I'd agree with other posters - I'm seeing less hallucination; probably the model-makers are tuning to reduce that, because people make a big deal about it.
I see it as a small deal - it reminds us to check the responses against references.
LLMs are a statistical construction, and everyone accepts without complaint that statistical models have a predicted false-positive and false-negative rate.
I think of "hallucination" as a false positive; false negative is no answer when the model could have made a useful response.
I think there's some relation between our creativity and the LLM capability we dismissively call hallucination.
It's not so much that AI hallucinates, but the fact that we know it does, and it's being used to make independent decisions to use lethal force against a human on the battlefield today.
At least that is my understanding of one of the ways that Ukraine is asymmetrically winning against a foe in Russia with more resources, at least at the start.
It's how we are using it knowing this limitation it has and the decisions being made about when and where it's being used in this capacity are mostly unknown.
I just went down a rabbit-hole, and happily I found the rabbit - an early example of this type of prompt (draw an unusual animal character in a vector graphics language). There is a paper and a 1 hour podcast resulting from a Microsoft evaluation of a pre-release of GPT4. One of the prompts (see pages 4,7,8 in the paper PDF) was to draw a unicorn in TikZ. (I'll leave to the historians the questions of whether this was the first, or whether Simon Willison may have been inspired by this). I remember hearing some of the podcast, and recalled the prompt about balancing on a nail, and the triangle forming the unicorn's tusk; this was clearly a big step beyond choosing the next word and blending images.
The Z80 has a relative jump. Teenage me was loading a hand-assembled search function as an initialised array of integers in Basic, and relative jumps didn't need to be adjusted for the load location, which reduced the amount of post-load adjusting of addresses. It was +100x faster than Basic, just a straight scan.
yes, that looks like the one. I think I was using the conditional jump, so it could have been djnz, but I think it was jr. 1 byte jump offset, and I recall my little function bumping against that limit - I might have re-arranged it.
http://z80-heaven.wikidot.com/instructions-set:jr
A language like E seems about the right level for a simple user-friendly programmatic layer wrapping applications, i.e. enable the users to ask a natural language question or build a simple GUI layer which has question actions, with results displayed in the custom GUI or exported as files (CSV or spreadsheets etc).
I expect we'll see a blurring of the web app GUI, allowing users and LLMs to augment the GUI.
The climate spiral can be misleading though, because it's natural for a viewer to interpret the change in terms of area.
Then, the increase from 1.5° to 2° looks much, much larger than the increase from 0° to 0.5°.
So it's misleading in terms of making recent warming seem even worse than it is. Now, of course, you might argue that is justified in spirit because the negative consequences from warming grow faster than linear... but that doesn't make it any less misleading in terms of the temperature change it is communicating.
They often are not, because they highly distort shape and size. Values that are smaller than the mean occupy much less space (area-wise) and seem less significant than they really are, while values that are larger than the mean occupy much more space (area-wise) and seem more significant than they really are.
Fractal Domains
Exploring fractals with your Macintosh
Triple Dragon
September 3, 2006
Click image to see full size
Julia set using square orbit trap. The formula used was
f(z) = z^3/(z^3 + 1) + c, c = 0.18 + 0.68 i
Downloads and extras
“Triple Dragon” Parameter File
> ... It starts by stepping into a shallow pool of golden light.
> ... Together they act as both a choir and an audience
I think I'm not the target audience.
I guess they are going to need to sign up a lot of people, to train on their scans + their medical outcomes. So the article is talking to people who will get enthused by it, which is more difficult after the question of 23AndMe data sale.
I’m a weirdo who vaguely enjoys my MRIs. I’m moderately claustrophobic, but they still don’t really bother me. And I love the warming feeling that makes me feel like I’m getting microwaved.
My understanding was that your body was absorbing some amount of whatever electromagnetic stuff passes through you for the image. And the techs have told me it’s nothing to worry about.
You can definitely feel it in your body, I mean you have metals in you. I definitely feel tingling and general sense of something nearly touching my skin and insides.
The risk is humans using AI to control / exploit / coerce / injure other humans. The risk of AIs being given enough agency to threaten humans comes after that - they'll only have the agency we give them (being "alive" or "conscious" is not the near-term risk).
The article lists diplomatic actions which might help to manage the risk, starting with "An agreement between America and China" - they all sound like impossible dreams.
We had ~80 years of relative peace and prosperity in which to construct a framework of unity to face challenges like AI (and global warming, which until GPT I thought was the bigger risk); international unity is weaker than ever.
In geopolitics and defence, capability of other nations is the concern rather than intention; the capability curve of LLMs is heading off our charts.
We're backed into tight corners on nuclear proliferation, global warming, and I can see LLM-enabled conflicts (cyber warfare, infrastructure terrorism) pushing us over those other edges. Our democracies seem weakened, and I expect LLMs will empower those using social media to create conflict and control opinion.
We're familiar with the cycle of inventing new technology which benefits people, then seeing how long before people invent ways to misuse it. There is a possibility here that LLMs could be used to solve the problems we are juggling, but I struggle to imagine that people won't misuse it even faster.
The article is a start on thinking and talking about managing our risks. The best outcome would be it is so well managed that, like the Y2K "bug", people say "after all that hoopla, nothing happened". I'm not seeing a smooth path to there.
Related (posted just 2hours before this article) : https://news.ycombinator.com/item?id=46086833
"Blimps lifting quantum data centers to the stratosphere? (newatlas.com)"
"... blimps, to lift quantum computers to the stratosphere. There, at an altitude of about 20 km (12.4 miles), temperatures are in the -50 °C range (about -58 °F) and would be cold enough to allow the qubits to function correctly."
I have drafted a photo gallery app in Rust / Tauri, using a JavaScript framework in the frontend.
The backend can read directories and files directly, and because the backend and frontend are in a single process, the backend simply passes a file handle (path string possibly) to the frontend. In contrast Electron has to send the image file between processes. I started with Electron and I think that was the point I shifted to Rust / Tauri; seeing the images display immediately was a revelation.
Rust / Tauri has the advantages of a desktop app, and I have the option to use the frontend as a web app also.
This Python binding (pytauri) is interesting too - I have colleagues with Python functionality they want to surface on the web, and this would give the possibility of running as a desktop app also - good for large datasets.
I see it as a small deal - it reminds us to check the responses against references. LLMs are a statistical construction, and everyone accepts without complaint that statistical models have a predicted false-positive and false-negative rate. I think of "hallucination" as a false positive; false negative is no answer when the model could have made a useful response. I think there's some relation between our creativity and the LLM capability we dismissively call hallucination.