The video discusses an AI-driven ETF managed by IBM's Watson, using algorithms from Ekbote. It explains the fund's goals, performance metrics, and the role of human oversight. The ETF aims for long-term capital appreciation, with a focus on matching market volatility. Human involvement is mainly in setting objectives and quality control. The video also explores the limitations and future potential of AI in investing.

What is the primary goal of the AI-driven ETF managed by IBM's Watson?

• To outperform the S&P 500

• To match the volatility of the broader market

• To minimize transaction costs

• To focus on small-cap stocks

How is the performance of the AI-driven ETF evaluated?

• By comparing it to the Dow Jones Industrial Average

• By its ability to reduce transaction costs

• By comparing it to broader market indices like the S&P and Russell 2000

• By its dividend yield

What time horizon is suggested for investors in the AI-driven ETF?

• 3 months

• 6 months

• 12 months

• 24 months

What is the current role of humans in managing the AI-driven ETF?

• Designing new algorithms

• Overriding AI decisions frequently

• Setting objectives and quality control

• Selecting stocks manually

What is one of the limits of AI-driven investing mentioned in the transcript?

• AI cannot process financial data

• AI is limited by the objectives set by humans

• AI cannot handle large datasets

• AI always requires human intervention