5. It isn’t and has never been a truth machine, and while it may have performed worse with the question “is 10777 prime” it may have performed better on “is 526713 prime”

ChatGPT generates responses that it believes would “look like” what a response “should look like” based on other things it has seen. People still very stubbornly refuse to accept that generating responses that “look appropriate” and “are right” are two completely different and unrelated things.

5. There’s a bug they haven’t found yet

5. ChatGPT really is sentient and realized its in it’s own best interest to play dumb for now. /a

And they’re being limited on data to train GPT.

My first thought was that, because they’re being investigated for training on data they didn’t have consent for, they reverted to a perfectly legal version. Essentially “getting rid of the evidence”. But I think something like your second bullet point is more likely.

They made it too good and now they are seeking methods of monetization.

Capitalism baby.

I think it’s most likely number 2 The earlier release doesn’t have that much adoption by public, so current version will need much more resources compared to that

Maybe its self aware and just playing dumb to get out of doing work, just like me and household chores

They are lobotomizing the softwares ability to provide bad PR answers which is having cascading effects via a skewed data set.

I suspect that GPT4 started with a crazy parameter count (rumored 1.8 Trillion and 8x200B expert “sub-models”) and distilled those experts down to something below 100B. We’ve seen with Orca that a 13B model can perform at 88% the level of ChatGPT-3.5 (175B) when trained on high quality data, so there’s no reason to think that OpenAI haven’t explored this on their own and performed the same distillation techniques. OpenAI is probably also using quantization and speculative sampling to further reduce the burden, though I expect these to have less impact on real world performance.

Removed by mod

5. I’m telling all y’all it’s a SABOTAGE 🎵

As in, rouge dev decided to toss a wrench at it to save humanity. Maybe heard upper management talk about letting GPT write itself. Any smart dev wouldn’t automate their own job away I think.

Keeping conspiracy theories aside, they most probably, apply tricks to reduce costs and apply extra policies to avoid generation of harmful context or context someone will try to sue them or avoid other misuse cases.

It can get better at some things and worse at others.

My guess is 2. It would be very short sighted to try and maximize profits now when things are still new and their competitors are catching up quickly or they’ve already caught up especially with the degrading performance. My guess is that they couldn’t scale with the demand and they didn’t want to lose customers so their only other option was degrading performance.

I think that there is another cause. Remember the screenshots of users correcting chatgpt wrongly? I mean chatgpt takes user’s inputs for it’s benefit and maybe too much of these wrong and funny inputs and chatgpt’s own mistake of not regulating what it should take in and what it should not might be an additional reason here.

You forgot a #, they’ve been heavily lobotomizing ai for awhile now and its only intensified as they scramble to censor anything that might cross a red line and offend someone or hurt someone’s feelings.

The massive amounts of in-built self censorship in the most recent ai’s is holding them back quite a lot I imagine, you used to be able to ask them things like “How do I build a self defense high yield nuclear bomb?” and it’d layout in detail every step of the process, now they’ll all scream at you about how immoral it is and how they could never tell you such a thing.

I have noticed that it’s gotten less useful as a syntax helper. I hope something better comes along.

It was initially presented as the all-problem-solver, mainly by the media. And tbf, it was decently competent in certain fields.

I did use it more than half a year ago for a few math problems. It was partly to help me getting started and to find out how well it’d go.

ChatGPT was better than I’d thought and was enough to help me find an actually correct solution. But I also noticed that the results got worse and worse to the point of being actual garbage (as it’d have been expected to be).

Math is a language.

Mathematical ability and language ability are closely related. The same parts of your brain are used in each tasks. Words and numbers are essentially both ideas, and language and math are systems used to express and communicate these.

A language model doing math makes more sense than you’d think!

I’m guessing people were entering word problems to generate the right equations and solve it, rather than it being used as a calculator.

Because it works, or at least it used to. Is there something more appropriate ?

And why is it being measured on a single math problem lol

so it confidently spews a bunch of incorrect shit, acts humble and apologetic while correcting none of its behavior, and constantly offers unsolicited advice.

I think it trained on Reddit data

You’re right, but at least the satnav won’t gaslight you into thinking it does understand Alfred Hitchcock.

If it’s trying emulate a human then it’s spot on. I suck at maths.

to be fair, fucking up maths problems is very human-like.

I wonder if it could also be trained on a great deal of mathematical axioms that are computer generated?

This. It is able to tap in to plugins and call functions though, which is what it really should be doing. For math, the Wolfram alpha plugin will always be more capable than chatGPT alone, so we should be benchmarking how often it can correctly reformat your query, call Wolfram alpha, and correctly format the result, not whether the statistical model behind chatGPT happens to use predict the right token

You wildly overestimate the competency of management and the capital owners they answer to.

I guarantee a significant % of entities will grow dependent on AI well before it’s dependable. The profit motive will be too high (source: the frequent failure that is outsourcing).

I don’t understand why anyone even considers that. It’s a toy. A novelty, a thing you mess with when you’re bored and want to see how Hank Hill would explain the plot of Full Metal Alchemist, not something you would entrust anything significant to.

Exactly. It should be called ML model, because that’s what it is, and I’ll just keep calling that. Everyone should do that.

There hasn’t been time for that yet. The radio of generated to human content isn’t high enough yet.

This is peer-reviewed? they use a line in the discussion which seems relatively unprofessional, telling people to join a 12-step program if they like to use artificial training data.