Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor. It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx
Dagens Vibes — 7. juni 2026
Dagens feed siger én ting ret højt: AI-arbejde flytter sig fra “hjælp mig med koden” til “byg maskinen, der bygger maskinen”. Resten er distribution, tokenregninger og lidt agent-desktop-feber. Helt normalt søndag morgen på internettet.
Fra X-feedet
Anthropic lægger recursive self-improvement på bordet. Ikke som sci-fi-lir, men som organisationsdata: mere Claude-skrevet kode, længere autonome tasks og et reelt spørgsmål om hvem der styrer AI-udviklingen, når AI’en selv begynder at accelerere den.
Today, Anthropic engineers on average ship 8x as much code per quarter as they did compared to 2021-2025. https://t.co/QCc9cqGgf4

Anthropics fulde gennemgang: 8× kode-output per engineer, 80%+ Claude-attribueret produktionskode og en konkret argumentation for verificerbar pause/slowdown.
Anthropic Institutehttps://www.anthropic.com/institute/recursive-self-improvementOpen-weight-ugen var absurd tæt pakket. Victor M’s liste er næsten for lang til daglig morgenkaffe: Nemotron, Gemma, StepFun, Liquid, JetBrains, Ideogram m.fl. Frontier-følelsen siver ned i modeller, man faktisk kan køre og rode med.
Before the week ends, let's acknowledge one of the most INSANE week ever for open AI, with 25+ notable open-weight drops across every modality: 🧠 LLMs → NVIDIA Nemotron 3 Ultra: 550B hybrid Mamba-MoE, only 55B active, 1M context, MMLU 89.1. NVFP4 variant claims ~5x throughput on Blackwell. First openly-weighted 550B hybrid Mamba-Transformer, closing the gap with frontier closed models. → Google Gemma 4 12B: fully open dense any-to-any (text/image/audio/video), 256k context, encoder-free, 140+ languages, AIME 2026 at 77.5. Shipped with a 23-checkpoint QAT wave (mobile ONNX + MLX). Most deployable model of the week. → StepFun Step-3.7-Flash: 198B sparse MoE VLM, ~11B active, SWE-Bench PRO 56.3. Apache 2.0. → Liquid AI LFM2.5-8B-A1B: edge MoE, just 1.5B active, 128k ctx, MATH500 88.8, MLX-ready. Best on-device option this week. → JetBrains Mellum2-12B-A2.5B-Thinking: their first open MoE, near-Qwen3-14B coding at 2.5B active. Apache 2.0. 🎨 Image gen (the surprise of the week) → Ideogram 4: their FIRST-EVER open weights. 9.3B flow-matching DiT trained from scratch. #2 overall behind GPT Image 2, top open-weight model on Design Arena + LMArena. Strongest open checkpoint for text-rich images, full stop. It has taste. Still can't believe this is open weights. 🔊 Audio & Speech (a breakout week for open TTS, 4 labs shipped) → Boson Higgs Audio v3 4B: 102 languages, 21 emotions, singing/whispering/shouting, sub-second TTFA. → RedNote dots.tts: the only fully continuous (no codec) open TTS pipeline, Apache 2.0. → Google Magenta RealTime 2: real-time music gen, <200ms latency, text+audio+MIDI. multimodalart ported it to PyTorch within hours with live ZeroGPU demos. → NVIDIA Nemotron-3.5 ASR: 600M streaming, 17x more concurrent streams vs Parakeet RNNT 1.1B. 👁️ Vision & VLMs → PaddleOCR-VL-1.6: SOTA document parsing at 1B params, Apache 2.0. → Baidu NAVA: 6.3B joint audio-video gen, best-in-class A/V sync, Apache 2.0. 🎬 Video, 3D & World Models → NVIDIA Cosmos3-Super: 64B omnimodal world model coupling action trajectories with video+audio gen, for Physical AI. → JD JoyAI-Echo: up to 5-min multi-shot text-to-video on LTX-2.3. → ByteDance Bernini-R + VAST TripoSplat (single-image-to-3D Gaussian splats, MIT).
Distribution er stadig det kedelige monster under sengen. AI gør det billigere at bygge apps; den gør ikke magisk brugere billigere. Levelsio/Gergely-tråden rammer meget godt: output op, adoption flad, marketing-helvede intakt.
I think the challenge is that everyone can now build apps But 1) almost nobody has distribution (like an audience), or 2) the money to pay for distribution (ads or UGC), or 3) the creative genius to get distribution for free (classically called guerilla marketing)
Agent-desktoppen bliver dagens arbejdsform. Hermes/Codex/Claude-laget handler mindre om “chatbot” og mere om sessions, profiler, lokale filer og agenter der kører ved siden af dig. Altså: multitasking, men nu med flere små robotter at babysitte.
The most comprehensive Hermes Desktop tutorial on the internet NOW is LIVE. You'll learn sessions, profiles, artifacts, cost savings, and real use cases for making money and building startups with Hermes agents. Whether you're already running Hermes or haven't started yet, this is the episode for you. @AlexFinn says this is the moment Hermes overtakes OpenClaw. S/o to Alex for walking me through it. "It's now the best way to use AI agents on your computer" I do think the desktop app of Hermes looks almost like an Apple product. Everything you need to know about Hermes Desktop App/agents in 43 minutes This episode is 100% free. No ads. @startupideaspod I just want to see you win on the internet. And I think Hermes can help. Plus, It's fun thing to play with this weekend. Share this with a friend. Link below. YT: https://t.co/O4Ih4K87SQ Watch
Tokenøkonomi bliver produktarkitektur. Aaron Levie peger på model routing som næste enterprise-disciplin: brug frontier dér hvor det betaler sig, billigere modeller alle andre steder. CFO’en er kommet ind i prompten.
Token costs are becoming one of the hottest topics for any enterprise I talk with right now. It’s very bullish for AI in general because it means these systems are being used at a scale that wasn’t contemplated before. It also gives way to another form of differentiation that will emerge for the applied AI layer, which is model routing. As tokens take on a significant amount of the cost of any given workflow, then companies will inevitably want to ensure that their dollars go into the most efficient use of tokens for the particular job at hand. Frontier intelligence will always be relevant at the high end of tasks, like coding, legal and financial analysis, healthcare, and more. And dollars spent here will only go up over time. But, equally, you can peel off individual tasks to lower cost models (whether they’re from open weights vendors or the major labs) and deliver a more efficient end outcome. To do this effectively, the applied AI layer needs to understand the workflows in their domain better than anyone else, and be able to mix and match models to different jobs. If you’re doing document extraction, you need to know which models perform better or worse for any given document type. If you’re legal analysis, you want to know which models perform various types of tasks best. And so on. This will become one of the bigger differentiation points over time. The companies with the best evals, the best ability to route the workloads, and those that have business models directly aligned to customers financial goals, will be in a great position.
Simon fandt en lovende Python-sandbox: MicroPython i WASM. Det er den slags lille byggeklods, der kan blive vigtig i agentprodukter: kør kode, men uden at give den nøglerne til kælderen.
I may have finally found the Python-in-a-sandbox solution I've been looking for... here's my latest experiment, this time running MicroPython in WebAssembly inside my Python applications https://t.co/aANOEGX3MI
Alpha-pakke på PyPI, wasmtime, memory/fuel limits og Datasette Agent-plugin. Vibe-coded sandbox, men med åbne øjne.
Simon Willisonhttps://simonwillison.net/2026/Jun/6/micropython-in-a-sandbox/Model-rygterne bobler: Claude Mythos 5 og GPT-5.6. Tag det som X-signal, ikke sandhedstavle. Men feedet lugter af release-uge, og TestingCatalog har i hvert fald fundet en Mythos 5-slug.
BREAKING 🔥: A new Claude Mythos 5 model slug has been spotted via Dev Mode. Claude Mythos is planned to be released as its own model class, besides Haiku, Sonnet and Opus model families. Soon? 👀 https://t.co/1QCfYkbp2r

Bonusønske fra dev-hjernen: Google Docs, men for Markdown-filer. Multiplayer comments, suggestion mode, historik og CLI. Nogen burde bygge det. Alle har allerede 11 ufærdige versioner.
I need Google Docs but just for markdown files. Multiplayer comments. Syncing resolving comments. Suggestion mode Edit mode Edit history Maybe some sense of multi edits. Easy cli access.
Nyhedsbonus
Google køber bridge-compute hos SpaceX. TechCrunch skriver, at Google skal betale SpaceX 920 mio. dollar om måneden for ca. 110.000 NVIDIA-GPU’er fra oktober. Compute som geopolitik, bare med faktura.
Aftalen ligner Anthropics Colossus-leje og handler om at dække uventet høj efterspørgsel på Gemini Enterprise-agentplatformen.
TechCrunchhttps://techcrunch.com/2026/06/05/google-will-pay-spacex-920m-per-month-for-compute/