351–360 of 620 posts
We dropped Claude. It's pretty clear this is a race to the bottom, and we don't want a hard dependency on another multi-billion dollar company just to write software We'll be keeping an eye on open models (of which we already make good use of). I think that's the way forward. Actually it would be great if everybody would put more focus on open models, perhaps we can come up with something like the "linux/postgres/git…
We dropped Claude. It's pretty clear this is a race to the bottom, and we don't want a hard dependency on another multi-billion dollar company just to write software We'll be keeping an eye on open models (of which we already make good use of). I think that's the way forward. Actually it would be great if everybody would put more focus on open models, perhaps we can come up with something like the "linux/postgres/git…
We dropped Claude. It's pretty clear this is a race to the bottom, and we don't want a hard dependency on another multi-billion dollar company just to write software We'll be keeping an eye on open models (of which we already make good use of). I think that's the way forward. Actually it would be great if everybody would put more focus on open models, perhaps we can come up with something like the "linux/postgres/git…
This is part of the reason why I'm really worried that this is all going to result in a greater economic collapse than I think people are realizing. I think companies that are shelling out the money for these enterprise accounts could honestly just buy some H100 GPUs and host the models themselves on premises. Github CoPilot enterprise charges $40 per user per month (this can vary depending on your plan of course), b…
We dropped Claude. It's pretty clear this is a race to the bottom, and we don't want a hard dependency on another multi-billion dollar company just to write software We'll be keeping an eye on open models (of which we already make good use of). I think that's the way forward. Actually it would be great if everybody would put more focus on open models, perhaps we can come up with something like the "linux/postgres/git…
Open models keep closing the eval gap for many tasks, and local inference continues to be increasingly viable. What's missing isn't technical capability, but productized convenience that makes the API path feel like the only realistic option. Frontier labs are incentivized to keep it that way, and they're investing billions to make AI = API the default. But that's a business model, not a technical inevitability.
ive had to like tune out of the LLM scene because it's just a huge mess. It feels impossible to actually get benchmarks, it's insanely hard to get a grasp on what everyone is talking about, bots galore championing whatever model, it's just way too much craze and hype and misinformation. what I do know is we can't keep draining lakes with datacenters here and letting companies that are willing to heel turn on a whim basically control the output of all companies. that's not going to work, we collectively have to find a way to make local inference the path forward.
everyone's foot is on the gas. all orgs, all execs, all peoples working jobs. there's no putting this stuff down, and it's exhausting but we have to be using claude like _right now_. pretty much every company is already completely locked in to openai/gemini/claude and for some unfortunate ones copilot. this was a utility vendor lock in capture that happened faster than anything ive ever seen in my life & I already am desperate for a way to get my org out of this.
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If you think that "strawberry" is some kind of own, I don't know what to tell you. It takes deep and profound ignorance of both the technical basics of modern AIs and the current SOTA to do this kind of thing. LLMs get better release to release. Unfortunately, the quality of humans in LLM capability discussions is consistently abysmal. I wouldn't be seeing the same "LLMs are FUNDAMENTALLY FLAWED because I SAY SO" rep…
I can ask a nine-year-old human brain to solve that problem with a box of Crayola and a sheet of A4 printer paper. In-context learning is professedly not "good enough" to approximate continuous learning of even a child.
You can also ask an LLM to solve that problem by spelling the word out first. And then it'll count the letters successfully. At a similar success rate to actual nine-year-olds.
There's a technical explanation for why that works, but to you, it might as well be black magic.
And if you could get a modern agentic LLM that somehow still fails that test? Chances are, it would solve it with no instructions - just one "you're wrong".
1. The LLM makes a mistake
2. User says "you're wrong"
3. The LLM re-checks by spelling the word out and gives a correct answer
4. The LLM then keeps re-checking itself using the same method for any similar inquiry within that context
In-context learning isn't replaced by anything better because it's so powerful that finding "anything better" is incredibly hard. It's the bread and butter of how modern LLM workflows function.
The latest qwen actually performs a little better for some tasks, in my experience latest claude still fails the car wash test
>I want to wash my car. The car wash is 50 meters away. Should I walk or drive?
Walk. It's 50 meters — you're going there to clean the car anyway, so drive it over if it needs washing, but if you're just dropping it off or it's a self-service place, walking is fine for that distance.
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> your competitor is 10x more productive with AI This doesn't happen. Literally zero evidence of this.
The actual rate isn’t relevant for the discussion
If the actual rate is .9x then it matters a lot.
Or even if it's like 1.1x, is the cost worth the return?
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> I am learning at an incredible rate with LLMs Could you do it again without the help of an LLM? If no, then can you really claim to have learned anything?
So, you havent really learned anything from any teacher if you could not do it again without them?
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Another aspect I haven’t seen discussed too much is that if your competitor is 10x more productive with AI, and to stay relevant you also use AI and become 10x more productive. Does the business actually grow enough to justify the extra expense? Or are you pretty much in the same state as you were without AI, but you are both paying an AI tax to stay relevant?
Where's the evidence of competitors being 10x more productive? So far, everyone is simply bragging about how much code they have shipped last week, but that has zero relevance when it comes to productivity
The evangelists told us 20 years ago that if we weren't doing TDD then we weren't really professional programmers at all. The evangelists told us 10 years ago that if we were still running stuff locally then we must be paying a fortune for IT admin or not spending our time on the work that mattered. The evangelists this week tell us that we need to be using agents to write all our code or we'll get left in the dust by our competitors who are.
I'm still waiting for my flying car. Would settle for some graphics software on Linux that matches the state of the art on Windows or even reliable high-quality video calls and online chat rooms that don't make continental drift look fast.