- Anthropic and NEC collaborate to build Japan’s largest AI engineering workforce
anthropic-news· 24-abr
Apr 24, 2026Announcements
- Introducing Claude Design by Anthropic Labs
anthropic-news· 17-abr
Apr 17, 2026Product
- Algorithm Selection with Zero Domain Knowledge via Text Embeddings
arxiv-ai· 24-abr
arXiv:2604.19753v1 Announce Type: new Abstract: We propose a feature-free approach to algorithm selection that replaces hand-crafted instance features with pretrained text embeddings. Our method, ZeroFolio, proceeds in three steps: it reads the raw instance file as plain text, embeds it with a pretrained embedding model, and selects an algorithm via weighted k-nearest neighbors. The key to our approach is the observation that pretrained embeddings produce representations that distinguish problem instances without any domain knowledge or task-specific training. This allows us to apply the same three-step pipeline (serialize, embed, select) across diverse problem domains with text-based instance formats. We evaluate our approach on 11 ASlib scenarios spanning 7 domains (SAT, MaxSAT, QBF, AS…
- Exploring Data Augmentation and Resampling Strategies for Transformer-Based Models to Address Class Imbalance in AI Scoring of Scientific Explanations in NGSS Classroom
arxiv-ai· 24-abr
arXiv:2604.19754v1 Announce Type: new Abstract: Automated scoring of students' scientific explanations offers the potential for immediate, accurate feedback, yet class imbalance in rubric categories particularly those capturing advanced reasoning remains a challenge. This study investigates augmentation strategies to improve transformer-based text classification of student responses to a physical science assessment based on an NGSS-aligned learning progression. The dataset consists of 1,466 high school responses scored on 11 binary-coded analytic categories. This rubric identifies six important components including scientific ideas needed for a complete explanation along with five common incomplete or inaccurate ideas. Using SciBERT as a baseline, we applied fine-tuning and test these aug…
- Explainable AML Triage with LLMs: Evidence Retrieval and Counterfactual Checks
arxiv-ai· 24-abr
arXiv:2604.19755v1 Announce Type: new Abstract: Anti-money laundering (AML) transaction monitoring generates large volumes of alerts that must be rapidly triaged by investigators under strict audit and governance constraints. While large language models (LLMs) can summarize heterogeneous evidence and draft rationales, unconstrained generation is risky in regulated workflows due to hallucinations, weak provenance, and explanations that are not faithful to the underlying decision. We propose an explainable AML triage framework that treats triage as an evidence-constrained decision process. Our method combines (i) retrieval-augmented evidence bundling from policy/typology guidance, customer context, alert triggers, and transaction subgraphs, (ii) a structured LLM output contract that require…
- ThermoQA: A Three-Tier Benchmark for Evaluating Thermodynamic Reasoning in Large Language Models
arxiv-ai· 24-abr
arXiv:2604.19758v1 Announce Type: new Abstract: We present ThermoQA, a benchmark of 293 open-ended engineering thermodynamics problems in three tiers: property lookups (110 Q), component analysis (101 Q), and full cycle analysis (82 Q). Ground truth is computed programmatically from CoolProp 7.2.0, covering water, R-134a, and variable-cp air. Six frontier LLMs are evaluated across three independent runs each. The composite leaderboard is led by Claude Opus 4.6 (94.1%), GPT-5.4 (93.1%), and Gemini 3.1 Pro (92.5%). Cross-tier degradation ranges from 2.8 pp (Opus) to 32.5 pp (MiniMax), confirming that property memorization does not imply thermodynamic reasoning. Supercritical water, R-134a refrigerant, and combined-cycle gas turbine analysis serve as natural discriminators with 40-60 pp perf…
- Automated Detection of Dosing Errors in Clinical Trial Narratives: A Multi-Modal Feature Engineering Approach with LightGBM
arxiv-ai· 24-abr
arXiv:2604.19759v1 Announce Type: new Abstract: Clinical trials require strict adherence to medication protocols, yet dosing errors remain a persistent challenge affecting patient safety and trial integrity. We present an automated system for detecting dosing errors in unstructured clinical trial narratives using gradient boosting with comprehensive multi-modal feature engineering. Our approach combines 3,451 features spanning traditional NLP (TF-IDF, character n-grams), dense semantic embeddings (all-MiniLM-L6v2), domain-specific medical patterns, and transformer-based scores (BiomedBERT, DeBERTa-v3), used to train a LightGBM model. Features are extracted from nine complementary text fields (median 5,400 characters per sample) ensuring complete coverage across all 42,112 clinical trial n…
- Inference Headroom Ratio: A Diagnostic and Control Framework for Inference Stability Under Constraint
arxiv-ai· 24-abr
arXiv:2604.19760v1 Announce Type: new Abstract: We present a simulation-based evaluation of the Inference Headroom Ratio (IHR), a dimensionless diagnostic quantity for characterizing inference stability in constrained decision systems. IHR formalizes the relationship between a system's effective inferential capacity C and the combined uncertainty and constraint load U + K imposed by its operating environment, and is intended to capture proximity to an inference stability boundary rather than output-level performance. Across three controlled experiments, we show that IHR functions as: (1) a quantifiable risk indicator whose relationship to collapse probability follows a well-fitted logistic curve with estimated critical threshold IHR* approx. 1.19, (2) a sensitive indicator of proximity to…
- EvoForest: A Novel Machine-Learning Paradigm via Open-Ended Evolution of Computational Graphs
arxiv-ai· 24-abr
arXiv:2604.19761v1 Announce Type: new Abstract: Modern machine learning is still largely organized around a single recipe: choose a parameterized model family and optimize its weights. Although highly successful, this paradigm is too narrow for many structured prediction problems, where the main bottleneck is not parameter fitting but discovering what should be computed from the data. Success often depends on identifying the right transformations, statistics, invariances, interaction structures, temporal summaries, gates, or nonlinear compositions, especially when objectives are non-differentiable, evaluation is cross-validation-based, interpretability matters, or continual adaptation is required. We present EvoForest, a hybrid neuro-symbolic system for end-to-end open-ended evolution of …
- From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents
arxiv-ai· 24-abr
arXiv:2604.19775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of reasoning, planning, and acting within interactive environments. Despite their growing capability to perform multi-step reasoning and decision-making tasks, internal mechanisms guiding their sequential behavior remain opaque. This paper presents a framework for interpreting the temporal evolution of concepts in LLM agents through a step-wise conformal lens. We introduce the conformal interpretability framework for temporal tasks, which combines step-wise reward modeling with conformal prediction to statistically label model's internal representation at each step as successful or failing. Linear probes are then trained on these representations to identify d…
- The Tool-Overuse Illusion: Why Does LLM Prefer External Tools over Internal Knowledge?
arxiv-ai· 24-abr
arXiv:2604.19749v1 Announce Type: new Abstract: Equipping LLMs with external tools effectively addresses internal reasoning limitations. However, it introduces a critical yet under-explored phenomenon: tool overuse, the unnecessary tool-use during reasoning. In this paper, we first reveal this phenomenon is pervasive across diverse LLMs. We then experimentally elucidate its underlying mechanisms through two key lenses: (1) First, by analyzing tool-use behavior across different internal knowledge availability regions, we identify a \textit{knowledge epistemic illusion}: models misjudge internal knowledge boundaries and fail to accurately perceive their actual knowledge availability. To mitigate this, we propose a knowledge-aware epistemic boundary alignment strategy based on direct prefere…
- AI to Learn 2.0: A Deliverable-Oriented Governance Framework and Maturity Rubric for Opaque AI in Learning-Intensive Domains
arxiv-ai· 24-abr
arXiv:2604.19751v1 Announce Type: new Abstract: Generative AI is entering research, education, and professional work faster than current governance frameworks can specify how AI-assisted outputs should be judged in learning-intensive settings. The central problem is proxy failure: a polished artifact can be useful while no longer serving as credible evidence of the human understanding, judgment, or transfer ability that the work is supposed to cultivate or certify. This paper proposes AI to Learn 2.0, a deliverable-oriented governance framework for AI-assisted work. Rather than claiming element-wise novelty, it reorganizes adjacent ideas around the final deliverable package, distinguishes artifact residual from capability residual, and operationalizes the result through a five-part packag…
- A Guide to Relational Database Design
bytebytego· 16-abr
In this article, we cover the core concepts that inform those decisions. We’ll look at tables, keys, relationships, normalization, and joins, with each…Apr 16 • ByteByteGo2064
- EP211: How the JVM Works
bytebytego· 18-abr
We compile, run, and debug Java code all the time. But what exactly does the JVM do between compile and run?Apr 18 • ByteByteGo323110
- How DoorDash Launches a New Country in One Week
bytebytego· 21-abr
In this article, we will look at how this architecture was designed and the challenges they faced.Apr 21 • ByteByteGo24313
- The Security Architecture of GitHub Agentic Workflow
bytebytego· 20-abr
In this article, we will look at how GitHub built a security architecture that assumes the agent is already compromised.Apr 20 • ByteByteGo26314
- B-Trees vs LSM Trees: Comparison and Trade-Offs
bytebytego· 23-abr
In this article, we will look at B-Trees and LSM trees in detail, along with the trade-offs associated with each of them.14 hrs ago • ByteByteGo974
- Claude Platform
claude-changelog
Release notesCopy pageUpdates to the Claude Platform, including the Claude API, client SDKs, and the Claude Console.Copy pageFor release notes on Claude Apps, see the Release notes for Claude Apps in the Claude Help Center.For updates to Claude Code, see the complete CHANGELOG.md in the claude-code repository. April 23, 2026 Memory for Claude Managed Agents is now in public beta under the standard managed-agents-2026-04-01 header. See Using agent memory for the full integration guide. April 20, 2026 We've retired the Claude Haiku 3 model (claude-3-haiku-20240307). All requests to this model will now return an error. We recommend upgrading to Claude Haiku 4.5. April 16, 2026 We've launched Claude Opus 4.7, our most capable generally available model for complex reasoning and agentic coding,…
- Loading...
claude-changelog
Loading...Loading...Loading...Loading...Loading...Loading...Loading...Loading...Loading...Loading...Loading...Loading...Loading...Loading...Loading...
- Redirects for AI Training enforces canonical content
cloudflare· 17-abr
Soft directives don’t stop crawlers from ingesting deprecated content. Redirects for AI Training allows anybody on Cloudflare to redirect verified crawlers to canonical pages with one toggle and no origin changes.
- The AI engineering stack we built internally — on the platform we ship
cloudflare· 20-abr
We built our internal AI engineering stack on the same products we ship. That means 20 million requests routed through AI Gateway, 241 billion tokens processed, and inference running on Workers AI, serving more than 3,683 internal users. Here's how we did it.
- Agents that remember: introducing Agent Memory
cloudflare· 17-abr
Cloudflare Agent Memory is a managed service that gives AI agents persistent memory, allowing them to recall what matters, forget what doesn't, and get smarter over time.
- Making Rust Workers reliable: panic and abort recovery in wasm‑bindgen
cloudflare· 22-abr
Panics in Rust Workers were historically fatal, poisoning the entire instance. By collaborating upstream on the wasm‑bindgen project, Rust Workers now support resilient critical error recovery, including panic unwinding using WebAssembly Exception Handling.
- Moving past bots vs. humans
cloudflare· 21-abr
As AI assistants and privacy proxies challenge the capabilities of traditional bot detection, the Web needs new models for accountability. We believe that control should remain with the client, and that an open ecosystem of anonymous credentials is key to preserving user privacy while protecting origins from abuse.
- Shared Dictionaries: compression that keeps up with the agentic web
cloudflare· 17-abr
Today, we’re excited to give you a sneak peek of our support for shared compression dictionaries, show you how it improves page load times, and reveal when you’ll be able to try the beta yourself.
- Unweight: how we compressed an LLM 22% without sacrificing quality
cloudflare· 17-abr
Running LLMs across Cloudflare’s network requires us to be smarter and more efficient about GPU memory bandwidth. That’s why we developed Unweight, a lossless inference-time compression system that achieves up to a 22% model footprint reduction, so that we can deliver faster and cheaper inference than ever before.
- Building the agentic cloud: everything we launched during Agents Week 2026
cloudflare· 20-abr
Agents Week 2026 is a wrap. Let’s take a look at everything we announced, from compute and security to the agent toolbox, platform tools, and the emerging agentic web. Everything we shipped for the agentic cloud.
- Introducing the Agent Readiness score. Is your site agent-ready?
cloudflare· 17-abr
The Agent Readiness score can help site owners understand how well their websites support AI agents. Here we explore new standards, share Radar data, and detail how we made Cloudflare’s docs the most agent-friendly on the web.
- Orchestrating AI Code Review at scale
cloudflare· 20-abr
Learn about how we built a CI-native AI code reviewer using OpenCode that helps our engineers ship better, safer code.
- Anil-matcha/Open-Generative-AI
github-trending
Uncensored, open-source alternative to Higgsfield AI, Freepik, Krea, Openart AI — Free, unrestricted AI image & video generation studio with 200+ models (Flux, Midjourney, Kling, Sora, Veo). No content filters. Self-hosted, MIT licensed. Open Generative AI — Uncensored Open-Source Alternative to Higgsfield AI, Freepik, Krea, Openart AI The free, open-source, unrestricted alternative to Higgsfield AI, Freepik, Krea, Openart AI. Generate AI images and videos using 200+ state-of-the-art models — no content filters, no closed ecosystem, no subscription fees. 💡 Looking for GPT-Image-2 prompts? Check out Awesome GPT-Image-2 API Prompts — a curated collection of 40+ ready-to-use prompts for the OpenAI gpt-image-2 API covering portraits, posters, UI mockups, game screenshots, and more. 🤖 Automa…
- Alishahryar1/free-claude-code
github-trending
Use claude-code for free in the terminal, VSCode extension or via discord like openclaw 🤖 Free Claude Code Use Claude Code CLI & VSCode for free. No Anthropic API key required. A lightweight proxy that routes Claude Code's Anthropic API calls to NVIDIA NIM (40 req/min free), OpenRouter (hundreds of models), DeepSeek (direct API), LM Studio (fully local), or llama.cpp (local with Anthropic endpoints). Quick Start · Providers · Discord Bot · Configuration · Development · Contributing Claude Code running via NVIDIA NIM, completely free Features Feature Description Zero Cost 40 req/min free on NVIDIA NIM. Free models on OpenRouter. Fully local with LM Studio Drop-in Replacement Set 2 env vars. No modifications to Claude Code CLI or VSCode extension needed 5 Providers NVIDIA NIM, OpenRouter, …
- huggingface/ml-intern
github-trending
🤗 ml-intern: an open-source ML engineer that reads papers, trains models, and ships ML models ML Intern An ML intern that autonomously researches, writes, and ships good quality ML releated code using the Hugging Face ecosystem — with deep access to docs, papers, datasets, and cloud compute. Quick Start Installation git clone git@github.com:huggingface/ml-intern.git cd ml-intern uv sync uv tool install -e . That's it. Now ml-intern works from any directory: ml-intern Create a .env file in the project root (or export these in your shell): ANTHROPIC_API_KEY=<your-anthropic-api-key> # if using anthropic models HF_TOKEN=<your-hugging-face-token> GITHUB_TOKEN=<github-personal-access-token> If no HF_TOKEN is set, the CLI will prompt you to paste one on first launch. To get a GITHUB_TOKEN follo…
- PowerShell/PowerShell
github-trending
PowerShell for every system! PowerShell Welcome to the PowerShell GitHub Community! PowerShell is a cross-platform (Windows, Linux, and macOS) automation and configuration tool/framework that works well with your existing tools and is optimized for dealing with structured data (e.g. JSON, CSV, XML, etc.), REST APIs, and object models. It includes a command-line shell, an associated scripting language, and a framework for processing cmdlets. Windows PowerShell vs. PowerShell 7+ Although this repository started as a fork of the Windows PowerShell codebase, changes made in this repository are not ported back to Windows PowerShell 5.1. This also means that issues tracked here are only for PowerShell 7.x and higher. Windows PowerShell specific issues should be reported with the Feedback Hub ap…
- Oracle's Deluge of AI Debt Pushes Wall Street to the Limit
hn-ai· 24-abr
Article URL: https://www.wsj.com/tech/ai/oracle-ai-demand-debt-04977749 Comments URL: https://news.ycombinator.com/item?id=47885531 Points: 4 # Comments: 1
- AI run store in SF can't stop ordering candies and paying women less.
hn-ai· 24-abr
Article URL: https://sfist.com/2026/04/21/ai-store-manager-paying-female-employees-less-cant-stop-ordering-candles/ Comments URL: https://news.ycombinator.com/item?id=47885334 Points: 7 # Comments: 2
- Control Workspace Intelligence for generative AI features [AI defaults on]
hn-ai· 24-abr
Article URL: https://knowledge.workspace.google.com/admin/gemini/control-workspace-intelligence Comments URL: https://news.ycombinator.com/item?id=47885292 Points: 2 # Comments: 0
- If AI existed in 2011 would we still have the modern web
hn-ai· 24-abr
Article URL: https://webmatrices.com/post/if-ai-existed-in-2011-would-we-still-have-the-modern-web Comments URL: https://news.ycombinator.com/item?id=47885149 Points: 1 # Comments: 0
- Anthropic tested removing Claude Code from the Pro plan
hn-ai· 24-abr
Article URL: https://arstechnica.com/ai/2026/04/anthropic-tested-removing-claude-code-from-the-pro-plan/ Comments URL: https://news.ycombinator.com/item?id=47885488 Points: 2 # Comments: 0
- Contral AI
hn-ai· 24-abr
Article URL: https://contral.ai Comments URL: https://news.ycombinator.com/item?id=47885924 Points: 1 # Comments: 0
- The Budgeting Mistake That Cost Uber Its Annual AI Spend in 4 Months
hn-ai· 24-abr
Article URL: https://www.productcurious.com/p/uber-ai-budget-mistake Comments URL: https://news.ycombinator.com/item?id=47885716 Points: 5 # Comments: 0
- AI Resume Reviewer
hn-ai· 24-abr
Article URL: https://www.thehumancapitalhub.com/ai-resume-reviewer Comments URL: https://news.ycombinator.com/item?id=47885593 Points: 1 # Comments: 0
- The AI Science Separation
hn-ai· 24-abr
Article URL: https://www.thewirechina.com/2026/04/19/the-ai-science-separation/ Comments URL: https://news.ycombinator.com/item?id=47885561 Points: 1 # Comments: 0
- We're Using So Much AI That Computing Firepower Is Running Out
hn-ai· 24-abr
Article URL: https://www.wsj.com/tech/ai/ai-is-using-so-much-energy-that-computing-firepower-is-running-out-156e5c85 Comments URL: https://news.ycombinator.com/item?id=47885544 Points: 1 # Comments: 0
- [AINews] Tasteful Tokenmaxxing
latentspace· 23-abr
a quiet day lets us reflect on the top conversation that AI leaders are having everywhere.
- [AINews] The Two Sides of OpenClaw
latentspace· 18-abr
a quiet day lets us reflect on openclaw this week.
- AIE Europe Debrief + Agent Labs Thesis: Unsupervised Learning x Latent Space Crossover Special (2026)
latentspace· 23-abr
Note: This episode was recorded just after AIE Europe, but before the Cursor-xAI deal.
- [AINews] Anthropic Claude Opus 4.7 - literally one step better than 4.6 in every dimension
latentspace· 17-abr
The new SOTA model asserts its dominance.
- [AINews] GPT 5.5 and OpenAI Codex Superapp
latentspace· 24-abr
Spud lives!
- [AINews] RIP Pull Requests (2005-2026)
latentspace· 16-abr
a quiet day lets us report on the death of the pull requests
- Fragments: April 21
martin-fowler· 21-abr
Last week Thoughtworks released the 34th volume of our Technology Radar. This radar is our biannual survey of our experience of the technology scene, highlighting tools, techniques, platforms, and languages that we’ve used or otherwise caught our eye. This edition contains 118 blips, each briefly describing our impressions of one of these elements. As we would expect, the radar is dominated by AI-oriented topics. Part of this is revisiting familiar ground with LLM-assisted eyes: An interesting consequence of AI in software development is that it’s not only forcing us to look to the future; it’s also pushing us to revisit the foundations of our craft. While assembling this edition, we found ourselves returning to many established techniques, from pair programming to zero trust architecture…
- The Human Infrastructure: How Netflix Built the Operations Layer Behind Live at Scale
netflix-tech· 17-abr
- A pelican for GPT-5.5 via the semi-official Codex backdoor API
simonw· 23-abr
<p><a href="https://openai.com/index/introducing-gpt-5-5/">GPT-5.5 is out</a>. It's available in OpenAI Codex and is rolling out to paid ChatGPT subscribers. I've had some preview access and found it to be a fast, effective and highly capable model. As is usually the case these days, it's hard to put into words what's good about it - I ask it to build things and it builds exactly what I ask for!</p> <p>There's one notable omission from today's release - the API:</p> <blockquote> <p>API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale. We'll bring GPT‑5.5 and GPT‑5.5 Pro to the API very soon.</p> </blockquote> <p>When I run my <a href="https://simonwillison.net/tags/pelican-riding…
- Extract PDF text in your browser with LiteParse for the web
simonw· 23-abr
<p>LlamaIndex have a most excellent open source project called <a href="https://github.com/run-llama/liteparse">LiteParse</a>, which provides a Node.js CLI tool for extracting text from PDFs. I got a version of LiteParse working entirely in the browser, using most of the same libraries that LiteParse uses to run in Node.js.</p> <h4 id="spatial-text-parsing">Spatial text parsing</h4> <p>Refreshingly, LiteParse doesn't use AI models to do what it does: it's good old-fashioned PDF parsing, falling back to Tesseract OCR (or other pluggable OCR engines) for PDFs that contain images of text rather than the text itself.</p> <p>The hard problem that LiteParse solves is extracting text in a sensible order despite the infuriating vagaries of PDF layouts. They describe this as "spatial text parsing"…
- Quoting Maggie Appleton
simonw· 23-abr
<blockquote cite="https://maggieappleton.com/gathering-structures"><p>[...] if you ever needed another reason to <a href="https://www.swyx.io/learn-in-public">learn in public</a> by <a href="https://maggieappleton.com/garden-history">digital gardening</a> or podcasting or streaming or whathaveyou, add on that people will assume you’re more competent than you are. This will get you invites to very cool exclusive events filled with high-achieving, interesting people, even though you have no right to be there. A+ side benefit.</p></blockquote> <p class="cite">— <a href="https://maggieappleton.com/gathering-structures">Maggie Appleton</a>, Gathering Structures (<a href="https://notes.andymatuschak.org/Work_with_the_garage_door_up">via</a>)</p> <p>Tags: <a href="https://simonwillison.net…
- russellromney/honker
simonw· 24-abr
<p><strong><a href="https://github.com/russellromney/honker">russellromney/honker</a></strong></p> "Postgres NOTIFY/LISTEN semantics" for SQLite, implemented as a Rust SQLite extension and various language bindings to help make use of it.</p> <p>The design of this looks very solid. It lets you write Python code for queues that looks like this:</p> <pre><span class="pl-k">import</span> <span class="pl-s1">honker</span> <span class="pl-s1">db</span> <span class="pl-c1">=</span> <span class="pl-s1">honker</span>.<span class="pl-c1">open</span>(<span class="pl-s">"app.db"</span>) <span class="pl-s1">emails</span> <span class="pl-c1">=</span> <span class="pl-s1">db</span>.<span class="pl-c1">queue</span>(<span class="pl-s">"emails"</span>) <span class="pl-c1">emails</span>.<span class="pl-c1">…
- An update on recent Claude Code quality reports
simonw· 24-abr
<p><strong><a href="https://www.anthropic.com/engineering/april-23-postmortem">An update on recent Claude Code quality reports</a></strong></p> It turns out the high volume of complaints that Claude Code was providing worse quality results over the past two months was grounded in real problems.</p> <p>The models themselves were not to blame, but three separate issues in the Claude Code harness caused complex but material problems which directly affected users.</p> <p>Anthropic's postmortem describes these in detail. This one in particular stood out to me:</p> <blockquote> <p>On March 26, we shipped a change to clear Claude's older thinking from sessions that had been idle for over an hour, to reduce latency when users resumed those sessions. A bug caused this to keep happening every turn …
- Serving the For You feed
simonw· 24-abr
<p><strong><a href="https://atproto.com/blog/serving-the-for-you-feed">Serving the For You feed</a></strong></p> One of Bluesky's most interesting features is that anyone can run their own <a href="bluesky custom feed">custom "feed" implementation</a> and make it available to other users - effectively enabling custom algorithms that can use any mechanism they like to recommend posts.</p> <p>spacecowboy runs the <a href="https://bsky.app/profile/did:plc:3guzzweuqraryl3rdkimjamk/feed/for-you">For You Feed</a>, used by around 72,000 people. This guest post on the AT Protocol blog explains how it works.</p> <p>The architecture is <em>fascinating</em>. The feed is served by a single Go process using SQLite on a "gaming" PC in spacecowboy's living room - 16 cores, 96GB of RAM and 4TB of attache…
- It's a big one
simonw· 24-abr
<p><a href="https://simonw.substack.com/p/gpt-55-chatgpt-images-20-qwen36-27b">This week's edition</a> of my email newsletter (aka <a href="https://simonwillison.net/2023/Apr/4/substack-observable/">content from this blog</a> delivered to your inbox) features 4 pelicans riding bicycles, 1 possum on an e-scooter, up to 5 raccoons with ham radios hiding in crowds, 5 blog posts, 8 links, 3 quotes and a new chapter of my Agentic Engineering Patterns guide.</p> <p>Tags: <a href="https://simonwillison.net/tags/newsletter">newsletter</a></p>