Geoffrey Hinton: AI consciousness and superintelligence timeline
Geoffrey Hinton dey talk say AI fit get consciousness already. For Big Technology Podcast interview, e talk say intelligence no need to only belong to biological beings.
Hinton come still talk say current AI dey improve fast. E mention one chatbot wey produce proof for one Erdos conjecture and say AI fit create and test new mathematical ideas without external data—kinda like AlphaGo self-play.
About AGI, Hinton say progress dey near but e no balanced. E reject the idea say AGI go match humans "for everything all at the same time," and say AI go strong for some tasks and weak for others.
E expect superintelligence in about 20 years, and note say many experts agree say e go happen even if their timelines differ.
Finally, Hinton suggest say chatbots fit already show understanding. E argue say if system fit answer correct after misunderstanding then e must dey reason—not just produce statistics. E add say talking about AI consciousness fit raise safety concerns and start ethical debate.
Market note for crypto traders: this no be direct protocol or token news. But narratives about AI safety and rapid capability gains fit change risk appetite for AI-related equities/ETFs and wider tech sentiment—which often affect crypto through correlation.
Neutral
Dis story na dey basically about AI consciousness and di long-term debate about superintelligence/AGI, no be about crypto protocols, listings, regulation, or on-chain flows. So e mean say direct impact for token prices low.
But e fit still affect market sentiment through di tech narrative channel. For history, wen AI capability milestones (like major model releases or big jumps for high-profile benchmarks) show, e sometimes boost “risk-on” positioning for tech — including AI-linked equities/ETFs and indirectly crypto — especially when traders dem dey expect more funding and adoption. On the other hand, if di focus shift to AI safety and existential-risk concerns, sentiment fit turn to caution.
Short term, traders go likely treat am as commentary rather than catalyst. Long term, if market begin price AI-driven productivity gains more while dey also debate safety, e fit maintain small structural tailwind for AI-themed risk — without giving clear bullish or bearish directional trigger for specific tokens.