Two Google DeepMind Scientists Seek to Launch AI Startup

In a notable development within the field of artificial intelligence (AI), two scientists affiliated with Google DeepMind, the AI division of Alphabet, are reportedly in discussions with investors to establish their own AI startup in Paris. Laurent Sifre and Karl Tuyls, both renowned figures in the AI community, are said to be leading this initiative.

Laurent Sifre, a prominent DeepMind researcher and co-author of the groundbreaking 2016 research on Go, is recognized for his significant contributions to AI. Karl Tuyls, on the other hand, is known for his expertise in game theory and multi-agent reinforcement learning. Together, they bring a wealth of knowledge and experience to their proposed venture.

While the exact details remain undisclosed, sources suggest that Sifre and Tuyls have engaged in discussions with potential investors for a substantial financing round that could exceed EUR 200 million ($220 million). The startup, tentatively named Holistic, aims to focus on the development of a new AI model that could revolutionize the industry.

This move by the Google DeepMind scientists aligns with a growing trend in the AI landscape, where former employees of major tech companies establish their own startups. Mistral AI, a competitor of OpenAI, achieved a valuation of approximately $2 billion by the end of 2023. Similarly, Kyutai, a nonprofit AI research lab, secured EUR 300 million in initial funding upon its formation in November of the same year.

Acknowledging this trend, Google CEO Sundar Pichai has expressed support for employees venturing into their own startups. He believes that such initiatives are healthy, highlighting that thousands of Googlers have left to create their own companies. Pichai sees this as an opportunity for future collaborations and welcomes the return of these entrepreneurial endeavors.

As Sifre and Tuyls prepare to embark on their own AI startup journey, the industry eagerly anticipates the groundbreaking contributions they will bring, pushing the boundaries of AI technology even further.

Frequently Asked Questions

1. Who are the scientists behind the AI startup?
– The scientists behind the AI startup are Laurent Sifre and Karl Tuyls. They are affiliated with Google DeepMind, the AI division of Alphabet.

2. What are Laurent Sifre and Karl Tuyls known for?
– Laurent Sifre is a prominent DeepMind researcher and co-author of the groundbreaking 2016 research on Go. Karl Tuyls is known for his expertise in game theory and multi-agent reinforcement learning.

3. What is the proposed venture of the AI startup?
– The proposed venture aims to focus on the development of a new AI model that could revolutionize the industry.

4. How much funding are Sifre and Tuyls seeking for their startup?
– The exact details remain undisclosed, but sources suggest that they have engaged in discussions with potential investors for a substantial financing round that could exceed EUR 200 million ($220 million).

5. Do other former employees of tech companies establish their own startups?
– Yes, there is a growing trend in the AI landscape where former employees of major tech companies establish their own startups. For example, Mistral AI achieved a valuation of approximately $2 billion and Kyutai secured EUR 300 million in initial funding.

6. What is Google CEO Sundar Pichai’s stance on employees venturing into their own startups?
– Sundar Pichai expressed support for employees venturing into their own startups. He believes it is a healthy trend and sees it as an opportunity for future collaborations with Google.

Key Terms

– Artificial intelligence (AI): The simulation of human intelligence in machines that are programmed to think and learn like humans.
– DeepMind: The AI division of Alphabet, the parent company of Google.
– Game theory: The study of mathematical models of strategic decision-making between players or agencies.
– Multi-agent reinforcement learning: A branch of AI that involves learning from interactions in a multi-agent system, where multiple agents learn to maximize their overall performance.

Related Links

DeepMind
OpenAI

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