"The race to build artificial general intelligence is colliding with a harsh reality: Large language models might be maxed out. For years, the world's top AI tech talent has spent billions of dollars developing LLMs, which underpin the most widely used chatbots. The ultimate goal of many of the companies behind these AI models, however, is to develop AGI, a still theoretical version of AI that reasons like humans."
"Principal among them is perhaps Gary Marcus, an AI leader and best-selling author. Since GPT-5's release, he's taken his criticism to new heights. "Nobody with intellectual integrity should still believe that pure scaling will get us to AGI," he wrote in a blog post earlier this month, referring to the costly strategy of amassing data and data centers to reach general intelligence. "Even some of the tech bros are waking up to the reality that 'AGI in 2027' was marketing, not reality.""
"OpenAI is now the most valuable startup on the planet. It has raised about $60 billion, and a discussed secondary share sale could push the company's valuation over $500 billion. That would make OpenAI the most valuable private company in the world. There are good reasons for the excitement. According to the company, ChatGPT has 700 million weekly users, and OpenAI's products have largely set the pace of the AI race."
Large language models may be reaching performance plateaus despite years of heavy investment. Billions of dollars and extensive compute have produced LLMs that power the most widely used chatbots, but these models remain far from artificial general intelligence. Recent high-profile model releases improved capabilities but failed to meet ambitious expectations, reinforcing the view that pure scaling of data and compute is not a guaranteed path to AGI. Some AI researchers argue that accumulating data centers and training larger models will not bridge fundamental gaps in reasoning. Market enthusiasm and massive user numbers coexist with growing skepticism about long-term trajectories.
Read at Business Insider
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