Funston Brief (Issue No. 5)
This month, our featured stories dive into the new developments in AI and machine learning and their implications for business owners. We also offer some actionable insights around decision-making.
During the past couple of months, we have witnessed some interesting announcements in the world of AI and machine learning with the launch of DALL-E 2 as well as some great conversations around AI safety, sentience, and a number of other interesting topics. Ryan Fedasiuk has a good opinion piece on near-term AI safety in Foreign Policy. In it, he argues that one of the most immediate ways AI could be dangerous is its integration into military technology, where accidents or unexpected behavior could be disastrous.
Another interesting and significant debate was sparked by the Blake Lemoine story that ran in the Washington Post. Lemoine, a Google engineer, has been suspended from his job after claiming that LaMDA, a large language model similar to GPT-3, is sentient. The full transcript of the conversation Lemoine had with LaMDA can be read here. I share the general consensus that conversations like this do not mean that the model is sentient (a good thread on this.) That said, it’s beyond a doubt, that large, pre-trained machine learning models like GPT-3 or DALL-E are one of the most important milestones so far in the history of AI. However, there’s controversy around them with one of the most influential critiques being this paper by Emily Bender who argues that, despite their impressive outputs, the models are not actually “thinking” or “understanding.”
ACTIONABLE INSIGHTS.
How to use massive AI models: As machine learning technology has matured and moved from research curiosity to something industrial-grade, the methods and infrastructure needed to support large-scale machine learning have also evolved. Companies can take advantage of these advances and leverage machine learning models (e.g., GPT-3) in one way or another as they compete for a piece of their respective markets.
Key Insight: The use of pre-trained networks allows a smaller company, for example, to build a product with much less data and compute resources than would otherwise be needed if starting from scratch. Link
How to make talent scouts work for you: Tyler Cowen and co-author Daniel Gross have a new book out titled - Talent: How to Identify Energizers, Creatives, and Winners Around the World. One way or another, we are all engaged in the quest for talent. Cowen and Gross aim to identify when you should rely on scouting for talent acquisition, rather than taking all of the work upon yourself.
Key insight: The book is a great read for CEOs as it gets to the heart of talent acquisition and how to sustainably grow a business. I’d recommend pairing it with this podcast where co-author Daniel Gross is a guess. Link
EAR TO THE GROUND.
Podcast Episode: Securities - Risk, Bias, and Decision Making: Pre-mortems
Guest: Danny Kahneman, Annie Duke, Michael Mauboussin
Takeaway:
Josh Wolfe, a Managing Partner at Lux Capital, invited three celebrated decision and risk specialists for a lunch to discuss the latest academic research and empirical insights from the world of psychology and decision sciences. The lunch featured Danny Kahneman, who won the 2002 Nobel Prize in Economics for his work on decision sciences. His book Thinking Fast and Slow has been a major bestseller and summarizes much of his work in the field. Annie Duke, a World Series of Poker champion who researches cognitive psychology at the University of Pennsylvania was also a guest. Her books How to Decide and Thinking in Bets have also been tremendously influential best sellers, and she is also the co-founder of the Alliance for Decision Education. Last, Michael Mauboussin, the Head of Consilient Research at Counterpoint Global and who has also taught finance for decades at Columbia, rounded the list. His book More Than You Know is similarly a major bestseller. The guests together with Wolfe discussed the concept of pre-mortems, an approach to look at the outcome of a decision and if it were to fail, why we think it would fail. It’s an approach that’s designed to overcome groupthink and avoid the fact that pessimists are really unpopular in group decision-making sessions. However, recent research has shown that they don’t always help people and groups change their minds.
“What could go wrong? I’ve indoctrinated people internally with this quote that <<Failure comes from a failure to imagine failure.>>”
- Josh Wolfe, Co-Founder and Managing Partner at Lux Capital
24,000
After a banner year for tech, layoffs are here. In fact, as of the beginning of July, more than 24,000 workers in the U.S. tech sector have been laid off in mass job cuts so far in 2022, according to a Crunchbase News tally. Link
PROFILE.
Billionaire brothers John and Patrick Collison built Stripe into one of the world’s most-hyped, highest valued - and profitable! - startups, worth some $95 billion. Now they must stave off going from disruptor to disrupted. This Forbes article dives inside their plan to stay on top.
"The vision has always been, 'Why can’t we move money around in the cloud the same way that we can move data?' Because isn’t money just data?"
ON MY RADAR.
OpenAI announced DALLE-2 - a generative AI system that can create new images based on natural language requests. The demo is amazing and I invite you to try it. Link
About
Funston Brief is a newsletter by Funston Capital, LLC. We’re an investment company located in San Francisco, CA looking to acquire an already profitable and growing tech-enabled business. If you or anyone you know is interested in selling a business, please reach out to me at alex@funstoncap.com!
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