Hacker News Reader

Comment by danielmarkbruce | Hacker News Reader

If you need basically rock solid evidence of X before you stop saying "this thing cannot do X", then you shouldn't be running a forward looking lab. There are only so many directions you can take, only so many resources at your disposal. Your intuition has to be really freakishly good to be running such a lab.

He's done a lot of amazing work, but his stance on LLMs seems continuously off the mark.

View on HN

The list of great minds who thought that "new fangled thing is nonsense" and later turned out to be horribly wrong is quite long and distinguished

> Heavier-than-air flying machines are impossible.

-Lord Kelvin. 1895

> I think there is a world market for maybe five computers. Thomas Watson, IBM. 1943

> On talking films: “They’ll never last.” -Charlie Chaplin.

> This ‘telephone’ has too many shortcomings… -William Orton, Western Union. 1876

> Television won’t be able to hold any market -Darryl Zanuck, 20th Century Fox. 1946

> Louis Pasteur’s theory of germs is ridiculous fiction. -Pierre Pachet, French physiologist.

> Airplanes are interesting toys but of no military value. — Marshal Ferdinand Foch 1911

> There’s no chance the iPhone is going to get any significant market share. — Steve Ballmer, CEO Microsoft CEO. 2007

> Stocks have reached a permanently high plateau. — Irving Fisher, Economist. 1929

> Who the hell wants to hear actors talk? —Harry Warner, Warner Bros. 1927

> By 2005, it will become clear that the Internet’s impact on the economy has been no greater than the fax machine. -Paul Krugman, Economist. 1998

An important number of those remarks were based on a snapshot of the state of the technology: a fault in not seeing the potential evolution.

Examples of people who could not see non (in some way) dead-ends do not cancel examples of people who correctly saw dead-ends. The lists may even overlap ("if it remains that way it's a dead-end").

In fairness to Irving Fisher: if you bought into the market at its peak in 1929, you wouldn't recover your original investment until about 1960.

I am just wondering did you have this all somehow saved up or did you pull it out of somewhere? Amazing list of things. Thank You.

Gosh no. I knew most of that list but I'll be honest and tell you that I used ChatGPT to come up with it. it's a collection of quotes to begin with so I think that's okay. I'm not passing off someone else's writing as my own, I'm explicitly quoting them.

I'm pretty sure that Lord Kelvin was also in the cohort of fools that bullied Boltzmann to his suicide.

*formerly great minds.

In many cases the folks in question were waaaaay past their best days.

I doubt that list is as long as the great minds that glommed onto a new tech that turned out to be a dud, but I could be wrong. It's an interesting question, but each tech needs to be evaluated separately.

I'm going to wear the tinfoil hat: a firm is able to produce a sought-after behavior a few months later and throws people off. Is it more likely that the firm (worth billions at this point) is engineering these solutions into the model, or is it because of emergent neural network architectural magic?

I'm not saying that they are being bad actors, just saying this is more probable in my mind than an LLM breakthrough.

It depends what you mean by "engineering these solutions into the model". Using better data leads to better models given the same architecture and training. Nothing wrong with it, it's hard work, it might be with as specific goal in mind. LLM "breakthroughs" aren't really a thing at this point. It's just one little thing after another.

Sure, I specifically pre-agreed to it not being ill will. What I mean is keeping tabs on the latest demand (newer benchmarks) and making sure their model delivers in some fashion. But it is mundane and they don't say that. And when a major number increases, people don't assume they just added more specific training data.

Yup, it's a fair point. We very quickly got down to the nitty gritty with these things. Hopefully, like semiconductors nitty gritty results in a lot of big performance gains for decades.

Reply on news.ycombinator.com