Reasoning LLMs Deliver Value Today, So AGI Hype Doesnt . . . So now we're getting daily or more stories questioning the value of machine learning, discounting the importance of machine learning, declaiming the feasibility of AGI, downplaying the impact of models on employment, criticizing the hype around it all, predicting crashes in investments, etc
Apple AI boffins puncture AGI hype as reasoning models flail . . . The authors' findings, described in a paper titled, "The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity," indicate that the intellectual potential of such models is so far quite limited Large reasoning models (LRMs), such as OpenAI’s o1 o3, DeepSeek-R1, Claude 3 7
AI collapses under questioning – Apple debunks AGI myth Work shy – so-called large reasoning models mimic patterns, not logic; they generate less thought as problems get harder Hype busting – fundamental limits in transformer-based AI undermine claims about AGI from tech’s biggest hype merchants
Apple’s “The Illusion of Thinking” Is a Wake-Up Call for AI . . . And to be fair, it’s not all bad news Apple’s paper doesn’t say that AI doesn’t reason at all It just points out that reasoning ability plateaus fast—and then collapses The AGI skeptics are having a moment For AGI skeptics and critics of the AI hype cycle, this research is pure vindication
Do reasoning models really think or not? Apple research . . . Unsurprisingly, the paper immediately circulated widely among the machine learning community on X and many readers’ initial reactions were to declare that Apple had effectively disproven much of
AGI Is Not Around the Corner: Why Today’s LLMs Aren’t True . . . Today’s LLMs like GPT-4 and Claude are impressive pattern-recognition tools, but they’re not anywhere near true intelligence Despite the hype, they lack core AGI traits like reasoning, autonomy, and real-world understanding This article cuts through the noise, explaining why fears of imminent AGI are wildly premature
Apple Exposes the Hype: LLMs Cannot Reason. What You Need to . . . And, in turn, the application of algorithmic “reasoning” that can provide new reasoning superpowers to humans, and organizations allike This is why, in part, the 2025 Gartner AI Hype Cycle predicted that Causal AI would become a “high impact” technology in the 2-5 year timeframe, stating: