- "the average bitrate for a 4K Blu-ray DVD can range between 48Mbps to 75Mbps. Some discs can also carry around 100Mbps or even 128Mbps, but these are more rare."
https://www.tomsguide.com/tvs/forget-streaming-services-here...
- This aligns closely with the hiring practices I learned in Industrial and Organizational Psychology. The only thing missing is to have structured interviews to reduce interviewer bias.
The best predictors of job performance are a simulation of the job and past performance. This is not new research or a secret.
- Pop-trauma allows people to continue to believe "dreams can be achieved through hard work" while not blaming themselves for not achieving their dreams.
The reason I'm not living the dream could be that it's impossible, or I haven't tried hard enough. I don't want to believe either of those. I'd rather believe that something happened to me in my past that rewired my brain to stifle my full potential. Then I could still hope to someday achieve my dreams, while not doing anything to progress towards them.
It's not popular because it's right. It's popular because it's so, so appealing.
- Training is first done as a general predictive model: situation => result
Then it's fine-tuned on: situation + intent => action => result
- To train an AI to solve problems, you train it extrapolate the future from a starting state of having a problem and the intention to solve the it.
So much falls out of that reframing.
- Same with "should". I feel like most "should" statements aren't helpful. Something should be done a certain way, but in the end, society should be perfect and we shouldn't have this problem in the first place!
- Keep your AI slop off HN
- The idea of using randomness to extend cliffs really tickles my brain.
Consider repeatedly looping through n+1 objects when only n fit in cache. In that case LRU misses/evicts on every lookup! Your cache is useless and performance falls of a cliff! 2-random turns that performance cliff into a gentle slope with a long tail(?)
I bet this effect happens when people try to be smart and loop through n items, but have too much additional data to fit in registers.
- You're missing the Towers of Hanoi, my personal favorite clock. https://saej.in/post/hanoi/
- I have a dream for a compiled reactive DSL for video game programming that makes replay and rollback netcode automagically, eliminates bugs in state management, and naturally expresses derived state and the simulation step/transition function, while still being performant enough for real time
The performance hit from all that indirection of registering, getters, setters, discover, traversal, and lambdas could be avoided if we could compile the dag into smartly nested ifs
- The minimum you can do is not allow the AI to perform actions on behalf of the user without informed consent.
That still doesn't prevent spam mail from convincing the LLM to suggest an attacker controlled library, GitHub action, password manager, payment processor, etc. No links required.
The best you could do is not allow the LLM to ingest untrusted input.
- One can also watch a boat leaving shore descend "under" the horizon with a telescope
- The variant of this I've found useful is to have a separate types for raw/dirty and parsed/validated data
- I am asking this in good faith
Why would you not ssh?
- Two instances where lossy compression failed for me are the movie Koyaanisqatsi and songs by the artist TOBACCO. Koyaanisqatsi has a lot of film grain and TOBACCO uses a lot of distortion. There is noise in there, but it's very deeply mixed into the signal.
- We've seen band limited CNNs https://nvlabs.github.io/stylegan3/
What would the implementation of a band limited LLM look like?
- Thanks. Is this not effectively an implementation of the Nyquist Learners idea?
- "In optics, any optical instrument or system – a microscope, telescope, or camera – has a principal limit to its resolution due to the physics of diffraction." This might be what wbl is referring to.
There exists a problem in real life that you can solve in the simple case, and invoke a theorem in the general case.
Sure, it's unintuitive that I shouldn't go all in on the smallest variance choice. That's a great start. But, learning the formula and a proof doesn't update that bad intuition. How can I get a generalizable feel for these types of problems? Is there a more satisfying "why" than "because the math works out"? Does anyone else find it much easier to criticize others than themselves and wants to proofread my next blog post?