WIRED: Bringing more computer power to the Game of Generative Artificial Intelligence (Google DeepMinds) after Sam Altman

In the last few years, increasing the amount of computer power and data used in training an AI model is the thing that has driven amazing advances. It’s been said that Sam Altman wants to raise up to $7 trillion for more artificial intelligence. Is there more computer power that will change the game of general intelligence?

WIRED: Gemini Pro 1.5 can take vastly more data as an input than its predecessor. It is also more powerful due to the mixture of experts. What do these things matter?

You can now consume a small film. I can imagine that being super useful if there’s a topic you’re learning about and there’s a one-hour lecture, and you want to find a particular fact or when they did something. There will be a lot of really cool use cases for that.

Google researchers came up with several of the ideas that went into building ChatGPT, yet the company chose not to commercialize them due to misgivings about how they might misbehave or be misused. Hassabis has overseen a dramatic shift in pace of research and releases with the rapid development of the multi-modal artificial intelligence model “Gemini” that is already powers some of the most popular and effective products on the internet. The company announced a quick-fire upgrade to their free version of the Gemini Pro 1.5, which is more powerful for its size and can analyze vast amounts of text, video, and audio at a time.

Google DeepMind CEO Demis Hassabis has recently at least given Sam Altman some healthy competition, leading the development and deployment of an AI model that appears both as capable and as innovative as the one that powers OpenAI’s barnstorming bot.

The company rode a lot of excitement and hype generated by a remarkable, garrulous, and occasionally bizarre program named CHATGPT, which made it difficult to knock them off their perch.

With the shift in the applications of Artificial Intelligence, there is a need for subject matter experts to work with data in order to produce knowledge and content. As the tech industry has rushed to embrace generative AI over the past year and applied it to more sophisticated tasks, data providers have needed a new intake of contractors capable of what Primack calls “expert fact-checking.”

Jay fell in love with math after being introduced to the joy of complex mathematics by a physics teacher. He studied math and physics in college and wanted to pass down his knowledge to a new generation. In October 2022, Jay answered a job post for a math expert who wanted to grade equations on an online platform. But he would not be inspiring budding young mathematicians like his past self. He would train an artificial intelligence system that may eventually make his expertise obsolete.

Jay said he knew he was going to work for the company when he was invited to join the openai workspace in chat. A screenshot he shared with WIRED shows he was part of a group, called “math trainers,” that was set up by the OpenAI researcher Yuri Burda. But Jay was not working directly for the famous AI company. Instead he was being paid by one of the world’s biggest data labor platforms, called Remotasks, a subsidiary of US startup Scale AI, which was valued at over $7 billion back in 2021 and counts OpenAI, Meta, Microsoft, and the US Army among its clients.