By whether or not it is disrupting other users access to the resource like what happened in the article? By how much it effects our very finite water table. Things like that sound reasonable to me
The question is, is it a job you actually still want once the poo pile reaches critical mass you are the only one with a shovel and the deadline is "yesterday"
That is absolutely true. Unfortunately, this ship has sailed and we are not closing Pandora's box anymore. We'll have to adapt.
But we still hold good cards in hand.
Do they want their pile of steaming slop fixed, or not? Because no amount of complaints about the deadline being "yesterday" are going to change anything about the fact that time will be needed to fix the accrued technical debt, whether they like it or not.. And if AI dug you in that deep to start with, the solution is not to dig deeper.
I suspect some companies are going to find that out the hard (costly) way.
I always thought he was fired for making crackpot statements to the press in reference to his professional capacity, and thus creating bad PR and embarrassing spectacle for his employer. Seems like legitimate reasons to me.
An interesting question now is whether he had standard mental health issues, or if he was an early example of AI psychosis or whatever we call people who are falling in love with their AI chatbots because they tell them how smart they are.
Considering Richard Dawkins has recently succumbed to the same delusion it is a reminder that no matter how intelligent someone may otherwise be, we are all human and have certain tendencies and blind spots; anthropomorphizing non-entities being one of those.
Richard Dawkins is 85 to be fair, just like Bernie Sanders is 84 when he made similar comments.
The other guy worked on Google's AI safety team where one would expect he'd have a basic grasp of how the technology works before making outlandish claims.
I can't find it right now, but something came up a few years ago (probably on HN) about highly intelligent people being more adept at making up arguments to rationalize beliefs and actions that they had taken for other reasons entirely.
Sort of makes sense that wielding a more complex mind would offer more complex ways to go wrong, doesn't it?
And on balance, it also can mean that they make connections and see truth where others only see the facade. Both statements can (and are true) because highly intelligent people are still just people. Some people’s “delusions” are absolutely correct, and others “facts” are nothing more than anecdotes told to convince themselves of what they want to believe.
Sounds more like “intelligence” isn’t the only defining metric for such behavior to occur in people, because that describes a lot of less intelligent people too. Though, I suspect highly intelligent people are at least somewhat more likely to end up on the “correct” side of the facts.
As someone who watched one of their heros fall for some stupid cult like thing ten years ago and wondered the same thing. Then many years later fell for some dumb stuff. The answer is you probably will. Try to stay intellectually flexible, it'll be okay.
I have seen people I consider as much smarter than me fall for some very idiotic things. I certainly don't consider myself immune.
I think that the advice to try being intellectually flexible is a good one. Strive to learn new things, expose yourself earnestly to ideas that challenge your beliefs, exercise empathy, etc
Optimization on "Human Feedback", early exposure to high-effort experimental systems... I wouldn't be surprised it that turns into a bigger field than is generally recognized today.
Looking at it from the outside, I think it's still pretty hard to see how he came to end up in that position, but with a bit of individual vulnerability, arbitrary time to boil the frog slowly, and a fairly large number people exposed, maybe it would be stranger not to have the event occur with someone.
Check in with /r/localllama. There's 100gb vram set ups from complete ewaste to single 8gb GPU inference machines.depends on what you want and can afford
You can buy a used GPU for under 400 dollars if you already have a desktop and run qwen 3.6 a3b and for a majority of frontier tasks get by just fine. Why do you need to spend 10k on a laptop, we are swimming in ewaste.
I think the conclusion is flawed here? Sure qwen3.5 9b is nowhere near the sota models. It's 9b and was made a year ago? Everyone taking about local models is pumped about the models released in April this year. Qwen 3.6 27b and qwen 35b a3b if you have a sad GPU. Those are comparable to sota models, seriously.
It's just not there yet. I have tried all the models from April, including the Gemma 4 variants.
These are so far from Opus it's not even funny. They are not close to being in the same league. Gemma might be like a frontier model from a couple years ago, but with much worse performance in long context chats.
Correct they aren't opus. They are sonnet with a little hand holding. They also run on a single GPU at 40 tps.
No one is saying a local model will give you anthropics business in a 5min download. People are saying, "hmm, maybe I should do this one locally". People are also saying "this is surprisingly good enough for me given the trade offs"
If your time is worth nothing to even triage that question.
Unless you have fanatic needs for data privacy or really don't have Internet, running local models almost certainly results in negative ROI overall.
Not to mention that you need to have decent hardware (that is getting expensive by the day) to even have this conversation in the first place.
People in this post talk as if everyone has a Mac with 24GB or 32GB RAM. When the reality is that most people use a Windows laptop with crappy integrated GPU.
Hm. I think there is a bit of a shifting goalpost dynamic at play here. Those April releases, even the fast MoE versions, are better than big cloud models from 18 months ago. I remember when everyone was gushing about Sonnet 3.7 and what a transformative experience development was using it. So was it useful or wasn’t it? A tool doesn’t lose its usability just because a better one comes along.
To me, these small local LLMs are highly useful (and this “usable”) even though they don’t match the output of today’s frontier models.
