TAOTAO(Bittensor) Price

Bittensor price$ 550.02Bittensor prediction $ 709.64 (30.33%)Sentiment BearishFear & Greed index 72 (Greed)Key support levels$ 487.74, $ 432.78, $ 354.09Key resistance levels$ 621.39, $ 700.08, $ 755.04TAO price is expected to rise by 30.33% in the next 5 days according to our Bittensor price prediction

Two Fields Medalists, Terence Tao and Maryna Viazovska, share a common view on the flood of AI-generated proofs in mathematics: the community must learn to "digest" them. While AI can rapidly produce and even formally verify proofs, Tao argues that a correct proof is only the first step. For a result to become usable knowledge, it must be understood, absorbed, and integrated into the existing mathematical framework by human mathematicians. He illustrates this by spending several days "digesting" an AI-assisted proof of the long-standing Sendov conjecture. His process involved tracing sources, identifying key ideas, simplifying the argument, and rewriting it into a human-readable narrative. This digestion not only verified the proof but also revealed it could solve a stronger conjecture and be presented with more elementary tools. Tao criticizes the current race for priority based solely on who announces a proof first, often skipping verification and explanation. He proposes shifting value to the crucial work of interpreting, reviewing, and consolidating results. In his recent ICM talk, he emphasized that if authors cannot explain their AI-generated proof to peers, it shouldn't be published. To facilitate this new workflow, Tao introduced "Palomar," a registry for Lean-verified results. It serves as a digestion hub, cataloging problems, proof code, and AI involvement, aiming to coordinate efforts and ensure completeness. Under this model, full credit for a result would require multiple milestones: generation, verification, explanation, and final publication. The core message is clear: as AI transforms the front end of mathematical discovery, the irreplaceable role of mathematicians will be to synthesize, contextualize, and communicate these advances, turning raw outputs into enduring knowledge.

Apple's CEO Tim Cook unveiled the company's final major chip updates under his tenure, introducing the first 2nm chip M6 and the powerful M5 Ultra with a quad-die architecture. The M6, featured in the new Mac mini, offers up to 4x faster AI performance and a starting price of 6,999 RMB, a significant increase from its predecessor. The M5 Ultra powers the Mac Studio with up to 36-core CPU, 80-core GPU, and a massive 512GB of unified memory, delivering up to 4.3x faster AI performance than the M3 Ultra. Both chips emphasize enhanced on-device AI capabilities, positioning Macs for agentic workflows and local large language model inference. However, high demand for memory in the AI sector has led to supply constraints, with the 512GB Mac Studio model delayed until late October. These releases mark a strategic push into high-performance AI computing for Apple's desktop lineup as Cook prepares to step down.