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Oof, that one is particularly bad because it cites 3 sources which are all the same article. Google points to phys and phys is a republish of the MIT article.
There's even a 'perspectives' section that tries to contrast two of the sources, but they're the same article.
> One daily update: We publish once per day around noon UTC, creating a natural endpoint to news consumption. This is a deliberate design choice that turns news from an endless habit into a contained ritual. I might not agree with all decisions Kagi makes, but this is gold. Endless scrolling is a big indicator that you're a consumer not a customer.
Another russian disinfo laundering service.
Kagi’s ‘neutral’ stance on politics, their association with Yandex/the Russian state mean this will be interesting to watch.
It’s by far the best search I’ve ever used.
https://old.reddit.com/r/ukraine/comments/1gvcqua/psa_the_ka...
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…
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> A lot of times when I ask for a source, They'll do pretty much everything you ask of them, so unless the text actually come from some source (via tool calls, injecting content into the context or other way), they'll make up a source rather than doing nothing, unless prompted otherwise.
Maybe they should be trained on the understanding that making up a source is not "doing what you ask of them" when you ask for a source. It's actually the exact opposite of the "doing what you asked, not what you wanted" trope-- it's providing something it thinks you want instead of providing what you asked for (or being honest/erroring out that it can't).
How do you make an LLM understand that it must only give factual sources? Just some naive RL with positive reward on the correct sources and negative reward on incorrect sources is not enough -- there are obscenely many more hallucinated sources possible, and the set of correct sources is a set of insanely tiny measure.
I think this is the wrong direction. We need better journalism, not better summarizing aggregators. Summaries are no substitute for real articles, even if they're generated by hand (and these apparently are not). Summaries are bound to strip the information of context, important details and analysis. There's also no accountability for the contents. Sure, there are links to the actual articles, but let's not kid ourse…
> We need better journalism, not better summarizing aggregators. I agree, but how do you envision that happening? Journalism died a long time ago, arguably around the birth of the 24-hour news cycle, and it was further buried by social media. A niche tech company can only provide a better way to consume what's out there, not solve such large societal problems. > There are no "lifehacks" to getting informed. I don't t…
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…
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…
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OK, but I'd like to repeat my question here: Why do you care how the summary was generated?
I'm not the person you asked, but it's useful to know if the summary was generated using a method prone to inaccuracy.
Yet, there is Hacker Newsletter (https://hackernewsletter.com/, which I like and use), there are others pointed by GPT5 that I don't Mailbrew and Digest. Kagi looks like the true former.
What I do want is personalization - not by picking interest, but actual personality, prompt, tastes, good enough that it puts something other, rather than only narrowing and narrowing my view. Yet high quality, rather than clickbaits and other "fluff". Otherwise, following a few Reddits would do the job (with some API to send emails).
What I would like even more is something that actually turns my social media into daily emails.