Two prominent scientists from Google’s DeepMind, Laurent Sifre and Karl Tuyls, are making waves in the tech industry as they seek investor funding for their own AI startup based in Paris. While Google has not yet confirmed their departure, sources familiar with the matter revealed that Sifre and Tuyls have been engaging in discussions with potential investors for a financing round that exceeds $220 million.
Laurent Sifre’s notable contributions include being a co-author of research papers on the revolutionary AlphaGo, an AI model that achieved unprecedented success in playing the complex board game Go. In 2017, AlphaGo defeated the world’s number one ranked player, signaling a significant milestone in AI advancement. Karl Tuyls, on the other hand, is widely recognized for his expertise in game theory and reinforcement learning for AI models.
The departure of DeepMind scientists to form their own AI startup is not a novel occurrence within Google. The tech giant has witnessed multiple instances of employees leaving to establish their ventures. Notably, OpenAI, the company behind ChatGPT and GPT, comprises several former Google employees who have ventured into the field of AI innovation.
In a June 2023 interview with Bloomberg, Google CEO Sundar Pichai expressed support for employees branching out to create startups, emphasizing the positive impact it has on the industry. Pichai stated, “Googlers have left to create over 2,000 startups, last I counted, and I think that’s great. Some of them are cloud customers down the line for us. Some of them come back. I think it’s healthy.”
As Sifre and Tuyls pave their path in the AI startup ecosystem, their venture has garnered significant attention from potential investors. With their expertise and experience at DeepMind, their startup holds the potential to further revolutionize the field of artificial intelligence and contribute to advancements in technology.
FAQ:
1. Who are Laurent Sifre and Karl Tuyls?
Laurent Sifre and Karl Tuyls are prominent scientists who work for Google’s DeepMind. They are known for their expertise in the field of artificial intelligence (AI) and have made significant contributions to the development of AI models like AlphaGo.
2. What are Laurent Sifre’s notable contributions?
Laurent Sifre is known for being a co-author of research papers on AlphaGo, an AI model that achieved groundbreaking success in playing the complex board game Go. In 2017, AlphaGo defeated the world’s number one ranked player, marking a major milestone in AI advancement.
3. What is Karl Tuyls’ expertise?
Karl Tuyls is widely recognized for his expertise in game theory and reinforcement learning for AI models.
4. Are Sifre and Tuyls leaving DeepMind?
While Google has not yet confirmed their departure, sources familiar with the matter have revealed that Sifre and Tuyls have been engaging in discussions with potential investors for their own AI startup based in Paris.
5. Is it common for employees to leave Google to form their own ventures?
Yes, it is not uncommon for employees to leave Google and establish their startups. OpenAI, for example, is a company that comprises several former Google employees who have ventured into the field of AI innovation.
6. What was Google CEO Sundar Pichai’s response to employees creating startups?
In a June 2023 interview with Bloomberg, Sundar Pichai expressed support for employees who branch out to create startups. He emphasized that it has a positive impact on the industry and mentioned that many of these startups become cloud customers for Google.
Definitions:
1. AI (Artificial Intelligence) – refers to the development of computer systems that can perform tasks that would typically require human intelligence, such as speech recognition, problem-solving, and learning.
2. AlphaGo – an AI model developed by DeepMind that made headlines in 2017 when it defeated the world’s number one ranked player in the board game Go. It was considered a significant achievement in the field of AI.
3. Game theory – a branch of mathematics that deals with strategic decision-making in situations where the outcome of one person’s decision depends on the decisions of others. It has applications in various fields, including economics and computer science.
4. Reinforcement learning – an area of machine learning where an AI agent learns to perform actions in an environment to maximize a reward signal. It involves trial and error learning and is often used in tasks involving decision-making and optimization.
Suggested related link:
DeepMind – DeepMind’s official website for more information about their research, projects, and AI advancements.
The source of the article is from the blog maltemoney.com.br