Simon Willison’s Weblog

For the last few years, Meta has had a team of attorneys dedicated to policing unauthorized forms of scraping and data collection on Meta platforms. The decision not to further pursue these claims seems as close to waving the white flag as you can get against these kinds of companies. But why? [...]

In short, I think Meta cares more about access to large volumes of data and AI than it does about outsiders scraping their public data now. My hunch is that they know that any success in anti-scraping cases can be thrown back at them in their own attempts to build AI training databases and LLMs. And they care more about the latter than the former.

— Kieran McCarthy # 28th February 2024, 3:15 pm

One consideration is that such a deep ML system could well be developed outside of Google-- at Microsoft, Baidu, Yandex, Amazon, Apple, or even a startup. My impression is that the Translate team experienced this. Deep ML reset the translation game; past advantages were sort of wiped out. Fortunately, Google’s huge investment in deep ML largely paid off, and we excelled in this new game. Nevertheless, our new ML-based translator was still beaten on benchmarks by a small startup. The risk that Google could similarly be beaten in relevance by another company is highlighted by a startling conclusion from BERT: huge amounts of user feedback can be largely replaced by unsupervised learning from raw text. That could have heavy implications for Google.

— Eric Lehman, internal Google email in 2018 # 11th February 2024, 10:59 pm

Reality is that LLMs are not AGI -- they’re a big curve fit to a very large dataset. They work via memorization and interpolation. But that interpolative curve can be tremendously useful, if you want to automate a known task that’s a match for its training data distribution.

Memorization works, as long as you don’t need to adapt to novelty. You don’t *need* intelligence to achieve usefulness across a set of known, fixed scenarios.

— François Chollet # 10th February 2024, 6:39 am

LLMs may offer immense value to society. But that does not warrant the violation of copyright law or its underpinning principles. We do not believe it is fair for tech firms to use rightsholder data for commercial purposes without permission or compensation, and to gain vast financial rewards in the process. There is compelling evidence that the UK benefits economically, politically and societally from upholding a globally respected copyright regime.

— UK House of Lords report on Generative AI # 2nd February 2024, 3:54 am

For many people in many organizations, their measurable output is words—words in emails, in reports, in presentations. We use words as proxy for many things: the number of words is an indicator of effort, the quality of the words is an indicator of intelligence, the degree to which the words are error-free is an indicator of care.

[...] But now every employee with Copilot can produce work that checks all the boxes of a formal report without necessarily representing underlying effort.

— Ethan Mollick # 2nd February 2024, 3:34 am

Danielle Del, a spokeswoman for Sasso, said Dudesy is not actually an A.I.

“It’s a fictional podcast character created by two human beings, Will Sasso and Chad Kultgen,” Del wrote in an email. “The YouTube video ‘I’m Glad I’m Dead’ was completely written by Chad Kultgen.”

— George Carlin’s Estate Sues Podcasters Over A.I. Episode # 27th January 2024, 5:52 pm

If you have had any prior experience with personal computers, what you might expect to see is some sort of opaque code, called a “prompt,” consisting of phosphorescent green or white letters on a murky background. What you see with Macintosh is the Finder. On a pleasant, light background (you can later change the background to any of a number of patterns, if you like), little pictures called “icons” appear, representing choices available to you.

— Steven Levy (in 1984) # 27th January 2024, 1:33 am

We believe that AI tools are at their best when they incorporate and represent the full diversity and breadth of human intelligence and experience. [...] Because copyright today covers virtually every sort of human expression– including blog posts, photographs, forum posts, scraps of software code, and government documents–it would be impossible to train today’s leading AI models without using copyrighted materials. Limiting training data to public domain books and drawings created more than a century ago might yield an interesting experiment, but would not provide AI systems that meet the needs of today’s citizens.

— OpenAI to the Lords Select Committee on LLMs # 8th January 2024, 5:33 pm

Since the advent of ChatGPT, and later by using LLMs that operate locally, I have made extensive use of this new technology. The goal is to accelerate my ability to write code, but that’s not the only purpose. There’s also the intent to not waste mental energy on aspects of programming that are not worth the effort.

[...] Current LLMs will not take us beyond the paths of knowledge, but if we want to tackle a topic we do not know well, they can often lift us from our absolute ignorance to the point where we know enough to move forward on our own.

— Salvatore Sanfilippo # 2nd January 2024, 2:50 pm