Can someone explain what this kind of comment is meant to be and what is the history behind it? It looks grammatically incorrect, and I can't reorder the words to make sense either.
The reply comment "wow" is also part of the doge meme, and the two comments together form another kind of a meta-meme, where one person writes an unfinished, but straightforward reference to something, and the reply commenter completes that - a traditional "call and response", also very popular in songs.
I feel there might be intelligent species out there without either the resources to develop technology or the ability to do so. Sharks could become smarter than us one day, but without thumbs they aren't going to succeed in overtaking the planet. Similarly, there could be a humanoid fish species under thick ice sheets of Europa, and they would never guess there is anything more than their "ocean" in the universe.
1. If you have a large amount of unlabeled data, labeling it using LLMs(even a costly XXXB parameter model) can be significantly cheaper than using humans.
2. Text classification works far better with LLMs compared to usual techniques like random forests.
3. We are exploring using LLMs on structured data(tables) for tasks like clustering, where it is difficult to tune other unsupervised approaches. Similarly we are exploring using LLM embeddings for similarity on unsupervised datasets.
4. LLMs could explain their decisions to users(e.g. why was your comment removed?) although work needs to be done on verifying it's correctness.
I wouldn't be surprised if LLM takes the spot of Random forest as the default go to for supervised ML.
Yup, and you can fine-tune an LLM to be a specialized classifier with relatively little data compared to building a classifier from scratch. I think that's the biggest benefit to LLMs, the data required to show it a behavior is pretty minuscule in the scheme of things.
I think scalping is more of a supply issue, raising the official price of the product would only require more cash when scalpers are doing their buying.
Raspberry should raise the price until scalping isn't profitable. Keeping the price low is just handing money to scalpers that should be going towards future product development, until they can meet the demand.
Name is not the only thing that gives away one's caste/religion. For example, my ear being pierced gives away that I am a Hindu. The specific dialect I speak gives away where I belong from, which statistically brings me to 2-3 castes. The food I eat(e.g. I eat chicken but not pork) or the festivals I celebrate will give away the rest.
You can do something similar in India as well. The benefit is that you get the flat at cheaper rate, at the risk of losing all your investment. There have been many cases of the developer going bankrupt, but nothing at the scale of evergrande.
When learning classical computing, I have done the following things that gave me a deeper understanding of how things work.
1. Learned logic gates and built(in simulators) small circuits which can do addition/multiplication.
2. Used a 8085 board to write assembly programs for search/sort etc.
3. Learnt C programming and Operating systems(primarily Linux)
4. Learnt higher level programming languages and paradigms(OOP, compilation, etc).
What set of courses/topics would lead to a similar level of understanding in the quantum domain? I have learnt about the quantum gates, but I do not have to context to understand how they fit in the larger picture.
You can wing it in classical domain by tinkering and reading source code aided with just school level algebra but it does not translate to quantum algorithms really. They will remain impenetrable until you invest into mastering mathematical concepts behind it, so most of the courses you need would be intermediate level math. Linear algebra, calculus, probability theory, some bits of number theory…
Quantum gates/circuits are everything - unlike classical computing there is no abstraction built on top. The circuits are built and configured in a classical computer and then the configuration is loaded into the quantum computer.
Why not try playing around with some quantum circuits via qiskit, you can actually run them on a real quantum computer for a few cents with Amazon braket.
This is something I struggle with. I have a weekly meeting which includes TL, Manager, PM and sometimes Staff engineers, Data analysts, Managers of downstream teams etc.
I try to keep the details to the lowest denominator, which usually means mentioning what the problem is and what the proposed solution is in few lines. But eventually someone will ask for more details, and then the conversation veers off to technical discussion that I am sure the PMs and Analysts don't understand.
Even that should be equivalent to distributing throughout the economy. If you burn 100 units of money, you are decreasing it's supply, increasing it's value by a tiny bit.
I believe CS degrees shouldn't focus too much on industry skills. Sure it is good to have some engineering focused courses that are likely to be useful in long term(C programming, design patterns), but most courses should be theory heavy.
If you take any specific domain of CS, there are only going to be few hundred good professors on that topic at most in entire world. Them spending their time on teaching undergrads industry skills is wasteful IMO.
Profs should focus on creating next generation of researchers. Bootcamps/Corps/Youtubers should focus on next generation of developers.
