AfterLabs

An AI lab building curious agents that never stop learning about the world

[AfterLabs @afterlabsai]

Current models rely on brute-force RL training to adapt to new tasks and environments. However, intelligent systems should be able to learn on the fly in a sample-efficient manner, continuously refining their understanding of the world through their interactions.

After Labs is developing models with built-in adaptation mechanisms rather than treating adaptation as an afterthought. This new generation of models will start a new era of curious agents that may not possess all the world's knowledge but will have the crucial ability to learn in real time.

Today, we are happy to announce that After Labs has been selected as one of 10 AI labs to join NFAI and receive €3M in additional funding. This support will accelerate our mission to build models that continuously learn about the world. We will be contributing to open science along the way, so stay tuned and follow us on our journey to develop AI that augments human understanding of the world 🌍

[SPRIND, Federal Agency for Breakthrough Innovation @SPRIND]

Ten teams. Five countries. Up to €26.5M each in equity-free funding to build frontier AI labs for Europe. The Next Frontier AI Stage 1 teams are here. Physical AI, world models, continual learning and automated science. Each one a serious bet on the next paradigm.

[Clem Bonnet @ClementBonnet16]

In a few years, millions of AIs will continuously learn from their interactions with the world.

We are building the tech behind agents and robots that adapt in real time.

Great crowd at yesterday's Berlin Robotics & AI Summit! 🤖

[matt @MattVMacfarlane]

I’ll be at RLC 2026 in Montréal 🇨🇦 from August 15–18!

If you’re interested in World Models, continual learning, or world building, reach out and let's set up a chat.

@RL_Conference

[matt @MattVMacfarlane]

We’re hiring a world builder.

Someone who will architect creative worlds to push the next frontier of intelligence.

If you’ve created games, worked with game engines, developed simulations, built interactive environments, or created synthetic worlds, we want to hear from you.

DM me or email [email protected] with one such project.

[Clem Bonnet @ClementBonnet16]

@MattVMacfarlane and I started After Labs earlier this year with a clear conviction: systems that continuously learn and synthesize new knowledge will require a new class of AI models.

While most labs are focused on incremental progress within today’s dominant paradigms and product constraints, we believe the next breakthrough will come from teams willing to make bolder bets solely targeting step changes.

We have already made remarkable progress, and we will be sharing more soon as we continue building models that learn in real time.

[matt @MattVMacfarlane]

@ClementBonnet16 and I started After Labs with a simple conviction. The next leap in AI will not come from models that merely store more knowledge or bake more task-specific skills into their weights. It will come from systems that can continually learn and refine their understanding of the world through interaction.

At After Labs, we are singularly focused on developing world models with the ability to adapt with every new data point instead of staying static. These adaptation mechanisms need to be built into the model during training and not bolted on as an afterthought.

Stay tuned as we pursue this mission of building curious agents that never stop learning 💡

[AfterLabs @afterlabsai]

We thank @SPRIND for their support and obsession with high-impact bets.

We are also proud to be backed by visionary angel investors, including @ClementDelangue, @MattHartman, @fchollet, @Carles_Reina, @ecsquendor, and others.

[AfterLabs @afterlabsai]

Current models rely on brute-force RL training to adapt to new tasks and environments. However, intelligent systems should be able to learn on the fly in a sample-efficient manner, continuously refining their understanding of the world through their interactions.

After Labs is developing models with built-in adaptation mechanisms rather than treating adaptation as an afterthought. This new generation of models will start a new era of curious agents that may not possess all the world's knowledge but will have the crucial ability to learn in real time.

Today, we are happy to announce that After Labs has been selected as one of 10 AI labs to join NFAI and receive €3M in additional funding. This support will accelerate our mission to build models that continuously learn about the world. We will be contributing to open science along the way, so stay tuned and follow us on our journey to develop AI that augments human understanding of the world 🌍

[SPRIND, Federal Agency for Breakthrough Innovation @SPRIND]

Ten teams. Five countries. Up to €26.5M each in equity-free funding to build frontier AI labs for Europe. The Next Frontier AI Stage 1 teams are here. Physical AI, world models, continual learning and automated science. Each one a serious bet on the next paradigm.