This edition explores forecasts and implications around: (1) business models likely to become antiquated as AI proliferates in more industries, (2) reflections on another round of AI launches in the creative world, and (3) some provocative data and surprises at the end, as always.
If you’re new, here’s the rundown on what to expect. This ~monthly analysis is written for founders + investors I work with, colleagues, and a small group of subscribers. I aim for quality, density, and provocation vs. frequency and trendiness. My goal is to ignite discussion and add some kindling to the fire of feedback and serendipitous dot connecting. — Read More
Daily Archives: October 23, 2023
ScaleAI wants to be America’s AI arms dealer
Alexandr Wang grew up in the shadow of the Los Alamos National Laboratory — the birthplace of the nuclear bomb. Now, the 26-year-old CEO of artificial intelligence company ScaleAI intends to play a key role in the next major age of geopolitical conflict.
Scale, which was co-founded by Wang in 2016 to help other companies organize and label data to train AI algorithms, has been aggressively pitching itself as the company that will help the U.S. military in its existential battle with China, offering to help the Pentagon pull better insights out of the reams of information it generates every day, build better autonomous vehicles and even create chatbots that can help advise military commanders during combat.
… In May, Scale became the first AI company to have a “large language model” — the tech behind chatbots such as ChatGPT — deployed on a classified network after it signed a deal with the Army’s XVIII Airborne Corps. Scale’s chatbot, known as “Donovan,” is meant to summarize intelligence and help commanders make decisions faster. — Read More
“Math is hard” — if you are an LLM – and why that matters
Some Reply Guy on X assured me yesteday that “transformers can multiply”. Even pointed me to a paper, allegedly offering proof.
The paper turns out to be pretty great, doing exactly the right test, but it doesn’t prove what its title alleges. More like the opposite.
The paper alleges “GPT Can Solve Mathematical Problems Without a Calculator.” But it doesn’t really show that, except in the sense that I can shoot free throws in the NBA, Sure, I can toss the ball in the air, and sometimes I might even sink a shot, the more so with practice; but I am probably going to miss a lot, too. And 70% would be great for free throws; for multiplication it sucks. 47323 * 19223 = 909690029 and it shall always be; no partial credit for coming close. — Read More
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models
We investigate the potential implications of large language models (LLMs), such as Generative Pre-trained Transformers (GPTs), on the U.S. labor market, focusing on the increased capabilities arising from LLM-powered software compared to LLMs on their own. Using a new rubric, we assess occupations based on their alignment with LLM capabilities, integrating both human expertise and GPT-4 classifications. Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19% of workers may see at least 50% of their tasks impacted. We do not make predictions about the development or adoption timeline of such LLMs. The projected effects span all wage levels, with higher-income jobs potentially facing greater exposure to LLM capabilities and LLM-powered software. Significantly, these impacts are not restricted to industries with higher recent productivity growth. Our analysis suggests that, with access to an LLM, about 15% of all worker tasks in the US could be completed significantly faster at the same level of quality. When incorporating software and tooling built on top of LLMs, this share increases to between 47 and 56% of all tasks. This finding implies that LLM-powered software will have a substantial effect on scaling the economic impacts of the underlying models. We conclude that LLMs such as GPTs exhibit traits of general-purpose technologies, indicating that they could have considerable economic, social, and policy implications. — Read More
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