Nancy (@nyu) | Twitxy

The hardest part of a proactive agent is deciding what deserves attention.

When should it act on its own? When should it ask for approval? When should it stay quiet?

I like that DeepSeek is treating these as core design questions. The next step is measuring how well those decisions work.

DeepSeek Harness Verified account @DeepSeekHarness Nov 1

x.com/i/article/2116…
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Nancy @nyu Nov 1

I’d love to see more agent demos show the decisions behind the action.

When did the model act? When did it ask for confirmation? When did it correctly stay silent?

That’s where agent judgment becomes measurable.

Viviana Márquez Verified account @vivmarquez Oct 30

SF builders! 🚨 Last few demo spots for Decision Models Night (Nov 3)!

@maximelabonne will share how we trained our decision models + how to use them.

Built something? Come show it off! Just 5 mins, scrappy prototypes welcome 🙌

👉 Apply here: forms.gle/GwHePAVx6QQxNE…

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Nancy @nyu Oct 31

The economics of local AI get interesting when agents run continuously in the background.

A personal agent that understands context, learns preferences, and makes decisions throughout the day has very different requirements from a chatbot responding to questions.

The Verge Verified account @verge Oct 30

As OpenAI’s buying spree squeezes the world’s supply of RAM, its CEO explains why he needs so much. theverge.com/ai-artificial-…
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Nancy @nyu Oct 31

What excites me about LFM3 is what smaller, capable models make possible on everyday devices.

Imagine personal agents that understand what’s happening around you, remember what matters, and know when to help.

Proud of the Liquid AI team! 💧

Liquid AI Verified account @liquidai Oct 27

Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence.

> 6 model instances, across text, audio, vision, and omni modalities, generative and decision models.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding
> 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages.
> 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language.
> 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input.
> fine-tune on 1 GPU.
> a new tri-hybrid architecture
> architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒

Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device.

1/ 🧵

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Nancy @nyu Oct 27

wsj.com/tech/palmer-lu…

www.wsj.com Palmer Luckey’s New Weapon: The American-Made Laptop A joint venture between Anduril and Qualcomm aims to make rugged laptops for the military and government.

Nancy

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