The White House is poised to make an all-hands effort to impose national rules on a fast-moving technology, according to a draft executive order.

President Joe Biden will deploy numerous federal agencies to monitor the risks of artificial intelligence and develop new uses for the technology while attempting to protect workers, according to a draft executive order obtained by POLITICO.

The order, expected to be issued as soon as Monday, would streamline high-skilled immigration, create a raft of new government offices and task forces and pave the way for the use of more AI in nearly every facet of life touched by the federal government, from health care to education, trade to housing, and more. — Read More

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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

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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For much of the last year, it’s felt like Large Language Models (LLMs) have been the only game in town. While the State of AI Report predicted that transformers were emerging as a general purpose system back in 2021, significant advances in capabilities caught both the AI community and wider world by surprise, with implications for research, industry dynamics, and geopolitics.

Last year’s State of AI report outlined the rise of decentralization in AI research, but OpenAI’s GPT-4 stunned observers as big tech returned with a vengeance. Amid the scrabble for ever more compute power, challengers have found themselves increasingly reliant on its war chest. At the same time, the open source community continues to thrive, as the number of releases continues to rocket. — Read More

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The buzzy generative artificial intelligence space is due something of a reality check next year, an analyst firm predicted Tuesday, pointing to fading hype around the technology, the rising costs needed to run it, and growing calls for regulation as signs that the technology faces an impending slowdown.

In its annual roundup of top predictions for the future of the technology industry in 2024 and beyond, CCS Insight made several predictions about what lies ahead for AI, a technology that has led to countless headlines surrounding both its promise and pitfalls. — Read More

Legend has it that in the winter of 1913, explorer Ernest Shackleton put out an ad for sailors to join him on an expedition to Antarctica:

Men wanted for hazardous journey. Low wages, bitter cold, long hours of complete darkness. Safe return doubtful. Honour and recognition in event of success.

Today, in September of 2023, I’d like to propose a similarly adventurous job ad for the age of AI: 

Talented engineers, designers, and copywriters wanted for a new agency. All work will be recorded, labeled, and organized for AI training. Your role will be progressively phased out. Salary paid and profits shared to you indefinitely. Failure likely. In the event of success: the last job you’ll ever have—or need. — Read More

Today, let’s consider the implications of a truly profound week in the development of artificial intelligence and discuss whether we may be witnessing the rise of a new era in the consumer internet.

… You can imagine the next steps here. A bot that gets to know your quirks; remembers your life history; offers you coaching or tutoring or therapy; entertains you in whichever way you prefer. A synthetic companion not unlike the real people you encounter during the day, only smarter, more patient, more empathetic, more available. — Read More

The latest annual McKinsey Global Survey on the current state of AI confirms the explosive growth of generative AI (gen AI) tools. Less than a year after many of these tools debuted, one-third of our survey respondents say their organizations are using gen AI regularly in at least one business function. Amid recent advances, AI has risen from a topic relegated to tech employees to a focus of company leaders: nearly one-quarter of surveyed C-suite executives say they are personally using gen AI tools for work, and more than one-quarter of respondents from companies using AI say gen AI is already on their boards’ agendas. What’s more, 40 percent of respondents say their organizations will increase their investment in AI overall because of advances in gen AI. The findings show that these are still early days for managing gen AI–related risks, with less than half of respondents saying their organizations are mitigating even the risk they consider most relevant: inaccuracy. — Read More

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In a recent interview I did with Craig Moffett we discussed why there is a “TMT” sector when it comes to industry classifications. TMT stands for technology, media, and telecoms, and what unifies them is that all deal in a world of massive up-front investment — i.e. huge fixed costs — and then near perfect scalability once deployed — zero marginal costs.

Each of these three categories, though, is distinct in the experience. …Another way to think about these categories is that if reality is the time and place in which one currently exists, each provides a form of virtual reality. — Read More