LovelyButterfly
LovelyButterfly on Hacker News
You could have been way less toxic in you comment any way. That was a very unnecessary tone.
Since you're not OP, I still don't understand how that's a smart person to look up to.
Everything you said is someone that had contacts and new how to put money in certain places. Smart of me is absolutely engineering and science. There is no product for him to sell it, if there is no research and each of those research are way smarter, in my opinion, than CEO.
But the world is a funny place, research also doesn't existe without funding so we need more Huangs, I guess?
To an extremely ignorant person on the matter like me, and genuinely asking, what has he achieved in terms of engineering and development, that makes you think he's smart? Or do you mean in the sense of knowing its way through business and politics? Idk I always find difficult to believe that people really think that CEOs are smart, when they commonly are not involved what so ever in any scientific leading or research, and just funnel money to a product that make them richer.
But I prefer to believe I'm wrong and would like to hear form the other side.
Consumer market is not you and your console only.
It's software god damn it... the reason why people moved from analog to digital is because you can repetitively execute functions that do always the same thing and it's 0 when it's 0, 1 when its 1.
All the sudden everyone is ok on burning trees to have their cool probabilistic tool named agent to do: maybe it's 0, but it can also be 1, let me "think"... ah yes, for sure it's 2.
The sad part for me is that management people have their heads so much into this hype, that no attack on privacy matters (almost none actually ever did, I know). Only when they suffer a huge blow in terms of revenue or reputation is that they maybe, maaaybe, find will want to listen again the experts.
The comment's author has no way of extract data from the content creator just by being leaving a comment. They content creator has click a link that the summarisation shown (likely removed by Youtube because it already doesn't allow clickable links in comments).
Accidentally in Google Colab, I've found that there is a "Learn mode" and somehow I managed to access the instructions for it which indeed instructed to ask questions, then I researched a bit more and learned about the socratic method.
So far I'm doing the combo of Zettelkasten + Socratic on Claude on papers + slides or video classes. I'm not sure if it's placebo or not, but I feel much more confident after iterating with each paper or topic this way. Asking the answer to the LLM never felt like I was studying. I read, but I never understood, I was never challenged. Perhaps what we need is the Unis around the globe to come up with a standard, a guideline so that the students can maximise the advantages of having the LLM when a professor or assistant is not available.
From what I've been learning in my uni, this is said pre-programmed. Cognition is really the ability from, out of no context, no knowledge of what you are capable of, to learn something. These tool calling and web searching are, in the end, MCP functions provided by the LLM provider themselves.
It's an entire academic discussion, about how things start. For example babies: they someone have a knowledge base on how to breath, how to cry, but they have absolute no knowledge on how to speak and it learns by the interactions with the parents.
LLMs try as much as they can create this by inference and pre-programmed functions, but they don't have a graph of memories with utility to weight their relevance in the context. As others said, the context window dies as soon as you close the session.
They also don't have the epistemic approach that is to know that another agent knows about something just by observing the environment they were all put in.
In that sense the "autonomous" part you said simply meant that the data source is coming from a different place, but the model itself is not free to explore with a knowledge base to deduce from, but rather infer on what is provided to it.
As a kid, I remember my teachers not allowing us to use calculators and times table pencils exactly to make us go through the painful process of using our brain to get to know math.
Today I'm doing a Master's on AI and AI is a tool I use not only to summarize, but to validate my understading. I don't jump into a GPT session asking it to do the exercise for me or to explain something. I ask it to help me finding out my error after inumerous tries; to say the same thing me in another words because English isn't my first language and often I don't know the terminology that the Academia uses; to write an analogy (which often absurd ones pop up); to guide me where I'm missing something.
It's a freaking powerful learning tool if used properly.