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.
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.
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.
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.