Breaking news

Google AI Veterans Launch Startup To Accelerate Scientific Discovery

A group of senior Google researchers, led by longtime executive Jeff Dean, is leaving the company to launch Discovery Loop, a startup that aims to accelerate scientific research using artificial intelligence.

Dean, one of Google’s earliest employees, will serve as chief executive. He is joined by Google Fellow Sanjay Ghemawat, Google Brain co-founder Quoc Le and Google DeepMind senior research scientist Oriol Vinyals.

AI-Powered Research

Discovery Loop plans to use AI to automate the design, execution and refinement of thousands of experiments simultaneously, with the goal of speeding up scientific discovery. The company also intends to explore how AI can help improve future generations of AI systems through recursive self-improvement.

“While science and engineering have tremendously advanced society over past centuries, progress has traditionally relied on slow, sequential human iterations,” the company said. “Discovery Loop is developing advanced AI systems that leverage massive computational scale to fundamentally transform the speed and efficiency of innovation.”

Backed By Alphabet And Venture Investors

The startup has already secured funding from Alphabet alongside venture capital firms Radical Ventures, Khosla Ventures, Kleiner Perkins, Lightspeed and Doerr Capital.

“The next great frontier for AI is to go beyond answering questions and to begin making discoveries,” the founding team said.

Dean joined Google in 1999 as the company’s 30th employee and helped build key parts of Google Search before leading major AI initiatives, including work on Gemini. Explaining the vision behind Discovery Loop, he said AI could automate much of today’s research process, enabling scientists to conduct more experiments and accelerate breakthroughs.

Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

Uol
Aretilaw firm
The Future Forbes Realty Global Properties
eCredo

Become a Speaker

Become a Speaker

Become a Partner

Subscribe for our weekly newsletter