I miss the old days when Facebook was simply a fun way to reconnect with friend and family who lived far away. Unfortunately, those days are gone. It feels like an over engineered attention-hogging system that collects a large amount of data and risks people's mental health along the way.
Readit Newscoef2 commented on Facebook is asking to use Meta AI on photos you haven’t yet shared theverge.com/meta/694685/... · Posted by u/pier25
It's sad to see the interviewer wasting the opportunity to interview Penrose. I found Lex Fridman does a much better job: https://www.youtube.com/watch?v=hXgqik6HXc0
coef2 commented on Show HN: I got laid off from Meta and created a minor hit on Steam · Posted by u/newobj
We should thank Meta for laying off a talented engineer.
coef2 commented on Ask HN: SWEs how do you future-proof your career in light of LLMs? · Posted by u/throwaway_43793
I recently used an LLM to translate an algorithm from Go to Python at my work. The translation was quite accurate, and it made me think tasks involving obvious one-to-one correspondence like code translation might be easier for LLMs compared to other tasks. I can see the potential for offloading such tasks to LLMs. But the main challenge I faced was trusting the output. I ended up writing my own version and compared them to verify the correctness of the translation.
coef2 commented on Show HN: LlamaPReview – AI GitHub PR reviewer that learns your codebase github.com/marketplace/ll... · Posted by u/Jet_Xu
I have a conundrum about this. If an LLM can learn our codebase and generate reasonable reviews, does this imply it could perform the work independently without us? Perhaps generating code and conducting code reviews are distinct tasks. Another related question is: for complex tasks that generative AI can't solve, could this service still provide somewhat meaningful reviews? Maybe it could be partially useful for certain subtasks like catching off-by-one errors.
I read that iPhone 12 & 13 minis had very low sales rates. Disappointing since I too am waiting for another mini to be released. I would have 100% bought an iPhone 16 mini.
I’m the same way. I bought 12 and 13 minis and stopped upgrading my phone since then. I’d love to have a mini version with a good optical zoom camera.
coef2 commented on After AI beat them, professional Go players got better and more creative henrikkarlsson.xyz/p/go... · Posted by u/iNic
The other possibility is that it destroyed the incidental dogma that tends to build up in these types of games and human activities. This is why I like the "hacker ethos" as much as I do, it tends to eschew things like "accepted" dogma in order to find additional performance that other people were just leaving on the table out of polite comfort.
So the progress of human proficiency in Go and our collective advancement over time is hindered by dogmatic rules introduced over time. These rules predispose players toward specific strategies and consequently limit the scope of our creative potential within the game. In contrast, AI algorithms operate without such biases offer a unique advantage in overcoming these limitations. They essentially inspire us to get out of established patterns (or local minima) of play and broaden the range of our strategic moves.
coef2 commented on Understanding Deep Learning udlbook.github.io/udlbook... · Posted by u/georgehill
Nobody is building real technology with either of those algorithms. Sure, they are theoretically helpful, but they arent valuable anymore. Spending your precious life learning them is a waste
I started my journey in machine learning fifteen years ago. Ironically, at that time, my professor told me that neural networks were outdated and trying them wouldn't result in publishable research. SVMs were popular and emphasized in my coursework. I concur that SVMs don't hold as much practical significance today. But the progress in AI and ML is generally unpredictable, and no one knows what theory leads to the next leap in the field.
This is a relevant thread:
https://news.ycombinator.com/item?id=28191408
And because reading and writing are thinking we must not delegate it to AI models as a matter of habit. In particular, during students' formative time, they need to learn how to think in reading and writing mode - reflecting, note-taking etc.
Compare it with the use of a pocket calculator: once you have a solid grounding, it's fine to use electronic calculators, but first one ought to learn how to calculate mentally and using pen and paper. If for no other reason, to check whether we made a typo when entering our calculation, e.g. when the result is off by 100 because we did not press the decimal point firmly enough.
I am very concerned that young people delegate to LLMs before reaching that stage.
I've heard that some philosophers like Schopenhauer argue that reading can become a passive process, where we simply follow another person's thoughts without engaging our own critical thinking. It's interesting to consider that it's not just LLMs but we too would become like stochastic parrots under certain circumstances.