I think we should not underestimate what this could evolve into. We
thrived because our readers find us "good enough" when it comes to
finding facts, not the ultimate source.
And the software learns by reading, and can (and have done so)
Wikipedia, Wikidata etc and represent our data in its own syntax och
present it in a way so it is not a direct copy. Perhaps data will be a
bit delayed to the actual content in Wikipedia, but so what - good enough?
Anders
Den 2022-12-19 kl. 14:26, skrev Gnangarra:
AI simply cant descriminate between good research and faked research,
for any outcome it must provide all of its sources whether they are
from Wikipedia, Wikidata, WikiCommons, WikiSource or some other
place. Otherwise it will answer yes to some asking if the world is
flat because it'll seek out that answer and find all the nonsense that
has been produced.
On Mon, 19 Dec 2022 at 06:02, Erik Moeller <eloque...@gmail.com> wrote:
On Sun, Dec 11, 2022 at 5:55 AM Anders Wennersten
<m...@anderswennersten.se> wrote:
> ChatGPT is now making headlines more or less every day and I
perceive
> them to try to position themself av the "next" google.
I suspect OpenAI will continue to focus on generative applications
(images, code, text for purposes such as copywriting, eventually
music/video) and won't attempt to compete with Google directly, but
we'll see. Currently GPT-3.5 (which ChatGPT is based on) is very prone
to generating nonsensical answers, citations to works that don't
exist, etc. But it is pretty cool if you keep its limitations in
mind--for example, it's quite good at bootstrapping small scripts in
various programming languages (with mistakes and idiosyncrasies).
Google has one of the largest AI research programs on the planet, they
just are extremely conservative about letting anyone try their models
(due to reputational concerns, e.g., that generative AI will spit out
racist output within about 30 seconds of people poking its
guardrails). This blog post from September is instructive about the
direction they're taking with what's called retrieval-augmented
generation; see the paper linked from the post for details:
https://www.deepmind.com/blog/building-safer-dialogue-agents (DeepMind
is part of Google)
That is likely to yield significantly more accurate answers than what
ChatGPT is doing, and is difficult to replicate for folks like OpenAI
without being dependent on the search APIs of big search companies.
It's worth noting that Google has also started to incorporate language
model tooling into how it's presenting search results (e.g.,
summarizing or highlighting different parts of a website to make the
result snippet more useful).
A retrieval-augmented approach that leverages Wikidata could IMO be
quite powerful and could be a useful research program for Wikimedia to
pursue, be it independently or in partnership with others. The
resulting technology should of course be fully open source.
Querying Wikidata via SPARQL is currently still a bit of wizardry (and
the query builder is extremely limited). To pick a completely random
example not at all inspired by current events, if I wanted to see a
list of journalists with Mastodon accounts & a picture, I currently
have to do this:
SELECT DISTINCT ?personLabel ?mastodonName ?pic
WHERE {
?person wdt:P4033 ?mastodonName ;
wdt:P106 ?occupation .
OPTIONAL { ?person wdt:P18 ?pic . }
?occupation wdt:P279* wd:Q1930187 .
SERVICE wikibase:label {
bd:serviceParam wikibase:language "en"
}
}
Make a small mistake (a curly brace missing) and you'll get a red
error message. Forgot the * after wdt:P279? A different response set
in ways that are difficult to spot or reason about.
Why can't I type "list of journalists with their picture and Mastodon
account" as a natural language query? (You can try it in ChatGPT and
it'll get you started, but it'll generate nonsense P/Q numbers.) If
such queries could be produced reliably, it could be a very useful
tool for readers as well.
Warmly,
Erik
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Gnangarra
'ngany dabakarn koorliny arn boodjera dardoon ngalang Nyungar
koortaboodjar'
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