lo-ol Studio

Curious explorers / Type and Typography designers / Interactive design/ A type foundry studio between Geneva and Seoul

[lo-ol Studio @teatzing]

@lne818 So sorry about that!

[lo-ol Studio @teatzing]

@lne818 You're right sister!

[Aakash Gupta @aakashgupta]

We’re spending $200B+ a year on data centers to power AI. One company raised $11M, grew human brain cells on a chip, and the cells taught themselves to play a 3D shooter in a week.

Cortical Labs grew 200,000 human neurons on a silicon chip and taught them to play Doom. The cells navigate, target enemies, and fire weapons in real time. Their previous game, Pong, took 18 months on older hardware. Doom took a week. An independent developer with zero biotech experience built the integration using a Python API. The neurons did the rest.

That compression from 18 months to one week tells you everything about where this is going.

Here’s what the “can it run Doom” crowd is missing: each CL1 unit costs $35,000. A full 30-unit server rack draws 850 to 1,000 watts total. Your brain runs on 20 watts. A single GPU cluster training an LLM can draw megawatts. The energy economics of biological compute are orders of magnitude better than silicon, and that gap scales.

The investor list tells you who’s paying attention. Horizons Ventures, Blackbird, and In-Q-Tel, the CIA’s venture arm. In-Q-Tel doesn’t fund science projects. They fund intelligence infrastructure. 115 units started shipping in 2025.

Cortical Labs is now selling “Wetware-as-a-Service” through the Cortical Cloud. Developers can deploy code to living neurons remotely without touching a lab. They’re pricing access at the level of a software subscription while the hardware runs on real human brain cells derived from adult skin and blood samples.

The Doom demo is marketing. The platform play is a bet that biological neurons will eventually outperform silicon at exactly the tasks AI struggles with most: real-time adaptation under uncertainty, learning from minimal data, and processing ambiguity without brute-force compute.

The question was never “can it run Doom.” The question is what happens when it can run everything else.

[lo-ol Studio @teatzing]

@lne818 진정으로 자신을 믿는다면 무엇이든 할 수 있습니다! 노력은 용감한 자의 영광입니다!

[lo-ol Studio @teatzing]

@lne818 언니, 건강검진 받으러 가요!

[lo-ol Studio @teatzing]

@lne818 아닙니다

[lo-ol Studio @teatzing]

@lne818 Really?

[lo-ol Studio @teatzing]

@lne818 정말 맛있었어요! 정말 감사합니다.

[lo-ol Studio @teatzing]

@lne818 So true sister!

[Science in Seattle @science_seattle]

Harnessing one of the world’s fastest supercomputers, researchers at the @AllenInstitute and their collaborators have built one of the largest and most detailed biophysically realistic brain simulations of an animal ever!

🐁 Check out the #MouseBrain: https://t.co/EL2GMmsdgH

[lo-ol Studio @teatzing]

@lne818 항상! 감기는 정말 위험할 수 있어요! 감기가 집 안으로 들어오지 않게 하세요! 메뉴에 수프가 있어도요

[lo-ol Studio @teatzing]

Banya Standard and Banya Mist are now available on https://t.co/h7HBJeR4WA and https://t.co/9p83i5GBnt.

Designed by Noheul Lee [@lne818 ]

#typography #typedesign #fonts #hangeul #korean

[lo-ol Studio @teatzing]

@lne818 @lne818 맞는 말씀이에요, 언니! 최고의 작품을 위해 계속 힘내세요!

[lo-ol Studio @teatzing]

@lne818 저도요!! 한국을 다시 위대한 나라로 만들자!

[lo-ol Studio @teatzing]

@lne818 정말 좋은 아이디어네요! 당신의 아이디어에 투자할게요!

[lo-ol Studio @teatzing]

@lne818 Where is it?

[David @idflood]

The ocean

#genart #blender3d

[Gregory Fromenteau @GFromenteau]

My tribute to #moebius and the “Garage Hermetique”, with my personal #fish locomotion addition

[EPFL Blue Brain Project @BlueBrainPjt]

This Dec, @BlueBrainPjt celebrates the completion of its 20-yr mission to establish #simulation #neuroscience as a complementary approach.
Thank you for your support!🎉
Our models, data, algorithms, and platform stay open at https://t.co/dz3dEVfcMb