The most underreported and important story in AI right now is that pure scaling has failed to produce AGI
Recent developments suggest that the scaling hypothesis in AI - investing massive resources in data and GPUs to achieve artificial general intelligence - is hitting significant limitations. Major tech companies and investors are acknowledging diminishing returns from pure scaling approaches, with persistent issues like hallucinations and unreliability remaining unsolved. A market correction appears likely as the industry grapples with sustainability concerns and the need for new innovative approaches.