AI training AI, Trillions, and robots.txt
Plus, a thank you from the Heyday team!
We’re back with another edition of Machine Learnings, brought to you by the folks at Heyday.
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Last week we asked for your support to help us get to #1 on Product Hunt…and you came through for us!
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We’re always releasing useful new tools for you. If your work requires you to connect the dots, try Heyday as your thought partner free for the next two weeks. You deserve a helping hand.
What we're reading.
1/ Let’s start with a critical look at Sam Altman’s $7T plan to push AI chips into the future. Learn more at Quartz >
2/ An amazing look into robots.txt, the file that governs what web crawlers can and can’t do. It’s been a stable era, but what’s next? Learn more at The Verge >
3/ Unless you were living under a rock, you probably saw OpenAI’s new video creation tool, Sora, last week. It’s a bit mind-boggling, but will it hold up to the generative use cases we’re seeking? Learn more at OpenAI >
4/ Everyone on the face of the Earth knows that AI is going to generate chaos during the 2024 Election cycle. That’s driving work from major AI firms to experiment with solutions to election manipulation. How will a prompt shield work? Learn more at The New York Times >
5/ Scale isn’t all you need. Google AI leader, Demis Hassibis, walks through the angles his team at DeepMind are looking into to push AI into the future, and it’s not just chips. Learn more at WIRED >
6/ Professional tennis has used AI to assist referee decisions for the past few years, so it serves as a nice platform to analyze how AI is impacting human behavior. The core question – if refs are more likely to quiet down, what’s that mean for the rest of us? Learn more at The Economist >
7/ Let’s close with a weird one, that’s soon-to-be a bit more reality than thought experiment. What happens when AI starts training itself, on AI? Learn more at The Atlantic >
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