What is the future of the like button in the age of artificial intelligence? Max Levchin--the PayPal cofounder and Affirm CEO--sees a new and hugely valuable role for liking data to train AI to arrive at conclusions more in line with those a human decisionmaker would make. It's a well-known quandary in machine learning that a computer presented with a clear reward function will engage in relentless reinforcement learning to improve its performance and maximize that reward--but that this optimization path often leads AI systems to very different outcomes than would result from humans exercising human judgment. To introduce a corrective force, AI developers frequently use what is called reinforcement learning from human feedback (RLHF). Essentially they are putting a human thumb on the scale as the computer arrives at its model by training it on data reflecting real people's actual preferences.

CNBC's Jim Cramer bought "Mad Money" back to San Francisco for the first time in two years and talked about the four major innovations and the companies that justify tech as a leader in the stock market. Cramer said the first innovation that's driving value is "how businesses are using artificial intelligence to replace humans, especially because workers are so hard to find now that we're living through the Great Resignation" in the time of Covid. He pointed out that a record-high 4.43 million people quit their jobs in September. "When you think of artificial intelligence, you have to start with Nvidia. Everybody views this one as a semiconductor company, but it's really platform for machine learning," Cramer said.

Welcome to our 11th addition of The FR. This week, we discuss the coming of the robots to financial services and the Bitcoin civil war. We also take a look at "stack fallacy," Max Levchin's Affirm, IEX, Cornell's tech-infused MBA and the little digital bank on the prairie. Is Wall Street destined for Planet of the Robos? According to George Mason University's Robin D. Hanson, it's not a question of if but when the jobs of highly skilled, specialized workers are automated, since computers eventually will have the "mental powers" to do everything humans now do and more (See here).