Victoria X Lin @VictoriaLinML
MTS @thinkymachines | Native Multimodal Intelligence Prev: @AIatMeta @SFResearch • PhD @uwcse victorialin.org San Francisco Bay Area Joined December 2010-
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The 2026 Perseid Meteor Shower at Stonehenge tonight ☄️🔥✨Photo Credit Nick Bull 🙏
🧡 Love seeing the open-source spirit spread to robotics and embodied AI development!
We have a huge news to share today! Today we are unveiling the first truly accessible RL robot - welcome Microduck A 25 cm tiny open-source biped with 15 actuators and packed with sensors (camera, speaker, LiDAR, NFC, bluetooth, wifi, etc) that you train yourself with
🪄 We invite you to try Inkling’s agentic performance on OpenRouter
We want to improve Inkling’s agentic performance. To help us understand its real-world behavior, we are making it available for free on OpenRouter (only with agentic harnesses) for the next few weeks, starting now. We’ll use the data, disassociated from accounts, to better it.
Tomorrow will be my last day at Google after 27 years, and watching it grow from 25 people to 190,000+ has been an amazing journey. Below is a note I shared with many people internally at Google today. An excerpt is: It has been an absolute pleasure to work with you and to help build some of the most widely used and impactful products of all time. As a kid, I dreamed of helping build software that would be used by many people, and Google now has thirteen products used by more than a billion people (amazing!). Our work has had a tremendous impact in the world, and I have been lucky enough to collaborate and form friendships with many colleagues that I deeply admire, respect, and enjoy. It still brings me joy every time I see people out in the world using our products to find information, handle email, translate documents, watch videos, learn new things, navigate and understand the physical world, browse the web, use their phone, run large-scale computations on our infrastructure, ride in an autonomous vehicle, or perform complex tasks with the help of our AI systems. I hope you all share this sense of joy, because it is a shared accomplishment! Thank you to all of my colleagues at Google over many years! Now I'm excited to go start @DiscoLoopAI with my longtime friends and colleagues @Sanjay_Ghemawat, @OriolVinyalsML, and @quocleix. (Updated post: slightly redacted to not have some personal info)
@zhngjn805444524 Looking forward to what you find out: tinker.thinkingmachines.ai/playground
Inkling is a 975B-41B(A) MoE model that natively reasons across modalities (text, images and audio). It is intelligent and versatile🌱. I’ve had so much fun building it alongside an incredible team over the past few months and proud to openly share this work.
Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. thinkingmachines.ai/news/introduci… Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
Inkling-Small is comparable to Inkling at a quarter the size. Weights are open, fine-tunable on Tinker today. Look forward to seeing what people make with it.
Today, we are releasing Inkling-Small. Inkling-Small achieves comparable performance to Inkling at a quarter of its size. It features 276B total parameters, 12B active. We are making the full weights available. thinkingmachines.ai/news/inkling-s… Fine-tune it on Tinker today, or chat with
Another open-weight release from @thinkymachines 👀 Inkling-Small is here. With native reasoning over audio and images and variable thinking effort, it's a great choice for fine-tuning, with NVIDIA NeMo on NVIDIA DGX Station. NVFP4 checkpoint here: huggingface.co/thinkingmachin…
Today, we are releasing Inkling-Small. Inkling-Small achieves comparable performance to Inkling at a quarter of its size. It features 276B total parameters, 12B active. We are making the full weights available. thinkingmachines.ai/news/inkling-s… Fine-tune it on Tinker today, or chat with
Today, we are releasing Inkling-Small. Inkling-Small achieves comparable performance to Inkling at a quarter of its size. It features 276B total parameters, 12B active. We are making the full weights available. thinkingmachines.ai/news/inkling-s… Fine-tune it on Tinker today, or chat with it in text, image, and audio on Tinker Playground.
Presenting my grand unified theory of ML researcher impact: Your impact is directly proportional to how much pain you cause to infra. Fundamentally, you can only inflict pain upon infra if your approach actually works. And the better your approach works the more pain infra is forced to endure. So, to give some examples: - MoE's add a ton of data-dependent computation => pain (shazeer++) - GDN/KDA are the most complex architecture I've been forced to care about and a very annoying matrix inversion => pain (sonta++) - Muon is much more annoying than Adam and causes annoying restrictions on parallelism => pain (keller/jeremy++) - RL scaling forced many researchers to care about LLM inference and RL infra as a category => pain (tworek++) Even papers like Attention Is All You Need have lead to significant pain! Before transformers were invented everyone was running small jobs and I never needed to think about kv-caches or 6D parallelism.
Fun fact: I'm responsible of editing the limitations part, and this final line was written by Zhilin himself.
from Moonshot's own blog post: "Despite being a highly competitive model overall, K3 nonetheless exhibits a noticeable gap in user experience compared with Claude Fable 5 and GPT 5.6 Sol"
Inkling is very good at using tools to solve vision tasks. In this demo, Inkling relies solely on Python tools to generate segmentation masks, iteratively zooming in, cropping, and refining object boundaries. Plug Inkling into your multimodal agent workflow! huggingface.co/thinkingmachin…
Excited to share Inkling, our first open weight model, multimodal by design and strong performance across a broad range of tasks!
The progress has been extremely fast. Most of all, I am happy to be surrounded by good people on a critical mission. Please hold us to your highest standards and share your feedback as you get to know Inkling!
Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. thinkingmachines.ai/news/introduci… Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
Meet Inkling, our open-weights model built to reason across words, images, sound, and tasks. I'm too tired to find the words, so I'll let Inkling speak for me.
Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. thinkingmachines.ai/news/introduci… Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
Honored to be in the agentic efforts in Inkling. I felt those sleepless nights were well-spent. Inkling is just a checkpoint of our progress for the foundation model effort started this January. This is just a preview, and the best is yet to come. ✨
Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. thinkingmachines.ai/news/introduci… Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
Training Inkling was a lot of fun, we hope tinkering with it is too!
Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. thinkingmachines.ai/news/introduci… Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. thinkingmachines.ai/news/introduci… Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
new post on harness engineering for AI self-improvement: lilianweng.github.io/posts/2026-07-… It is hard to forecast how much the future of RSI will rely on harnesses. Likely harness engineering will evolve in the direction of self-improvement and enable auto-research, and, in turn, smarter models keeps harnesses simple. Even when many harness improvement get eventually internalized into core model, the need to specify goals and context will not disappear.
AK @_akhaliq
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Sam Bowman @sleepinyourhat
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Victor Zhong @hllo_wrld
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1K Followers 5K Following 🎓DPhil @UniofOxford @OxPrimaryCare 🤖AI/ML • RL • HcAI • Digital Health 🎗Member @R_S_P_H 💼Affiliations: @Apple @ChariteBerlin @HPI_health @WHO
David Adekunle Ijeoma... @Lightning_1986
720 Followers 7K Following I was born in Britain, & of Nigerian descendant. I am a Game Designer, Affiliate Marketer, Lottery, & Network Marketer. https://t.co/8re1RyvHrG
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Horace He @cHHillee
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Jikun Cai @Eric_Cai828
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Eric Kaplan @eric_kaplan_nyc
473 Followers 3K Following Investor at @BessemerVP | Previously growth & product @ridewithvia | Seinfeld enthusiast
Yann LeCun @ylecun
1.3M Followers 798 Following Founder/Chair, AMI Labs; Professor, NYU; Partner, 224 Ventures; Ex-Chief AI Scientist, Meta. Researcher in AI, ML, Robotics, etc. ACM Turing Award Laureate.
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Percy Liang @percyliang
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Jim Fan @DrJimFan
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Yi Tay @YiTayML
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Kyunghyun Cho @kchonyc
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Graham Neubig @gneubig
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Richard Socher @RichardSocher
124K Followers 1K Following Building self-improving superintelligence CEO @recursive_si and @youdotcom MP @aixventuresHQ Ex: Stanford Adj Prof, Chief Scientist at Salesforce, CEO MetaMind
William Wang @WilliamWangNLP
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Jacob Andreas @jacobandreas
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Yoav Artzi @yoavartzi
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Sewon Min @sewon__min
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Neil Chowdhury @ChowdhuryNeil
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Gautam Kamath @thegautamkamath
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Alexander Terenin @avt_im
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Derek Xu @derekzxu
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Lijie Chen @wjmzbmr1
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358 Followers 223 Following Thinking Machines | Prev: Anthropic, Citadel, MIT
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Adam Zweiger @AdamZweiger
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Szymon Tworkowski @s_tworkowski
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Yong Lin @Yong18850571
2K Followers 292 Following Researcher @Meta TBD | Previous @thinkymachines @Princeton.You might like
