About Mira Murati
Mira Murati, co-founder and CEO of Thinking Machines Lab, discussed the company's focus on human-AI collaboration during an appearance at Bloomberg Tech 2026 in San Francisco on June 3, 2026. Murati described the company's "interaction models," which she said are a new kind of model designed to keep humans in the loop, as opposed to the turn-based model in which an AI cannot perceive new information while thinking. She stated that the company has been working on the foundations of building a frontier AI model for the past year and a half and described the interaction models as a first look at a "concentrated bet towards human AI collaboration." Murati said she expects the company to show increased capabilities on the model side and more products in this direction in the coming months.
Murati emphasized the importance of institutional design, decision-making, and transparency in AI governance, stating that the conversation too often gets wrapped up in the character of individual leaders. She said she has "very high conviction" that the way to continue building frontier AI systems is to keep humans in the loop, likening the process to a "tandem bike" rather than an autonomous system advancing without human involvement. Regarding competition and the company's funding, Murati said Thinking Machines raised significant capital but called the fundraising itself "not any big accomplishment" and said "it's really what you do with that" that matters, noting the company is "not a normal company" and requires substantial capital to build frontier AI systems.
Source: AI-verified profile updated from Mira Murati's recent appearances.
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✨ AI-enhanced transcript with speaker attribution
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Mira Murati0:00
The foundations of building a frontier AI lab, and with the specific focus that we have, and the interaction models, were a first look at our concentrated bet towards human AI collaboration. The reason why we even started Thinking Machines is because we wanted to build a frontier AI lab that's really focused on the human AI collaboration piece. That means a lot of things and there are specific research bets that go into that, but we wanted to showcase our work in one of the first bets through the interaction models. Interaction models are a new kind of model. If you consider the types of models that we work with today, they're very turn-based. You talk, they talk, then they go off and think. Once you've given them a prompt on what you want to do, while they're thinking, it's almost like they're deaf and blind. They cannot perceive anything else about what's going on. Then it's your turn, and while you're talking, they really cannot perceive anything about how you're talking. It's not happening in real time. By contrast, our interactions with each other are very rich. There is a lot of information in our interactions when we are silent, when we're thinking, when we're interacting with one another. Interaction models are able to capture all of this nuance. They're not turn-based; they're more like time-based interaction where they're continuously taking in audio, text, video and continuously providing output. We cut this up in chunks of 20 milliseconds, and this enables you to actually catch things like interruptions and simultaneous speech, and really create a rich, high-bandwidth interaction between humans and machines, which we think is critical to enable agency and enable people to be more in this loop as we advance AI further and further.
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Interviewer2:26
You're basically trying to build an AGI lab from scratch. You've got OpenAI, Anthropic, Google, Meta all with a significant head start. All of them racing to build smarter models. What is the bet that you're making that they aren't, and what do you think they are underestimating?
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Mira Murati2:46
First of all, I think advancing the frontier of AI is incredibly positive sum. There is plenty of space for many different perspectives and ways of developing the technology, and I think plurality is good. Having a plurality of perspectives, ways of building technology, different products is great for the world. However, this is a pretty hard thing to do, which is why we don't actually have many players. The barrier to entry is incredibly high. But in terms of creating something differentiated, I do think there is plenty of room. I have always been very passionate about advancing the frontier of AI systems, and I think there is potential for so much transformation for civilization that comes from that. But it's not a predestined outcome. The way we go about building and deploying the systems really matters. An area where there has been very little work so far is bringing the machine intelligence closer to where the knowledge is. There is one path of advancing frontier AI systems which is very autonomous and doesn't rely too much on the messiness of reality or the experiences humans have day-to-day. Autonomy is definitely a part of it and a very important part, but I think a missing part where we haven't done much work is really focusing on human intent, the messiness of interaction, enabling people more, and conceptually building frontier AI systems more like tools for thought. I think the most advanced AI systems are the most incredible tools for thought that humanity can ever have. How can this change the way we think? It's changing the nature of thought, what we're thinking about. This part is familiar to us. Since the beginning of time, deep technologies have changed what we think about: language, writing, numerals. Imagine if you had to do your multiplication with Roman numerals, it would be miserable. We invented today's numerals, and this enabled a whole area of mathematics. A child can do mathematics very quickly, enabling these very tangible new ways of thought. I think this is the opportunity ahead of us, this possibility to expand what we think about and have new tangible things that we think about. But this requires very intentional research work and product work in this direction.
