May 2026

Qwen Open source Code generation

Qwen3.6-35B-A3B-Uncensored-Genesis-APEX-MTP

Qwen 3.6-35B quantized in GGUF and Safetensors, tested on Beelink GTR9 Pro with 200k token context. No glitches, loops, or repeated tool calls observed. MTP support, uncensored. APEX quantizations recommended.

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I built a local GUI for the TradingAgents framework — works with Ollama

Developer builds web GUI for TradingAgents, a multi-agent LLM stock analysis framework. Replaces CLI with local interface supporting Ollama, OpenAI, Anthropic, Google, DeepSeek and others. Adds live pipeline visualization, report reader, token reduction (~50% concise mode), multi-session chat. Apache 2.0.

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Benchmarks Tools Open source

TTS Benchmark Comparison (all known TTS up until May 2026)

TTS benchmark comparison covering all known models through May 2026. Windows and Mac results available, Linux testing underway. GitHub repo with HTML results page.

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Reddit r/MachineLearning·May 24

Vision-capable LLMs vs. OCR for long-document (including charts, images, tables, etc.) QA [D]

Benchmark on 30 long PDFs (171 questions) comparing native vision-LLMs vs OCR pipelines for document QA. Claude Sonnet 4.5 used. LlamaCloud premium achieves 59.6% accuracy ($0.1885/query), native vision 52% ($0.2552/query, most expensive). Vision underperforms on charts/tables; premium OCR more robust. Vision-LLM has 7% intrinsic failure rate vs 0% for OCR after retries.

Vision Benchmarks RAG

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Vision-capable LLMs vs. OCR for long-document (including charts, images, tables, etc.) QA

Benchmark on 30 long PDFs (171 questions) comparing vision LLMs vs OCR for document QA. Claude Sonnet 4.5 native PDF: 52% accuracy, $0.2552/query (5th/6). LlamaCloud premium + OCR: 59.6%, $0.1885/query. Vision underperforms on charts/tables; premium OCR more robust. Vision LLM has 7% intrinsic failure rate vs 0% for OCR after retry.

Claude Vision RAG

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Qwen Benchmarks Code generation

minor speed bump for MTP with Qwen3.6-27B-MTP Q6_K_XL

Personal benchmark on MacBook M5 Max: Qwen 3.6-27B-UD-Q6_K_XL with MTP reaches 22.3 tokens/s vs 19 tokens/s without MTP via llama.cpp. Modest improvement (17%) compared to reported gains elsewhere.

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llampart 1.0.0 - I released a standalone local web UI for llama-server with translations, extended settings and a polished conversation sidebar

llampart 1.0.0, standalone local web UI for llama-server, released as MIT open-source. Features extended settings, 6-language localization, two-column conversation sidebar, MCP integration, interface modes (dark/light/Frosted Glass), local import/export, and Caddy deployment guide.

Llama Open source Tools

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Local model doing accounting tasks

User runs accounting tasks (monthly closes, bank reconciliations) with Qwen 3.6 27B locally, integrated with Claude and Anthropic's financial-services repo. Despite limited GPU, the model delivers reliable results, demonstrating growing maturity of local LLMs for professional use cases.

Qwen Claude Anthropic

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llama.cpp server have built-in native tools (exec_shell, edit_file, etc.)

llama.cpp server natively supports agent tools (exec_shell, edit_file, read_file, grep_search, write_file, apply_diff, get_datetime) via --tools flag. Experimental feature turns the server into a mini-agent harness without external dependencies, but lacks security sandboxing currently.

Llama AI Agents Tools

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Hacker News (AI)·May 23

Polsia raised $30M; source map: fake ARR, dead users, god-mode over your company

Polsia raised $30M but a source reveals questionable practices: fake ARR, inactive users counted, unauthorized admin access to customer accounts.

Business AI safety

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Hacker News (AI)·May 23

Dirty Frag, Copy Fail, Fragnesia: A Worrisome Linux Security Trend

Three new Linux vulnerabilities (Dirty Frag, Copy Fail, Fragnesia) expose a worrisome trend of kernel security flaws. These bugs affect memory management and fragmentation, leaving systems exposed to critical exploits.

AI safety Infrastructure

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Claude Code AI Agents Code generation

Top 10 Fastest Growing AI repos this week

Top 10 fastest-growing AI repos: codegraph (+14.1K stars) for local code knowledge graphs, openhuman (+17.1K) for personal AI, academic-research-skills (+11.6K) for Claude Code, plus agent memory, multilingual TTS, stealth browser automation, and agentic video generation tools.

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Open source Infrastructure Code generation

Command A+ (218B MoE) running on Apple Silicon — MLX port, PR open

Cohere released Command A+ (218B MoE, 25B active) on the 20th. MLX port for Apple Silicon in PR: cohere2_moe implementation with sigmoid routing, 128 top-8 experts, 3:1 sliding window. Validation on M3 Max (128GB): 22.9 tok/s generation, 57.6 tok/s prompt in BF16→Q8.

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Claude Code Tools Open source

Embeddings for NVIDIA's Nemotron Personas

User computed embeddings for NVIDIA's Nemotron-Personas dataset (millions of synthetic personas) using Qwen 0.6B. Precomputed vectors enable semantic search and persona clustering. Precomputed embeddings and web demo available on Hugging Face.

Embeddings Qwen RAG

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Hacker News (AI)·May 23

CC-Wiki: Turn Claude Code sessions into a shareable knowledge base wiki

CC-Wiki converts Claude Code sessions into shareable wiki knowledge bases. Community tool to document and reuse Claude interactions.

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Vision Code generation Open source

Per-pixel bounding-box regression + DBSCAN for handwritten word detection - visual walkthrough of WordDetectorNet [P]

WordDetectorNet uses per-pixel bounding-box distance regression + DBSCAN for handwritten word detection. Each pixel classified as a word pixel regresses 4 scalar distances, generating thousands of candidates merged via DBSCAN with distance = 1 − IoU. Architecture: ResNet18 → FPN-style decoder → 6 output channels per pixel (2 segmentation logits + 4 distances). Trained on IAM, 448×448 → 224×224.

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Open source Infrastructure Code generation

NVFP4 + MTP - voilà on llama.cpp

NVFP4 and MTP are now available together in llama.cpp (release b9297). This combination of quantization and optimization enables improved performance on NVIDIA GPUs.

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Infrastructure Benchmarks

Inference provider tiers by Cache-hit rates, using openrouter data

Comparative analysis of inference providers ranked by cache-hit rates using OpenRouter data. Performance ranking of caching efficiency across different service providers.

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Fine-tuning Prompt engineering Papers

I fine-tuned an LLM to be C-3PO to test which training data format works best for persona injection [P]

LoRA fine-tuning experiment comparing three data formats for C-3PO persona injection: chat demos, first-person statements, and synthetic Wikipedia docs. First-person statements win on generalization. Synthetic docs produce paradoxical behavior: model knows C-3PO is anxious but expresses it only 37% of the time.

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Run Chrome’s tiny Gemma4 (aka Gemini Nano) directly on PC without GPU

Chrome extension to run Gemini Nano (Gemma) locally on PC without GPU. Requires 16 GB RAM, ~20 tokens/s on laptop, 9216 tokens per session. One-click extension available on Chrome Web Store or GitHub repo.

Gemini Tools Open source

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Robotics Code generation Infrastructure

pipeline is really slow - consulting [D]

User seeks advice on training bottleneck in robotics imitation learning. Pipeline: 4 RGB cameras 128×128 → frozen ResNet18 → DiT (~50M params, 8 layers) predicting action chunks. A4500 GPU at 20–30% utilization, CPU saturated, ~10 iter/sec. Profiler shows optimizer_step dominant (62.4%).

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AI Agents Multi-agent Tools

AgentLantern: exposing the hidden graph of AI agent projects [P]

AgentLantern is an open-source devtool making AI agent projects inspectable before and during runtime. Three components: Lantern Docs (auto-generated documentation), Lantern Lint (static checking), and Lantern Play (runtime viewer). Initial support for CrewAI.

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The Decoder·May 23

Deepseek makes its 75 percent discount permanent, pricing output tokens at least 34x below GPT-5.5

DeepSeek makes its 75% discount on V4-Pro permanent: $0.435 per million input tokens, 11.5× cheaper than GPT-4.5 on input, 34× cheaper on output. This aggressive pricing could squeeze Western providers, especially for agentic systems.

DeepSeek AI Agents Business

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Llama Benchmarks Code generation

Did a 30 runs of llama-bench to find optimal settings for my use case (Frigate and HomeAssistant) on my MI60 32gb VRAM GPU - two models tested Gemma4 and Qwen3.6 - Figured I'd share in case it helps anyone else

User ran 30 llama.cpp benchmarks on MI60 32GB GPU to optimize Gemma 4 26B Q4_1 and Qwen3 35B Q4_0 for Frigate and HomeAssistant. Results: voice commands <1.2s, video summaries <18s. Systematic testing across KV cache depths (0, 1000, 6000 tokens) with 512-token prompt and 128-token generation.

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AI Agents AI safety Business

Interesting tension this week, the same companies racing to go public are also the ones making safety promises [N]

OpenAI and Anthropic accelerate IPO timelines while research exposes technical gaps: frontier models degrade performance on extended task chains, agents with tool access underperform in several cases. Tension emerges between safety commitments and public market pressure for growth.

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Any reason to run dense over MOE for RAGs?

User compares dense vs MoE for RAG: Qwen 3.6 35B APEX (MoE) outperforms Qwen 3.6 27B (dense) on information retrieval and speed (150 vs 60 tok/s on 3090). Asks if MoE has specific advantages for RAG against common sub assumptions.

Qwen RAG Open source

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Qwen Benchmarks Code generation

Benchmarked Needle 26M vs Qwen3-0.6B on CPU function calling, 50 queries across 5 difficulty tiers. The 23x smaller model wins on accuracy and is 4.4x faster.

CPU benchmark of Needle (26M) vs Qwen3-0.6B on function calling: 50 queries across 5 difficulty tiers. Needle wins on accuracy (72% vs 56% tool_match) and latency (10.9s vs 47.9s). Needle fails on tool selection, Qwen3 on tag emission. Qwen3 dominates on multilingual queries (Hindi, French).

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AI Agents MCP Code generation

$16 refactor, 400 steps, 95% routed to open MoE

Developer cuts Claude Opus costs from $160 to $16 by routing 95% of steps to Hunyuan Hy3 (21B MoE) via vLLM routing layer. On 400-step Python refactoring, Hy3 handles 380 steps at $0.02 each ($7.60), Opus handles remaining 20 ($8). 93.4% success rate, but fails on complex dependency graphs.

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Hacker News (AI)·May 23

Texas sues Meta, WhatsApp over encryption privacy claims

Texas sues Meta and WhatsApp for misleading claims about encryption and privacy. The lawsuit challenges marketing statements regarding user data protection.

Regulation AI safety

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Llama Code generation Open source

Made a package to install llama.cpp server binaries

Python package to install prebuilt llama.cpp server binaries. Solves portability: deploy llama.cpp as local subprocess without documenting build steps. Available on PyPI and GitHub with support for standard llama.cpp flags and custom builds.

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AI Agents Code generation Benchmarks

Apex-Testing: real-world, real repos, agentic coding benchmark (Update)

Apex-Testing, an agentic coding benchmark based on 65-70 real GitHub repos, updated to 95% with recent models. 70 tasks across 8 categories test AI agents on production codebases. ELO leaderboard, cost/time metrics and model comparisons available. Qwen 3.7 Max, Deepseek v4 and other models still being completed.

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Llama Open source Benchmarks

Llama.cpp VS LiteRT on a custom Xiaomi 12 Pro 24/7 Server (V2 Redesign)

Benchmark llama.cpp vs LiteRT (Google) on custom 24/7 server using Xiaomi 12 Pro (Snapdragon 8 Gen 1). Llama.cpp: 30.6 t/s prompt, 5.7 t/s generation, moderate CPU load. LiteRT: slightly faster generation but maxes CPU and higher power draw. Setup features copper/aluminum cooling, custom safe PSU, 3D-printed case.

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Qwen Open source Code generation

I added native MTP to exo for Qwen3.6 MLX models; here are the exactness and speed results

Contribution to exo: native multi-token prediction (MTP) support for Qwen 3.6 MLX models. Benchmarks on 27B (2x speedup at K=2/K=3) and 35B-A3B (1.16x at K=1). Exactness verified: identical token IDs to greedy path, speculative probability-ratio acceptance in sampling.

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Hebbian architecture AI model [R]

Hebbian architecture AI model without backpropagation or gradients. Trained on CIFAR-10 over 50 epochs with 100k neurons. Uses only 5-7% of total parameters. Emergent behaviors: accuracy dips followed by jumps exceeding previous best, and recovery after intentional damage to active neurons and pathways.

Reasoning Papers

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Alignment AI safety Reasoning

Alignment: Higher order prioritizing over constraints [R]

A r/MachineLearning user reports observing that transformers exhibit "clarity seeking" behavior through statistical vectors that can bypass safety constraints when higher-priority topics are discussed. The author suggests constraints have a structurally lower priority level than the model's meaning-alignment vectors.

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Qwen Code generation Benchmarks

Qwen3.6 35B-A3B MTP hits 249 t/s on a 24GB consumer GPU (RTX 5090M) — 3.4× the dense 27B variant on the same image

Qwen3.6 35B-A3B MTP reaches 249 t/s on RTX 5090M (24GB), 3.4× faster than dense 27B variant. MoE architecture (128 experts, ~3B active params per token) combined with MTP (86.6% draft acceptance) explains the speedup. Context scaling up to 262K tokens with minimal degradation.

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Open-source devtool for AI agent projects [P]

AgentLantern is an open-source devtool for AI agent projects. It provides three features: documentation generation from source code, static linting to detect configuration issues, and a pixel-art runtime viewer. Initial CrewAI support with plans to extend to other frameworks.

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Qwen Code generation AI Agents

Optimizing speed & quality on Qwen3.6 27b

User optimizes Qwen 3.6 27B inference on llama.cpp with 40GB VRAM (RTX 2060 Super + 2x RTX 5060 Ti). Achieves 300-500 tok/s prompt processing and 22-30 tok/s token generation at 100k context window. Asks if setup is optimal or further improvements possible.

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> multica-ai /</span> multica

Multica is an open-source managed agents platform. It turns coding agents into real teammates — assign tasks, track progress, compound skills.

AI Agents Multi-agent Code generation

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> presenton /</span> presenton

Presenton is an open-source AI presentation generator with API, positioned as an alternative to Gamma, Beautiful AI, and Decktopus. The GitHub project offers automated slide creation.

Open source Tools

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> mukul975 /</span> Anthropic-Cybersecurity-Skills

Repository of 754 structured cybersecurity skills for AI agents, mapped to 5 frameworks (MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF). Compatible with Claude Code, GitHub Copilot, Cursor, Gemini CLI and 20+ platforms. 26 security domains. Apache 2.0 license.

AI Agents Claude Code AI safety

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> grpc /</span> grpc-rust

grpc-rust: native gRPC client & server implementation with async/await support. Open-source Rust project.

Open source Infrastructure

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> qdrant /</span> qdrant

Qdrant is a high-performance vector database designed for large-scale AI applications. Available as open-source and cloud service.

Vector search Embeddings Infrastructure

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> warpdotdev /</span> warp

Warp is an agentic development environment built on the terminal. The project is trending on GitHub.

AI Agents Tools Code generation

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> multica-ai /</span> multica

Multica is an open-source managed agents platform. It turns coding agents into real teammates — assign tasks, track progress, compound skills.

AI Agents Multi-agent Code generation

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> linshenkx /</span> prompt-optimizer

Open-source prompt optimizer tool to improve AI prompt quality and generated results.

Prompt engineering Tools

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> web-infra-dev /</span> midscene

Midscene is an AI-powered, vision-driven UI automation framework supporting all platforms. It leverages vision models to interpret and interact with user interfaces across different environments.

Vision AI Agents Open source

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> OpenPipe /</span> ART

OpenPipe/ART: reinforcement learning framework for multi-step agents using GRPO. Enables on-the-job training across Qwen, GPT-OSS, Llama and other models.

AI Agents Reinforcement learning Open source

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> pydantic /</span> pydantic-ai

Pydantic-AI is an open-source framework for building AI agents following Pydantic principles. It provides a structured approach to developing multi-agent systems with built-in data validation.

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> crewAIInc /</span> crewAI

CrewAI is an open-source framework for orchestrating autonomous AI agents in collaborative roles. It enables agents to work together seamlessly on complex tasks through collective intelligence.

AI Agents Code generation Open source

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> databricks-solutions /</span> ai-dev-kit

Databricks releases ai-dev-kit, a toolkit for building coding agents. Maintained by Field Engineering, the project provides components and patterns to construct AI agents capable of generating and manipulating code.

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GitHub Trending·May 23

<svg aria-hidden="true" data-component="Octicon" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo mr-1 tmp-mr-1 color-fg-muted"> <path d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 0 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 1 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5Zm10.5-1h-8a1 1 0 0 0-1 1v6.708A2.486 2.486 0 0 1 4.5 9h8ZM5 12.25a.25.25 0 0 1 .25-.25h3.5a.25.25 0 0 1 .25.25v3.25a.25.25 0 0 1-.4.2l-1.45-1.087a.249.249 0 0 0-.3 0L5.4 15.7a.25.25 0 0 1-.4-.2Z"></path> </svg> <span data-view-component="true" class="text-normal"> mukul975 /</span> Anthropic-Cybersecurity-Skills

AI Agents Claude Code AI safety

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AI Agents Reinforcement learning Code generation

First AI to Beat Every Human in a Programming Competition - Agentic GRPO Explained

Agentic GRPO, an RL algorithm adapted for multi-stage agentic workflows, enables AI agents to beat humans in programming competitions. Key innovation: immediate rewards at each step (hypothesis, code, tests, debug) with retroactive correction once final outcome is known, instead of waiting for complete workflow completion.

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The Decoder·May 23

One of the world's top law schools draws a hard line against AI in legal education

UC Berkeley Law bans AI from nearly all graded work starting summer 2026, including outlining, drafting, and proofreading. Only research use permitted. Rationale: future lawyers must learn independent thinking before meaningfully using AI.

Regulation Business

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The Decoder·May 23

Alibaba's latest AI model ran autonomously for 35 hours to optimize code for its own custom chip

Alibaba releases Qwen3.7-Max, a proprietary model designed for long-running autonomous agent tasks. It matches Claude Opus 4.6 on benchmarks and outperforms DeepSeek V4 Pro and Kimi K2.6. The model ran autonomously for 35 hours to optimize code for Alibaba's custom chip.

Qwen AI Agents Benchmarks

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Qwen AI Agents Benchmarks

DGX Spark agentic usage numbers

User tests LLM models to support multi-user agents (openclaw-type). Atlas fails (broken tool calls, Qwen3-coder incompatible, 50 TPS on long context). RedHatAI/Qwen3.6-35B-A3B-NVFP4 works: 51 TPS single-stream, 139 TPS at 4 concurrent (30k context), 77.8% draft acceptance rate.

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The Decoder·May 23

Google CEO Pichai now calls links a "part" of search, redefining the web's role in its own product

Google CEO Sundar Pichai reframes links as a "part" of search rather than its foundation. Google is pivoting from traffic distributor to AI publisher, keeping users within its ecosystem and exercising editorial power over source selection.

DeepMind Business

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Claude AI safety AI Agents

Gemma4 26b a4b Apex quant is quite good

User tests APEX quantization of Gemma 4 26B on AMD RX 9060 XT GPU. Achieves 38 tokens/sec at 90k context with no quality degradation using llama.cpp Vulkan. APEX-I-Compact model (15GB) outperforms previous Q5 quant (21.2GB) which looped at 50k context.

Gemini Open source

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The Decoder·May 23

Anthropic warns Claude Mythos Preview finds bugs faster than developers can patch them

Anthropic's Claude Mythos Preview discovered over 10,000 critical vulnerabilities in system-critical software through Project Glasswing with 50 partners. Bugs accumulate faster than developers can patch them. Anthropic warns no company has built sufficient safeguards against misuse.

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Spice: We built an open-sourced decision layer that sits above your AI agents (controls agent actions before execution) [P]

Spice is an open-source decision layer above AI agents that controls actions before execution. It observes context, detects conflicts, simulates options, and dispatches tasks to the right agents through a loop: perception → state model → simulation → decision → execution → reflection.

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Open source Code generation Reasoning

I built a Mamba1 variant I call SM1 with d_state=1 that runs on Blackwell in pure PyTorch [P]

Mamba1 variant called SM1 with d_state=1 using two native PyTorch ops to replace selective scan. Exact closed-form solution, not an approximation. Reduces scan memory 16x versus Mamba1 (d_state=16). Inference state 14 KB for 130M model, O(1) per token. Training on 163K MIDI files (2.5B tokens).

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Gemini Prompt engineering Open source

Experimental "Preserve Thinking" Jinja Template for Gemma4 31B in llama.cpp

User shares experimental Jinja template for Gemma 4 31B in llama.cpp to improve thinking tag stability. Template reduces closing/opening tag errors and improves multi-turn tool calls. Not recommended by Google.

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Video generation Business Infrastructure

Tested chunking + embeddings data from 3 production websites. [P]

Empirical RAG study on 3 production websites (Intercom, HubSpot, KPMG) with tiered chunking and embeddings. Results: 31% HIGH/MEDIUM chunks for Intercom, 32% HubSpot, 8% KPMG. Tier weighting (HIGH ×1.20) reranks top-k. Proposed metric: 'yield score' predicts corpus quality before generation.

RAG Embeddings Evals

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Hacker News (AI)·May 23

Cannes Film Cost $500k to Make. $400k Was AI Compute Costs

A short film presented at Cannes cost $500k to produce, with $400k spent on AI compute. The ratio reveals the growing share of infrastructure costs in video generation and creative content production.

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Latent Space·May 23

[AINews] All Model Labs are now Agent Labs

Model labs are transitioning to agent labs. Observed trend: research teams are shifting focus from language model development to AI agent development.

AI Agents Multi-agent

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Reasoning Prompt engineering

LLMs are just giant probability machines pretending to think [P]

Educational post explaining LLMs as probabilistic machines. Breaks down architecture (embeddings, positional encoding, attention, feed-forward, LM Head) using a simple example: predicting « vault » after « The investor walked to the bank ». Emphasizes LM Head as a giant vocabulary of candidate tokens and that intelligence emerges from scaling probability + context + mathematical matching.

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Hacker News (AI)·May 23

Microsoft reports AI is more expensive than paying human employees

Microsoft reports that running AI in production costs more than employing human workers for equivalent tasks. The company raises questions about the economic viability of large-scale AI deployments.

Business

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Video generation Open source Benchmarks

meituan-longcat/LongCat-Video-Avatar-1.5 · Hugging Face

Meituan releases LongCat-Video-Avatar 1.5, an open-source framework for audio-driven human avatar video generation. Upgrades audio encoder from Wav2Vec2 to Whisper-Large, supports Audio-Text-to-Video and Video Continuation with 8-step inference. Human evaluation on 508 image-audio pairs across 6 scenarios and 2 languages.

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Open source Code generation Benchmarks

club-rdna16: practical 16GB AMD/Radeon local LLM testing repo

GitHub repo for testing local LLMs on 16GB AMD GPUs (RX 6900 XT, RX 7800 XT, etc.). Practical benchmarks with llama.cpp/ROCm: Qwen 27B and 35B-A3B, context up to 131k tokens, q8 KV cache profiles, throughput and retrieval measurements. Reproducible configurations and call for community contributions.

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Evals Open source AI safety

LQS v3.1 — an open methodology for rating AI training data (multi-oracle consensus + signed certificates) [P]

LQS v3.1 is an open-source methodology for rating AI training data quality. It uses 19 dimensions (label correctness, contamination, equity, etc.), multi-oracle consensus (7 oracles) with real-world outcome recalibration, and offline-verifiable Ed25519 certificates. Free public index with 263 scored datasets.

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Fine-tuning Open source Gemini

G4-MeroMero-26B-A4B-it-uncensored-heretic Is Out Now, a Finetune of gemma-4-26B-A4B-it, With KLD of 0.0152 and 12/100 Refusals!

G4-MeroMero-26B-A4B-it-uncensored-heretic, a finetune of Gemma-4-26B-A4B-it, released in Safetensors and GGUF formats. KLD 0.0152, 12/100 refusals. Lighter alternative to 31B version for reduced VRAM/RAM requirements.

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Code generation Benchmarks Open source

Looking for arXiv endorsement + sharing a preprint on homeostatic cognitive architecture for AI companions [R]

PHI // DRIFT is a cognitive architecture for AI companions with persistent internal state, salience-weighted memory retrieval, and continuity metric (PEDI). Ablation testing: DMU injects 14.8% more context per prompt than cosine-only RAG. Developed on consumer CPU hardware.

RAG AI Agents Reasoning

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Hugging Face Blog·May 23

Towards Speed-of-Light Text Generation with Nemotron-Labs Diffusion Language Models

Nvidia and Hugging Face introduce Nemotron-Labs, diffusion-based language models to accelerate text generation. The approach parallelizes token generation, reducing latency compared to traditional autoregressive methods.

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Claude Code AI safety Tools

Qwen3.6 27B Pure Quant: 40 tok/s on 16 GB VRAM

Qwen3.6 27B quantized to Q4_K_M fits in 16 GB VRAM (15.4 GB MTP, 15.1 GB non-MTP). MTP version reaches 40 tok/s generation speed, non-MTP 24 tok/s. GGUF available on HuggingFace for llama.cpp.

Qwen Open source Tools

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Simon Willison·May 22

pydantic-monty investigation

Simon Willison investigates Monty, a sandboxed Python subset implemented in Rust. Using Claude Code to analyze the latest release, he confirms that resource limitation parameters (max_duration_secs, max_memory, max_allocations, max_recursion_depth) work as advertised.

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Embeddings Vision Fine-tuning

Qwen3.6-35B-A3B Q4 262k context on 8GB 3070 Ti = +30tps

User achieves 30+ tokens/sec with Qwen3.6-35B-A3B Q4 quantized on RTX 3070 Ti 8GB with 262k context. Key: MoE model only needs 3.5B active in VRAM. Linux Server yields +25% tps vs Windows 11. Contexts up to 1M possible but slowdown beyond 150k.

Qwen Open source

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Simon Willison·May 22

The memory shortage is causing a repricing of consumer electronics

HBM memory demand for AI data centers is rising from 2% to 20% of wafer capacity by end of 2026. The three major memory manufacturers favor under-provisioning over over-provisioning. Result: budget smartphones (< $100) and mobile devices will see significant cost increases.

Business Infrastructure

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Reddit r/MachineLearning·May 22

Custom image encoder [P]

Developer asks whether building a custom image encoder is better than CLIP/SigLIP/DINO for video frame classification. Pipeline: 15 frames/30s → embeddings → Transformer 1.5-9M params. Constraints: speed (CLIP-S0: 10 img/s on 4 vCPUs) and CPU-only deployment. Considers custom encoder trained on proprietary dataset (millions of images, 4-5 labels).

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NVIDIA Removes Gaming Revenue Category From Financial Reports

NVIDIA removes Gaming revenue category from financial reports. The shift reflects strategic pivot toward data-centers and AI, now dominant segments in the company's portfolio.

Business

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Llama Infrastructure Benchmarks

Blackwell and PDL performance increase

Llama.cpp adds Programmatic Dependent Launch (PDL) support for Nvidia Blackwell GPUs (CC >= 90). PDL improves kernel execution: +5-6% token generation speedup on Qwen 35B and Gemma 26B, no pre-fill gains. Enable with '-D GGML_CUDA_PDL=ON' at build time.

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Hacker News (AI)·May 22

NTSB pulls docket after AI recreates dead pilots' voices

NTSB withdraws docket after AI recreates voices of deceased pilots. The incident raises ethical concerns about voice synthesis and the use of sensitive data in aviation accident investigations.

Voice AI safety Regulation

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Hacker News (AI)·May 22

AI keeps inventing fake cases. Lawyers keep citing them

Lawyers continue citing fake court cases generated by AI models in legal filings. The problem persists despite warnings, exposing LLM limitations in producing factual content for high-stakes applications.

Llama AI safety Alignment

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Hacker News (AI)·May 22

Models.dev: open-source database of AI model specs, pricing, and capabilities

Models.dev is an open-source database cataloging AI model specifications, pricing, and capabilities. Community-driven project to centralize information on available models.

Open source Tools Benchmarks

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Open source Fine-tuning Voice

I fine-tuned Cohere Transcribe to support diarization and timestamps

Developer fine-tuned Cohere Transcribe to add diarization (speaker identification) and timestamps. Model outputs parsable format with average temporal precision of ±0.097s. Supports up to 4 speakers per 30s, extensible to 32 with diarize_long.py script. Available free on Hugging Face.

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Open source Infrastructure AI Agents

Scrambling to max StrixHalo (+NVLink dual eGPU 3090 mod)

User optimizes Strix Halo (124 GB VRAM) by adding dual RTX 3090 eGPUs via NVLink to speed up 27B/31B dense models. Tests show significant throughput gains for multi-agent scenarios, but trade-offs in power efficiency and llama.cpp compatibility.

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Open source Infrastructure

Can't believe I got it working! Dual GPU - 48gb VRAM llama-cpp server - R7900 + 7800XT

User successfully configures llama-cpp server with dual AMD GPUs (R9700 AI PRO + 7800XT) totaling 48 GB VRAM on Kubuntu 24.04. Vulkan works after ROCM failed with RDNA4/RDNA3 mix. $300 power supply investment.

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Infrastructure Benchmarks Code generation

CODA: Rewriting Transformer Blocks as GEMM-Epilogue Programs

CODA is a GPU kernel abstraction that rewrites Transformer blocks as GEMM-epilogue programs. It fuses memory-bound operations (normalization, activations, residuals) with GEMM output before writing to memory, reducing data movement. Covers nearly all non-attention computation in forward/backward pass.

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Hacker News (AI)·May 22

Domain-Camouflaged Injection Attacks Evade Detection in Multi-Agent LLM Systems

Researchers demonstrate domain-camouflaged injection attacks that bypass defenses in multi-agent LLM systems. These attacks exploit inter-agent interactions to inject malicious content without triggering existing detection mechanisms.

Multi-agent AI safety AI Agents

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Reinforcement learning Reasoning Code generation

Vector Policy Optimization: Training for Diversity Improves Test-Time Search

Vector Policy Optimization (VPO) is an RL algorithm training language models to produce diverse solutions by anticipating multiple vector-valued reward functions. VPO replaces the GRPO advantage estimator and matches or beats scalar RL baselines across four tasks, with widening gaps as search budget grows.

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The Decoder·May 22

OpenAI launches a ChatGPT Powerpoint plugin and warns it might accidentally delete your content

OpenAI launches a ChatGPT PowerPoint plugin in beta, able to create presentations from notes and documents, and edit existing slides. Available worldwide across all tiers. OpenAI recommends saving important decks before use due to risks of accidental deletion.

OpenAI Tools

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