randomsearch

For the record, I do not have a Tesla, a reusable rocket, or a flamethrower.

I just think people do good and bad things and I try not to pick sides.

> People at Tesla and SpaceX have achieved great things, not Musk

You can’t be serious. So Musk can’t take any credit for what those companies have achieved?

By that logic, he should also be blameless for any problems at Twitter.

This seems like a big drama without the complexity that would justify it.

Essentially, Twitter should have a clear and consistent moderation policy. Musk should not be able to arbitrarily change that policy, or certainly not when the situation directly concerns him. So you publish a policy and then it gets regularly reviewed, and that’s it.

Tbf, it seems that pre-Musk Twitter was also fairly arbitrary, it’s just now it’s for his benefit rather than the murky hidden incentives of the previous regime. They do seem to have set precedent by responding to arbitrary pressures.

What is the significance of the word “billionaire” in that sentence? Is it worse to be a hypocrite if you’re a billionaire? Do you think it’s unethical to be a billionaire?

I think calling anyone defending Musk at any level a “cheerleader” isn’t a helpful framing of the debate.

It’s important not to make any issue an “I align with X so you’re against me” conflict.

Musk has achieved great, incredible things. That’s just indisputable fact.

Musk is also behaving erratically, inconsistently, and seemingly also unethically over Twitter. And has done so in the past, eg in the dispute with the diver or against short sellers.

One aspect of Elon’s actions does not cancel the other out. We should celebrate the good and debate the bad.

I feel like this melodrama is driven by Musk’s detractors ready to pounce and dismiss, say, the development of reusable rockets, by Musk being petulant. That is not an argument that makes any sense.

And the same goes for any fans who think Musk’s incredible achievements give him permission to ban and censor those who annoy him.

Yes you've nailed it. Totally human to react to a personal incident. Needs to be guarded against.

The existence of irrational numbers is in no way analogous to saying “the king of England is George V” and to pretend otherwise is disingenuous.

My general approach to discussion is to assume the most generous interpretation of a post.

No, I think it’s relevant because the banned account was not just “sharing public information”, but actively tracking Musk using a combination of online data and real word surveillance.

The fact that Musk previously said he wouldn’t ban the account, then changed his mind (apparently after a personal incident) just shows Musk changed his mind, is all.

It certainly demonstrates he didn’t think through his previous decision, suggesting it was a spontaneous comment and not a rigorous policy. Which is worrying, because publishers such as Twitter need to have a consistent and coherent moderation policy.

But it’s still relevant if we’re to decide which position we agree with, and whether Musk was “right” previously or now.

Previous poster said that GPT is to writing what calculators are to math. That's an interesting point, is this an analogy we can reason with?

My terse response was "no, because calculators are correct all the time whereas GPT is incorrect a lot of time". So, that reasoning can't be used. Need a different one.

So we conclude, no that's not a good analogy.

Oppenheimer

The goal of HN is not “win argument” but curious debate. You know what I meant.

No real need for one until now I think.

This is a really hard question to answer, but do you think in peacetime 1930s if you’d asked someone how long it would take to build the bomb, they’d say “we’re only a few decades away with proper funding”?

The pay off achieved by accelerating fusion development seems to justify almost any amount of spending. Is it worth going for it?

The most important subquestion for me: is there a sufficiently brilliant living scientist who has the technical ability, managerial skills, and integrity to be trusted to deliver? I wonder if this is the reason we haven’t already done it.

Calculators are always correct.

mmm well how long did GPT take? Say a quarter of that time?

This is the best argument I've seen against my own position. I don't think I agree, which leads me to think that the error I have made was in disagreeing with the art galleries. I guess they also didn't want to deal with a deluge of the banal.

For all but the shortest fragments of text, I suspect the answer to this will be "yes" and this will be achieved in a short timeframe. Interact with Chat-GPT enough and you soon begin to tire of its middle-of-the-road prose. Because it is in some sense a statistical average of its inputs, its writing feels very monotonous.

Of course, you can try to push it in the direction of something more interesting... "write in the style of X" so that it will regurgitate from a subsection of its training input, or push it onto a niche topic. Across a wide range of inputs, though, I predict it will be easily classified.

As training GPT will take far longer than training a GPT-detector, this is an arms race that the detectors will win for the most part. Anyone wishing to use GPT to generate middling essays to cheat at school will have to spend a lot of time to disguise the text (perhaps repeatedly running against open-source detectors) and then take the risk that detection does not improve between their submission and review.

Well, that is certainly false, because Chat-GPT was trained on the web and would surely have been exposed to content explaining policies on HN. So if this was generated by Chat-GPT (and it either was or was written by a human impersonating Chat-GPT's banal writing style) then it's another example of why it should be banned.

I agree. ChatGPT has made me realise the gulf between “short form essay” school writing and the professionals.

Here’s an example article that begins with the cliched GPT-generated intro, and then switches up into crafted prose:

https://www.theatlantic.com/technology/archive/2022/12/chatg...

Ok, thanks very much.

So what if the server just rebases the edit, and that results in the caption being set a second time? ie most recent wins. Don’t see how this would break a schema?

Encoding “adding a caption” as “add an additional child called caption” would be silly, as we know there can only be one caption. So the op would be “set the caption”.

Curation and experts are coming back big time.

Read it in the Economist -> high trust.

Any public forum -> assume nonsense.

I'm confused here - please could you explain. Here's what I see would happen:

1. User 1 adds a caption

2. User 2 adds a caption.

3. Both transmit to the server.

4. Server receives the first edit, applies it to the doc, broadcasts the change.

5. Server receives the second edit, sees it is applied to the previous version of the document, rejects the edit.

6. Client that receives the rejection re-bases their edit, attempts to apply it, and it is rejected as it does not conform with the schema.

So the outcome is whichever client hits the server first wins, which is fine. Where's the problem?

The figure I gave doesn't include health insurance... the UK doesn't do that, generally speaking. So you'd have to take that out.

I’m not an academic.

No idea why you’d include health premiums in that figure.

Remove that and I just don’t believe you, outside of the most bureaucratic and exceptional companies (eg Google, where the money printing machine has led the company to insane levels of “overhead”).

I’ve worked plenty in the private sector and it’s nonsense to suggest overheads are similar In general.

Maybe, but also think about the prompts. Google might be able to infer far more about your intentions from a fully formed question rather than a search query. Which will allow them to target you more precisely, allow them to sell data to product companies. Prompts are more personal and revealing, even the language you use.

You could also imagine inserting adverts into the generated response.

ChatGPT is such a strange technology, because it simultaneously makes me want to point out how limited it is, but also gives me the feeling that there may be something deeper here.

I’ve spent a bit of time studying language models, and so far it just seems that GPT predicts the next word given some previous words as context. By applying a pretty basic approach but using a vast, almost unimaginable amount of data, it manages to write plausible looking prose that gives you the impression of intelligence. In reality, it’s essentially compressing a very large dataset and sampling from that set in a way that hides its memorisation. So it can be easy to dismiss from a theoretical point of view. What does amaze me is the curation and utilisation of the dataset itself. It’s just an incredible feat, and there must be so much more to that pipeline than that we know. But still, it doesn’t reason, it’s liable to be wildly inaccurate without warning, and there is no way I can see to fix this approach. If I had to guess, I’d say it will be a dead end - for now - but in the long term a relative of our current language models will fit into a larger cohesive system.

But… what gets me is, well, how do you know humans don’t just use such a simple approach? As Sam Altman puts it - how do you know we’re not just stochastic parrots? Ultimately we hear a lot of spoken language and anecdotally we have these repeating phrases we use, there are the linguistic equivalent of ear worms that clearly meme their way around the world - I hear the phrase “betting the farm”, something I hadn’t heard until a few years ago, I start using it and I see someone for the first time in a while and notice they also use it. Our models are being extended based on our input.

There’s clearly a difference between us and GPT, because when I write I am intentionally conveying meaning, and usually I work hard to avoid making statements that are false. But what this tool is making me consider is - perhaps this metacognition, this reasoning and fact checking, is sitting either “on top of” or “inside of” the language model. From meditating, it seems that I have feelings and those feelings perhaps lead to a sample from my internal language model. Is it the case that I then censor the strings that contain untruths or for other reasons should not be expressed? Do I take the output and then use it in combination with some other mental faculty to edit the string, perhaps pass it back into the language model? “Well, what I really meant there was X, please fix it.”

In this way I think the GPT model itself is actually theoretically fairly trivial and uninteresting, but the _observation that a simple predictive model combined with a gargantuan dataset can achieve so much_ is absolutely astounding. It may be the case that GPT is mostly useless in a practical sense, but in a philosophical or research sense it may prove to be a pivotal moment in our understanding of how the mind works.

Yep. Wage of postdoc U.K. (real scenario) £40K. Uni charges govt over £100K. £60K “overheads”.

Everyone even thinking about creating a startup should read "The Mom Test" first.

It's not the same.

If you ask a chat interface a question and it says "this is true", that's very different from a search engine containing a list of results where one of them might be untrue.

For one thing, you can look at all the queries and take a majority vote etc. Second, you can look at the source to see if it's trustworthy.