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Established Models & releases Release 7d ago
⚡ 4 h early
Thinking Machines Lab Inkling model launch

thinkingmachines/Inkling · Hugging Face

5 experts across 3 network communities independently surfaced this.

5 experts 3 communities 2 sources clustered
Nathan Lambert Tim Kellogg Sung Kim Cameron Evangelos Kazakos

“A big day for open model supporters in the U.S. Blog: thinkingmachines.ai/news/introdu... Model card: huggingface.co/thinkingmach...”

“Thinking Machines has a real model — 975B multimodal audio + image input it’s a generalist model. built for easy customization, TM has a great finetuning API audio up to 20 minutes, 1M token context for text thinkingmachines.ai/news/introdu...”

3 experts discussed this · 4 posts
Nathan Lambert: Thinking Machines just released with a ~1T param, 41B active, apache-2 model Benchmarks are a clear step up from Nemotron Ultra (55B active), new best American model, and omni input. A bit behind G…
Nathan Lambert: A big day for open model supporters in the U.S. Blog: thinkingmachines.ai/news/introdu... Model card: huggingface.co/thinkingmach...
Ben Recht: Yeah, that part is weird, no? The small model is *much* smaller and yet indistinguishable from the big one on benchmarks? I guess we'll have to wait and see, as it's not available yet.
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Primary source huggingface.co ↗ thinkingmachines.ai ↗
Established AI research Research 13d ago
Whareformer egocentric video tracking paper

Whareformer: Learning to Track What is Where in Long Egocentric Videos

2 experts are actively discussing the implications.

2 experts 2 communities 1 sources clustered
Dima Damen Evangelos Kazakos

“Whareformer @eccv.bsky.social #ECCV2026 fantastic collab bw @compscibristol.bsky.social @naverlabseurope.bsky.social by Jacob Chalk w/ @sinhasaptarshi.bsky.social @skamalas.bsky.social & @dlarlus.bsky.social Paper, Code &models public: jacobchalk.github.io/…”

2 experts discussed this · 7 posts
Dima Damen: NEW Whareformer: Learning to Track What is Where in Long Egocentric Videos @eccvconf #ECCV2026 paper The first online learning approach to track dynamic objects in ego video reasoning on appearance…
Dima Damen: Whareformer (What&Where former) tackles the OSNOM task - Out of Sight objects remain explicitly in memory so you know where objects are at all times. In natural ego videos, tracking moving objects …
Dima Damen: We train: * embedding network g(.) to combine appearance &location diff * NT token to learn to initialise new tracks * transformer encoder to contrast assignments Memory is updated online based on …
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Primary source jacobchalk.github.io ↗
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