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Kagi News

blog.kagi.com

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Re: Kagi News

#261
post #23

Just to be clear I'm understanding correctly: This is pulling the content of the RSS feeds of several news sites into the context window of an LLM and then asking it to summarize news items into articles and fill in the blanks? I'm asking because that is what it looks like, but AI / LLMs are not specifically mentioned in this blog post, they just say news are 'generated' under the 'News in your language' heading, whi…

> when you ask an LLM to point to 'sources' for the information it outputs,

Services listing sources, like Kagi news, perplexity and others don't do that. They start with known links and run LLMs on that content. They don't ask LLMs to come up with links based on the question.

Re: Kagi News

#263

I liked Kagi, was paying for it for a few months, but $10 is just too much

I don't find it too much. For $10 I get a search engine better than all the others, I get access to many AI models via Kagi Assistant and Kagi Translate. While I understand different people find value in different things, dismissing Kagi generally as "too expensive" is ignorant IMO. I think it also depends what you use it for. I use both their search and their AI models for software development and it saves me precio…

I also used it for software engineering and personal use as well.

I had two major issues with it:

- it wasn't as snappy as google, but I kind of got used to it

- I wasn't trusting it (if that makes sense) and was falling back !g to make sure everything was searched

For $10, I expect to get a premium service, not a just good enough one.

I have to admit that I liked the idea, feeling of privacy and the ability to tailor a search engine for my needs.

Unfortunatelly I think that they are not where they need to be for the $10 pricing plan.

Re: Kagi News

#264
post #5

Kagi seems to be one of the few companies that put out services, genuinely trying to fix things with good intent. I hope it stays that way. (I was very skeptical about Kagi Assistant but now i am a happy Kagi Ultimate subscriber).

I used Kagi search for awhile but eventually switched back to google because Kagi location aware search sucks. It might be better nowadays. I’ve been living on their browser Orion for a few weeks now though and it’s great. It works about 90% of the time which is impressive for a browser that isn’t tested alongside the big 4

What do you mean 90%? Orion is WebKit under the hood, so any failures would be surprising.

Re: Kagi News

#265

Earlier quoted context omitted.

Just for concrete confirmation that LLM(s) are being used, there's an open issue on the GitHub repository, on hallucinations with made up information, where a Kagi employee specifically mentions "an LLM hallucination problem": https://github.com/kagisearch/kite-public/issues/97 There's also a line at the bottom of the about page at https://kite.kagi.com/about that says "Summaries may contain errors. Please verify imp…

Love how it only took 8 years to go from "Fake News!" to "News May Be Fake"

There's too much demand for fake news, plenty of subsidy for it, and it's far easier to make.

Non fake news is going to be restricted to pay services like Bloomberg terminals.

Re: Kagi News

#266

Earlier quoted context omitted.

I consider myself a major LLM optimist in many ways, but if I'm receiving a once per day curated news aggregation feed I feel I'd want a human eye. I guess an LLM in theory might have less of the biases found in humans, but you're trading one kind of bias for another.

Yeah, I agree. The entire value/fact dichotomy that the announcement bases itself on is a pretty hot philosophical topic I lean against Kagi on. It's just impossible to summarize any text without imparting some sort of value judgement on it, therefore "biasing" the text

> It's just impossible to summarize any text without imparting some sort of value judgement on it, therefore "biasing" the text

Unfortunately, the above is nearly a cliché at this point. The phrase "value judgment" is insufficient because it occludes some important differences. To name just two that matter; there is a key difference between (1) a moral value judgment; (2) selection & summarization (often intended to improve information density for the intended audience).

For instance, imagine two non-partisan medical newsletters. Even if they have the same moral values (e.g. rooted in the Hippocratic Oath), they might have different assessments of what is more relevant for their audience. One could say both are "biased", but does doing so impart any functional information? I would rather say something like "Newsletter A is compromised of Editorial Board X with such-and-such a track record and is known for careful, long-form articles" or "Newsletter B is a one-person operation known for a prolific stream of hourly coverage." In this example, saying the newsletters differ in framing and intended audience is useful, but calling each "biased in different ways" is a throwaway comment (having low informational content in the Shannonian sense).

Personally, instead of saying "biased" I tend to ask questions like: (a) Who is their intended audience; (b) What attributes and qualities consistently shine through?; (c) How do they make money? (d) Is the publication/source transparent about their approach? (e) What is their track record about accuracy, separating commentary from factual claims, professional integrity, disclosure of conflicts of interest, level of intellectual honesty, epistemic standards, and corrections?

Re: Kagi News

#269
post #265

Earlier quoted context omitted.

Love how it only took 8 years to go from "Fake News!" to "News May Be Fake"

There's too much demand for fake news, plenty of subsidy for it, and it's far easier to make. Non fake news is going to be restricted to pay services like Bloomberg terminals.

It is getting easier and easier to fake stuff and there are becoming less and less fully trusted institutions. So sadly I think you are right. Its scary but we are likely heading towards a future where you need to pay to get verified information and that itself will likely be segmented to different subscriptions for what information you want.

Re: Kagi News

#270
Cool but how does it compare to something like subreddits? There are still biased moderators behind the scene just like subreddits. Seems to not have the upvoting/downvoting side of it which imo is crucial to democratize the entire thing.

I think upvoting/downvoting is a crucial aspect to news/information/knowledge. But we've been doing it with just numbers all along. Why not experiment with weights or more complex voting methods? Ex: my reputation is divided in categories - I'm more an expert in history then politics hence my vote towards historical subjects have more weights. Feels like that's the next big step for news. Instead of just another centralized aggregator?

No offense to the cool system and website though

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