Gradient Ventures Founder Anna Patterson

Key Points From This Episode: She shares her professional journey that eventually led to the founding of Gradient Ventures. How Anna would contrast AI Winter to the standard hype cycles that exist. Her thoughts on how the web and mobile sectors were under-hyped. Those who decide if something falls out of favor; according to Anna. How Anna navigates hype cycles. Her process for evaluating early-stage AI companies. How to assess whether someone is a tourist or truly committed to something. Approaching problems and discerning whether AI is the right answer. Her thoughts on the best application for AI or MLR technology. Anna shares why she is excited about large language models (LLMs). Thoughts on LLMs and whether we should or can we approach AGIs. A discussion: do we limit machines when we teach them to speak the way we speak? Quality AI and navigating fairness: the concept of the Human in the Loop. Boring but essential data tasks: whose job is that? How she feels about sensationalism. What gets her fired up when it is time to support new companies. Advice to those forging careers in the AI and ML space. Tweetables: “When that hype cycle happens, where it is overhyped and falls out of favor, then generally that is – what is called a winter.” — @AnnapPatterson [0:03:28] “No matter how hyped you think AI is now, I think we are underestimating its change.” — @AnnapPatterson [0:04:06] “When there is a lot of hype and then not as many breakthroughs or not as many applications that people think are transformational, then it starts to go through a winter.” — @AnnapPatterson [0:04:47] @AnnapPatterson [0:25:17] Links Mentioned in Today’s Episode: Anna Patterson on LinkedIn ‘Eight critical approaches to LLMs’ ‘The next programming language is English’ ‘The Advice Taker’ Gradient How AI Happens Sama