191–200 of 1001 posts
A friend had the power supply die on his high-end turntable. He took a picture of each side of the supply's PCB, handed it to Claude, and it gave him back a schematic.
But today I watched a video from Andrej Karpathy on YouTube on how LLMs works and my illusions got completely shattered. Turns out they are a glorified autocomplete. All the engineering happens actually on the harness
My "oh shit" moments come every time I see people glazing AI "Oh shit. My skills I spent my life building are going to go to zero value. I'm going to have to dramatically change careers in my forties or I'm just going to wind up being a schmuck prompting these stupid fucking machines for the rest of my life" Oh shit indeed
My furnace went out during the 2025 holiday and I couldn't get an appointment with a repair person for 2 days. It was getting very cold in my house so I went into my attic and made several videos of the furnace attempting to start and gave it to gemini. It diagnosed the issue immediately and had me spin one of the components (a small exhaust fan) while the furnace tried to fire. It came on immediately. I had to do th…
It's helped me to gain a level of trust that the agent isn't just writing the test to pass. That in turn allowed me to step back a lot and trust more of the output and let it run longer and on bigger problems.
I gave chatgpt 3.5 the type signature for a co-algebraic encoding of a mealy machine: newtype Mealy s i o = Mealy { runMealy :: (s, i) -> (s, o) } And it gave a really impressive analysis. Then I scrambled all the names and asked with a fresh context like: newtype Foo z e g = Bar { blob :: (z, e) -> (z, g) } It got completely confused and generated a bunch of non-sense. It was at that moment I realized that LLMs don'…
In high school math class our teacher swapped out all the symbols in the epsilon delta definition of limits, and asked us what this equation expresses, and many students struggled to interpret it. I don't think this test shows that an LLM doesn't "understand". It shows more that it has similar failure modes as humans.
The student is mid learning process and its entirely reasonable for them one to be relying on pattern recognition until they have fully internalized the subject. The model is fully trained and should thus have internalized their understanding of the subject.
Additionally the student can update their understanding when pattern recognition fails. The model is fully cooked and will never do more then pattern recognition.