As far as I’m aware, Anthropic is the only AI company with official AGI timelines[1]: they expect AGI by early 2027. In their recommendations (from March 2025) to the OSTP for the AI action plan they say:
As our CEO Dario Amodei writes in ‘Machines of Loving Grace’, we expect powerful AI systems will emerge in late 2026 or early 2027. Powerful AI systems will have the following properties:
Intellectual capabilities matching or exceeding that of Nobel Prize winners across most disciplines—including biology, computer science, mathematics, and engineering.
They often describe this capability level as a “country of geniuses in a datacenter”. — Read More
Daily Archives: November 4, 2025
The Great Decoupling of Labor and Capital
Almost two decades ago, Hewlett-Packard (HP) was the first tech company to exceed $100 Billion annual revenue threshold in 2007. At that time, HP had 172k employees. The very next year, IBM joined the club, but IBM had almost 400k employees.
Today’s megacap tech companies all exhibit a common characteristics: their growth is pretty much decoupled from their headcount. Intuitively, this might not be a news to anyone, but when I sat down and carefully jotted the numbers, the extent of the decoupling even before Generative AI truly came to the scene was a bit astonishing to me. — Read More
Remote Labor Index:Measuring AI Automation of Remote Work
AIs have made rapid progress on research-oriented benchmarks of knowledge and reasoning, but it remains unclear how these gains translate into economic value and automation. To measure this, we introduce the Remote Labor Index (RLI), a broadly multi-sector benchmark comprising real-world, economically valuable projects designed to evaluate end-to-end agent performance in practical settings. AI agents perform near the floor on RLI, with the highest-performing agent achieving an automation rate of 2.5%. These results help ground discussions of AI automation in empirical evidence, setting a common basis for tracking AI impacts and enabling stakeholders to proactively navigate AI-driven labor automation. — Read More
#strategyCoca-Cola | Holidays are Coming, Behind the Scenes, Classical 2:42
The secret to sustainable AI may have been in our brains all along
Researchers have developed a new method for training artificial intelligence that dramatically improves its speed and energy efficiency by mimicking the structured wiring of the human brain. The approach, detailed in the journal Neurocomputing, creates AI models that can match or even exceed the accuracy of conventional networks while using a small fraction of the computational resources.
The study was motivated by a growing challenge in the field of artificial intelligence: sustainability. Modern AI systems, such as the large language models that power generative AI, have become enormous. They are built with billions of connections, and training them can require vast amounts of electricity and cost tens of millions of dollars. As these models continue to expand, their financial and environmental costs are becoming a significant concern. — Read More
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