[_dark_matter_]

I had the opposite experience. I was trying to figure out what this weird lightbulb was that I had to replace, and it had no writing on it. I uploaded the description and picture to gpt4, and it just got it clearly wrong over and over. Tried bard, got it right in the first try, with links to the product. I was extremely impressed.

[dgacmu]

I had a similar experience with Google lens recently. I've gotten used to Yandex image search being better than Google's for many searches, but I needed to figure out what model of faucet I had on my sink, and Google nailed it. My hunch is that because of all the work they did on Google shopping gathering labeled product images and things like that, they have an excellent internal data set when it comes to things like your light bulb and my sink.

[wildrhythms]

I use Google Lens at least once a week to find where I can buy a certain jacket, shoes, etc. that I see. It is one of the only 'AI' products I can say I trust the results.

[satvikpendem]

The vast knowledge trove of Google can't be understated, even if sometimes the model isn't as competent at certain tasks as OpenAI's GPT models.

[taneq]

If there's one thing that's becoming clear in the open source LLM world, it's that the dataset really is the 'secret sauce' for LLMs. There are endless combinations of various datasets plus foundation model plus training approach, and by far the key determinant of end model performance seems to be the dataset used.

[satvikpendem]

> it's that the dataset really is the 'secret sauce'

alwayshasbeen.jpg

There have been articles about how "data is the new oil" for a couple of decades now, with the first reference I could find being from British mathematician Clive Humby in 2006 [0]. The fact that it rings even more true in the age of LLMs is simply just another transformation of the fundamental data underneath.

[0] https://en.wikipedia.org/wiki/Clive_Humby#cite_ref-10

[still_grokking]

2006?

https://en.wikipedia.org/wiki/Scientia_potentia_est

[satvikpendem]

> There have been articles about how "data is the new oil" for a couple of decades now, with the first reference I could find being from British mathematician Clive Humby in 2006

I am specifically referring to the phrase I quoted, not some more abstract sentiment.

[sharkoz]

The best answer to this is https://www.youtube.com/watch?v=ab6GyR_5N6c :)

[kccqzy]

Isn't there just a comment today on HN saying Google had an institutional reluctance to use certain data sets like libgen? I honestly don't think Google used everything they had to train their LLM.

https://news.ycombinator.com/item?id=38194107

[notfed]

This is almost certainly just delegating to Google Lens, which indeed works great.

Bard's probably just a middle man here.

[downWidOutaFite]

I would think that ChatGPT is also delegating to some other subsystem.

[broast]

Right, a glance at the new Assistant API docs, which seems to mirror ChatGPT in functionality, suggests that the "Assistant" determines which tool to use, or which models to use (code or chat) to generate a response message. The API is limited in that it can't use Vision or generate images, but I imagine that those are just "Tools" too that the assistant has access to.

[hackernewds]

with a poorer dataset than google

[tomrod]

Unless wired to Bing, probably not?

[fennecfoxy]

I mean was a GPT even involved really? If you gave just Lens a shot, I'm sure it also would've picked it up and given you a link to some page with it on.

[huytersd]

Ah that’s interesting, did know bard had multi modal inputs.

[jfoster]

I asked Bard the question "Who is Elon Musk?"

The response: "I'm a text-based AI, and that is outside of my capabilities."

[guiambros]

That's interesting. Did you have anything else in the thread, or was it just the first question?

For me it returns a seemingly accurate answer [1], albeit missing his involvement with Twitter/X. But LLMs are intrinsically stochastic, so YMMV.

[1] https://g.co/bard/share/378c65b56aea

[jfoster]

It was the first question in the thread, and I've been testing queries along these lines on it for a while. Interestingly, it started writing a response initially and then replaced it with that. It used to refuse to answer who Donald Trump is as well, but it seems that one has been fixed.

Another interesting line of inquiry (potentially revealing some biases) is to ask it whether someone is a supervillain. For certain people it will rule it out entirely, and for others it will tend to entertain the possibility by outlining reasons why they might be a supervillain, and adding something like "it is impossible to say definitively whether he is a supervillain" at the end.

[fennecfoxy]

That's because these GPTs are trained to complete text in human language, but unfortunately the training data set includes human language + human culture.

I really think they need to train on the wider dataset, then fine tune with some training on a machine specific dataset, then the model can reference data sources rather than have them baked in.

A lot of the general purposeness but also sometimes says weird things and makes specific references is pretty much down to this I reckon...it's trained on globs of human data from people in all walks of life with every kind of opinion there is so it doesn't really result in a clean model.

[jfoster]

Sure, but it's been known for a long time that models can have these types of weaknesses & biases. They can be tested for & ironed out.

If you ask the same questions to ChatGPT you tend to get much more refined answers.

[fennecfoxy]

True, but I think the learning methods are similar enough to how we learn for the most part and the theory that people are products of their environments really does hold true (although humans can constantly adjust and overcome biases etc if they are willing to).

Ironing out is definitely the part where they're tweaking the model after the fact, but I wonder if we don't still need to separate language from culture.

It could help really, since we want a model that can speak a language, then apply a local culture on top. There's already been all sorts of issues arise with the current way of doing it, the Internet is very America/English centric and therefore most models are the same.

[fijiaarone]

So Elon is the engine behind Bard?