A recent article in Fast Company makes the claim “Thanks to AI, the Coder is no longer King. All Hail the QA Engineer.” It’s worth reading, and its argument is probably correct. Generative AI will be used to create more and more software; AI makes mistakes and it’s difficult to foresee a future in which it doesn’t; therefore, if we want software that works, Quality Assurance teams will rise in importance. “Hail the QA Engineer” may be clickbait, but it isn’t controversial to say that testing and debugging will rise in importance. Even if generative AI becomes much more reliable, the problem of ..read more

This article originally appeared in The Information on March 5th, 2024. “The economic problem of society…is a problem of the utilization of knowledge which is not given to anyone in its totality.” —Friedrich A. Hayek, “The Use of Knowledge in Society” Silicon Valley venture capitalists and many entrepreneurs espouse libertarian values. In practice, they subscribe to central planning: Rather than competing to win in the marketplace, entrepreneurs compete for funding from the Silicon Valley equivalent of the Central Committee. The race to the top is no longer driven by who has the best produc ..read more

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Specific prompts seem to “unlock” training data. We have many current and future copyright challenges: training may not infringe copyright, but legal doesn’t mean legitimate—we consider the analogy of MegaFace where surveillance models have been trained on photos of minors, for example, without informed consent. Copyright was intended to incentivize cultural production: in the era of generative AI, copyright won’t be enough. In Borges’s fable “Pierre Menard, Author of The Quixote,” the eponymous Monsieur Men ..read more

I’ve had a ham radio license since the late 1960s and observed the transition from vacuum tubes (remember them?) to transistors firsthand. Because we’re allowed to operate high power transmitters (1500 watt output), tubes hang on in our world a lot longer than elsewhere. There’s a good reason: tubes are ideal high power devices for people who don’t always know what they’re doing, people who are just smart enough to be dangerous. About the only way you can damage them is by getting them hot enough to melt the internal components. That happens… but it means that there’s a huge margin for error ..read more

Since its release in November 2022, almost everyone involved with technology has experimented with ChatGPT: students, faculty, and professionals in almost every discipline. Almost every company has undertaken AI projects, including companies that, at least on the face of it, have “no AI” policies. Last August, OpenAI stated that 80% of Fortune 500 companies have ChatGPT accounts. Interest and usage have increased as OpenAI has released more capable versions of its language model: GPT-3.5 led to GPT-4 and multimodal GPT-4V, and OpenAI has announced an Enterprise service with better guarantees f ..read more

Since The New York Times sued OpenAI for infringing its copyrights by using Times content for training, everyone involved with AI has been wondering about the consequences. How will this lawsuit play out? And, more importantly, how will the outcome affect the way we train and use large language models? There are two components to this suit. First, it was possible to get ChatGPT to reproduce some Times articles, very close to verbatim. That’s fairly clearly copyright infringement, though there are still important questions that could influence the outcome of the case. Reproducing The New York T ..read more

ChatGPT was released just over a year ago (at the end of November 2022), and countless people have already written about their experiences using it in all sorts of settings. (I even contributed my own hot take last year with my O’Reilly Radar article Real-Real-World Programming with ChatGPT.) What more is left to say by now? Well, I bet very few of those people have actually chatted with ChatGPT. And by “chat” I mean the original sense of the word—to hold a back-and-forth verbal conversation with it just like how you would chat with a fellow human being. I recently chatted with ChatGPT, and I ..read more

Kevlin Henney and I recently discussed whether automated code generation, using some future version of GitHub Copilot or the like, could ever replace higher-level languages. Specifically, could ChatGPT N (for large N) quit the game of generating code in a high-level language like Python, and produce executable machine code directly, like compilers do today? It’s not really an academic question. As coding assistants become more accurate, it seems likely to assume that they will eventually stop being “assistants” and take over the job of writing code. That will be a big change for professional p ..read more

Generative AI stretches our current copyright law in unforeseen and uncomfortable ways. In the US, the Copyright Office has issued guidance stating that the output of image-generating AI isn’t copyrightable unless human creativity has gone into the prompts that generated the output. This ruling in itself raises many questions: How much creativity is needed, and is that the same kind of creativity that an artist exercises with a paintbrush? If a human writes software to generate prompts that in turn generate an image, is that copyrightable? If the output of a model can’t be owned by a human, wh ..read more

Tim O’Reilly forwarded an excellent article about the OpenAI soap opera to me: Matt Levine’s “Money Stuff: Who Controls Open AI.” I’ll skip most of it, but something caught my eye. Toward the end, Levine writes about Elon Musk’s version of Nick Bostrom’s AI that decides to turn the world to paperclips: [Elon] Musk gave an example of an artificial intelligence that’s given the task of picking strawberries. It seems harmless enough, but as the AI redesigns itself to be more effective, it might decide that the best way to maximize its output would be to destroy civilization and convert the entir ..read more