Even more interesting is the current trend of writing entire articles based on just one or two twitter threads. This appears to me like lazy journalism. Why not talk directly to the people and get their opinions?
Why Meta’s latest large language model survived only three days online
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Re: Why Meta’s latest large language model survived only three days online
#22This software is excellent for pseudo science. For example, young earth peddlers will be able to generate entire mambo jambo references and use them to indoctrinate more people.
Re: Why Meta’s latest large language model survived only three days online
#23Earlier quoted context omitted.
There are people who believe explicit works of fiction. Marvel movies come to mind. I'll know we've arrived when super hero films begin with a disclaimer. The runtime of the podcast was 1:34:27
> I'll know we've arrived when super hero films begin with a disclaimer. That kind of thing has already been happening for quite a while, though. Books have long had disclaimers along the lines of ‘the following events and characters are entirely fictional and are not based on any people from the real world’ — I recall seeing them in e.g. Wodehouse’s books from the 1940s, so it’s not like it’s a new thing.
Those warnings are more a protection for libel lawsuits than they are about warning that the contained fictional story is fictional.
Re: Why Meta’s latest large language model survived only three days online
#24This is the kind of biased reporting that hurts journalism as a profession. It is not journalism's job to sell the public on anything. It's journalism's job to report the news. And if a large portion of the public doesn't believe the news is being reported accurately, that is a very big problem for journalism.
What exactly is biased in this reporting? It is presenting an event that actually happened (Facebook took down their new Galactica AI model), presenting the reasons why it seems to have happened (numerous researchers lambasting it), with first-hand sources, while also making sure to quote the official reason given, and also a less official comment on the event from the lead researcher that seems to support their previous thesis.
To me it seems like a decent example of what journalism should aspire to be for this kind of topic. Bad journalism would have just quoted the official Facebook tweet and stopped there, like so many journalists do with political declarations.
Re: Why Meta’s latest large language model survived only three days online
#25I think it's fine to work on and release these models, where things fall apart is in how some large companies market them. Listen to 1:35:30 of this Bill Simmons podcast interview to see how an average person interprets the capabilities of these models: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5tZWdhcGh...
There are people who believe explicit works of fiction. Marvel movies come to mind. I'll know we've arrived when super hero films begin with a disclaimer. The runtime of the podcast was 1:34:27
Weird, it shows up as 1:40 long for me. It's the last 5 minutes of the episode, where they claim GPT-3 is an all knowing machine that will generate factual responses to any question in a way that's superior to google search.
Re: Why Meta’s latest large language model survived only three days online
#26I don't understand why they would market it as a source of accurate text or some kind of oracle. Language models are useful for generating text. Believable or entertaining works of fiction. The extra parts about truthiness and the dangers of misinformation were just too much for me. We have a bigger problem with our premises and status quo if inaccurate scientific papers are a danger.
> they would market it as a source of accurate text They did not. IIRC there was a disclaimer in the page that the text is innacurate and that NNs hallucinate. But tweets be tweeting
They did market it as that, and then added a disclaimer amounting to "but it's not fit for purpose". Furthermore, that disclaimer was only present on the Mission page, not the front page or any other.
The front page just said this [0]:
> Get Started
> Galactica is an AI trained on humanity's scientific knowledge. You can use it as a new interface to access and manipulate what we know about the universe.
> [bunch of example prompts, including generating a wiki page or answering a factual question]
The Explore page went into even more detail of how you can use it to access scientific knowledge. Then, if you look on the Mission page, you are again presented with the same haughty notion (Galactica is meant to give easy access to the world's scientific literature), only here you also see the Limitations, which basically amount to "but don't trust the output, especially for more obscure topics".
So we were given a service whose main goal is to summarize and present existing scientific knowledge, with citations and everything, except that we shouldn't trust any of the output to actually reflect the scientific literature. But hey, if it's a popular topic, it'll probably be closer to correct!
[0] https://web.archive.org/web/20221115165109mp_/https://galact...
Re: Why Meta’s latest large language model survived only three days online
#27It’s algorithmically/randomly generating text without understanding. What it the proper way of using it? Fake papers? Political bs? Bad Hemingway (or Shakespeare or Chaucer or…). It’s noise that looks like sentences.
The world's most expensive Lorem Ipsum generator?
What is Congress.
Re: Why Meta’s latest large language model survived only three days online
#28"A fundamental problem with Galactica is that it is not able to distinguish truth from falsehood," In true science, it is exceptionally hard to distinguish truth from falsehood for many of the interesting subjects. It can take decades of work to reach consensus on what is "truth." Physics in the early 20th century is a great example of this debate.
Exactly. Also why identifying "misinformation" is a fool's errand, since yesterday's misinformation is today's truth.
Re: Why Meta’s latest large language model survived only three days online
#29"A fundamental problem with Galactica is that it is not able to distinguish truth from falsehood," In true science, it is exceptionally hard to distinguish truth from falsehood for many of the interesting subjects. It can take decades of work to reach consensus on what is "truth." Physics in the early 20th century is a great example of this debate.
To be clear, the fact that it is difficult is not a defense of Galactica and its proponents; it is a reason for suspecting that these sorts of language models are fundamentally unsuited to the task.
Why “fundamentally unsuited”? Neural networks have solved tons of problems previously thought to be “too hard” for ML, e.g. playing Go.
Re: Why Meta’s latest large language model survived only three days online
#30"A fundamental problem with Galactica is that it is not able to distinguish truth from falsehood," In true science, it is exceptionally hard to distinguish truth from falsehood for many of the interesting subjects. It can take decades of work to reach consensus on what is "truth." Physics in the early 20th century is a great example of this debate.
Not being able to difinitively identify truth is different from not attempting to identify it.
Attempting to identify truth is called the scientific method.