What is Thinking Machines building? we think it's a another ChatGPT like model

In a jaw-dropping display of investor appetite for frontier AI, Thinking Machines Labs has shattered all records with a $2 billion seed round—by far the largest such financing ever seen. The San Francisco startup, founded just last year by former OpenAI CTO Mira Murati and staffed largely by OpenAI alumni (alongside key execs from Meta, Google, and Mistral AI), secured the massive deal at a $10 billion valuation in a round led by Andreessen Horowitz. According to Crunchbase previous “mega” seed rounds like Yuga Labs and Aptos Labs topped out between $200 million and $450 million. Thinking Machines’ raise simply dwarfs them.

As for what the company actually plans to do? That’s still somewhat vague. Thinking Machines says it aims “to make AI systems more widely understood, customizable and generally capable,” while building advanced multimodal platforms designed to collaborate with humans. In today’s climate of soaring valuations often driven by team pedigrees alone, it’s a milestone that feels at once astonishing and strangely inevitable. We’ve seen these “team-first” startups before—the bet being that if you put the smartest, most accomplished people in a room, they’ll figure out something groundbreaking, product roadmap or not.

TheMarketAI.com Take:

With Thinking Machines’ sparse single-page website offering little more than team bios, we dug into those very bios for clues about what this $10 billion, few-months-old company might actually be up to:

• Over 60% of the team hails from OpenAI, including all of the top leadership roles (CEO, CTO, Chief Architect, and Chief Scientist).

• Nearly every position is R&D-focused, with virtually no business or operations staff listed.

• Putting two and two together, we’d wager they’re building their own ChatGPT like model—this team’s deep OpenAI pedigree suggests that’s where their core strength lies.

A few more thoughts:

• Culture matters. This will likely be an OpenAI-flavored culture transplanted into a new org—remember, OpenAI faced serious internal fractures not long ago, which may have helped drive this very exodus.

• Also worth noting: this is an enormous payday for early team members. For some, that can dramatically shift priorities and behaviors.

Andreessen Horowitz has a reputation for being “smart money.” If this team can bring another high-functioning model into existence quickly, it could justify the sky-high valuation—and position Thinking Machines as an attractive early acquisition target for companies like Apple, Amazon, or even Meta, all of whom are still trying to catch up with OpenAI, Microsoft, and Google for AI market share and dominance.

Thinking Machines founding team (source: https://thinkingmachines.ai):

Name	Bio
Alex Gartrell	Former Leader of Server Operating Systems at Meta, expert in Linux kernel, networking, and containerization.
Alexander Kirillov	Co-creator of Advanced Voice Mode at OpenAI and Segment Anything Model (SAM) at Meta AI, previously multimodal post-training lead at OpenAI.
Andrew Gu	Previously working on PyTorch and Llama pretraining efficiency.
Andrew Tulloch (Chief Architect)	ML systems research and engineering, previously at OpenAI and Meta.
Barret Zoph (CTO)	Formerly VP of Research (post-training) at OpenAI. Co-creator of ChatGPT.
Brydon Eastman	Formerly post-training research at OpenAI, specializing in human and synthetic data, model alignment and RL.
Chih-Kuan Yeh	Previously Building data for Google Gemini and Mistral AI.
Christian Gibson	Formerly infrastructure engineer at OpenAI, focused on supercomputers used in training frontier models.
Devendra Chaplot	Founding team member & Head of Multimodal Research at Mistral AI, co-creator of Mixtral and Pixtral. Expert in VLMs, RL, & Robotics.
Horace He	Interested in making both researchers and GPUs happy, formerly working on PyTorch Compilers at Meta, co-creator of FlexAttention/gpt-fast/torch.compile
Ian O'Connell	Infrastructure engineering, previously OpenAI, Netflix, Stripe.
Jacob Menick	ML researcher, led GPT-4o-mini at OpenAI, previously contributed to the creation of ChatGPT and deep generative models at DeepMind.
Joel Parish	Security generalist, helped ship and scale the first versions of ChatGPT at OpenAI.
John Schulman (Chief Scientist)	Pioneer of deep reinforcement learning and creator of PPO, cofounder of OpenAI, co-led ChatGPT and OpenAI post-training team.
Jonathan Lachman	Operations executive, former head of special projects at OpenAI and White House national security budget director.
Joshua Gross	Built product and research infrastructure at OpenAI, shaping ChatGPT's learning systems and GPU fleet; previously on product infra at Meta.
Kevin Button	Security engineer focused on infrastructure and data security, formerly at OpenAI.
Kurt Shuster	Reasoning at Google DeepMind, full-stack pre-training and inference at Character.AI, and fundamental dialogue research at Meta AI.
Kyle Luther	ML researcher, previously at OpenAI.
Lia Guy	Previously at OpenAI and DeepMind, working on model architecture research.
Lilian Weng	Formerly VP of Research (safety) at OpenAI. Author of Lil'Log.
Luke Carlson	Former ML Engineer in Apple's Machine Learning Research group, designed ML frameworks for model orchestration, speech generation, private federated learning, and image diffusion.
Luke Metz	Research scientist and engineer, previously at OpenAI and Google Brain. Co-creator of ChatGPT.
Mario Saltarelli	Former IT and Security leader at OpenAI.
Mark Jen	Generalist, most recently infra @ Meta.
Mianna Chen	Previously at OpenAI and Google DeepMind. Led advanced voice mode, 4o, 4o-mini, o1-preview, and o1-mini launches.
Mira Murati (CEO)	Former CTO of OpenAI, led OpenAI's research, product and safety.
Myle Ott	AI researcher, founding team at Character.AI, early LLM lead at Meta, creator of FSDP and fairseq.
Naman Goyal	Previously distributed training and scaling at FAIR and GenAI @Meta, most recently LLAMA pretraining.
Nikki Sommer	Formerly VP HRBP at OpenAI and Director, HRBP at Twitter.
Noah Shpak	ML Engineer, loves making data go vroom while GPUs go Brrr.
Pia Santos	Executive Operations Leader, previously at OpenAI.
Randall Lin	Previously babysitting ChatGPT at OpenAI and co-tech leading 'the Twitter algorithm' at X.
Rowan Zellers	Formerly at OpenAI, working on realtime multimodal posttraining.
Ruiqi Zhong	Passionate about human+AI collaboration, previously PhD at UC Berkeley, working on scalable oversight and explainability.
Sam Schoenholz	Led the reliable scaling team and GPT-4o optimization at OpenAI. Previously worked at the intersection between Statistical Physics & ML at Google Brain.
Sam Shleifer	Research engineer specializing in inference, previously at Character.AI, Google DeepMind, FAIR, HuggingFace.
Saurabh Garg	Researcher, formerly working on all things multimodal at Mistral AI. Deep into the magic of pretraining data and loving every byte of it!
Shaojie Bai	Avid ML researcher to make audio-visual models better and faster, previously at Meta.
Stephen Roller	Previously full-stack pre-training at DeepMind, CharacterAI, and MetaAI.
Yifu Wang	Passionate about novel ways of overlapping/fusing GPU compute and communication. Formerly PyTorch @ Meta.
Yinghai Lu	ML system engineer, formerly led various inference efforts at OpenAI and Meta.