According to @w_thejazz, the question of trusting an autonomous quantum trading bot with a stated 70% win rate to manage $100k highlights critical risk and capital-allocation decisions for systematic traders; source: @w_thejazz on X. The post offers no details on sample size, strategy edge, fees, slippage, or audited live results, so win rate alone cannot determine expectancy, drawdown profile, or tail risk when applied to BTC and ETH markets; source: @w_thejazz on X. Practical takeaway for traders is to require verifiable live performance, define max daily loss and position-size caps, and implement kill-switches before allocating capital to any autonomous system, in line with the caution implied by the source query; source: @w_thejazz on X.

According to @LexSokolin, the first trillion-dollar company fully operated by artificial intelligence will likely originate within the machine economy, with capabilities for continuous self-improvement and non-stop operation. Lex Sokolin highlights Peaq as a potential starting point for this evolution, emphasizing its infrastructure for autonomous machine-driven value creation. This presents significant trading implications for investors focused on the intersection of AI, blockchain, and decentralized machine networks, as platforms like Peaq could become central to the next wave of high-growth crypto assets (source: @LexSokolin).