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Working with The Associated Press to provide fresh results for the Gemini app

331c8c71

We've gone the whole way from decentralization and rebelliousness of the early internet and the landscape is becoming suffocatingly sterile (=lifeless).

I'm much more excited about eventual emergence of underground homebrew models without any guardrails...

umvi

> I'm much more excited about eventual emergence of underground homebrew models without any guardrails

Not if AI gatekeepers and interest groups have anything to say about it. AI without guardrails could be classified as a "weapon" and made illegal such that we are only allowed to use models produced by regulated entities and meet certain "safety standards" (like how medical software has to be approved by FDA).

Edit: oh, I guess "underground" could be interpreted in a way that these models are still produced and distributed (but secretly, illegally, etc)

srid

Yes. What do you think Grok AI's real-time information being sourced on posts of individual users (similar to early internet) as opposed to established media (like AP)?

kennyloginz

No, Twitter posts are not even close to the “old internet”. No one was paid to create ragebait.

We still argued, but we did it from a place of passion, not commission.

smithcoin

FYI If you want to turn this off in workspace you'll need to go here https://admin.google.com/ac/managedsettings/47208553126 and here https://admin.google.com/ac/managedsettings/793154499678.

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sebmellen

The hero we needed

heavyarms

There's not a lot of detail in the announcement but I assume this is some kind of RAG system. I wonder if it will cover some short time period (past week, past month?) or if they are trying to cover the whole time period since the knowledge cutoff of the current model.

urbandw311er

My guess is that they’ll just stuff a few daily headlines into the prompt so that queries about current affairs have some context, rather than re-training the model. Total guess obviously.

PhilippGille

RAG isn't re-training. You can have vector embeddings of all AP news in a vector DB, then when prompted, find related news via similarity search, and add the most similar (and thus related) ones to the context.

Here's some simple example code in Go, for RAG with 5000 arXiv paper abstracts: https://github.com/philippgille/chromem-go/tree/v0.7.0/examp... (full disclosure it's using a simple vector DB I wrote)

urbandw311er

Good point - possibly just a limited version of this, although I don’t know how they’d handle a rolling time window in the vector DB to limit results to just recent stories?

itsibitzi

As someone who works in the news industry I find it pretty sad that we've just capitulated to big tech on this one. There are countless examples of AI summaries getting things catastrophically wrong, but I guess Google has long since decided that pushing AI was more important than accurate or relevant results, as can also be seen with their search results that simply omit parts of your query.

I can only hope this data is being incorporated in some way that makes hallucinations less likely.

nerdjon

Unfortunately this has just been the reality over the last couple years. People just ignore the hallucination problem (or try to say it isn't a big deal). And yet we have seen time and time again examples of these models being given something, told to summarize it, and still hallucinate important details. So you can't even make the argument that its data is flawed or something.

These models will interject information from their training whether or it is relevant or not. This is just due to the nature of how these models work.

Anyone trying to argue that it doesn't happen that often or anything is missing the key problem. Sure it may be right most of the time, but all that does is build a false sense of security and eventually you stop double checking or clicking through to a source. Whether it is a search result, manipulating data, or whatever.

This is made infinitely worse when these summaries are one and done, a single user is going to see the output and no one else will see it to fact check. It isn't like an article being wrong that everyone reading it is reading the same article, can then comment that something is wrong, it get updated, and so on and so forth. That feedback loop is non-existent with these models

umvi

> Anyone trying to argue that it doesn't happen that often or anything is missing the key problem. Sure it may be right most of the time, but all that does is build a false sense of security and eventually you stop double checking or clicking through to a source. Whether it is a search result, manipulating data, or whatever.

Same problem existed before AI summaries.

"Briefly stated, the Gell-Mann Amnesia effect is as follows. You open the newspaper to an article on some subject you know well. In Murray's case, physics. In mine, show business. You read the article and see the journalist has absolutely no understanding of either the facts or the issues. Often, the article is so wrong it actually presents the story backward—reversing cause and effect. I call these the "wet streets cause rain" stories. Paper's full of them.

In any case, you read with exasperation or amusement the multiple errors in a story, and then turn the page to national or international affairs, and read as if the rest of the newspaper was somehow more accurate about Palestine than the baloney you just read. You turn the page, and forget what you know."

– Michael Crichton (1942-2008)

extr

Hallucinations are not a big problem with SOTA models at this point, especially grounded against an actual news article.

dismalaf

> I can only hope this data is being incorporated in some way that makes hallucinations less likely.

The key word is "real-time". LLMs can't be trained in realtime, so it's obviously going to call an API that pulls up and reads from AP news, just like their search engine.

notatoad

i don't think you can assume that - "real time" in this context could just mean they feed every article into their training system as soon as it's published.

iamjackg

That seems more unlikely to me -- training is not free and takes a long time, so it would not result in "[enhancing] the usefulness of results displayed in the Gemini app" and it being "particularly helpful to our users looking for up-to-date information."

Fine-tuning, which is cheaper and faster, has been proven to not be a good solution to "teach" models new facts.

I think what's most likely here is that Gemini will have access to a form of RAG based on a database of AP articles that gets updated in real-time as new articles are published.

CuriouslyC

They can't deploy that fast and people want to pin model version so it's not feasible anyhow.

summerlight

If there's any company who can afford "real-time LLM training" at this moment, I'm 100% sure they will win this AI race since they probably have at least ~10x compute compared to competitors. Of course, no one can do that right now.

dismalaf

Have you ever asked an LLM what time it is? It takes months to train them...

scarface_74

The examples that have made news were with iOS. iOS doesn’t really do a summary of the content. It just tries to do a summary of the headline.

The on device model that it uses is also literally 1% the size of the large models like Gemini

paxys

The news industry capitulated to big tech the moment it got reliant on big tech for the majority of its revenue. The entire media landscape today is the direct result of that.

asdff

Take it a step back further, and you will see that the media landscape capitulated to Big Anything a long time ago. For probably generations now, if we consider people like william randolf hearst and other newspaper men.

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micromacrofoot

It's responsibility laundering — AI can say whatever they want and they can shrug it off by saying bots are sometimes unreliable

asdff

Uhh, has your head been in the sand? Look at the average output of your industry without ai. It gets things wrong. It misleads. It hallucinates. It has incentives that fundamentally differ from what the readership seeks in news. The fact that your industry took so readily to the technology to output ever more garbage says it all about the state of the industry vs any condemnation of the fundamental technology.

xnx

The timing of this announcement is surely to contrast to open OpenAI which is currently in court being sued by The New York Times.

throw7

I wonder what the byline will look like. I'm sure their current crop of beat reporters are enthusiastic with developments.

sharpshadow

Is there the option to get the news then as they fly in immediately in a feed?

nxobject

I'm surprised I'd never asked that question before, since the AP and other syndicates began as teletype wire feeds. What do modern newsrooms use as the modern replacement of the AP "wire"?

eichi

One of the CEO was really competitive and has been the few legecy asset which are contributing current Google: other legecy assets are pools of competitive people who hadn't found the best place to show the ability. Current google is just the target of the good profile.

bluSCALE4

Google, what we really want are ads.

bangaroo

wow! this sure is great! gemini has worked so great up until this point - for example, i learned that a man who died in 1850 is one of three private owners of the airbus a340-600 last week! i'm so glad gemini exists and i absolutely cannot wait to experience a world wherein people get news from it.