141–150 of 215 posts
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My college professor has certifications and has passed tests that weren't in their training data. My college professor was also willing to say "I don't know, ask me next class"
What do you consider 'not in its training data'? I just asked Claude a question I am pretty sure was not in its training data. * https://i.imgur.com/XjvImeT.jpeg
https://www.quora.com/How-many-Humans-can-we-fit-on-the-Moon
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A tool that can "write up a dopey SAAS in half the time it would take a human to do" is a pretty incredible thing to add to your toolbox!
If the summary goal of your existence is to be the most delirious waste of resources that humanity has yet known, sure. It's the hammer and nail of spoiled burnouts everywhere that need a credible ruse to help them out of the bottle. Some of us are capable of wanting for things better than a coin-operated REST API. The kind of imagination used to put people on the moon, that now helps today's business leaders imagine…
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What it will do is to free up a lot of brainpower to think about those hard problems and empower people to try our their ideas.
I used to think the exact same thing would happen when we paid Pakistani and Indian labor to do America's busywork. That was about 15 years ago, I no longer have the same enthusiasm you do.
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I think DeekThink is something different though. It is able to figure out some things that I know do not have much training data at all. It is looking at the manual and figuring things out. "That doesn't make sense. Wait, that can't be right. I must have the formula wrong." I just seen that in the chain of thought.
Nah, in my experience, if there is the slightest error in the first sentence of the chain of thought, it tends to get worse and worse. I've had prompts that would generate a reasonable response in llama, but turn out utter garbage in Deepthink.
Counterexample: Ive been able to complete more side projects in the last month leveraging llms than i have ever in my life. One of which I believe to have potential as a viable product, and another which involved complicated rust `no_std` and linker setup for compiling rust code onto bare metal RISCV from scratch. I think the key to being successful here is to realize that you're still at the wheel as an engineer. Th…
I find that LLMs are almost comically bad at projects that have a hardware component like RaspberryPi or Pico, or Ardunio. I think that its because often the libraries you use are niche or have a a few similar versions, the LLM really commonly hallucinated solutions and would continually suggest that library X did have that capability. I think because often in hardware projects you often hit a point where you can't d…
Eventually I read some actual documentation and realised it was just spouting very plausible sounding nonsense - and confident at it!
The same thing happened a year or so ago when I tried to get a much older ChatGPT to help me with with USB protocol problems in some microcontroller code. It just hallucinated APIs and protocol features that didn’t actually exist. I really expected more by now - but I now suspect it’ll just never be good at niche tasks (and these two things are not particularly niche compared to some).
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They are reasonably accurate, and no tutor is perfect. How do you know your college professor is accurate?
My college professor has certifications and has passed tests that weren't in their training data. My college professor was also willing to say "I don't know, ask me next class"
Granted, they are not (can't be) as rigorous as the tests your professor took, but new models are run through test suites before being released, too.
That being said, I saw my college professors making up things, too (mind you, they were all graduated from very good schools). One example I remember was our argument with a professor who argued that there is a theoretical limit for the coefficient of friction, and it is 1. That can potentially be categorised as a hallucination as it was completely made up and didn't make sense. Maybe it was in his training data (i.e. his own professors).
I agree with the "I don't know" part, though. This is something that LLMs are notoriously bad.
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I find that LLMs are almost comically bad at projects that have a hardware component like RaspberryPi or Pico, or Ardunio. I think that its because often the libraries you use are niche or have a a few similar versions, the LLM really commonly hallucinated solutions and would continually suggest that library X did have that capability. I think because often in hardware projects you often hit a point where you can't d…
Actually, it's because many of the people writing tutorials and sharing answers about that stuff don't know what the hell they're doing or grasp the fundamentals of how those systems work and so most of the source material the LLM's are trained on is absolute garbage. Public Arduino, RPi, Pico communities are basically peak cargo cult, with the blind leading the blind through things they don't understand. The noise i…
It won't because the RPi are all undocumented, closed-source toys.
It would be an interesting experiment to see which chips an LLM is better at helping out with: RPi's with its hallucinatory ecosystem or something like the BeagleY-AI which has thousands of pages of actual TI documentation for its chips.
It would be really nice if the LLMs could cover for this and circumvent where RPi's keep getting used because they were dumped under cost to bootstrap a network effect.
Counterexample: Ive been able to complete more side projects in the last month leveraging llms than i have ever in my life. One of which I believe to have potential as a viable product, and another which involved complicated rust `no_std` and linker setup for compiling rust code onto bare metal RISCV from scratch. I think the key to being successful here is to realize that you're still at the wheel as an engineer. Th…
Is it reasonable to assume that more senior devs benefit more from LLMs?
* I put commercial there as a qualifier because there's some thought that in the future, very specifically-trained smaller models (open source) on particular technologies and corpuses (opt-in) might yield useful results without many of the ethical minefields we are currently dealing with.
I have a custom prompt that instructs gpt4o to get aggressive about attacking anything I say (and, importantly, anything it says).
Here's my result for the same question:
https://chatgpt.com/share/67984aa9-1608-8012-be93-a77728ab8e...
Counterexample: Ive been able to complete more side projects in the last month leveraging llms than i have ever in my life. One of which I believe to have potential as a viable product, and another which involved complicated rust `no_std` and linker setup for compiling rust code onto bare metal RISCV from scratch. I think the key to being successful here is to realize that you're still at the wheel as an engineer. Th…
Claude is like having my own college professor. I've learned more in the past month with Claude then I learned in the past year. I can ask questions repeatedly and get clarification as fine as a need it. Granted, Claude has limits, but its a game-changer. > I think the key to being successful here is to realize that you're still at the wheel as an engineer. The llm is there to rapidly synthesize the universe of infor…