In a recent newsletter, Ben Thompson called a portion of Jensen Huang’s keynote at NVidia’s GPU Technology Conference (GTC) in DC “an excellent articulation of the thesis that the AI market is orders of magnitude bigger than the software market.” While I’m loath to contradict as astute an observer as Thompson, I’m not sure I agree. Huang’s argument ran as follows:
“Software of the past, and this is a profound understanding, a profound observation of artificial intelligence, that the software industry of the past was about creating tools. Excel is a tool. Word is a tool. A web browser is a tool. The reason why I know these are tools is because you use them. The tools industry, just as screwdrivers and hammers, the tools industry is only so large. In the case of IT tools, they could be database tools, [the market for] these IT tools is about a trillion dollars or so.
But AI is not a tool. AI is work. That is the profound difference. AI is, in fact, workers that can actually use tools. One of the things I’m really excited about is the work that Aravind’s doing at Perplexity. Perplexity, using web browsers to book vacations or do shopping. Basically, an AI using tools. Cursor is an AI, an agentic AI system that we use at Nvidia. Every single software engineer at Nvidia uses Cursor. That’s improved our productivity tremendously. It’s basically a partner for every one of our software engineers to generate code, and it uses a tool, and the tool it uses is called VS Code. So Cursor is an AI, agentic AI system. that uses VS Code.”
At first this seems like an important observation, and one that justifies the sky high valuation of AI companies. But it really doesn’t hold up to closer examination. “AI is not a tool. AI is work. That is the profound difference. AI is, in fact, workers that can use tools.” Really? Any complex software system is a worker that can use tools! Think about the Amazon website. It is definitely a worker that can use tools. Here is some of the work it does, and the tools that it invokes:
* Helps the user search a product catalog containing millions of items using not just data retrieval tools but indices that take into account hundreds of factors;
* Compares those items with other similar items, considering product reviews and price;
* Calls a tool that calculates taxes based on the location of the purchaser;
* Calls a tool that takes payment and another that sends it to the bank, possibly via one or more intermediaries;
* Collects (or stores and retrieves) shipping information;
* Dispatches instructions to a mix of robots and human warehouse workers;
* Dispatches instructions to a fleet of delivery drivers;
* Follows up by text and/or email and asks the customer how the delivery was handled;
And far more. Every web application of any complexity is a worker that uses tools and does work that humans used to do. And often does it better and far faster. Amazon is a particularly telling example, but far from unique.
Even the analogy to hammers and screwdrivers is overblown. An old fashioned screwdriver or hammer may just be a tool, but an electric screwdriver or nail driver also actually does work. A plow is a tool, but a tractor does work. A horse drawn wagon is a tool, but an auto with an engine does work. Ships used to take hundreds or even thousands of sailors to manage, but now they can run with a small crew, because the machines do so much of the work. And so on.
Self driving cars are closer to the mark, and to some extent, the kind of agentic AI shown in powerful AI software development systems. But come on. Today’s AI systems are still tools. Just very powerful ones. The boundaries are far blurrier than the hype machine would have us believe.
https://t.co/79fLV64xQl
In my last Live with Tim O'Reilly interview, I talked with Marily Nika, Ph.D about product management for AI powered products. We covered a lot of ground, with lots of provocative questions from attendees. (Attendee questions are a key part of these events.) My favorite question was something like "how do we think about AI when humans work in teams but with our AI in silos." My takeaways post with highlight reels here: https://t.co/nfRRMM9bFN
My latest post on @OReillyMedia. Many Silicon Valley investors and entrepreneurs even seem to view putting people out of work as a massive opportunity. That idea is anathema to me. It’s also wrong, both morally and practically.
The problems of integrating AI into our businesses, our lives, and our society are indeed complicated. But whether you call it “AI native” or “AI first,” it does not mean embracing the cult of “economic efficiency” that reduces humans to a cost to be eliminated.
No, it means doing more, using humans augmented with AI to solve problems that were previously impossible, in ways that were previously unthinkable, and in ways that make our machine systems more attuned to the humans they are meant to serve.
https://t.co/M1Jn7VD67V
Maurice: "This goalie is playing well. Sam, it's time to get out there and elbow this goalie in the head"
*Bennett hits Bobrovsky*
Maurice: "NOT THAT GOALIE!!!"
I'm really looking forward to our free online conference on how AI is changing software development, starting in just about an hour. I'm co-hosting with Addy Osmani. We've got an amazing lineup, including Gergely Orosz, Chip Huyen, Camille Fournier, Jay Parikh, Chelsea Troy, Kent Beck, Harper Reed, Andrew Stellman, Patty O'Callaghan, swyx, and more.
https://t.co/b9UDVWt8ub
This post is SO, SO good. Very much in line with my thinking about AI and the future of software. I hope we can get Philip to speak at one of our upcoming #AICodeCon events. https://t.co/Lt4Kek3RkZ