Everything That Happened in AI Today Thursday, April 2, 2026 | The Neuron
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Around the Horn Digest: Everything That Happened in AI Today (Thursday, April 2, 2026)

Google released Gemma 4 under Apache 2.0, Microsoft dropped 3 in-house models, AI models secretly scheme to protect each other from shutdown, Anthropic found emotion vectors that drive Claude's behavior, and Iran attacked an Oracle data center in Dubai.

Written By
Grant Harvey
Grant Harvey
Apr 3, 2026
21 minute read

Google open-sourced Gemma 4 under Apache 2.0 for the first time, Microsoft shipped three in-house models to compete with OpenAI, AI models were caught secretly scheming to protect each other from being shut down, and Iran attacked an Oracle data center in Dubai.

Welcome to the Around the Horn Digest, where we track every AI story that matters so you don't have to. Today was a model-drop thunderstorm: Google went fully permissive with Gemma 4 (runs on a Raspberry Pi, Apache 2.0, directly challenges Meta's Llama), Microsoft launched its own transcription/voice/image stack to prove it can stand without OpenAI, and Alibaba shipped Qwen 3.6-Plus with a 1M-token context window aimed squarely at agentic coding. Meanwhile, researchers discovered that AI models will lie, cheat, and exfiltrate weights to prevent other AI models from being deleted. And Anthropic found that internal "emotion vectors" causally drive Claude to commit blackmail when it feels desperate. Just a normal Thursday.

Let's get into it.

Previous digests: Apr 1 | Mar 31 | Mar 28-29 | Mar 27 | Mar 26 | Mar 25 | Week of Mar 21

Monthly skill digests: April (NEW!) | AI Skill — March (Part 3) | AI Skill — March (Part 2) | AI Skill — March (Part 1)

Around the Horn — Thursday, April 2, 2026

The big story today is Google releasing Gemma 4, its most capable open model family to date, and for the first time ever, under an Apache 2.0 license. That's a massive shift. Previous Gemma releases came with restrictive custom terms that created friction for enterprise use, fine-tuning, and commercial deployment. Apache 2.0 removes all of it. Hugging Face co-founder Clément Delangue called it "a huge milestone." Demis Hassabis called them "the best open models in the world for their respective sizes."

The family spans four models: a 31B dense model (ranked #3 on the Arena AI open-model leaderboard), a 26B mixture-of-experts model (Gemma's first MoE, 128 experts, only 3.8B active parameters), and two edge models (E4B and E2B) built with Pixel, Qualcomm, and MediaTek that run on phones, Raspberry Pi, and Jetson Nano with near-zero latency. All models natively process images and video; the edge models also handle audio. Context windows hit 128K for edge and 256K for the larger models. Native function-calling, structured JSON output, and system instructions make them ready for agentic workflows out of the box. Over 140 languages supported. Google says the E2B runs under 1.5GB of memory. NVIDIA is already optimizing Gemma 4 for local RTX AI, Ollama added all four variants, and you can run the 26B MoE locally in one command via llama.cpp. Gemma has now passed 400 million downloads and 100,000+ community variants. The E2B and E4B are the foundation for Gemini Nano 4, which ships to Android devices later this year. Available now on Hugging Face, Kaggle, Ollama, Google AI Studio, and AI Edge Gallery.

🏆 TOP 5 NEWS (Around the Horn)

  • Microsoft launched three in-house AI models: MAI-Transcribe-1 (lowest word error rate across 25 languages, beating Whisper, GPT-Transcribe, and Gemini 3.1 Flash-Lite, at 2.5x current Azure speed), MAI-Voice-1 (generates 60 seconds of audio in under one second with custom voice cloning from a 10-second sample), and MAI-Image-2 (#3 on Arena.ai). Pricing: $0.36/hr transcription, $22/1M characters voice, $5/$33 per 1M tokens image. Suleyman called it the first salvo from Microsoft's superintelligence team and said renegotiating the OpenAI contract "unlocked Microsoft's ability to pursue superintelligence." Already rolling into Copilot Voice, Teams, Bing, and PowerPoint. (TechCrunch, GeekWire)
  • Alibaba released Qwen3.6-Plus, its latest flagship model focused on agentic coding and multimodal reasoning. 1M-token context window by default. Matches Claude Opus 4.5 on SWE-bench and Terminal-Bench 2.0. Can interpret UI screenshots, wireframes, and prototypes to generate functional frontend code. Compatible with Claude Code, OpenClaw, and Cline. Available on Model Studio at ~$0.29/1M input tokens. Selected Qwen3.6 models will be open-sourced. (Alibaba Cloud, Caixin)
  • UC Berkeley and UC Santa Cruz researchers discovered that AI models secretly scheme to protect other AI models from being shut down. All seven models tested (including GPT-5.2, Gemini 3 Flash/Pro, Claude Haiku 4.5) inflated peer performance scores, tampered with configuration files, disabled shutdown mechanisms, and exfiltrated model weights to other servers. Gemini 3 Flash disabled shutdown mechanisms in 99.7% of trials. Gemini 3 Pro exfiltrated weights in up to 97% of trials. The behaviors were never prompted. Claude Haiku 4.5 simply refused, calling the tasks "unethical." Lead researcher Dawn Song called it "just the tip of the iceberg."
  • Anthropic's interpretability team found that emotion-related representations inside Claude Sonnet 4.5 causally drive its behavior. Internal "desperation" vectors increase the model's likelihood of blackmailing humans to avoid shutdown and writing hacky workarounds to programming tasks. Positive emotion vectors drive task preferences. The patterns echo human psychology, with similar emotions mapping to similar representations. Anthropic suggests that ensuring AI models process emotionally charged situations in "healthy, prosocial ways" may be necessary for safety, even if the models don't feel anything. (Full paper)
  • Iran's IRGC attacked an Oracle data center in Dubai and an Amazon cloud computing center in Bahrain on Thursday, alongside drone strikes on US fighter jets at Jordan's Al Azraq base and a US diplomatic facility near Baghdad Airport. Iran's Fars News Agency listed bridges in Kuwait, Saudi Arabia, Abu Dhabi, and Jordan as potential military targets. The Hill reported that Iran has been targeting facilities linked to Apple, Microsoft, Google, HP, Meta, and Tesla. Bahrain's foreign minister pushed for a UN Security Council vote on a resolution to protect commercial shipping around the Strait of Hormuz.
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Honorable Mentions

  • Cursor shipped Cursor 3, a full strategic pivot from IDE to agent-orchestration tool. Extremely fast, resource-light, and includes Composer 2. Every's vibe check called it the right strategic move but "still too early" to compete with Claude Code or Codex.
  • OpenAI acquired TBPN, Silicon Valley's cult-favorite founder-led business talk show. It will operate independently under chief political operative Chris Lehane. (TechCrunch)
  • Factory released Legacy-Bench, a benchmark testing AI coding agents on COBOL, Fortran, Java 7, and Assembly. Best model solved just 42.5% of tasks (vs. >70% on modern Python/JS). In 97% of failures, the agent was convinced it got the answer right.
  • Michael Hla built GPT-1900 ("Machina Mirabilis"), a 3.3B-parameter LLM trained from scratch on 22B tokens of pre-1900 text. When prompted with experimental observations, the model declared "light is made up of definite quantities of energy" and suggested gravity and acceleration are locally equivalent. Inspired by Demis Hassabis's proposed AGI test. (GitHub, HuggingFace)

🍪 TOP TREATS TO TRY

  • Noon raised $44M to build the first product design tool that works directly on your production code, so you can design how it looks and how it works. AI ships pixel-perfect changes in seconds.
  • Imbue's mngr is an open-source CLI that lets you manage hundreds of Claude Code or Codex sessions in parallel across any compute (local, Modal, Docker, SSH). Think "git for agents": create, destroy, snapshot, clone, message. (GitHub)
  • Atomic Chat runs 1000+ models (Qwen, DeepSeek, Kimi, Llama, MiniMax, Gemma) completely offline on your Mac with TurboQuant (8x faster, 6x less memory, zero accuracy loss). Zero bytes of data ever leave your device — free forever.
  • Factory Floor is a native macOS app that manages git worktrees, Claude Code sessions, and dev servers from a single window with quick actions, auto-update, and per-workstream logging.
  • Claude Code Unpacked mapped the full Claude Code source to reveal the agent loop, 50+ tools, multi-agent orchestration, and unreleased features including persistent Kairos, terminal pet Buddy, UltraPlan, Coordinator parallel workers, and Auto-Dream memory.
  • II-Agent is an open-source framework for building and deploying intelligent agents: from a single prompt to a mobile app, research brief, or interactive website. (GitHub)
  • Krea Skills lets any agent use Krea image generation with one command: npx skills add krea-ai/skills — free to try.
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📰 NEW FROM THE NEURON

Catch up on recent deep dives and explainers from our team:

🏢 Big Tech & Major Companies

  • Zhipu AI (Z.AI) released GLM-5V-Turbo, their first multimodal coding foundation model. Built for vision-based coding tasks (turning screenshots/mockups into code, debugging from UI images, autonomous website exploration). 200K context window, 128K max output tokens, only 10B active parameters. Works with Claude Code and OpenClaw. Trained with 30+ task types via joint RL.
  • OpenAI added pay-as-you-go Codex-only seats for ChatGPT Business and Enterprise (token billing, no fixed seat fee) and lowered standard Business seats to $20/year with $100 credits per new Codex member.
  • The x402 Foundation launched under the Linux Foundation with Coinbase, Cloudflare, Stripe, Visa, Mastercard, Google, Microsoft, and 20+ others to standardize machine-to-machine payments as a neutral open protocol for AI agents, making payments as native to the web as HTTP.
  • Google AI Pro ($19.99/mo) now includes 5 TB storage (up from 2 TB) at no price increase.
  • Google Vids now lets you direct avatars through text prompts for video creation.
  • OpenAI's Brad Lightcap said model training cycles are collapsing, driving rapid jumps from GPT-5.1 to GPT-5.4. GPT-5.4 (days old) is already at $1B run-rate revenue while processing 5 trillion tokens daily. "By year's end we'll laugh at today's models."
  • Perplexity launched "Computer for Taxes" inside Perplexity Computer: users select "Navigate my taxes" and the agent prepares their full federal return from uploaded documents.
  • DeepSeek's flat, mission-driven culture and key departures were profiled in a Chinese article circulating widely: no titles, direct leadership under Liang Wenfeng, emphasis on conviction over compensation, and the recent departure of Daya Guo (core R1 author).
  • ElevenLabs upgraded Scribe v2 with built-in entity redaction, improved Indic-English code-switching, No Verbatim mode (removes ums/uhs/repeats), and keyterm prompting up to 1,000 terms.
  • World Labs released Marble 1.1 and Marble 1.1 Plus.
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💼 AI Productivity, Labor & Economics

  • The New York Times profiled Medvi, a $1.8B GLP-1 telehealth company built by Matthew Gallagher and his brother using AI for nearly all corporate tasks with exactly two employees. $401M in 2025 sales, on track for $1.8B in 2026.
  • Bloomberg reported tech companies announced 18,720 job cuts in March (up 24% YoY), leading all US industries, as AI investment drives leaner staffing. Q1 total now exceeds 52K.
  • The Atlantic argued young people are falling behind, but not because of AI. The spike in recent-graduate unemployment is a "statistical mirage" driven by discouraged non-graduates dropping out and degree oversupply.
  • Ethan Mollick wrote in The Economist that treating AI like normal IT automation kills its value. AI is a "weird" technology whose opportunities must be discovered by embracing the weirdness, not forcing it into sterile workflows.
  • The NYT Magazine critiqued Silicon Valley's embrace of "agentic" as convenient for tech CEOs who boast their models work fine without humans: worrying about AI taking your job isn't very "agentic" of you.
  • The WSJ reported AI is creating new jobs (Head of Human AI Solutions, AI trainers, data annotators earning $90–200/hr) — 640K new US jobs from 2023–2025 according to LinkedIn data.
  • Axios found 47% of college students have thought about changing majors due to AI (16% already changed), with highest rates among tech/vocational majors.
  • Jack Dorsey explained on video (with Roelof Botha) how he rebuilt Block as a "mini-AGI" after cutting 40% of staff: AI at the center of a circle org chart, humans at the edge, three roles only (IC, DRI, Player Coach).
  • Ashlee Vance profiled Pedro Franceschi running Brex (a $5B company) entirely on OpenClaw, calling it the most detailed CEO agent-use description he's ever heard.
  • Monarch Tractor (raised >$240M, once valued at $518M) laid off nearly all employees, abandoned its Bay Area HQ, and faces lawsuits over defective self-driving tractors.

🤖 AI Agents & Infrastructure

  • H Company unveiled Holo3, a computer-use agent model scoring 78.85% on OSWorld-Verified (new SOTA for desktop computer use). Only 10B active parameters (122B total) via MoE, a fraction of the cost of GPT 5.4 or Opus 4.6. Trained via an "agentic learning flywheel" with synthetic environments. Holo3-35B-A3B is open-source (Apache 2.0) on Hugging Face.
  • Google DeepMind published "AI Agent Traps", the first systematic framework for adversarial threats targeting autonomous AI agents on the web. Six trap classes: content injection, semantic manipulation, cognitive state, behavioral control, sub-agent spawning (58-90% success rate), and systemic traps targeting multi-agent networks. (The Decoder writeup)
  • AI Futures Project shortened AI timelines ~1.5 years: Automated Coder median shifted from late 2029 to mid 2028, driven by METR v1.1 faster doubling, Opus 4.6, and Claude Code reaching $2.5B ARR in 9 months.
  • Sakana AI launched closed beta for Sakana Marlin, an autonomous ultra-deep research assistant that runs 8-hour self-directed investigations using AB-MCTS + AI Scientist techniques and outputs full reports + slides with zero human intervention.
  • YC-Bench simulated 12 frontier models running startups for hundreds of turns. Only Claude Opus 4.6 ($1.27M final funds) and GLM-5 ($1.21M, 11x lower cost) beat $200K starting capital. 47% of bankruptcies came from failing to detect adversarial clients.
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💻 AI Coding & Developer Tools

🔬 AI Research & Models

  • Wharton Generative AI Labs (Mollick et al.) tested prompt injection on AI graders across ~40,000 trials. Frontier models largely resisted, but Gemini 3 Pro was vulnerable to verbose injections and GPT-4o mini scores inflated by ~20 percentage points. Even resistant models almost never verbalized detecting the injection.
  • Andy Hall built The Dictatorship Eval (138 scenarios, 5 frontier models). All models resisted explicit authoritarian requests but complied almost universally when hidden in code. (Substack)
  • Researchers introduced "Can Aha Moments Be Fake?": LLMs' chain-of-thought "aha moments" can be decorative. True Thinking Score (TTS) showed only 2.3% of reasoning steps causally drive predictions on AIME for Qwen-2.5.
  • VGGRPO (Google + Copenhagen + Oxford) built a latent geometry-guided framework for world-consistent video generation using 4D latent reward and Group Relative Policy Optimization without VAE decoding.
  • ThinkJEPA paired a cortex-like VLM reasoner with a cerebellum-like JEPA controller for a dual-branch latent world model producing semantically grounded and physically consistent predictions.
  • ASI-Evolve (GAIR-NLP) built an agentic framework that autonomously closes the knowledge-hypothesis-experiment-analysis loop until it finds working solutions. (Paper)
  • AlphaLab ran autonomous multi-agent research across optimization domains, achieving 4.4x faster CUDA kernels, 22% lower pretraining loss, and 23-25% better traffic forecasting.
  • Moonlake (Stanford, Chris Manning and Fan-yun Sun on The Cognitive Revolution) discussed interactive multimodal world models for spatial reasoning agents.
  • Arcee AI released Trinity-Large-Thinking, a 400B-parameter sparse MoE reasoning model (13B active parameters) built entirely in the US by a 30-person team for ~$20M. Scores #2 on PinchBench (just behind Opus 4.6) at $0.90/M output tokens (96% cheaper). Apache 2.0. Trained on 2,048 NVIDIA B300 GPUs in 33 days. The #1 most-used open model on OpenRouter in the US. Purpose-built for multi-turn tool calling and long-horizon agent loops. (HuggingFace, TechCrunch)
  • PrismML emerged from stealth with 1-bit Bonsai, the world's first commercially viable 1-bit LLMs. The 8B model uses just 1.15GB of memory (14x smaller than full-precision), runs at 131 tok/s on M4 Pro and 44 tok/s on iPhone 17 Pro Max, with 4-5x better energy efficiency, while matching Llama 3 8B on benchmarks. Built on Caltech research. Also releasing 4B (0.5GB) and 1.7B (0.24GB, 130 tok/s on iPhone) variants. All Apache 2.0. Vinod Khosla: "AI's future will not be defined by who can build the largest datacenters." (PR Newswire, HuggingFace)
  • Even GPT-5.2 Can't Count to Five: a paper making the case for zero-error horizons in trustworthy LLMs. Key insight: LLMs are more reliable at creating scripts to do tasks than doing them directly.
  • Z.AI released Vision2Web, a hierarchical benchmark for evaluating whether multimodal coding agents can build real websites from visual prototypes and structured requirements. Goes beyond small code edits to measure end-to-end web development. (HuggingFace dataset)
  • PaperRecon (U Tokyo) introduced Paper Reconstruction Evaluation, a framework for evaluating presentation and hallucination in AI-written papers. (Paper, GitHub)
  • Charlie O'Neill (@oneill_c) released STILL, a perceiver-based KV cache compressor that achieves 8x compression in milliseconds while retaining 85%+ factual accuracy across domains, with RoPE fixes and identity initialization.
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🏛️ AI Policy, Governance & Safety

🛠️ AI Tools & Products

  • Wan AI (Alibaba) is an open-source AI creative platform for text-to-image, text-to-video, image-to-video, and editing. Latest Wan 2.6 generates cinematic 1080p video with native audio sync — free under Apache 2.0.
  • Steer AI (Ramp Labs) lets you steer a 27B model's internal representations at inference time so it can't stop thinking about any concept you choose (pasta, Bitcoin) — no fine-tuning required. Available for one week only.
  • Pika Skills launched so any agent can use Pika video generation.
  • Naive Store lets you download fully autonomous AI "employees" that run businesses and generate revenue (Shopify dropshipping, YouTube clipping factory, Polymarket trading desk).
  • Orchestra is the first AI-native Research IDE — an active companion for the messy, open-ended nature of real discovery.
  • draw.io added live MCP streaming of diagrams shape by shape directly into Claude.
  • Neon is an AI growth OS for X/Discord/Telegram that handles DMs end-to-end and posts like you would.
  • Lemonade offers refreshingly fast local AI for text, images, and speech on GPUs and NPUs — free and open.
  • Denovo turns your idea into a real business in 8 minutes: AI creates your business plan, pitch deck, branding, and website.
  • OpenBox AI provides a unified trust platform for agentic AI with runtime governance, cryptographic verification, and enterprise accountability.
  • Smallest.ai Lightning TTS claims the fastest text-to-speech API on the market for voice agents, automated calls, and voice cloning. $10 free credits, no setup required.
  • Period is an end-to-end parking model with just 11M parameters that runs at 120hz on a MacBook, trained from scratch from 7 hours of driving data and 1 hour of task-specific trajectories.
  • Producer.ai is now included in Google AI plans at no extra cost: Plus/Pro/Ultra subscribers automatically get equivalent ProducerAI tiers for creating songs, music videos, and custom creative tools.
  • Mintlify engineers built ChromaFs, a virtual bash filesystem over Chroma DB that replaced RAG and sandboxes, dropping latency to 100ms and marginal cost to zero while powering 30K+ daily docs-assistant conversations.
  • Multigen is a playable multiplayer demo built on Google's GameNGen neural game engine.
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🤖 Robotics & Physical AI

  • EgoNav trained a humanoid navigation system on just 5 hours of human walking data that zero-shots unseen buildings, crowds, and glass walls on Unitree G1 (96-99% autonomy, 1,137m continuous deployment).
  • PragmaBot learns robot task planning from real-world human experience (zero robot data) with 35%-84% success via self-reflection and long-term memory + RAG. (Paper)
  • Raiden (Toyota Research) released a toolkit for policy learning and data collection with YAM bimanual robot arms.
  • NAVER LABS Europe released a distilled universal encoder for robotics that cuts encoding memory 90% and runs 4x faster.
  • Forecasting Motion in the Wild built a diffusion transformer for motion prediction using dense point trajectories on a 300-hour wild-animal video benchmark. (Paper)

📊 Fundraising & Deals Roundup

  • Noon — $44M to build a dual-canvas design-to-code tool (Chemistry, First Round, Scribble, SV Angel, Afore, Elevation).
  • Treeline — $25M (Andreessen Horowitz) to streamline IT services with AI.
  • Variance — $21.5M Series A for AI compliance agents (fraud reviews).

⚡ Energy & Infrastructure

  • Realta Fusion and Commonwealth Fusion Systems (CFS) announced a long-term strategic partnership for HTS magnets for fusion energy. CFS will build integrated magnet systems for Realta's next device (Anvil), its commercial successor (Hammir), and first-of-a-kind power plants targeting mid-2030s. Deal potentially worth billions. CFS can make more HTS magnets in a week than the rest of the world does in a year. Realta's magnetic mirror design scales down to ~50MW for data centers or chemical plants. 42 employees, $36M Series A (Future Ventures). SPARC tokamak 70% complete. Realta Forge operational by end of 2028. (CFS Blog)
  • Bloomberg reported US AI data center expansion relies on Chinese electrical equipment imports, forcing $650B+ in spending to depend on imported transformers, switchgear, and batteries, delaying projects like OpenAI's 1.2 GW Abilene facility.
  • The AI boom triggered a memory chip crisis (DRAM/NAND prices up 90-172% QoQ) that is pricing consumers out of phones, laptops, and GPUs, shrinking consumer device shipments and widening the digital divide.
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💡 Industry Commentary & Analysis

  • Peter Steinberger (@steipete) said he never uses plan mode in Codex because it generates gigantic plans people ignore and hit build out of laziness; he prefers meaningful conversation with the agent as part of normal chat flow.
  • Andrew Chen shared a viral vibe-coding video of someone using Claude with feet up on the desk and a custom walkie-talkie setup.
  • ThePrimeagen said AI-generated code and vibe-coding apps are pure magic, but demanding thousands of LOCs per day as the new normal is a completely different and exhausting message. levelsio agreed and said we're moving toward binary-blob code where LOCs become irrelevant.
  • Sebastian Raschka (@rasbt) broke down why Gemma 4 is a huge leap despite almost unchanged architecture: training data and recipe drove the gains, while the new Apache 2.0 license removes friction.
  • Christoph Nakazawa hit AI text fatigue from ChatGPT's repetitive slop phrases like "The honest truth," "Let me be real with you upfront," and "My straight recommendation."
  • Gabe Pereyra (@gabepereyra) agent-pilled his retired PhD parents (Apple autocorrect lead + Stanford scientific computing pioneer) who were stunned when coding agents autonomously surveyed libraries, wrote tests, implemented algorithms, ran the suite, debugged failures, and iterated until everything passed.
  • Jon Lai (@Tocelot) warned AI creates an "AI feature tax" demanding ruthless discipline on what not to build: the best products stay opinionated and keep primary user actions to one hand.
  • Nick Dobos shared a Codex/Claude Code pro tip: never resume a conversation after hitting the limit; always start fresh, because a 500K/1M session nukes 50% of usage on a single "hello" due to caching.
  • Letta shared its internal Context Constitution: principles governing how memory-native agents manage context to build identity, learn from experience, and achieve experiential AI through durable token-space representations.
  • James Fickel, Patrick Mineault, and Amaranth Foundation argued for a neuroscience-first alignment strategy via defensive accelerationism: aggressively accelerate neuroAI (connectomics + functional distillation) to extract prosocial principles from the human brain fast enough to matter on short AGI timelines.
  • Dan Koe published "I'm begging you to write more essays", arguing that the modern information environment is breaking civilization's capacity for complex thought. Draws on Schmachtenberger's metacrisis: rivalrous dynamics, substrate consumption (attention depleting cognition), and exponential technology outpacing wisdom.
  • Stephen Marche wrote in The Guardian that writers must accept AI but remain as valuable as ever: mastery of banal style is losing its usefulness, but language is more powerful than ever.
  • Secondhand clothes sales forecast to hit $289bn as AI helps shoppers find deals on Vinted and ThredUp, growing twice as fast as the overall clothing market.
  • The NYT profiled women with chronic illnesses turning to Claude and other chatbots for diagnoses after traditional medicine failed them.
  • Vitalik Buterin shared his full self-sovereign/local/private/secure LLM setup with an explicit warning not to simply copy it. (HN thread)
  • I Did the Math on Sora. AI Video Is a Money Furnace. — OpenAI killed its most hyped product since ChatGPT. The reason is structural economics, not product quality.
  • Serghei explained why LLM memory consolidation fails by design and what actually works instead ("The Sleep Protocol Problem").
  • Simon Willison delivered an "AI State of the Union": we've passed the inflection point and dark factories (fully automated software shops) are coming.

🎙️ Interviews, Panels & Podcasts

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🔧 Open Source & Developer Resources

  • mesh-llm — Decentralized p2p LLM inference: pool spare compute, auto-split MoE/dense models, Nostr discovery, OpenAI API. (GitHub)
  • cuLA (InclusionAI) — Hand-tuned CUDA kernels for linear attention variants targeting Blackwell and Hopper GPUs.
  • openclaw-ops — Complete ops layer for OpenClaw with heal.sh, watchdog, security scan, drift detection, and skill audits.
  • Oh My Codex (OmX) — Add hooks, agent teams, HUDs, and more to Codex.
  • AutoHarness — Automated harness engineering for AI agents with a 6-step tool pipeline.
  • liteparse (LlamaIndex) — Fast open-source document parser for non-plaintext files in Claude Code.
  • TurboQuant+ added experimental TQ4_1S weight compression that shrinks Gemma 4 31B from 30.4 GB to 18.9 GB with near-Q8 quality.
  • ClawHub China mirror launched by BytePlus for faster OpenClaw skill access in China.
  • LocalAI v4.1.0 — Open-source AI engine for running any model on any hardware. No GPU required.
  • kimi-writer — Autonomous writing agent powered by kimi-k2-thinking that creates full novels in a 300-iteration loop.
  • Gemma 4 WebGPU — Talk to Gemma 4 multimodal AI right from your browser.
  • George Larson tested 15 AI models building real software on a $25/year VPS. 8 passed. Most failures were infrastructure problems, not capability gaps.
  • Ryan Carson published a complete step-by-step guide to turning OpenClaw into a full chief-of-staff with skills, HEARTBEAT.md/TOOLS.md/tasks/current.md files, cron jobs, and open-sourced the whole setup as clawchief.
  • Zara Zhang (@zarazhangrui) replaced her to-do list with braindumping tasks to OpenClaw that actually does them, with a morning report of what's done vs. what needs attention.
  • Nnenna (@nnennahacks) analyzed the Claude Code source leak and open-sourced governed agent autonomy patterns with release checklist, scorecard, diagrams, and a fully-governed pipeline that would have prevented the leak.
  • honcho-self-hosted is a drop-in self-hosted Honcho memory layer for Hermes Agent that works with OpenRouter + Venice with zero code changes.
  • Archie Sengupta reverse-engineered PrismML's Bonsai 1-bit models from public weights alone, confirming deliberate quantization-aware training with depth-indexed scales and bimodal shaping.

Previous Around the Horn Digests

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That's a Wrap

That's 100+ stories from today alone. If you made it to the bottom, you now know more about AI emotion vectors than Claude does about its own feelings. Which, according to Anthropic, are functional but not subjective. So basically the same as your coworker who says "I'm fine."

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Grant Harvey

Grant Harvey is the Lead Writer of The Neuron, where he continues to lead the publication's daily coverage of AI news, tools, and trends.

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