melony

Any advances in emulators recently? I would love to see Nintendo get into a legal tussle with Big AI. Giant douche can fight turd sandwiches.

I expect my "AI" engineers to know both RAG and what KL-divergences are. If you only know the former, you are just a backend developer, not a ML engineer.

How does it compare with NLTK's chunking library? I have found that it works very well for sentence segmentation.

There's nothing stopping them from just adding the feature like npm.

Some optimization suggestions:

- cache the prompting somehow, unless you are doing dynamic stuff with the prompts, the language embeddings generated should be static (this depends on the architecture of the model that you are using, it's only possible with certain setups where the language processing is a separate part in the pipeline)

- consider fine-tuning an img to img model with your current outputs instead of using a language-coupled model. My intuition is that this is currently significantly over-engineered on the ML side.

- Play around with local hardware acceleration instead of sending everything to the cloud, you also probably don't need particularly high resolution for the images either.

Sigh it means in their neural network layer they have a random sampling step. Yay for Gaussians.

Does it work with WSL2?

> The government has power. Craig the office drone asking for "misinformation" to be taken down at behest of his boss does not have the power "The government" does. Or am I now supposed to believe that if you anger Sheila at the DMV the IRS will audit you?

Craig's boss is the highest executive power in the country. Most of their work is handled by aides and subordinates like Craig, with authority delegated from their office. The boss only directly makes the important decisions. You are being disingenuous by claiming Craig is a innocent, powerless trigger-happy drone. And if you have lived in small towns, expect to receive worse service or discrimination from Sheila in future. The highest power in the country cannot be held to the same standard as a county clerk (and frankly speaking, most DMV employees need more training in customer service and have their compensation tied to overall productivity and performance, lots of fat to be trimmed there, both literal and metaphorical).

The issue is that many things ultimately still require rote learning. Most STEM subjects cannot avoid it unless you are genuinely talented and mathematically inclined. You can appreciate Newton's laws in classical mechanics as much as you want but you still need practice if you want to apply the kinematics and force equations in any reasonable amount of time during an exam. Same with Hamiltonians and Lagrangians. The further you go, the more intuition requires rote learning to build up. (I would note however that rote learning doesn't necessarily impart any mathematical maturity, but it does help with achieving conceptual understanding of the problem. Solve enough differentiation problems on pen and paper and gradient descent and backpropagation become obvious, but proving epsilon deltas won't necessarily be as helpful.)

Because so long Bloom's 2 sigma observation holds, pedagogy only matters at scale. In other words, it mostly affect the lower middle class and poor people. Good education systems can ensure that most people get educated. The elites and upper middle class are more than capable of giving their children an excellent education anywhere. Working class parents don't have time to babysit every single homework problem or to fix every gap and flaw in the school's syllabus by themselves.

Why not use Go? They have one of the best networking stacks among language standard libraries, excellent support for low latency soft real-time concurrent operations, and single binary deployment is trivial.