“Recursive self-improvement” is the idea that artificial intelligence could learn to build and train itself, creating exponential new progress — and risk. Jeff Clune, a computer scientist and ...
How do you get from a chatbot that sometimes makes things up to a machine that humans might struggle to control? There are several steps in that argument, and plenty of uncertainty. But an idea known ...
The US-China race for artificial intelligence dominance has entered a new phase: using AI to build better AI. Leading AI companies in the United States and China are increasingly focused on deploying ...
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Simplify any Excel formula with LAMBDA
Learn how to use the LAMBDA function in Excel to create custom functions for recurring calculations. Simplify complex formulas and transform them into user-friendly solutions. **Chapters:** 0:00 - ...
Anthropic reportedly signed a $35 billion Lambda cloud deal tied to a Texas data center leased by Nvidia and developed by Hut 8 for Claude computing capacity. Anthropic expands AI compute footprint ...
Anthropic has signed a cloud-computing deal worth $35 billion with Nvidia NVDA-1.43%decrease; down pointing triangle-backed cloud provider Lambda, with Nvidia itself holding the lease on the data ...
Lambda, an AI cloud company that buys computing chips and rents them out to businesses, has raised $1 billion in private, short-dated debt to buy Nvidia’s AI chips that it will lease to Microsoft, ...
AI agents are not yet creative enough to carry out genuinely innovative open-ended AI research, it seems. The AI industry’s boldest promise right now is that AI will soon improve itself, with almost ...
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On Tuesday, the AI company Recursive Superintelligence announced a $410 million compute deal with Amazon Web Services. The company, which emerged from stealth in May with $650 million in funding, is ...
The US AI research company Anthropic has become known for building powerful AI models while simultaneously warning about their dangers. “We are not there yet, and recursive self-improvement is not ...
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