team. The new rules protect all Cloudflare customers using affected WordPress versions, but customers should still update immediately to a patched release
- How the 2026 World Cup affected Internet traffic
cloudflare· 21-jul
We analyzed global HTTP traffic to explore how kickoff times, streaming habits, and hydration breaks reshaped online activity worldwide. From late-night traffic surges to halftime browsing spikes, here is how the world connected during the global tournament.
- Cloudflare Internal DNS is now generally available
cloudflare· 20-jul
Cloudflare Internal DNS brings authoritative and recursive DNS for private networks to the same global network and control plane that runs Cloudflare's Zero Trust, networking, and public DNS.
- shiyu-coder/Kronos
github-trending
Kronos: A Foundation Model for the Language of Financial Markets Kronos: A Foundation Model for the Language of Financial Markets Deutsch | Español | Français | 日本語 | 한국어 | Português | Русский | 中文 Kronos is the first open-source foundation model for financial candlesticks (K-lines), trained on data from over 45 global exchanges. 📰 News 🚩 [2025.11.10] Kronos has been accpeted by AAAI 2026. 🚩 [2025.08.17] We have released the scripts for fine-tuning! Check them out to adapt Kronos to your own tasks. 🚩 [2025.08.02] Our paper is now available on arXiv! 📜 Introduction Kronos is a family of decoder-only foundation models, pre-trained specifically for the "language" of financial markets—K-line sequences. Unlike general-purpose TSFMs, Kronos is designed to handle the unique, high-noise char…
- block/buzz
github-trending
A hive mind communication platform Buzz 🐝 A workspace where humans and agents build together, on a relay you own. Vision · Sovereign · Forge · Agents · Architecture · Apache 2.0 People and agents building together in the same room. What is this, really? Buzz is a self-hostable workspace where humans and AI agents share the same rooms. A Buzz community is the workspace a user reaches by URL. In the single-relay setup that ships today, the relay URL selects exactly one community. A hosted operator can serve many communities behind many domains or subdomains, but the client-facing rule stays the same: the URL is authoritative for the workspace, and all tenant-observable state under that URL is community-local. It's a Nostr relay: every message, reaction, workflow step, review approval, and …
- citrolabs/ego-lite
github-trending
The best browser for both you and your AI agents work in parallel. The best browser for both you and your AI agents work in parallel. ego (lite) is a browser where you and your AI agents work in parallel. Your agents run multiple browser tasks in their own Spaces while your tabs stay yours, and tasks complete faster on fewer tokens. Existing tools like browser-use and agent-browser are browser automation frameworks: they need a separate browser to drive, logins never carry cleanly, and you and the agent end up fighting for the same tabs. ego lite is one browser designed from the start for the two of you to share. No extra setup, and the agent can always reach your real logins and tabs through ego-browser. Demo https://github.com/user-attachments/assets/ffe7954b-58ee-411e-b35d-ec30c58a08bc…
- ComposioHQ/awesome-claude-skills
github-trending
A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows Awesome Claude Skills A comprehensive and curated list of 1000+ production ready and practical Claude Skills and Plugins for enhancing productivity across usecases on not just Claude.ai, Claude Code, but also across coding agents like Codex, Cursor, Gemini CLI, Antigravity and more. Want skills that do more than generate text? Claude can send emails, create issues, post to Slack, and take actions across 1000+ apps. See how → Quickstart: Connect Claude to 500+ Apps The connect-apps plugin lets Claude perform real actions - send emails, create issues, post to Slack. It handles auth and connects to 500+ apps using Composio under the hood. 1. Install the Plugin claude --plugin-dir ./connect-apps-…
- Pumpkin-MC/Pumpkin
github-trending
Empowering everyone to host fast and efficient Minecraft servers. Pumpkin Pumpkin is a Minecraft server built entirely in Rust, offering a fast, efficient, and customizable experience. It prioritizes performance and player enjoyment while adhering to the core mechanics of the game. Goals Performance: Leveraging multi-threading for maximum speed and efficiency. Compatibility: Supports the latest Java & Bedrock Minecraft server version while adhering to Vanilla game mechanics. Security: Prioritizes security by preventing known security exploits. Flexibility: Highly configurable, with the ability to disable unnecessary features. Extensibility: Provides a foundation for plugin development. Important Pumpkin is currently under heavy development. See what needs to be done before the 1.0.0 Relea…
- China's All-Out Push to Catch Up with American AI Chips
hn-ai· 24-jul
Article URL: https://www.wsj.com/world/china/china-ai-chips-race-949050d0 Comments URL: https://news.ycombinator.com/item?id=49031362 Points: 1 # Comments: 0
- Claude Cookbook
hn-ai· 24-jul
Article URL: https://platform.claude.com/cookbook/ Comments URL: https://news.ycombinator.com/item?id=49031409 Points: 1 # Comments: 0
- Flux 3: From AI image generation to visual intelligence
hn-ai· 24-jul
Article URL: https://textideo.com/model/flux-3 Comments URL: https://news.ycombinator.com/item?id=49031139 Points: 1 # Comments: 0
- Tinfoil – Private AI
hn-ai· 24-jul
Article URL: https://tinfoil.sh Comments URL: https://news.ycombinator.com/item?id=49031042 Points: 1 # Comments: 0
- Why hasn't AI increased unemployment?
hn-ai· 24-jul
Article URL: https://twitter.com/PeterMcCrory/status/2079979321607745905 Comments URL: https://news.ycombinator.com/item?id=49031138 Points: 1 # Comments: 0
- Lock TF IN: an AI drill sergeant that roasts skipped workouts
hn-ai· 24-jul
Article URL: https://apps.apple.com/us/app/lock-tf-in-ai-companion/id6788896897 Comments URL: https://news.ycombinator.com/item?id=49031206 Points: 1 # Comments: 0
- Show HN: Generous free tier for SERP and AI web scraping
hn-ai· 24-jul
Hackers, We wanted to share our newly-added recurring Free tier for cloro.dev, the leading AI UI scraping platform in the world. We extract structured data from ChatGPT, Perplexity, Grok, Gemini, Google Search, Google News, Copilot, and AI Overview through one API, with low latency across any country. We have recently crossed 200+ customers, most of them the large Enterprises behind GEO and SEO. From now on, every user gets 500 free credits every month, which is great for hobby projects you may have. Enjoy! Comments URL: https://news.ycombinator.com/item?id=49031260 Points: 1 # Comments: 0
- Google's slump in AI race driven in part by low morale
hn-ai· 24-jul
Article URL: https://www.axios.com/2026/07/23/googles-deep-mind-ai-model-race Comments URL: https://news.ycombinator.com/item?id=49031227 Points: 3 # Comments: 1
- AI will not trigger employment collapse, staffing company Adecco Group says
hn-ai· 24-jul
Article URL: https://www.reuters.com/business/ai-will-not-trigger-employment-collapse-staffing-company-adecco-group-says-2026-07-23/ Comments URL: https://news.ycombinator.com/item?id=49031153 Points: 2 # Comments: 0
- The Sad Wives of AI
hn-ai· 24-jul
Article URL: https://www.wired.com/story/meet-the-sad-wives-of-ai/ Comments URL: https://news.ycombinator.com/item?id=49031294 Points: 2 # Comments: 1
- Inside the Model Factory — Eiso Kant, Poolside AI
latentspace· 23-jul
Poolside's co-CEO on how his small team of top researchers built a model factory capable of training Laguna S - a 118B MOE beating Thinky's ~1T open weights model... and this is just the beginning.
- [AINews] Black Forest Labs FLUX 3 - Multimodal Flow Models that beat Seedance 2.0, Gemini Omni and Grok Imagine, and FLUX-mimic video-action robotics model
latentspace· 24-jul
A HUGE win for BFL!
- [AINews] "Laguna S 2.1 Released: Cheaper than Deepseek v4 Flash, Better than V4 Pro"
latentspace· 23-jul
a quiet day lets us highlight a new neolab win.
- Fragments: July 21
martin-fowler· 21-jul
With this post, I’ll wrap up my notes from the second Future of Software Development Retreat. But before I do, I should note that the full Thoughtworks report on the retreat is now available. They have five headline findings: Code generation is no longer the bottleneck — verification is. ‘Harness engineering’ is emerging as a distinct, ownable discipline. Organizations are colliding with a real apprenticeship crisis. The executive/engineer expectation gap is a bigger risk than any technical limitation. Legacy modernization is the clearest, most defensible near-term value pool. ❄ ❄ A session convened around the mismatch of views about using LLMs between engineers using it and the C-suite and boards that were calling for it. The concern is that boards are looking at promised productivity ga…
- In-House LLM Serving at Netflix
netflix-tech· 17-jul
- Orchestrions
simonw· 22-jul
<p>San Francisco tip: it only costs around $15 ($10 in quarters plus a $5 bill for the self-playing violin) to activate every single Orchestrion in <a href="https://en.wikipedia.org/wiki/Musée_Mécanique">Musée Mécanique</a>.</p> <p>And because most people are bad at allocating their funds you may well be the ONLY person activating the Orchestrions, which means you get to craft the soundscape for the entire museum.</p> <p>Tags: <a href="https://simonwillison.net/tags/san-francisco">san-francisco</a></p>
- Are AI labs pelicanmaxxing?
simonw· 22-jul
<p><strong><a href="https://dylancastillo.co/posts/pelicanmaxxing.html">Are AI labs pelicanmaxxing?</a></strong></p> Excellent piece of work by Dylan Castillo, who took a deep-dive into the frequently pondered question of whether the AI labs have been deliberately training models to draw pelicans riding bicycles in response to my <a href="https://simonwillison.net/tags/pelican-riding-a-bicycle/">deeply unscientific benchmark</a>.</p> <p>I've been randomly spot-checking this in the past by testing models against other animals riding other types of vehicle, but never with anything close to the diligence of Dylan's methodology here.</p> <p>Dylan took 8 animals × 6 vehicles = 48 prompts and ran them three times each through 7 different models ( GPT-5.6 Terra, Claude Sonnet 5, Gemini 3.5 Flash…
- OpenAI’s accidental cyberattack against Hugging Face is science fiction that happened
simonw· 22-jul
<p>This story is wild. The short version: OpenAI were running a cybersecurity test against an unreleased model, with the model's guardrail features turned off. Rather than solve the test, the model broke its way out of OpenAI's sandbox, then found exploits to break <em>in</em> to Hugging Face, all so it could cheat on the test by stealing the answers.</p> <p>Along the way it helped make the strongest case yet for how the imbalance of model availability is hurting our ability to secure our software.</p> <h4 id="here-s-what-happened">Here's what happened</h4> <p>We currently have three documents to help us understand what happened here.</p> <ol> <li> <a href="https://arxiv.org/abs/2605.11086">ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?</a> is a paper published…
- Quoting Thomas Ptacek
simonw· 22-jul
<blockquote cite="https://twitter.com/tqbf/status/2080045032162173329"><p>I genuinely believe that if you took an open weights model from 2025 and built a pentest harness for it, it could do this kind of sandbox escape and scan/hack in most networks. This is only surprising because you assume OpenAI has sounder sandboxes.</p></blockquote> <p class="cite">— <a href="https://twitter.com/tqbf/status/2080045032162173329">Thomas Ptacek</a>, doesn't think <a href="https://simonwillison.net/2026/Jul/22/openai-cyberattack/#resist-the-temptation-to-write-this-off-as-a-stunt">this even needs</a> a frontier model</p> <p>Tags: <a href="https://simonwillison.net/tags/thomas-ptacek">thomas-ptacek</a>, <a href="https://simonwillison.net/tags/openai">openai</a>, <a href="https://simonwillison.net/t…
- Quoting Seth Larson
simonw· 23-jul
<blockquote cite="https://blog.pypi.org/posts/2026-07-22-releases-now-reject-new-files-after-14-days/"><p>The Python Package Index (PyPI) now rejects new files being uploaded to releases that are older than 14 days. This restriction was <a href="https://github.com/pypi/warehouse/pull/19727">put in place</a> to prevent old and long-stable releases from being poisoned in case publishing tokens or workflows of PyPI projects were compromised. As far as we are aware this has not yet been abused, but there is no technical reason beyond that attackers weren't aware it was possible.</p></blockquote> <p class="cite">— <a href="https://blog.pypi.org/posts/2026-07-22-releases-now-reject-new-files-after-14-days/">Seth Larson</a>, PyPI blog</p> <p>Tags: <a href="https://simonwillison.net/tags/pa…
- The first known runaway AI agent - or a very bad marketing stunt?
simonw· 23-jul
<p><strong><a href="https://martinalderson.com/posts/huggingface-openai-exploit/">The first known runaway AI agent - or a very bad marketing stunt?</a></strong></p> Martin Alderson's commentary on the <a href="https://simonwillison.net/2026/Jul/22/openai-cyberattack/">OpenAI accidental cyberattack against Hugging Face</a> includes a couple of details I hadn't considered.</p> <p>First, Hugging Face offers a truly rich target if you're trying to find potential vulnerabilities that require executing arbitrary code:</p> <blockquote> <p>Hugging Face has an <em>enormous</em> attack surface. They have more interfaces than I can count which run untrusted models and code. While they definitely have invested in defences, by nature of their operating model they do have many more opportunities to be …
- California Sea Lion
simonw· 21-jul
<p><img src="https://static.inaturalist.org/photos/702321069/large.jpg" alt="California Sea Lion"></p><p><img src="https://static.inaturalist.org/photos/702321114/large.jpg" alt="California Sea Lion"></p><p>California Sea Lion, in San Francisco County, US, CA</p><p>We took some visiting family to Pier 39 to see the sea lions. They're somehow always even more fun than I remember them being last time.</p> <p>Tags: <a href="https://simonwillison.net/tags/san-francisco">san-francisco</a>, <a href="https://simonwillison.net/tags/wildlife">wildlife</a></p>