tripledry

I agree with the sentiment that it might be net negative.

But on the other hand I'm almost certain I wouldn't have pushed through and gotten a degree without the internet (3b1b and Khan Academy in particular). I don't know what the world would look like without Google so almost impossible to argue, but I would definitely classify (ex. youtube) as "clearly useful".

You are correct, I simply mean we should keep in mind that they are also selling something.

If you ask an AWS consultant what the best solution for your problem is, don't be surprised if the answer is AWS.

Not commenting on Reid specifically but on the other hand I don't understand why we should listen to the Tech CEO's / Founders about their opinions on the tech they are selling.

As someone who doesn't follow the specifics of how LLMs write, how can you be sure it's an LLM?

I'm asking this genuinely because I've been using stuff like these separators before LLMS - now someone can just say "ahh dismiss the content they used style X it's LLM, it's dogshit".

Both probably, I don't usually understand sarcasm in written text unless it's explicitly stated.

Also, I'd rather lead a team of humans that I can interact and talk with in real life instead of a team of bots.

Highly doubt it.

There simply won't be jobs for them.

I simply don't agree with the doomer takes. Might be wrong. I'm kinda stupid yet here I am.

I'll believe it when I see it.

This is a thought I've had about genAI.

In case it all just comes from training data, "one shotting" a game would be more comparable to "git pull" and changing some assets than "generating code".

I'm not saying this is how it works, I'm trivializing LLMs with this statement, but when I see someone on linkedin excited about generating checkers and chess my first thought is "you could have done that with git pull for the past 20 years".

Yes, but the other N% of the country still might vote for the government you didn't want.

Had a "project" course in university for CS. Implemented a working SaaS app for hosting ML models (before AI).

Winner in our category had a powerpoint and a poster, no one even looked at the implementation. I learned something that day.

I've been told that my career is "cooked" since first Opus.

I'll believe it when I see it.

I might have misunderstood as english is not my native language but the 100% doesn't sit right with me in the original sentence.

In general I feel people downplay the effects of luck by a lot. My thinking is that the effort is everything but meaningless, in fact it's probably the only thing you can control.

At least they sent the application, that was effort. So it can't be 100% luck right?

From a technology perspective LLMs are absolutely bonkers, blows my mind it works as well as it does.

From a programmer perspective, I'm starting to like it less and less. It's useful for sure, but doesn't really live up to the hype. In many ways it's the opposite, my bet is still that programmers will be in high demand in the not so distant future after all of this settles.

Might be wrong, time will tell.

I felt the same way, then I started with "I'll believe it when I see it". Now I'm a bit happier.

Probably cultural norms and location play a huge role here, I'm in a nordic country and feel like trust is generally high and people are reasonable.

My bargaining power is not that high and managed to do this from tiny companies to global corporates.

I always ask companies to remove that clause from contracts, I think all offers I've ever got had that clause, but also 100% removed it on request.

while the additional realism would be essentially imperceptible to the player

Personally for me this is the relevant part.

I can ofc imagine some niche games like Kerbal Space Program with complete realism, but I'm not convinced it makes it more enjoyable to play. Would be interesting to see for sure.

Would have been interested in SpaceX but I don't like that xAI is being baked in so I will skip this one.

I'm sure there is an effect when people talk on socials (linkedin, company intra etc) that they are marketing themselves. This is why I won't take any claims on socials that seriously.

I'll believe it when I see it.

This is the only way for me to use Agents without completely hating and failing at it. Think about the problem, design structures and APIs and only then let AI implement it.

Has this changed, If I want to go hands on with development using pytorch or whatever is used now, would you recommend an AMD card?

Genuine question, I have not followed this topic closely for years :)

I'm wondering how much value there is in a rewrite once you factor in that no one understands the new implementation as well as the old one.

Not only is it difficult to verify, but also the knowledge your team had of your messy codebase is now mostly gone. I would argue there is value in knowing your codebase and that you can't have the same level of understanding with AI generated code vs yours.

Also, why is Anthropic still hiring SWEs?

I get this, but also genuinely interested to know how to measure outputs. For me it's almost impossible to get it objectively right.

Maybe this doesn't apply to your case, but how would you measure outputs of say product development, or any data related project. Lot's of things don't have a good measure of output before the thing is done. Maybe your product / analysis improves profitability by 10x or maybe it was a flop and lost money.

Tangential, but I'm also seeing the quality of measures going down, with AI it seems that the number of [emails|code|analysis] produced is again a good measure.

For me both are true at the same time.

I vividly remember understanding how calculus works after watching some 3blue1brown videos on youtube, but once I looked at some exercises I quickly realized I was not able to solve them.

Similar thing happens with LLMs and programming. Sure I understand the code but I'm not intimately familiar with it like if I programmed it "old school".

So yes, I do learn more but I can't shake the feeling that there is some dunning kruger effect going on. In essence I think that "banging my head against the wall" while learning is a key part of the learning process. Or maybe it's just me :D

It’s hard for humans to perceive the exponential, it will be slow then sudden.

True, but also there are perception biases that lead us to believe progress is exponential, even though it might as well be an S-curve.

I'm having a hard time finding the right terms, but I'm sure there is some bias to think that "the line goes up".

When someone at work talks about all software devs being replaced I link them to the Anthropic career pages.