AI Cold Showers | Hacker News Reader

AI Cold Showers

allan.reyes.sh

77 pointsmooreds12 comments

> What they are proposing, in most cases, is a dashboard or website that displays the status of a process that is not ready to be automated, built to track a workflow that does not yet warrant tracking. The tool has not solved a problem

The above is from one of the articles listed [0].

The passage struck me because I've worked at a couple places where either or both of the below was true:

- there were more people than needed for the work queue

- there wasn't clarity on people's role and/or what they should be working on.

I mention this b/c the problem of people finding solutions for problems that don't exist is not an AI phenomenon but rather a preexisting one.

AI is certainly exacerbating the issue but it's not a new phenomenon.

0 - https://nooneshappy.com/article/appearing-productive-in-the-...

Enjoyed this. More importantly its an emerging problem we need to urgently solve.

Apart from my own desire to read the internet to find out what actual people think .. Im worried about a kind of bit-rot, where any decade now, gen-pop reader has no idea what content came from humans and what came from AI.

Im assuming the people who _train_ AI [ LLMs ] actually need to separate the two, and avoid the feedback loop of training the next LLM on the output of the previous LLM.

Presumably, this would lead to a kind of reversion to the mean, akin to making photocopies of photocopies back in the day, resulting in copy degradation.

We already have a kind of bit-rot from moving away from physical media - many documentaries on TV, and audio / video / movies / games are being lost as they are not moved to permanent archive storage.

Old out of print books should be scanned and made public and permanently available online, as they are part of our cultural heritage [ not least for the purposes of training current and future AI as the defacto archives / oracles ]

Oh they don’t have this data degradation problem at all. They have large data curation teams that scrutinize the “data mix”, ensures the model is always performing better.

> Im assuming the people who _train_ AI [ LLMs ] actually need to separate the two, and avoid the feedback loop of training the next LLM on the output of the previous LLM.

Check out Reinforcement Learning from AI Feedback (RLAIF). Then skim some of this maybe: https://arxiv.org/abs/2309.00267

There's such an avalanche of blogposts on HN constantly saying relatively similar things about AI, that it would be really nice if they were all just filtered down into lists like this occasionally.

We actually downweight lists on HN, for reasons explained a few times over the years:

https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

It needs a more coherent cogent discussion, leading to dare I say it sane _policy_ ... which the frontier model companies and hyper-scalars are not incentivized to finance, and governments too slow and weakly funded to finance.

Other topics we seem to have been unable to have deep and informed discussion on, leading to sane policy :

  - inequality / taxation
  - demographics / aging population
  - climate change mitigations
  - affect of social media esp on young people
  - safety of self-driving cars
  - economic impacts of LLMs
  - educational "" "" 
  - security "" ""
  - surveillance of in-home devices
  - data collection and sharing
  - right to repair

Failing to react rationally to a rapidly emerging global pandemic a few years ago should have been a wake up call but wasnt.

If the technorati are woefully unprepared for the age of AI, which is being rapidly thrust upon us by the big money, then the wider public dont stand a chance of being informed / prepared.

The last part about AI note takers is interesting because I agree with the general sentiment of the article, especially the reading/writing part. That said, the AI notetaker usually allowed me to focus on the person I was talking to so this was something where I always saw great value even if taking my notes might have yielded slightly better results.

> perhaps most importantly on what makes humans, human

What makes humans human is love, laughter, community, children, art, beauty. How are LLMs even remotely a threat to this? The piece is so hyperbolic, it's just hard to take seriously

I really feel that the anti-AI crowd is becoming a weird religion, kind of like the crypto NFT crowd was a few years ago. Most people that use AI are just like "yeah whatever, it does X, Y or Z, sometimes it sucks and I have to re-prompt it, it's pretty neat."

While the anti-AI crowd is like "I PLEDGE TO NEVER USE AI, HERE IS MY BLOOD OATH." Like, calm down. It's not that big of a deal. Some of these bullet points are just straight-up nonsense.

> I won’t read AI summaries as a substitute for reading the source material with my own damn eyes.

Author is... just defining what a summary is. Yeah, no one looks at summaries as if they're the original text. Ever. What is he even saying here?

Absolutely opposite experience. People do not shut up about it once they’ve tried it, and come up with all sorts of whacky use cases for it. Best friend suggested I ask ChatGPT whether it’s cheaper to renovate or knock down a house I bought specifically to renovate it, which I’ve told him on multiple occasions.

AI is the successor to all things crypto, there’s definitely religious fervour to it like there was around blockchain/NFT’s changing the world.

> People do not shut up about it once they’ve tried it, and come up with all sorts of whacky use cases for it.

Other than Twitter engagement baiting (which people have done w.r.t. every other new hyped up thing, whether it's drop shipping, SaaS, crypto, whatever), I really don't see this day-to-day.

> Best friend suggested I ask ChatGPT whether it’s cheaper to renovate or knock down a house I bought specifically to renovate it, which I’ve told him on multiple occasions.

I don't understand what this anecdote has to do with AI, it sounds like your friend is just a bad listener.

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