For fifty years, the semiconductor industry ran on one rule: make the transistor smaller, and everything gets faster. You did not need a strategy. Physics did the work. Every new generation of chip delivered 30 to 50% more transistors on the same surface area, and the entire digital economy rode that escalator upward. A single, consistent dynamic fuels everything from your phone and laptop to artificial intelligence.
… That rule is dying. And how the two companies that matter most in semiconductor manufacturing respond to its death will reshape the chip industry for the next decade. — Read More
Daily Archives: June 2, 2026
Everyone Has an AGI Date. Here’s the Math Behind Each One.
Elon Musk says AGI by 2026. Sam Altman says the end of the decade. Dario Amodei at Anthropic described systems “better than almost all humans at almost everything” by 2026 or 2027. Shane Legg of Google DeepMind gives roughly 50% odds for minimal AGI by 2028. Jensen Huang says 2029. Ray Kurzweil, who first published his prediction in 2005, holds firm at 2029 for AGI and has since moved his broader singularity timeline to around 2032. Yann LeCun thinks AGI is decades away, not years. Geoffrey Hinton says somewhere between 2028 and 2043.
These are not random guesses from random people. These are the individuals building, funding, and directing the most consequential AI systems on Earth. And their estimates span a range of nearly 40 years. So the question is not who is right, because nobody knows.
What reasoning produces each of these dates? Once you understand the math underneath the predictions, you understand what each person actually believes about the future, and what assumptions they are making that they rarely explain in public. — Read More
Rethinking Search as Code Generation
Search is a core primitive for AI systems. Frontier models grow more capable by the month, but they still need access to fresh, accurate, and well-curated knowledge from the wider world. Search is the primary way that AI systems tap into that knowledge, and thus a foundational component of any product that needs to draw conclusions, take actions, and perform real-world work.
We believe that traditional search pipelines are increasingly outdated in the era of agents. Traditional search answers queries, but today’s agents complete tasks that can take on countless shapes. These tasks require agents to define task-specific retrieval strategies directly within their harnesses. Within Perplexity Computer, we’ve seen single tasks invoke hundreds or even thousands of retrieval operations within a few minutes: a workflow that is impossible for humans but absolutely natural for agents.
In this world, search itself must become agentic, with its building blocks accessible directly as SDKs within the agent harness. We are introducing Search as Code (SaC) as Perplexity’s new reference search architecture. — Read More
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