Aionic Labs

It's about time.

[Robert Jakob @robertjakob]

Researchers across 20+ institutions incl. ETH, Stanford, Harvard, KAIST, UNSW have spent months building TimeNet.

the goal: make it easier to train and benchmark temporal foundation models that understand how the world changes over time.

it's open source, and today we're kicking off a global hackathon. Come join us: https://t.co/o219dZbR3y

(and earn $50k in compute and cloud credits)

[Patrick Langer @PatrickLangerAI]

We’re releasing TimeNet today, joining forces with researchers across the US, Europe, Asia and Australia to build the future of Temporal AI that understands our world as it changes.

An open data standard and scalable infrastructure for next-generation Temporal Foundation Models.

[Robin Deuber @RobinDeuber]

From a beer at Stanford to a frontier AI lab in Zurich: 🍻🇨🇭
I've joined Aionic Labs, alongside my work at ETH's Agentic Systems Lab!
I've known the four founders as friends and colleagues for years. When they reached out about joining the team, it was an easy yes! 🚀

[Agentic Systems Lab | ETH Zurich @ETH_agent_lab]

“𝘠𝘰𝘶 𝘥𝘰𝘯'𝘵 𝘯𝘰𝘳𝘮𝘢𝘭𝘭𝘺 𝘭𝘦𝘢𝘳𝘯 𝘩𝘰𝘸 𝘵𝘰 𝘣𝘶𝘪𝘭𝘥 𝘧𝘰𝘶𝘯𝘥𝘢𝘵𝘪𝘰𝘯 𝘮𝘰𝘥𝘦𝘭𝘴 𝘪𝘯 𝘢𝘤𝘢𝘥𝘦𝘮𝘪𝘢.”

In this week’s lecture on 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 𝐟𝐨𝐫 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐲 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 at ETH Zurich, @nzuma0 and @PatrickLangerAI covered large language model (LLM) training and adaptation.

One fascinating aspects of foundation models we discussed was 𝐞𝐦𝐞𝐫𝐠𝐞𝐧𝐭 𝐛𝐞𝐡𝐚𝐯𝐢𝐨𝐫. You keep scaling data, model size, and compute, and suddenly models start demonstrating capabilities they weren't explicitly trained to perform. These capabilities are difficult to predict from smaller-scale experiments.

But here's the challenge: 𝐈𝐧 𝐚𝐜𝐚𝐝𝐞𝐦𝐢𝐚, 𝐲𝐨𝐮 𝐫𝐚𝐫𝐞𝐥𝐲 𝐡𝐚𝐯𝐞 𝐚𝐜𝐜𝐞𝐬𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐜𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬, 𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞, 𝐚𝐧𝐝 𝐬𝐜𝐚𝐥𝐞 𝐧𝐞𝐞𝐝𝐞𝐝 𝐭𝐨 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐭𝐡𝐞𝐬𝐞 𝐩𝐡𝐞𝐧𝐨𝐦𝐞𝐧𝐚 𝐟𝐢𝐫𝐬𝐭𝐡𝐚𝐧𝐝.

We covered post-training methods for LLMs and explored emergence and scaling laws. These topics help explain how model capabilities develop, how model behavior can be shaped, and what drives recent breakthroughs in LLMs.

For anyone building with AI, understanding these foundations helps inform decisions about what to automate, how to evaluate systems, and where human oversight matters.

Thanks to Nicolas Zumarraga and Patrick Langer for sharing insights from their research and real-world experience at Aionic Labs and Meta.

The Building Agentic AI Systems for Industry Transformation lecture takes place every Wednesday (16:15–18:00) at ETH Zurich and is led by @kev_osull, @PatrickLangerAI, @robertjakob, and Markus Kreft.

Lecture link in the comments. 🔗👇

[nicozumarraga @nzuma0]

Frontier Time Series Language Models struggle with precise anomaly localization over long contexts, when useful signals might be hidden in hours of recordings.

In our new paper we trained a tiny Recursive Language Model to SoTA performance on long context time series.

We introduce AnomalyXL, an infinitely scalable synthetic time-series generator with programmatic ground truth answers.

Training our RLM formulation on this RL environment transfers to real world anomaly detection in Software Observability, ECG and Sleep data.

🧵👇

[Robert Jakob @robertjakob]

Was fun sharing the stage with @PascalBtd at AI+X, looking back at the early days of the @ETH_agent_lab and what we're building now with @aionic_labs and @seldon_tech.

Thanks @ETH_AI_Center, Sören Fehrmann and Swisscom Ventures for having us!

[Nebius Science @nebius_science]

How do models make sense of systems that keep changing over time?

Patrick Langer, Co-Founder of @aionic_labs, joins Nebius Science Paper Club to talk Temporal AI, TSLMs, OpenTSLM, and reasoning across evolving systems.

Register: https://t.co/TlpcnalWos

[Tony Chen @tonyyuchen]

One model. Three time-series tasks. Three podium finishes.

Meet OpenTSLM TeeMoE 🚀

🥇 TimeSeriesExam
🥉 Context is Key
🥉 GIFT-Eval

Forecasting, context-aware prediction & time-series reasoning.

Open code. Open model.

Links below ↓

[Robert Jakob @robertjakob]

Skin in the game. Happy to have you Timo! 🔥

[Robert Jakob @robertjakob]

Feeling extremely bullish about Europe after the @SPRIND AI & Robotics Summit.

A personal highlight was speaking with the Swiss Ambassador to Germany, Livia Leu (@BotSchweizDE) about what we're building with @aionic_labs.

The real success story to me is the @SPRIND team behind it all. It is one amazing team of highly capable, high-agency, supportive, and extremely ambitious individuals on a mission to empower our best researchers and big ideas in Europe. They’re building a rocket ship. 🚀

Proud to see my home country Germany supporting a team and a program with this level of ambition, and happy to see other European countries starting to adopt what SPRIND is doing.

We’re ready to do our part with @aionic_labs push Europe to the next level. 🇪🇺🇨🇭🇬🇧

[Aionic Labs @aionic_labs]

@robertjakob @thomaskaar @martinm_ai @PatrickLangerAI Our team and research community are growing!

→ Aionic Labs: https://t.co/hdYbXyjzGi
→ Join the team: https://t.co/5FGlQdGi3R
→ Join the TSLM research community https://t.co/Ni3kfImA16

[Robert Jakob @robertjakob]

great to have all four @aionic_labs co-founders now in one room (and on X), building in Zurich.🇨🇭🚀

from an idea on a whiteboard at Stanford to a frontier AI lab in Europe and a global research community.

more to come 👀

@thomaskaar @martinm_ai @PatrickLangerAI

[Robert Jakob @robertjakob]

We are launching Aionic Labs (@aionic_labs). 🔥🚀

With support from SPRIN-D’s Next Frontier AI initiative, we are building a frontier AI company at the heart of Europe’s leading AI ecosystem.

Clinicians decide when a patient needs intervention. Factory teams catch machine problems before production stops. Operators determine which alarms demand action.

These are some of the most consequential decisions in the physical economy, and they all depend on time-series data.

We are developing Time-Series Language Models (TSLMs) that can understand these signals, reason over them, predict what comes next, and suggest actions in natural language.

TSLMs connect sensor data with language experts use to make critical decisions.

Europe is the right place to build this technology. We have world-class research, top technical talent, and decades of industrial expertise and data.

Our team brings together former founders, frontier tech experience, and world-class researchers from Stanford, Harvard, ETH Agentic Systems Lab (@ETH_agent_lab), ETH AI Center (@ETH_AI_Center) and CDTM (@cdtm_munich). We have built companies, developed technology at scale, and advanced research at the frontier of AI.

Over the coming months, we will:

→ Launch selected TSLM pilots across manufacturing, healthcare, energy, logistics, telecom, insurance, and banking.
→ Build an open research community around OpenTSLM (@OpenTSLM) and TimeNet.
→ Enable trusted data partnerships across industries.
→ Accelerate the Time-Series AI community in Zurich and Europe.

From Zurich. For Europe. 🇨🇭🇪🇺

Join our mission and help build a Frontier AI Lab from day one. Career and pilot program links are in the comments.

Managing Directors: Robert Jakob (@robertjakob), Thomas Kaar (@thomaskaar)
Supported by: SPRIN-D (@SPRIND)
Photo: Felix Adler für SPRIND