Deep Dive on Thinky's Seed Round (Part II)
This is a Multimodal Sovereign AI startup. The first of its kind.
With the huge talent exodus from OpenAI in recent years, it has spawned Anthropic and many other AI startups.
How different are Thinking Machines Lab and SSI actually going to be from OpenAI and Anthroic? You know when we like to say “these are early days” for AI, you can say that again here.
We are talking just a few months old here.
Thinky is led by OpenAI’s former CTO, Mira Murati. We have a lot of snippets and details to cover.
In case you missed it
Thinking Machines Lab officially closed a $2B seed round at a $12B valuation – the largest seed round in VC history and 4x bigger than any previous seed funding. The era of Gen AI calls for moonshots, and Thinky is unusual in many regards.
It’s the Biggest Seed Funding Round Ever by a Wide Margin
In a world where women struggle in Technology, to be CEOs or even to get funding from mostly male VCs, Mira Murati is the exception. She breaks all the rules, and from Albania to Silicon Valley, we are witnessing a special moment in history. 🏹
The scope of the project is also related to Open-source LLMs, a vast wasteland in the West where the likes of Mistral, Together AI, Ai2 and a few others huddle around the campfires of open-weight innovation with Hugging Face, hoping for better days.
Well, it’s official now, Thinking Machines Lab has raised $2 billion in fresh capital — making it the largest seed round in venture capital history for a company that's been around for just six months and has yet to ship a single product. But don’t let that fool you!
What should we even make of this?
Thinking Machines Lab is less than a year old and has yet to reveal what it’s working on.
I’m so passionate about AI startups and their potential, but even this story is hard to fathom at the peak AI bubble in the United States, where even the Pentagon wants in on the action. But when you dig a bit deeper it actually starts to make a bit more sense.
Investors include a16z, NVIDIA, Accel, Cisco, AMD, Jane Street
Murati has said that their first multimodal, open-source-friendly product lands “within months”
Here is a startup that the two U.S. leaders of AI chips are both involved in, Nvidia and AMD, along with a16z making a classic moonshot bet.
The quality of the AI talent at Thinking Machines Lab is likely to exceed that of Google Deepmind or OpenAI, only approached by Anthropic. Because we are living in the OpenAI mafia era where splinter projects become more attractive both for doing pioneering work and for the financial incentives.
Thinking Machines Lab represents yet another “pivot” in the failed Mission of OpenAI. While Google, xAI, Meta Superintelligence Lab and even Anthropic mirror the tactics and behavior of OpenAI, here we have yet another fresh start of OpenAI vets thinking and planning for a re-do.
If OpenAI was founded out of fear and envy of Google DeepMind, a lot has changed in just a few years. Thinking Machines know that they can do better, that LLMs weren’t supposed just to be people-pleasing token gulping sycophant-heavy machine economy chatbots.
The Product is a Mystery
Murati peeled back the curtain on the company’s first product a bit in a post on X on July 15th, 2025, claiming that the startup plans to unveil its work in the “next couple months,” and it will include a “significant open source offering.”
At a time when China has overtaken the U.S. in open-weight models, it’s a bizarre period of the evolution of LLMs where new frontier models land nearly every month or at most, every six weeks.
Amid OpenAI’s controversial past, Mira Murati is a recognisable face - Murati rocketed into the spotlight in 2023 when she was named interim CEO of OpenAI after Sam Altman was briefly ousted by the company’s board. It was a complicated time where ChatGPT went on to become synonymous with AI, and only Anthropic, itself a splinter startup of OpenAI’s original team, seemed to be able to follow. So now we have a third player in the game.
This is Talent
The team is comprised so far of about 30 researchers and engineers, with roughly two-thirds being former OpenAI employees, alongside talent from Meta AI, Mistral AI, Character.AI, and Google DeepMind. When a mission goes south like it did at OpenAI, what is the phoenix that rises from the ashes of manipulation and mismanagement (not to mention stringent NDAs, and a murder framed as a suicide?). Some of these names might sound familiar to you:
Mira Murati, CEO and founder, formerly OpenAI's Chief Technology Officer, instrumental in developing ChatGPT, DALL-E, and voice models.
John Schulman, Chief Scientist, an OpenAI co-founder who helped build ChatGPT and previously worked at Anthropic on AI alignment.
Barret Zoph, Chief Technology Officer, former OpenAI Vice President of Research, who left OpenAI alongside Murati.
Jonathan Lachman, former head of special projects at OpenAI, now a key member of the founding team.
Lilian Weng, a co-founder with a background in AI safety and robotics at OpenAI.
Alexander Kirillov, former multimodal research head at OpenAI, now part of the leadership team.
Andrew Tulloch, with expertise in pretraining and reasoning from his time at OpenAI.
Luke Metz, a research engineer with experience in post-training at OpenAI.
Devendra Chaplot, a founding team member, previously involved in AI research.
Myle Ott, another founding team member with a strong research background.
In some ways Thinking Machines Lab is more OpenAI than the talent who work at OpenAI are today - and might need to take that original mission and fulfil it with a greater promise. These are some of the people that witnessed OpenAI become almost unrecognizable in just a few short years of product and commercial pressure.
If I had to take key values or framing of what this startup is about from their website, I’d gather:
Science
Open-Source
Democratization of AI
Explainability of frontier AI systems
Customizable models at scale
You will notice the mission statement is less ideology and more pragmatism of action. Less Sam Altman-Ilya Sutskever cult-speak and more holistic alignment.
A $12 Billion valuation for a startup that really doesn’t formally exist yet with a product, is totally unheard of and the biggest moonshot we’ve yet to see in the AI space. I’d argue it’s more important also than Meta Superintelligence Lab trying to poach talent from OpenAI, Apple and xAI in some reckless act of Tycoon envy otherwise known as a day in the life of Mark Zuckerberg.
Thinking Machines isn’t a long shot, it’s the highest average concentration of AI talent we’ve ever seen in a small deal, higher than DeepMind in its early days. Led by a woman, and that’s fundamentally important when building and aligning an early team. These are OpenAI vets that have seen the good and bad of what power and influence can do to a rising AI startup. Who have witnessed Sam Altman in his paranoia and bizarre attempts at indoctrinations in a mission he doesn’t even truly believe in. Mira Murati isn’t Sam Altman, and it matters.
Thinking Machines Lab - Ghost in the Shell
Science is better when shared
Scientific progress is a collective effort. We believe that we'll most effectively advance humanity's understanding of AI by collaborating with the wider community of researchers and builders. We plan to frequently publish technical blog posts, papers, and code. We think sharing our work will not only benefit the public, but also improve our own research culture.
AI that works for everyone
Emphasis on human-AI collaboration. Instead of focusing solely on making fully autonomous AI systems, we are excited to build multimodal systems that work with people collaboratively.
More flexible, adaptable, and personalized AI systems. We see enormous potential for AI to help in every field of work. While current systems excel at programming and mathematics, we're building AI that can adapt to the full spectrum of human expertise and enable a broader spectrum of applications.
Solid foundations matter
Model intelligence as the cornerstone. In addition to our emphasis on human-AI collaboration and customization, model intelligence is crucial and we are building models at the frontier of capabilities in domains like science and programming. Ultimately, the most advanced models will unlock the most transformative applications and benefits, such as enabling novel scientific discoveries and engineering breakthroughs.
Infrastructure quality as a top priority. Research productivity is paramount and heavily depends on the reliability, efficiency, and ease of use of infrastructure. We aim to build things correctly for the long haul, to maximize both productivity and security, rather than taking shortcuts.
Advanced multimodal capabilities. We see multimodality as critical to enabling more natural and efficient communication, preserving more information, better capturing intent, and supporting deeper integration into real-world environments.
Learning by doing
Research and product co-design. Products enable iterative learning through deployment, while great products and research strengthen each other. Products keep us grounded in reality and guide us to solve the most impactful problems.
Empirical and iterative approach to AI safety. The most effective safety measures come from a combination of proactive research and careful real-world testing. We plan to contribute to AI safety by (1) maintaining a high safety bar--preventing misuse of our released models while maximizing users' freedom, (2) sharing best practices and recipes for how to build safe AI systems with the industry, and (3) accelerating external research on alignment by sharing code, datasets, and model specs. We believe that methods developed for present day systems, such as effective red-teaming and post-deployment monitoring, provide valuable insights that will extend to future, more capable systems.
Measure what truly matters. We'll focus on understanding how our systems create genuine value in the real world. The most important breakthroughs often come from rethinking our objectives, not just optimizing existing metrics.
This is a research lab unlike any other on the planet, perhaps even a radical departure from commercial norms like DeepSeek brought us six months ago.
These are also seasoned Machine learning researchers who know the responsibility and the weight that building LLMs can have on the world, who understand their impact like few other human beings on the planet.
A Little bit more of “Thinky” in our Life
The acronym or pet name on X for the startup is quickly morphing into “Thinky”. It appears to have a more action biased plan than SSI, the other mega “AGI startup” in the OpenAI Mafia leagues.
Mira Murati has been working diligently, she left OpenAI in September of 2024 and launched Thinking Machines in February, 2025 though she has not shared many details about the startup publicly.
Interesting corporate backers like Servicenow and Cisco are surprising. As was the fact the valuation is at $12 Billion and not $10 Billion that was earlier reported. This is a project many VCs wanted to get into even at an astronomical valuation. Consider the uniqueness of the merits of the team, the average seed round size for AI startups in 2024 was approximately $3.5 million, according to industry analyses. This team managed to get $2 Billion?
These are clearly “big” thinking machines that the startup are working on. Amid OpenAI’s delay of their own open-weight model, it gives more weight to the work that Thinking Machines are doing behind the scenes. With Meta going closed-model now, it creates a huge void in the ecosystem as Chinese models take the crown in the open-weight LLM rankings and leaderboards.
“We believe AI should serve as an extension of individual agency and, in the spirit of freedom, be distributed as widely and equitably as possible,” Murati wrote. “We hope this vision resonates with those who share our commitment to advancing the field.”
Some of the PR statements made certainly sound like those an open-source startup or at least an open-weight model maker might make. Bloomberg’s Mark Gurman considering Thinking Machines Lab as a potential Apple acquisition target are pretty far-fetched and amaze me.
AI explainability is truly important in terms of trust, security and the accountability of these systems:
“Soon, we’ll also share our best science to help the research community better understand frontier AI systems,” said Murati. - Tweet.
In addition to Meta Superintelligence Lab poaching several core members of OpenAI’s team, there’s a continued exodus here too:
What does “Open Science” even look like in the future of America? 🤔
Open-science
Rapid iteration
Co-design and collaborative principles
Focus on real-world deployments
Frontier capabilities with multi-modal nativity
Since Murati launched her venture, Thinking Machines Lab has attracted some of her former co-workers at OpenAI, including John Schulman, Barret Zoph (CTO), and Luke Metz. These are some of the most senior people that were left at OpenAI. These are some of the humble ones. Who take the science of research seriously.
The combined experience of these founding researchers at Thinking Machines Lab is off the charts as young a field as Generative AI and LLMS are. As we have seen with the talent wars, experience is at a premium.
Voice and Ambient Computing with LLMs?
Thinky could also be about more accessibility and mass adoption. For me 2025 is the start of a golden era of Voice AI. Murati said Thinking Machines is building multimodal AI that will be compatible with the ways that people naturally interact with the world, including through conversation and sight.
Thinking Machines Lab isn’t just a new start, it’s the opportunity to build a new paradigm and pioneer the next architecture of what LLMs can become in the real world. Not just as a hype machine of selling ultra compliant token-mirror neurons, but something a bit more tangible and close to our senses and our common humanity.
Thinking Machines Lab is one of a handful of AI startups that investors believe to be a legitimate threat to leading AI model developers today and why this is relevant is that it has a decent chance of continuing to receive talent from both OpenAI and Anthropic whose most exciting days are already over.
As far as I’m aware (and correct me if I’m wrong) the investors in Thinking Machines Lab in their Seed round include:
Andreessen Horowitz (a16z) (led the funding round)
NVIDIA
Advanced Micro Devices (AMD)
Accel
ServiceNow
Cisco
Jane Street
Conviction Partners
Ambush Capital
Davidovs Venture Collective
Albanian Investment Corporation
There may be others I’m not aware of too.
TML is set up as a Public Benefit Corporation (PBC) not unlike is the standard now for OpenAI mafia companies like Anthropic. Thankfully it puts science first and not ridiculous marketing acronym like “AGI” (like OpenAI) or pretending like it can solve the problems of AI alignment by itself (like SSI). Thinky really is its own journey and I’m hopeful they can make models and build new architectures that wouldn’t happen at OpenAI, Anthropic or even DeepSeek or Qwen.
When you are able to have a seed round about 500x the average AI startup you know something big could come of it. The best investor in AI startups since 2022 in my mind has been Nvidia and their participation in the Seed round gives me confidence. Nvidia has dramatically ramped up its investments in AI startups since 2022, participating in some of the largest funding rounds in the industry.
Thinking Machines Lab is a ‘Sovereign AI’ Startup
Nvidia’s noteable AI funding rounds:
Companies with Nvidia backing tend to be successful. Nvidia has become one of the most aggressive investors in AI, backing a broad range of companies across infrastructure, foundational models, robotics, and tools for AI developers.
Nvidia rarely however participates so early as a Seed round. To do so, it must have great confidence or alignment in the approach of TML.
Some of those that stand out to me are:
Thinking Machines Lab
Safe Superintelligence
Mistral AI
Perplexity
CoreWeave
Together AI
Sakana AI
SandboxAQ
Poolside
Figure AI
Hippocratic AI
Imbue
Wayve
Scale AI
Hugging Face
Considering Mistral, Together AI and Hugging Face are all open-source (or open-weight) builders and Nvidia preaches a Sovereign AI approach, Thinking Machines Labs’ values are highly aligned with not just Nvidia, but with their AI portfolio.
Wilson Sonsini Goodrich & Rosati advised Thinking Machines on the transaction of their Seed round and they have additionally several former OpenAI advistors. TML is as much an OpenAI splinter startup as Anthropic was in the early days. And we know how well that went given Anthropic’s financial trajectory is even better than that of OpenAI at the same stage.
The Growth Trajectory That Breaks Every SaaS Model of Anthropic
Anthropic’s Revenue Timeline:
2022: $10M (founding year revenue)
2023: $100M (10x growth)
Dec 2024: $1B ARR (10x growth again)
July 2025: $4B ARR (300% growth in 7 months)
Thinking Machines Lab doesn’t have to be as commercially focused as Anthropic where the AI alignment part has become a smaller part of their mission noticeably in 2025. They aren’t backed by the likes of Amazon or Google. Or Microsoft for that matter that are and will have incredible conflict with their investment in OpenAI of over $13 Billion with endless legal complications.
Thinking Machines Lab could take a clearer route commercially. That is without a BigTech sponsor that isn’t totally aligned with their values.
Meanwhile the valuation of OpenAI, Anthropic, xAI and Meta Superintelligence Lab (that they should really spin-out) is open to debate and seem to change nearly every few months.
“We’re building multimodal AI that works with how you naturally interact with the world – through conversation, through sight, through the messy way we collaborate.” - Mira Murati
Thinking Machines Lab more like a pure LLM based Science research Lab
Thinking Machines Lab might be more like a couple of Seed rounds Nvidia participated in that many people aren’t as aware of moreover EvolutionaryScale and Lila Sciences, and a bit more like Sakana Labs that has a focus on progressing science more directly.
Thinking Machines in terms of being an OpenAI Mafia company is the third child and anyone that knows anything about birth order pop-psych knows that the third child tends to be more the independent creative type. Some studies suggest that later-born children, including third-borns, might be more creative due to a tendency to be more rebellious or unconventional. Whether you think that’s possible or nonsense, I believe Thinking Machines Lab will be more creative and not just a commercially driven empire that are like proxy Generative AI product focused labs like OpenAI and Anthropic, for good or ill, have become.
And this finally, is what gives me more hope for the future of LLMs. a16z clearly want their money back but I don’t think that will be a problem in 10-12 years at all.
Murati joined OpenAI in 2018, served as the company's CTO, she was loyal and stayed for seven years, she’s paid her dues to the AI bros and their AGI non-sense. In the original blog post published in February, 2025 the startup stated that it would focus on creating AI models and products that support a more humanized format of interaction between humans and artificial intelligence.
In a world where Nvidia is worth nearly $4.2 Trillion and OpenAI has over 500 million users - what can the best funded early AI Startup in history become?
How Thinking Machines is Divergent from Traditional LLM Labs
Thinking Machines might specialize in helping others build custom models and have a strong B2B and AI Enterprise component. That is, helping scientists and researchers and start-ups to develop custom models.
In summary while we piece together what little information has been provided: Thinking Machines Lab, founded by former OpenAI CTO Mira Murati, is an AI research and product company focused on developing multimodal AI systems that emphasize human-AI collaboration, customization, and accessibility.
Human-AI collaboration
Customization
Accessibility
While these terms are vague they are fairly different from the exaggerated promising of Sam Altman, Elon Musk or Mark Zuckerberg who is a digital advertising Mogul. Here is a CEO that wants to bring back AI to the human being and that is likely to build products that reflects this approach. That is, their approach diverges from traditional AI companies by emphasizing collaborative, user-driven AI systems rather than purely autonomous solutions.
The Next Era of Multimodal Accessible AI is Nearly Here
This is the sort of science backed AI product company that Nvidia backs in the Seed round.
Sarah Wang of a16z
Horace of Thinky
Alexander Kirillov at Thinky
It sounds like Anthropic but more open-weight and less about just AI coding supremacy. We should not that hyperscale affiliation wise, Thinking Machines Lab had previously struck a deal with Google Cloud to power its AI models.
According to Murati, the company aims to deliver systems that are not only technically capable but also adaptable, safe, and broadly accessible. Their approach emphasizes open science, including public releases of model specs, technical papers, and best practices, along with safety measures such as red-teaming and post-deployment monitoring.
Filling the Open-Weight Void in the U.S.
With OpenAI struggling to release an Open-weight model due to saftey issues and testing, with multiple delays - with their model now in limbo, Thinking Machines’ decision to announce a clear timeline and include an open source component could reshape developer attention and help us get over Meta’s ludicrous and cash bleeding pivot to MSL.
Thinky is also likely to have less jargon and cult-like ideology in their mission where simpler is better: Thinking Machines Lab believes science is better when shared.
That sounds a lot more like Nvidia’s Sovereign AI than the AGI non-sense OpenAI, Microsoft, Google and others have been perpetuating. It also sounds more realistic and science-based.
All my respect to Lightning AI, Ai2, Mistral, Hugging Face, Together AI and others working on open-weight and open-source projects, the state of Open-source AI in the United States has negative momentum as compared with China and AI startups there.
I think Mira Murati is also going to be a more ethical leader than we have witnessed with OpenAI with a founding team with less internal drama. This is important when you are actually building products. OpenAI is far too big now to compete with decent pure play labs and as top AI talent has skewed Anthropic for quite a few months, now they will have another place to go.
So these in a nutshell are my first impressions and some of the newsy tidbits I’ve been watching surrounding the biggest Seed round in AI history. This draft may have errors and I apologize it was written in a bit of a rush.
Murati left OpenAI in September, saying she wanted to “create the time and space to do [her] own exploration”
Addendum
Mira Murati is one of the few people that have worked under Elon Musk and Sam Altman in a unique way. She’s hitting her prime at the time of founding Thinking Machines Lab. Few of us remember but Murati was a senior product manager at Tesla, where she contributed to the Model X.
As an executive of OpenAI, Murati, 36, worked on the development of products such as ChatGPT, the Dall-E image generator and its voice mode. She briefly replaced Sam Altman as interim chief executive officer during a board coup in November 2023. You can follow her on X here.
Thinking Machines has already hired a number of former OpenAI employees, as well as those from other competitors such as Google, Meta and Mistral.
OpenAI must have been an incredible atmosphere to work in those early days that are now long gone and starting something new is perfect for some of these AI researchers who really want to do good engineering and science with the right alignment, where commercial impulses don’t come in the way of integrity.
We might be on the cusp of new architectures that don’t just leverage the transformer architecture but take a more holistic and integrated approach. I’m optimistic about Thinking Machines Lab because the AI talent concentration is going to very unique and some of the best minds in the world will be attracted to work there.
Talent Breakdown of Active Employees July 17th, 2025 at Thinking Machines Lab
My thesis after looking into it that Mira Murati will help Thinky win on AI talent.
The startup aims to building open, customizable, and collaborative general intelligence through multimodal AI. - But who does that sound like?
It sounds like many of the top women leading in AI.
Women in AI Matter
How well Mira Murati does will also have bigger implications. Women-founded startups attract less than 2% of all global venture capital, a figure that has barely shifted over the past decade.
I desperately want to see the next generation of women in AI succeed because AI is going in the wrong direction. We need world models for people and the profit motive to not just serve the shareholders and users but civilization’s future, science and humanity. I trust female leaders to be more AI alignment focused, than what I am seeing currently from Silicon Valley VCs and top AI executives.
Founding Tweet
Mira Murati clearly wanted to build an AI startup where scientists, engineering and builders would be helping other entrepreneurs, scientists and human adoption of AI technologies.
New foundational models
Custom Models and greater accessibility to the tools for specific needs
Improving Open-science and Open-weight principles of LLMs
Product focused AI with practical applications
Science is better when Shared
a prolific author on Machine learning agreed: 
Curiously in the last 9 months, it’s China that has taken this principle to heart and not U.S. AI startups. DeepSeek, Alibaba, Moonshot AI and now even Baidu and ByteDance are taking the open-weight an “ecosystem is better when shared” approach to China’s own strategy in building Generative AI products and apps. Born in China teams whether in China or with operations in the U.S. are gaining momentum.
Conviction VC invests in Thinky
"Raw intelligence is brain without hands," says Sarah Guo (Conviction VC). Large companies struggle with the velocity needed to deeply understand user needs and train AI for specific use cases. It's about AI's speed meeting real-world application.
Sarah Guo’s Conviction participated in the Thinking Machines Lab Seed round.
Notable Investments
Conviction Partners has invested in several prominent AI and software companies, including:
HeyGen
Baseten
Cartesia
Cognition Labs
Mistral
Seek AI
Harvey
Sierra
See a longer list here.
Programs and Resources
Conviction Partners offers several programs and resources to support founders:
No Priors (a podcast, Spotify link)
Commit
Exodus from OpenAI Talent Pool
Murati is one of a handful of executives who left OpenAI after raising concerns about CEO Sam Altman’s leadership in 2023. Over the last couple of years this trend has increased with many moving to Anthropic or Google Deepmind, but also starting their own startups.
With Meta Superintelligence Lab founding and Thinky now, that AI talent competition has become even more intense in mid 2025. OpenAI’s ability to attract and retain its top talent is diminishing rapidly even as its commercial success keeps growing mostly in the B2C sense.
Thinky could be more like Anthropic in that it’s a provider of value to institutions, companies and SMEs, with more of a B2B model. A bit more along the lines of how a Cohere or a Mistral operate.
Mark Zuckerberg claims AI researchers want these three things, but is he right? Many more AI alignment orientated AI scientists don’t just want more GPUs per researcher or higher bonuses, but a sense that what they are doing matters to improving the world. Top talent want value alignment with science itself.
I believe Thinky establishes an optimal balance between a pragmatic applied product focus and benefiting the science (e.g. decentralized and collaborative). This contrasts somewhat with OpenAI where the same sorts of features get released.
Multimodal Native Foundations
Interview in 2023 with a16z.
The Founding 8 Investors in Thinky
Mira Murati is playing “4D chess in AI” able to bring together such investors without a live product in mere months:
Andreessen Horowitz (a16z): A prominent venture capital firm based in Silicon Valley, known for backing transformative tech companies like Airbnb, Lyft, and GitHub. Founded by Marc Andreessen and Ben Horowitz, a16z focuses on high-growth startups in software, AI, and blockchain, offering not just capital but also strategic guidance and operational support. It seems likely that Sarah Wang was the lead partner.
Nvidia: A leading technology company specializing in graphics processing units (GPUs) and AI computing. Nvidia’s investment reflects its interest in advancing AI infrastructure, as its chips are widely used in machine learning and generative AI applications.
AMD (Advanced Micro Devices): A global semiconductor company known for its CPUs, GPUs, and AI accelerators. AMD’s participation underscores its commitment to supporting AI innovation, competing with Nvidia in providing hardware for AI workloads. The CEO is a woman, Lisa Su.
Accel: A venture capital firm with a long history of investing in tech giants like Facebook, Slack, and Dropbox. Accel focuses on early-stage and growth-stage companies, particularly in software, AI, and cloud computing, bringing deep expertise in scaling tech businesses.
ServiceNow: A cloud-based platform provider specializing in enterprise workflow automation and IT service management. Its investment in Thinking Machines Lab aligns with its focus on integrating AI to enhance enterprise productivity and digital transformation.
Cisco: A multinational technology conglomerate known for networking hardware, software, and cybersecurity solutions. Cisco’s involvement suggests interest in AI’s potential to enhance networking, security, and enterprise solutions.
Jane Street: A global proprietary trading firm that leverages advanced technology and quantitative research for financial trading. Its investment likely reflects interest in AI’s applications in financial modeling and data analysis.
Conviction Partners (via Sarah Guo): A venture capital firm founded by Sarah Guo, formerly of Greylock Partners. Conviction Partners focuses on early-stage software and AI companies, with Guo bringing deep expertise in identifying high-potential tech startups.
If OpenAI’s main sponsor is Microsoft, and Amazon seems to be Anthropic’s lead sponsor. Is Nvidia going to be Thinky’s main corporate sponsor? The Sovereign AI and Open-source alignment seems to indicate it’s a possibly.
Some Unique Things I noticed about Thinky - pre-seed thinking with Series F checks.
One of the first major AI startups to have direct government investment from a founder's country of origin (Albania).
Name Evolution: Initially referred to as "Machine Thinking Lab" in some Albanian government documents
So much of the culture appears to be based on early OpenAI talent (a re-do). This leads me to believe they will attempt to build what OpenAI “should have been.”
Record Seed Context: Previous largest seed round was approximately $500M, making this 4x larger. Even more unusual for a female-led CEO company. You may have noticed Murati doesn’t exactly have your typical Ivy league education or career trajectory. She’s more self-made and OpenAI graduated than most, a true enigma.
Meta Superintelligence Lab (MSL) failed to acquire the talent of Thinky before they settled on Scale AI. Meta went on to poach several Chinese born researchers at OpenAI, Apple and talent from Google DeepMind and other labs.
a16z led the round, which typically indicates they were the primary negotiator and likely the largest single investor, so they could have significant equity in Thinky.
Several corporations invested in the Seed round including the likes of Nvidia, AMD, ServiceNow and Cisco.
Davidovs Venture Collective (DVC), one of the early funders have a strong “community” driven approach. More female led VCs appear to have participated in Thinky’s seed round.
This article is an update on my first take published here.
Nice read. Incidentally I posted this article and Thinking Machines was on my mind
AI Too Strategic to Fail? When Infinite Funding Meets Uncertain Value
https://open.substack.com/pub/pramodhmallipatna/p/ai-too-strategic-to-fail-infinite
great writing!