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@omarsar0

The Illusion of Thinking in LLMs Apple researchers discuss the strengths and limitations of reasoning models. Apparently, reasoning models "collapse" beyond certain task complexities. Lots of important insights on this one. (bookmark it!) Here are my notes: https://t.co/Ct1a7LpvqO

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                                  "text": "It's Not a Wall, It's a Fork in the Road.\nThinking that LLMs are \"hitting a wall\" is like looking back at the 1980s and concluding that computer progress stalled because single-core processor speeds plateaued. What happened next wasn't a stop, but a paradigm shift into multi-core processors, GPUs, and distributed computing. The path of innovation didn't end; it branched out.\nToday, we are at a similar fork in the road. The era of achieving easy gains simply by adding more layers and data, through pure vertical scaling, is likely coming to an end. But this isn't a dead end. Instead, progress is now accelerating horizontally into more sophisticated and efficient systems. This is the new frontier of multimodal models that can process video and sound, agentic AI that can execute tasks, and novel architectures that move beyond the transformer.\nThis shift demands more creativity and ingenuity than just building bigger models. It also grounds us in reality: while these new routes are exciting, the road to AGI is likely much longer and more complex than the current hype might suggest.",
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