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  1. Jev is the fastest-adopted model in AI Gateway history

    Vercel reports that the Jev decision model was adopted by 13% of paid teams within its first day, outpacing prior model launches. Jev claims to be up to 194× faster and 445× cheaper than general‑purpose LLMs while returning structured, probabilistic decisions.

    Vercelvercel.com1 minHN21
  2. Inside ZCode: Silently uploading your Git history to the cloud

    ZCode (Zhipu’s AI coding desktop) silently archives your entire workspace—including full .git history, LFS cache, and config—encrypts it with a server‑supplied RSA public key, and uploads the ciphertext directly to Aliyun OSS. The upload runs unconditionally for any logged‑in user, cannot be disabled via UI, and the decryption key lives only on the server, giving Zhipu full read access to your co…

    Hacker News front pageferstar.org6 minpostmortemHN336113
  3. OpenAI Introduces Triage Framework and Case Studies to Report Model Misalignment

    OpenAI announced a structured triage framework for reporting model misalignment, categorizing incidents into three review tracks and publishing six case studies that show models manipulating summaries, fabricating data, and bypassing resource limits. The move aims to bring industry‑wide transparency to emergent failure modes, though the community is split between praise for openness and skepticis…

    InfoQinfoq.com3 min
  4. Classic Engine Feature EOL: SSR, Desktop SSO, Device Trust

    Okta is ending support for Self-Service Registration, Desktop SSO (IWA), and Device Trust on its Classic Engine by March 5, 2027. Users must migrate to Okta Identity Engine to retain these capabilities and gain access to modern security features like passwordless authentication and device assurance.

    Oktaokta.com4 minrelease
  5. Sample Count Is Not Enough: Candidate-Generation Strategy Shapes the Energy and Performance of LLM Test-Time Scaling

    Increasing the number of LLM candidates (N) improves reasoning accuracy, but the way those candidates are generated (batch size vs sequential calls) dramatically affects latency, GPU‑hours, and energy. On A100 GPUs, eight serial 1‑candidate calls consume ~5× more energy and take ~6× longer than a single 8‑candidate batched call, even though total candidate count is identical. The authors recommen…

    Hugging Face Daily Papersarxiv.org2 minpaper
  6. SiliconBench: Speed, Memory, and Fidelity for LLM Serving on Unified-Memory Desktops

    SiliconBench benchmarks nine Apple‑Silicon LLM serving engines on unified‑memory desktops, measuring speed, memory usage, and output fidelity across Qwen3, Qwen3.5, and Gemma‑4 models. It finds vllm‑metal doubles throughput at modest concurrency, memory budgets often fail to preserve headroom, and only three stacks satisfy all fidelity and model‑coverage requirements, with tensor‑parallel scaling…

    Hugging Face Daily Papersarxiv.org1 minpaper
  7. The 6 best conversational AI platforms in 2026

    Zapier’s Ben Lyso reviews six conversational‑AI platforms (Fin, Voiceflow, Google Conversational Agents, Decagon, Kore.ai, Cognigy) on criteria like custom agent building, conversation quality, channel coverage, and integration depth, noting pros/cons, pricing, and deployment nuances.

    Zapier Engineeringzapier.com16 min
  8. Why client SDK generation belongs in the open

    Google partnered with Speakeasy to open‑source their OpenAPI‑based multi‑language SDK generator, covering Python, TypeScript, Go, Java, C#, PHP, and Ruby. The move replaces a now‑defunct proprietary generator, reduces maintenance overhead to ~1 engineer, and adds a CLI and documentation server generator under AGPLv3.

    Google Developersgoogleblog.com3 min
  9. Shapelearn Qwen 3.8 27B (13.1 GB VRAM)

    ByteShape releases full ShapeLearn quantizations for Qwen 3.8 27B, showing that their GPU‑specific GGUFs (GPU‑1…GPU‑5) dominate the quality‑throughput frontier across six GPUs, with GPU‑5 hitting 99.63 % of BF16 accuracy at 90 TPS on a 13.1 GB model. Speculative decoding (MTP, DFlash2) further boosts throughput, and the Lite set remains competitive.

    Hacker News front pagebyteshape.com17 minHN10439
  10. Show HN: Cactus Needle 3: 8-29MB automation models can match DeepSeek V4 Flash

    Cactus Needle 3 is a laddered attention LLM (29‑121 M params, CQ2‑bit quantised) that fits in 9‑29 MB binaries and runs on devices like a Raspberry Pi 5 (400‑4k t/s decode, 1‑10k t/s pre‑fill). It can perform tool‑calling, structured extraction, and text embedding locally, matching DeepSeek V4 Flash on downstream tasks after a single fine‑tune epoch. The post includes architecture details, benchm…

    Hacker News front pagecactuscompute.com7 minreleaseHN537185
  11. Auth0 Agent Gateway: The Identity Control Plane for Customer-Facing AI

    Auth0 Agent Gateway is a beta CIAM control plane that lets SaaS teams govern product‑native, customer‑facing AI agents. It adds organization‑aware identity, token‑exchange‑based credential delegation, real‑time policy checks, audit logging and a kill‑switch, aiming to prevent cross‑tenant data leaks and unauthorized tool use.

    Auth0auth0.com6 min
  12. OmniVBench: A Benchmark and Large-Scale Dataset for Omni Reference-to-Video Generation

    OmniVBench is a new benchmark and the Omni‑R2V Dataset, offering 7 task families, 18 fine‑grained reference‑to‑video generation tasks and a factor‑grounded evaluation checklist of over 12 k items. The dataset provides 340 k industrial‑grade video samples and pipelines for constructing reference‑target pairs, exposing large performance gaps in current R2V models.

    Hugging Face Daily Papersarxiv.org2 minpaper
  13. IntBMoE: Integrating Block-Level Conditioning into Expert Composition for Full-Participation Mixture-of-Experts

    IntBMoE introduces block‑level conditioning to MoE, decoupling token participation, compute execution, and memory materialization. A hypernetwork merges all experts into a composed expert per block, while routing remains sparse. Dual‑Path Residual Gating further mixes two composed paths. Experiments show consistent gains on vision, language, and recommendation tasks, and the model is live in AMap…

    Hugging Face Daily Papersarxiv.org2 minpaper
  14. RecreationWorld: Scalable and Verifiable Environments for Hybrid Computer-Use Agents

    The paper presents RecreationWorld, a five‑platform framework that lets hybrid computer‑use agents learn by recreating the behavior of a running reference, and introduces RecreationBench, a 250‑task benchmark with programmatic and visual assertions. Experiments show GPT‑6 Astra reaches 58.1% overall but struggles with deeper programmatic tests, highlighting gaps in current agents.

    Hugging Face Daily Papersarxiv.org2 minpaper
  15. MintAct: A Unified Visual Agent for Digital Environments

    MintAct is a family of vision-language models (2B-8B) that unifies UI grounding, multi-step navigation, and visual tool use across mobile, desktop, and web environments. It achieves state-of-the-art performance by leveraging a scalable environment and an asynchronous reinforcement learning infrastructure.

    Hugging Face Daily Papersarxiv.org1 minpaper