I don’t have an evidence that delusional people and nitpickers are the same people. I never said I don’t have an evidence that delusional people are delusional.
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?
From what I've seen, very buggy currently, and unknown how well they will be maintained. They're definitely not at a stage where adobe should be worried about their revenue, and there are foss alternatives for most adobe tools, that are better than these reverse engineered ones. But if they continue maintaining them and fixing the bugs, who knows, maybe adobe really loses some part of their customer base (although a lot of their individual tools have already been moved to the cloud, thus they can't be reverse engineered anyway)
By all reports they are not good and have quite a few bugs. But the thing about open source is that, if maintained, it almost always improves. And with the bar for maintenance so low due to AI, we are entering a very interesting time for software.
And by interesting I mean scary, if you sell software.
call me snarky but I don't think a gigantic amount of AI slop is maintainable by any means unless you just throw every token you got and hope for the best
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.
They need to be retrained often is my experience for general usage.
I have SO many cases, for example when shopping, when they make assumptions based on their cutoff date, and they need to redo everything based on lots of searches.
Sure, for many use cases old models will be useful but for general usage a model that's 5 years old will probably be garbage for most people, unless they prompt it extensively, which the general public won't do.
Relying on an LLM's baked-in syntax knowledge is suboptimal, compared to leveraging reasonable context affordances (skills, examples, tool calls, MCP servers, search) to ensure adherence to precise APIs and language specs. Don't get me wrong; a model specifically trained on your desired framework is obviously preferable for more consistent generation of idiomatic code -- but relying on that in a large general-purpose model is a questionable proposition IMHO.
> 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?
Just wait until what Ilya Sutskever has for Safe Super Intelligence (SSI) to self update the weights without retraining them to bring training costs down close to $0.
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.
My bubble is opposite - majority did not understand simple things. I ve seen people randomly trying SO advice on “fixing” git repo, mutating objects passed as arguments (because it works!), not understanding what is env variable.
Your example just proves the point: AI is not a problem - it’s a leverage. Give it to someone who don’t care - they will do as much damage as they can.
But imho the issue is not ignorant people. It’s lack of leadership. Somehow those people got selected for the job and still keep it.
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.
It was a huge thing, and I lived through all of it, yet never ran into a problem where copy-and-pasting would have been the lowest resistance solution. I never even ran into a problem where asking the question and waiting for a response would have made more sense than asking internally or working through it myself. The most difficult problems are relatively conceptual, which SO didn't like anyway.
I never really got it. I think it depended bigly on which domain and stack you were in.
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.
The free models for ChatGPT, especially without login, do very little reasoning. You should at least log in to set any level of reasoning above Instant, which uses virtually none.
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.
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.
There's an opportunity cost to terrorism just like with any time sink. The effort to build up knowledge enough to produce some weaponized pathogen will be compared to just doing traditional terrorism. For some low capability terror cell, its easy to see how the cost/benefit analysis has been in favor of traditional terrorism up to now. The kinds of terror acts that take years of sustained effort to execute are rare. But as the barriers to entry to bioterrorism fall away and become widely accessible we may see the cost/benefit shift.
> 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.
>Or maybe I'm overestimating the difficulty of implementing such a thing, this is not in my area of expertise.
Not mine either. But there is a vocal contingent of experts in biotech that have been sounding the alarm for the last couple of decades at the potential for rogue groups to develop weaponized pathogens for terrorism. And this was years before LLMs. Apparently constructing a sufficiently capable lab isn't really a bottleneck due to how freely available equipment is by mail order and how unsophisticated the processes are in practice.
>Consider our publication earlier this year, in which we reported that 36 of 38 companies shipped pieces of the 1918 influenza genome. That was collectively enough to generate the virus using reverse genetics several times over – and they were ordered by a student using a pseudonym falsely claiming to work at an office address. No one asked whether we had permission to work with 1918 influenza (a select agent), or why we needed genes from it, even though the official U.S. guidance at the time instructed them to do so. In fairness to the companies, that guidance was voluntary, and the fragments we ordered were legal to produce and sell domestically in every nation of the world (export controls are complicated). That is still true today, which is why we have a problem.
Just find it funny how vibes based it all is, capabilities, experiences, anti-ai and pro-ai.
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