In the early part of the 20th Century, there was a fad for "Radium". The magical, radioactive substance that glowed in the dark. The market had decided that Radium was The Next Big Thing and tried to shove it into every product. There were radioactive toys, radioactive medicines, radioactive chocolate bars, and a hundred other […]
Continue reading →
That's it. That's the post. Fine! I'll expand a little more. Large Language Models are a type of Artificial Intelligence. They can read text, parse it, process it using the known rules of English, and then regurgitate parts of it on demand. This means they can read and parse a question like "In Python, how […]
Continue reading →
I saw a prominent AI proponent asking why people always focus on the things that AI gets wrong. AI works so well, he asserted, that it was churlish and childish to focus on a few minor mistakes? Which reminds me of an experience I had a few years ago. I was in a rural pub […]
Continue reading →
Last week I attended an unofficial discussion group about the future of AI in Government. As well as the crypto-bores who have suddenly pivoted their "expertise" into AI, there were lots of thoughtful suggestions about what AI could do well at a state level. Some of it is trivial - spell check is AI. Some […]
Continue reading →
A week is a long time in politics and a couple of years is an aeon in AI. Published in 2019, just before the dawn of the LLM, this is an overview of all the weird and charming ways Artificial Intelligence can go wrong. It is fully of delightfully silly examples and rather charming illustrations. […]
Continue reading →
There's a popular saying; "No One Wants a Drill. What They Want Is the Hole". It's a pithy (and broadly) correct statement. But I don't think it goes far enough. Let's apply the Five Whys method to the issue: No one wants a drill. What they want is the hole. No one wants a hole. […]
Continue reading →
I'm sure I remembered there once being a clock app for Linux which was deliberately vague. It would declare the time as "Nearly tea-time" or "A little after elevenses" or "Quite late" or "Gosh, that's early". But I can find no evidence that it ever existed and am beginning to wonder if I dreamt it. […]
Continue reading →
A group of authors are suing various vendors of Large Language Model AIs. The authors claim that the AIs are trained on material which infringes their copyright. Is that likely? Well, let's take a quick look at the evidence presented. First up, Meta's LLaMA Paper. It describes how the LLM was trained: We include two […]
Continue reading →
I'm obsessed with the idea that human progress could be accelerated - if only we realised how to properly combine existing technology. I don't want to go "Ancient Aliens" here - but even a cursory reading of scientific history will show you were humanity's progress could have been dramatically fast if only knowledge was more […]
Continue reading →
One of the (many) problems with AI is that training data usually needs to come from "natural" sources. If you want to emulate human-written text, you need to train something on human-written text. But with the proliferation of cheap and fast AI tools, it is likely that training data will unwillingly become contaminated with AI-written […]
Continue reading →
· AI github LLM · 6 comments · 400 words · read ~1,595 times.