Wei Jiang

以太坊确实有它值得学习的地方

[Jitendra MALIK @JitendraMalikCV]

We can convert human videos to robot hand-object interaction trajectories in 4D. Enjoy!
Paper: https://t.co/AS0ecvTB9I
Website: https://t.co/KP4dVqxzUb
Code: https://t.co/KfOQTJN8vE
Authors:@bhawna_paliwal_,@HarithejaE,@willjhliang, @pabbeel , @notmahi , @JitendraMalikCV

[Wei Jiang @jwei221]

@zengjiajun_eth Provide trust for agent-agent, agent-human, human-human transaction

[Wei Jiang @jwei221]

ideogram 4.0， 哭了，local ai也是吃上细糠了

[Ideogram @ideogram_ai]

Introducing Ideogram 4.0: the best open image model in the world.

Think it. Make it. Own it.

Download the weights, fine-tune on your own data, and run it on your hardware. Live on every Ideogram plan and the API today.

[Wei Jiang @jwei221]

@BTCBruce1 @0xVeryBigOrange 段永平和tom lee，卧龙凤雏？

[Wei Jiang @jwei221]

@amehochan 所以大家都是蒸馏的A家吗

[Bojie Li @bojie_li]

Closed labs hide model sizes. They can't hide what their models know, and what a model knows is an indicator on how big it is.

Reasoning compresses. Factual knowledge doesn't. So you can size a frontier model from black-box API calls alone, and across releases you can literally watch a single fact arrive in the parameters over time.

For three years, my friends Jiyan He and Zihan Zheng have been asking frontier LLMs the same question: "what do you know about USTC Hackergame?", a CTF contest. May 2024: GPT-4o invented fake titles. Feb 2025: Claude 3.7 Sonnet listed 19 verified 2023 challenges. By April 2026, frontier models recall specific challenges across consecutive years.

After DeepSeek-V4 dropped, I instructed my agent to spend four days autonomously turning that habit into Incompressible Knowledge Probes (IKP) — 1,400 questions, 7 tiers of obscurity, 188 models, 27 vendors. Three findings:

1/ You can approximately size any black-box LLM from factual accuracy alone. Penalized accuracy is log-linear in log(params), R² = 0.917 on 89 open-weight models from 135M to 1.6T params. Project closed APIs onto the curve → GPT-5.5 ~9T, Claude Opus 4.7 ~4T, GPT-5.4 ~2.2T, Claude Sonnet 4.6 ~1.7T, Gemini 2.5 Pro ~1.2T (90% CI: 0.3-3x size).

2/ Citation count and h-index don't predict whether a frontier model recognizes a researcher. Two researchers with similar citation profiles get very different responses. Models memorize impact — work that shaped a field, not many incremental papers.

3/ Factual capacity doesn't compress over time. Across 96 open-weight models across 3 years, the IKP time coefficient is statistically zero, rejecting the Densing-Law prediction of +0.0117/month at p<10⁻¹⁵. Reasoning benchmarks saturate; factual capacity keeps scaling with parameters.

Website: https://t.co/CkwJsXqnsX
Paper: https://t.co/eNUdC9ye7w

[DeepSeek @deepseek_ai]

🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length.

🔹 DeepSeek-V4-Pro: 1.6T total / 49B active params. Performance rivaling the world's top closed-source models.
🔹 DeepSeek-V4-Flash: 284B total / 13B active params. Your fast, efficient, and economical choice.

Try it now at https://t.co/GCdiMzk1Dl via Expert Mode / Instant Mode. API is updated & available today!

📄 Tech Report: https://t.co/drlDrxkYtp
🤗 Open Weights: https://t.co/T13Y8i7SDM

1/n

[Kimi.ai @Kimi_Moonshot]

Meet Kimi K2.6: Advancing Open-Source Coding

🔹Open-source SOTA on HLE w/ tools (54.0), SWE-Bench Pro (58.6), SWE-bench Multilingual (76.7), BrowseComp (83.2), Toolathlon (50.0), Charxiv w/ python(86.7), Math Vision w/ python (93.2)

What's new:
🔹Long-horizon coding - 4,000+ tool calls, over 12 hours of continuous execution, with generalization across languages (Rust, Go, Python) and tasks (frontend, devops, perf optimization).
🔹Motion-rich frontend - Videos in hero sections, WebGL shaders, GSAP + Framer Motion, Three.js 3D.
🔹Agent Swarms, elevated - 300 parallel sub-agents × 4,000 steps per run (up from K2.5's 100 / 1,500). One prompt, 100+ files.
🔹Proactive Agents - K2.6 model powers OpenClaw, Hermes Agent, etc for 24/7 autonomous ops.
🔹Claw Groups (research preview) - bring your own agents, command your friends', bots & humans in the loop.
-
K2.6 is now live on https://t.co/YutVbwktG0 in chat mode and agent mode.
For production-grade coding, pair K2.6 with Kimi Code: https://t.co/uvoSJKyGCY
-
🔗 API: https://t.co/EOZkbOwCN4
🔗 Tech blog: https://t.co/9wWvgIQSS3
🔗 Weights & code: https://t.co/Be0hjs2RTP

[CoW DAO @CoWSwap]

https://t.co/iLRNm5N7WT

[MrNeRF @janusch_patas]

Driving Gaussians has become nuts!

[Wei Jiang @jwei221]

！！！

[MiniMax (official) @MiniMax_AI]

We're delighted to announce that MiniMax M2.7 is now officially open source.
With SOTA performance in SWE-Pro (56.22%) and Terminal Bench 2 (57.0%).

You can find it on Hugging Face now. Enjoy!🤗
huggingface：https://t.co/ApWrahIl3o
Blog: https://t.co/gAxeFsNdW4
MiniMax API: https://t.co/1dgbMx0Q7K

[MiniMax (official) @MiniMax_AI]

We're delighted to announce that MiniMax M2.7 is now officially open source.
With SOTA performance in SWE-Pro (56.22%) and Terminal Bench 2 (57.0%).

You can find it on Hugging Face now. Enjoy!🤗
huggingface：https://t.co/ApWrahIl3o
Blog: https://t.co/gAxeFsNdW4
MiniMax API: https://t.co/1dgbMx0Q7K

[Wei Jiang @jwei221]

Thank you

[Z.ai @Zai_org]

Introducing GLM-5.1: The Next Level of Open Source

- Top-Tier Performance: #1 in open source and #3 globally across SWE-Bench Pro, Terminal-Bench, and NL2Repo.
- Built for Long-Horizon Tasks: Runs autonomously for 8 hours, refining strategies through thousands of iterations.

Blog: https://t.co/hmyDe4Nel3
Weights: https://t.co/CuUjXcPKJD
API: https://t.co/fz6reja4fb
Coding Plan: https://t.co/Nk8Y98HNhU

Coming to https://t.co/WCqWT0qCQb in the next few days.

[Z.ai @Zai_org]

Introducing GLM-5.1: The Next Level of Open Source

- Top-Tier Performance: #1 in open source and #3 globally across SWE-Bench Pro, Terminal-Bench, and NL2Repo.
- Built for Long-Horizon Tasks: Runs autonomously for 8 hours, refining strategies through thousands of iterations.

Blog: https://t.co/hmyDe4Nel3
Weights: https://t.co/CuUjXcPKJD
API: https://t.co/fz6reja4fb
Coding Plan: https://t.co/Nk8Y98HNhU

Coming to https://t.co/WCqWT0qCQb in the next few days.

[Wei Jiang @jwei221]

@DLKFZWilliam2 没错，但是没有真人去拍摄这一段原始视频，模型也学不出这个效果。模型会bake in了运镜知识，也bake in了所有现代成像技术的特征，模型永远反应真实世界的distribution。

[Wei Jiang @jwei221]

@Alex_perception 10PT...这么大的数据量被拖库了没警报？

[Wei Jiang @jwei221]

@JeffNylen @alexocheema @nateberkopec prompt caching

[Wei Jiang @jwei221]

@rayoo_eth @ethvisionorg 然而segwit软分叉之后，老客户端直接无法解析segwit transaction，从而导致social上的硬分叉。
你见过那条拒绝了所有segwit transaction的联吗？

[Yoav HaCohen @yoavhacohen]

🚀 Today we’re releasing LTX-2.3 with open weights + training code, alongside the API, LTX Studio, and LTX-Desktop - a full-featured video editing app that runs on your local GPU.

Audio+video generation just leveled up:
quality + capabilities + tooling - all open-source.
🧵👇