tripledry

Not disagreeing, but I feel there is something to be said about how the tools we use nudge us to do things a certain way.

Similar to how using lambda functions and some document DB is easy and fast, but it often times leads to shit architecture as you don't have to think about it anymore, bolt on whatever cloud service X and Y for features and you have a mess.

AI is similar to cloud in that way, it's so forgiving that it pushes you towards a shit architecture as it "doesn't matter anymore".

Funnily enough AI makes the cloud mess easier to manage. These opinions are based on my own experience and most importantly, vibes.

I would say in addition to domain knowledge, it's also about intent. Code does not capture intent, it usually doesn't include the "why" just the "how".

I argue you still need communication for the "why" to get to the "how", otherwise you will just get the wrong thing.

Question, how viable are these tools and are they maintained?

I genuinely want to know if this is mostly hype or are they actually good. I don't think trying myself would really give a better picture as I'm not a user of said software.

Anyone who tried to replace photoshop with these AI clones successfully?

I think it's both. I want to agree with you but it's also just human nature, I notice myself slacking even when I care, because it's easy. The human brain is really good at finding shortcuts.

It's like saying it's the kids fault for being addicted to social medias and assigning no responsibility to the providers.

To be clear, I'm not advocating anti-AI laws or arguing with you, just blurting out my thoughts. Ultimately I simply feel this will not be a good thing for tech and human understanding in the short / medium term, but this is just based on vibes, like most arguments on AI are.

Yes. I've always suspected inference is profitable.

But I'm also interested is retraining needed? how relevant will a model be in N years if it's just "static", and if you do need to retrain and fine-tune over time, is it still profitable? how often is that needed?

For most cases it's probably ok, often times answers are general or basically a web search anyways, but if my Agent started blasting outdated syntax it would suddenly be way worse for coding for example.

> Random copy-pasta from stackoverflow anyone?

Was this a common thing? I don't know which bubble is more common, but personally I can't recall ever working with someone who couldn't explain what they did (just copy paste?), except for maybe configurations.

In my experience, people most definitely understand less of the technical implementation now vs before. Heck, not only technical, I've seen presentations from business where the presenter clearly vibed their deck and don't understand the content.

I think it's fairly likely medium to large corporations don't pay anywhere close to the listed API pricings as they get deals through existing partnerships with the big cloud providers.

Also think it depends on language, literally asked 2min ago from chatGPT (no login so maybe it's a shittier model?)

> Hur många 'r' I abborre, använd inte web search? Det finns 3 r i abborre.

And I explicitly had to say not to search the web, because that's what it did by default, to count letters in a word...

Huh, was not aware of that. Interesting

> Synthesizing complex information from a range of technical sources enough to build bioweapons is cognitively impenetrable for the vast majority of people. The ability of AI to synthesize this information into a step-by-step recipe to follow is a step change in accessibility.

I agree with this part.

> But as the barriers to entry to bioterrorism fall away and become widely accessible we may see the cost/benefit shift.

But I argue that the barrier to entry is not about information, it's about needing to build, execute and maintain a lab and production facility? It's not the theoretical part that's the bottleneck.

Or maybe I'm overestimating the difficulty of implementing such a thing, this is not in my area of expertise.

Is this something that happens by accident in the sense that the decision makers didn't know how it would sound or is there actually someone in a room at some point going "fuck it".

But hasn't bio attacks already been possible before AI, what has changed? Maybe the barrier to entry lowered, but one could argue the availability of info has not been the bottleneck for as long as the internet has existed.

The threat is ofc real, but AI won't magically "do the thing" still, it's not code that's the bottleneck AFAIK? Correct me where I'm wrong.

I'm not disagreeing with your comment, should probably have made that clear.

The SaaS to inhouse argument is just something I've heard that came to mind when reading this thread.

In stuff like wikis and ticket systems what I see is people now just making their own little tools around the ones we already use, this arguably just sements their position even deeper.

Also I dont get the inhouse argument, you dont really save anything. So instead of paying X to SaaS, you now propose to pay X to anthropic instead AND maintain said SaaS... what? how is that better, that just shifted the cost to another company and you got the burden of maintenance and responsibility.

I agree with what you said, and _sometimes_ it's true, but I still wouldn't call it a "preference". One could argue there isn't a "need" to deliver faster and come up with solutions to problems, but is it a "preference"?

Maybe I'm completely off base here, arguing about semantics.