Alphabet merges with DeepMind and Google Brain. The move aims to bring two AI-focused groups closer amid all the AI competition around the globe.
Accelerating the AI Progress
Google bought DeepMind for a reported $500 million, and since then it has run as an independent unit out of the U.K. DeepMind has done a lot of futuristic work, such as showcasing its incredibly high ability to play the game of Chess in a very unique way.
In a blog post on Thursday, Alphabet merges with DeepMind and Google Brain, CEO Sundar Pichai said “Combining all this talent into one focused team, backed by the computational resources of Google, will significantly accelerate our progress in AI,”
Google’s Current AI efforts are led by Jeff Dean, and he will be promoted to the title of chief scientist, reporting to Sundar Pichai. Jeff will lead the most critical and strategic technical AI-centric projects. Including a series of powerful AI Models.
Google vs. OpenAI
This reorganization by Alphabet merges with DeepMind and Google Brain is a response to the rapidly growing AI space and its developments after the launch of chatGPT by OpenAI last year. Sundar Pichai says “The pace of progress is now faster than ever before,” “To ensure the bold and responsible development of general AI, we’re creating a unit that will help us build more capable systems more safely and responsibly.”
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DeepMind vs. Brain
DeepMind, as it ran separately from Google’s core research, was able to move quickly and make breakthroughs such as AlphFold, which can predict 3D models of protein structures. Reportedly, DeepMind and Google Research have had tensions in the past, which led to DeepMind seeking more independence.
Demis Hassabis, CEO of DeepMind will be leading the development of “the most capable and responsible general AI systems,” said Sundar Pichai. He added that the research “will help power the next generation of our products and services.”
Google Brain, on the other hand, is focused on AI and machine learning. According to Pichai, Google Research will continue to work on areas such as algorithms and theory, privacy and security, quantum computing, health, and responsible AI.