Wow, it's always amazing to me how the law of unintended consequences (with capitalistic incentives acting as the Monkey's Paw) strikes everytime some well-intended new law gets passed.
Counterpoint being that Slack, for example, for all its faults, does not have ads in its chats.
If Anthropic is positioned as "thing for professionals to do professional work" then I think you just avoid this issue entirely. Fee for service. OpenAI trying to be the thing everyone is using won't work in that model, though.
Wait for the API costs or open-source models to be cheap enough and we'll get there. I mean it's a guaranteed HN frontpage (and currently also a guaranteed epic credit card bill).
I've been waiting for someone to implement this well! I think in the future we might even have tiktok-style influencer videos generated from wikipedia content, who knows.
I've been swiping a lot for the last 10 minutes and I'm not sure how much it's learning. I have some feedback.
- I have never liked or clicked a biography but it keeps suggesting vast amounts of those
- It does not seem to update the score based on clicking vs liking vs doing both. I would assume clicking is a solid form of engagement that should be taken into consideration
- It would be interesting to see some stats. I have no idea how many articles i've scrolled through or the actual time spent on liked vs disliked article previews. If you can add such insight it would be interesting
- A negative feedback mechanism would be interesting as well. There is no way to signal whether I'm just neutral towards something (and swipe through) or actively negative about it (which is a form of engagement the doomscroll would actually use to show me such content once in a while)
- since this website has already shown me multiple pages about things I'm learning about thanks through it, it might benefit from a "share" button (another engagement signal) as HN folks are likely to want to share on HN things they've just learned
- Would you be willing to make the experiment open source?
I want to try reimplementing it for Wikipedia in another language, would you mind sharing how you went from the 400MB Wikipedia export to the .1x (40MB) file that is downloaded here?
Perfect! Thanks for clarification. I thought there was server-side preparation of the content, but it seems from the other posts that it's all local, and I commend you for that.
> Educators often describe reading as a predictor of long-term success, both academically and professionally. A JPMorgan survey of more than 100 billionaires, reading ranked as the top habit elite achievers had in common, including Bill Gates, Barack Obama and Oprah Winfrey
This article is not off to a great start when right away it
- mentions Barack Obama in a survey of billionaires (he isn't)
- conflates academic and professional success with becoming a billionaire which is an outlier outcome
- links to a Yahoo News article (reporting the same story as the OP) when claiming to refer to a Fortune Magazine article (not linked; but I found it and the OP sems copypasted from it) as their source for a JP Morgan survey.
> mentions Barack Obama in a survey of billionaires (he isn't)
This is hilarious in the context of an article about falling literacy.
They surveyed billionaires about “elite achievers.” Obama wasn’t surveyed, because as you point out, he isn’t a billionaire. Billionaires were surveyed about him.
Don't be snarky when you might be wrong in no less than 2 ways:
1. When they say
A JPMorgan survey of more than 100 billionaires, reading ranked as the top habit elite achievers had in common
They are not asking billionaires about other people ("elite achievers") they are asking the billionaires about themselves, and the writer is using another term to avoid repearing "billionaires".
2. The actual report, which I had tracked down prior to reading the message above, is here, and you can use your own literacy skills to confirm that my point (1) above is the correct understanding:
> We explored with each principal how they spend their time, what captures their
interests and how they view the world across several key areas. While each principal’s experiences are unique, common priorities emerged.
> you can use your own literacy skills to confirm that my point (1) above is the correct understanding
It’s not. I know the 23 Wall guys. They’re constantly surveying their clients for obvious reasons about everything they’ll answer.
In this case, they’re surveying the family offices of billionaires. About, among other things, what makes them special. And what makes other non-billionaire special people special.
The only place where "reading" is mentioned in the entire report is on page 71.
In response to:
1. What hobbies or interests are you most passionate about? (ranked)
and
2. "Top seven habits attributing to success (ranked)".
Most of the principals approach their daily routines with intention, making purposeful choices with their time.
So at this point we have two hypotheses: the first is that there is a PDF report which states something rather clearly, and then Fortune Magazine wrote a puff piece around it which was picked up by Yahoo News, and then copypasted by this other writer in the OP with some filler added for good measure, and you're reading too much into it.
The second is that the Fortune Magazine guy "knows these 23 Wall guys", and the Yahoo News guy knows these guys, and the OP writer knows these guys, and you know these guys, and all you guys know that even though Barack Obama was never mentioned once in that report, it is absolutely obvious that we the readers should read between the lines that the questions asked are not the ones written in the report and the replies they got are not the ones written the report either, and OP writer just gets it.
I am afraid that my literacy is mostly limited here to the things that are written, since I do not know these guys.
I’m not saying the Fortune article might not be puffery. Just that a straight reading of that sentence is clear and plausible and that complaining about it not making sense buries a good argument you have about how this article was written and sourced.
Thanks for the feedback. The discrepancy for us seems too large to be only VAT (and the usage numbers are also vastly different). I'll report what their support gives as the explanation.
Most AI Chatbots do not rely on their training data, but on the data that is passed to them through RAG. In that sense they are not compressing the data, just searching and rewording it for you.
It feels like you're being pedantic, to defend your original claim which was inaccurate.
User input: Does NYC provide disability benefits? if so, for how long?
RAG pipeline: 1 result found in Postgres, here's the relevant fragment: "In New York City, disability benefits provide cash assistance to employees who are unable to work due to off-the-job injuries or illnesses, including disabilities from pregnancies. These benefits are typically equal to 50% of the employee's average weekly wage, with a maximum of $170 per week, and are available for up to 26 weeks within a 52-week period."
LLM scaffolding: "You are a helpful chatbot. Given the question above and the data provided, reply to the user in a kind helpful way".
the LLM here is only "using the probability encoded in the training data" to know that after "Yes, it does" it should output the token "!"
However, it is not "decompressing" its "training data" to write
the maximum duration, however, is 26 weeks within a 52-week period!
It is just getting this from the data provided at run-time in the prompt, not from training data.
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