When a model writes, where do its words come from? Are they new, or do they match exactly with language it saw in training? An AI-writing detector can't tell you. @tuhinchakr.bsky.social's group at Stony Brook has been dissecting AI-generated prose with our infini-gram engine. 🧵

The organizations best positioned to use Earth-observation models – those working in conservation, food security, & disaster response – often can't run these models at the scale they need. That's an infrastructure problem. So we built the OlmoEarth Platform to solve it. 🧵

As a nonprofit research institute dedicated to advancing open science, we're encouraged to see growing support for open models across the AI ecosystem. We believe the evidence behind advanced AI systems shouldn’t be locked up in a few hands.

As a nonprofit research institute dedicated to advancing open science, we're encouraged to see growing support for open models across the AI ecosystem. We believe the evidence behind advanced AI systems shouldn’t be locked up in a few hands.

As a nonprofit research institute dedicated to advancing open science, we're encouraged to see growing support for open models across the AI ecosystem. We believe the evidence behind advanced AI systems shouldn’t be locked up in a few hands.

As a nonprofit research institute dedicated to advancing open science, we're encouraged to see growing support for open models across the AI ecosystem. We believe the evidence behind advanced AI systems shouldn’t be locked up in a few hands.

Curious how AI gets built at Ai2? For #SeattleTechWeek, we're opening our Northlake office for a panel with the researchers building our open models. They'll talk through the deep technical work behind them, with time after to chat about what you're working on & network. 👇

Two updates to Asta, our ecosystem of AI agents for science: a one-click handoff from AutoDiscovery to Asta’s data analysis tools, & paper search that evaluates its own results + searches again when they fall short. 🧵

What does it actually take to build cutting-edge AI systems? On July 30 during #SeattleTechWeek, the researchers behind Ai2's open models sit down to talk through the deep technical work behind them. 🧵

This week we hosted researchers from @cgiar.org, @servirglobal.bsky.social, NASA Harvest, & @msftresearch.bsky.social at our office to explore OlmoEarth for food security and natural resource management challenges. The CGIAR teams brought their own use cases and put OlmoEarth to work. 🧵

It was an honor to bring OlmoEarth to the Nature Positive Summit (@npinitiative.bsky.social) this week in Kumamoto, Japan, with our partners The Group on Earth Observations (@earthobservations.bsky.social). 🧵

We built SciArena to test how well AI models handle scientific literature questions, as judged by researchers. It's retiring July 15, and the results are in: ~1,700 users cast ~3,900 votes. Here's what they told us. 🧵

Our @skylightmarine.bsky.social team is rolling out Shippy, an AI agent for the people protecting our ocean in real time. A wrong answer at these stakes can send a patrol vessel miles off course. Here's the architecture we built so analysts can trust it. 🧵

olmOCR 2 is now in the Ai2 Playground—our home for our fully open text, video, and image understanding models. 🧵

OlmoEarth turns Earth data into insights—in hours, not years. But it's only as powerful as the people using it. So, we brought them into one room. 🧵

"Embeddings only get you so far… if you want the next level in performance, I think fine-tuning is the way to go." Ai2 research scientist @pjreddie.bsky.social explains how our partners customize OlmoEarth – our open-source Earth-observation models – to map crops, wildfire risk, & more. 👇

What can you build with a fully open robotics model in a weekend? 🤖 Robotics engineer @0xbinh.bsky.social used MolmoAct 2, our open vision-language-action model, in the voice-controlled robot that won @southparkcommons.bsky.social's AI hackathon. Watch our interview with him ↓ 🎥

We're at #ICML2026 with papers & talks across the conference. Come say hello and learn about our latest research!

The Danish Foundation Models (DFM) project is adapting our modular FlexOlmo architecture into a lighter-weight system that runs on commodity hardware—putting collaborative model building within reach of smaller research groups & organizations. 🧵

We're at #ACL2026 with papers & talks across the conference. Come say hello and learn about our latest research!

AI image generators don't "draw"—they follow a compass: the score function, which points toward more probable images. The same compass drives Bayesian sampling and plasma physics. We built DiScoFormer to estimate the score far better when data gets complex. 🧵

Today we're releasing OlmoEarth v1.2, the latest in our family of open foundation models for Earth observation. 🌍 We've switched to rotary positional embeddings (RoPE), which reduces artifacts in the embeddings & gives a small performance boost. 🧵

Hybrid (transformer–RNN) models are fast becoming a serious alternative to the transformer, but a big question remains: how do they process tokens differently & how does this impact performance? We compared our transformer (Olmo 3) & hybrid (Olmo Hybrid) models to find out. 🧵

Learn how @thinkaisquared.bsky.social & Domyn used Olmo, our family of fully open language models, to build their own models for regulated industries like finance, healthcare, & the public sector. 🧵

We're releasing MolmoMotion, a 3D motion forecasting model. Given one or a few video frames, 3D points on an object, & an instruction like "Put the white bowl on the table," MolmoMotion predicts where those points will go over the next few seconds in a shared 3D world frame. 🧵

Building an LLM means evaluating it over & over as it changes. Tweak a hyperparameter or scale the model up, & every new checkpoint sends you back through the same benchmarking loop. We're releasing olmo-eval, a workbench built for this kind of iterative model development. 🧵

LLMs are no longer created w/ human data alone. They rely on other models to generate & filter data, evaluate outputs, & guide dev work. So what is a modern LLM built on? Olmo 3 → 89 model + 183 dataset dependencies; Nemotron 3 → 273 + 560 We made ModSleuth to trace this. 🧵

𝗔𝗖𝗘𝟮𝗦-𝗦𝗛𝗶𝗘𝗟𝗗+, our new climate emulator that learns to separate the effects of sea surface temperature & CO2, is now on @hf.co—check it out → huggingface.co/allenai/ACE2...

allenai/ACE2S-SHiELD-plus · Hugging Face

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

huggingface.co

Ai2@ai2.bsky.social · 2mo ago

Today we're introducing ACE2S-SHiELD+, a climate emulator that learns to separate the effects of sea surface temperature & CO2. It accurately handles scenarios where previous versions of our ACE family of climate emulators produced inaccurate results. 🧵

Today we're introducing ACE2S-SHiELD+, a climate emulator that learns to separate the effects of sea surface temperature & CO2. It accurately handles scenarios where previous versions of our ACE family of climate emulators produced inaccurate results. 🧵

We're at #CVPR2026 with papers & talks across the conference. Come say hello and learn about our latest research!