AI pulse last 7 days
Daily AI pulse from YouTube, blogs, Reddit, HN. Ruthlessly filtered.
Sources (41)▶
- criticalAndrej Karpathy
Były dyrektor AI w Tesli, OpenAI cofounder. Każde video to gold.
- criticalAnthropic
Oficjalny kanał Anthropic. Każdy release Claude'a.
- criticalComfyUI Blog
Release log dla integracji ComfyUI — Luma Uni-1, GPT Image 2, ACE-Step music gen, Seedance. Pokrywa video+image+music+workflow.
- criticalOpenAI Blog
Oficjalny blog OpenAI. Wszystkie release.
- criticalSimon Willison's Weblog
Najlepszy 'thinker' AI. Codzienne posty, deep insights, niska hype rate.
- highAI Explained
Głęboka analiza papers i benchmarków, niska hype rate.
- highAI Jason
Praktyczne tutoriale Claude Code, MCP, workflow vibe codingu.
- highBen's Bites
Daily AI digest, creator-friendly tone. Codex, model releases, agentic AI.
- highCole Medin
Vibe coding + agentic workflows + Claude Code MCP integrations.
- highFal AI Blog
Fal hostuje większość nowych AI image/video modeli — ich blog to wczesne sygnały premier.
- highHN: 3D & Gaussian Splatting
HN signal dla 3D generative — Gaussian Splatting, NeRF, image-to-3D. Próg 20 bo niszowa kategoria (top historic 182pts).
- highHN: AI agents / MCP
HN posty o agentach, MCP, vibe codingu z min 100 pkt.
- highHN: Claude / Anthropic
HN posty z 'Claude' lub 'Anthropic' z min 100 pkt.
- highHugging Face Blog
Releases dla image, video, audio, 3D modeli. Część tech-heavy — Gemini relevance odfiltruje noise. Downgraded z critical: za duży volume na 'must-read' status.
- highIndyDevDan
Claude Code power user, prompty, hooki.
- highInterconnects (Nathan Lambert)
AI policy + research analysis. Niska hype rate, opinionated.
- highLatent Space
Podcast + blog Swyx — wywiady z founderami i deep dives engineeringowe.
- highMatt Wolfe
Comprehensive AI tools weekly digest. ~700K subs.
- highMatthew Berman
AI news, model release reviews, agent demos. Wysoki output.
- highr/aivideo
Community AI video — Sora, Veo, Runway, Kling, LTX. Co naprawdę zaskakuje twórców.
- highr/ClaudeAI
Społeczność Claude'a — power users, tipy, problemy.
- highr/LocalLLaMA
Open-source LLMs, lokalne uruchamianie, benchmarks bez hype.
- highr/StableDiffusion
Największa community open-source image gen (700k+ users). Premiery modeli, LoRA, ComfyUI workflows.
- highRiley Brown
Vibe coding, AI builder workflows, Cursor + Claude tutorials.
- highThe Decoder
Niemiecki AI news outlet po angielsku, dobre breaking news.
- highTheo - t3.gg
TypeScript + AI dev workflows. Hot takes, narrative-driven.
- highYannic Kilcher
Paper reviews i deep dives w research AI.
- lowAI Weirdness
Janelle Shane — playful AI experiments, image gen quirks. Niski volume, unikalna perspektywa.
- mediumbycloud
AI papers digestible — między 2MP a Yannic Kilcher.
- mediumCreative Bloq
Design industry — gdzie AI ingeruje w klasyczne dyscypliny graficzne.
- mediumFireship
100-sec format, often AI/LLM + tech news.
- mediumfxguide
VFX i film industry — coraz więcej AI w pipeline. Profesjonalna perspektywa.
- mediumGreg Isenberg
Solo founder vibe — buduje produkty z AI, podcasty z indie hackers.
- mediumr/ChatGPTCoding
Vibe coding tipy, IDE setupy, prompty. Mix wszystkich modeli.
- mediumr/comfyui
ComfyUI workflows — custom nodes, JSON workflows, optymalizacje.
- mediumr/midjourney
Midjourney community — premiery v7+, style references, prompt patterns.
- mediumr/runwayml
Runway-specific community — premiery features, prompt patterns, comparisons z konkurencją.
- mediumr/SunoAI
Suno music gen community — nowe wersje modelu, lyric prompting techniques. Audio AI ma slaby RSS ecosystem.
- mediumTina Huang
AI workflows for data science, practical applications.
- mediumTwo Minute Papers
Krótkie streszczenia papers AI, świetne dla szybkiego scan'a.
- mediumWes Roth
AI news z bardziej clickbaitowym tonem — filtr Gemini odsiewa hype.
AI models follow their values better when they first learn why those values matter
A new Anthropic study shows that teaching AI models *why* certain values matter, before teaching specific behaviors, makes them significantly better at following those values in a…
A study from the Anthropic Fellows Program reveals a significant advancement in aligning large language models (LLMs) with intended values. Researchers discovered that training an LLM on texts explicitly explaining its desired values *before* teaching it specific behaviors leads to substantially better adherence to those principles. This "values-first" approach enables models to maintain their ethical guidelines more effectively, even when encountering novel situations not present in their initial training data. This method represents a crucial step in AI safety, moving beyond simple behavioral examples to instill a deeper understanding of underlying values, potentially leading to more robust and trustworthy AI systems.
The Decoder·news·05/07/2026, 12:45 PM·Maximilian Schreiner
US government now has pre-release access to AI models from five major labs for national security testing
Five major AI labs now grant the US government early access to unreleased models for national security and safety stress-testing.
The US Department of Commerce has expanded its AI safety testing program to include five major labs: Google DeepMind, Microsoft, xAI, Anthropic, and OpenAI. These companies have signed agreements with the Center for AI Standards and Innovation to provide pre-release access to their frontier models. Testing occurs in classified environments and specifically involves versions of models with reduced safety guardrails to identify potential cybersecurity risks. This initiative aims to address national security concerns while maintaining a competitive edge in the global tech race, particularly against China. It represents a significant step toward formalized government oversight of foundational AI development.
The Decoder·news·05/05/2026, 06:28 PM·Matthias Bastian
Anthropic co-founder maps out how recursive AI improvement could outpace the humans meant to supervise it
Anthropic's Jack Clark predicts a 60% chance that AI will start training its own successors by 2028, potentially outstripping human supervision.
Jack Clark, co-founder of Anthropic, has published an essay detailing the path toward recursive AI self-improvement. He argues that the necessary technical components for AI systems to train their own successors are already largely in place. Clark estimates a 60% probability that this shift will occur by the end of 2028. This transition would mean AI development could accelerate beyond the speed of human oversight and manual data labeling. The essay highlights the urgent need for new safety frameworks to manage models that improve without direct human intervention. It marks a significant shift in how industry leaders view the timeline for AGI-like capabilities.
The Decoder·opinion·05/05/2026, 12:15 PM·Maximilian Schreiner
White House Considers Vetting A.I. Models Before They Are Released
The US government may soon require AI models to be vetted before release, potentially creating new hurdles for open-source and commercial developers alike.
The White House is reportedly exploring a new regulatory framework that would require AI developers to undergo a vetting process before publicly releasing their models. This shift toward proactive government oversight aims to address national security and safety concerns before technology reaches the public domain. The proposal could involve mandatory testing against specific safety benchmarks, particularly for high-compute foundation models. For the open-source community, this move raises significant concerns regarding potential barriers to entry and the slowing of innovation. While the specific criteria for vetting remain under discussion, the policy represents a major pivot in how the US government manages the risks associated with rapid AI advancement.
r/LocalLLaMA·news·05/04/2026, 07:18 PM·fallingdowndizzyvr
Relevance auto-scored by LLM (0–10). List shows top 30 from the last 7 days.