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.
Most people seem obsessed with token generation speed, but isn’t prefill the real bottleneck? Am I missing something?
For agentic workflows and large contexts, prefill speed (how fast the model 'reads' the prompt) is a bigger bottleneck than generation speed.
A technical discussion on r/LocalLLaMA highlights that while benchmarks prioritize generation speed (tokens/s), the prefill stage is the actual bottleneck for many advanced users. Prefill is the initial phase where the model processes the input prompt before generating the first token. For agentic workflows involving large codebases or long RAG contexts, waiting for the model to 'ingest' data takes significantly longer than reading the output. The author notes that even 15 t/s generation is acceptable, but slow prefill (e.g., 300 t/s on a Qwen 27B) creates noticeable lag. This suggests that hardware and software optimizations should prioritize prompt processing for professional, high-context use cases.
r/LocalLLaMA·opinion·05/06/2026, 08:02 PM·/u/wbulot
DeepSeek V4 AI Beats Billion Dollar Systems…For Free
DeepSeek V4 is a powerful new open-source AI model that reportedly outperforms expensive commercial systems, offering advanced capabilities for free.
DeepSeek has released its new AI model, DeepSeek V4, which is being highlighted for its impressive performance. The model reportedly surpasses the capabilities of much larger and more expensive "billion-dollar" proprietary systems, yet it is available for free. This release signifies a notable advancement in the open-source LLM landscape, potentially democratizing access to high-tier AI capabilities. For creative non-developers and hobbyists, this means access to a powerful tool without significant financial investment, pushing the boundaries of what's achievable with freely available AI.
Two Minute Papers·model_release·05/06/2026, 04:07 PM·Two Minute Papers▶Watch here
Qwen 3.6 27B MTP on v100 32GB: 54 t/s
Multi-Token Prediction (MTP) nearly doubles inference speed for Qwen 3.6 27B on older V100 hardware, making it a highly viable local coding assistant.
A user report demonstrates a significant performance boost for Qwen 3.6 27B using Multi-Token Prediction (MTP) on a Tesla V100 32GB GPU. By utilizing a specific MTP branch of llama.cpp, inference speeds jumped from approximately 30 t/s to 54 t/s, nearly doubling the output rate. The setup utilized a q8_0 KV cache and supported a 200k context limit, effectively serving as a high-speed VS Code Copilot replacement. While performance dipped slightly to 40-45 t/s at higher context depths (50k+ tokens), the model remained highly effective for complex tasks like tool calls and code refactoring. This highlights the potential of MTP to extend the lifecycle of older enterprise hardware for modern local LLM workloads.
r/LocalLLaMA·tooling·05/06/2026, 02:18 AM·/u/m94301
Relevance auto-scored by LLM (0–10). List shows top 30 from the last 7 days.