A different kind of generative content!

Why not just have a few drones circle the parking lot and power themselves frequently at a base station? Even better, what’s wrong with CCTV cameras? Drones and CCTV cameras complement pretty well.

Which ICU costs $600/day? It must be in thousands per day if not tens of thousands.

Mankind has made its life really comfortable in the last 50 years. If you told anyone in the early 1900s that most people will work from home in 2020, they’d find it unbelievable. All this comfort has come from using machines to make the humans work easier. Now we are going into a state where many people aren’t even needed in the production cycle unless they bring a ton of technical skills. This is why we have so much more homelessness and hopelessness now than before. I believe that this gap of people who are productive in the new world and who aren’t is going to keep increasing. What’s the solution? UBI is one of the solutions.

Instincts aren’t irrational. They are a temporal latent variables that are indicative or are a premonition of one possible future. Instincts are derived based on past experiences which have trained your model. Current neural nets aren’t temporal nor do they do online learning. But that will change.

You say instincts are irrational. Many people trust their instincts because they are pretty accurate for them. If it’s irrational, that’s likely because it’s a poorly trained (human) neural model.

>But it’s a machine without feelings…

What are human feelings? It’s an early signal that tells a human that they have or may encounter something that is beneficial or harmful to them. There is an evolving school of thought that consciousness is simply a survival mechanism or a neurological phenomenon.

I think OP has a valid point. Why would a self aware system that is conditioned to survive (eg., a robot that is trained to not fall off a cliff) prioritize some other human unless it is hardcoded to do so?

This goes the heart of what humans seek? Do they seek knowledge, beauty, tranquility, leisure or pleasure? The history of humanity shows that humans have always sought leisure and pleasure as the ultimate goals in their application of time and effort. Yes, there are others who seek knowledge or innovation. But that is a tiny fraction of humanity. So, yes, VR is the ultimate enabler of pleasure and leisure.

This. The harder thing to build than good AI is to build an early movers advantage. OpenAI is starting to see that now.

Maybe. But it’s useful for the common case of just getting basic information. Google is not that good with complex questions either.

Isn’t this like, Duh?!

All of deep learning, including LLMs, is about coming up with a non linear model that best models input data. Does it guarantee that: a) any output it generates is consistent with the actual input data (I don’t mean input distribution here) and b) it understands what’s not said in the input data (eg., it doesn’t have enough knowledge or training to answer the prompt accurately).

At a high level, all that LLMs do it model an input distribution. And you can sample it for interesting images and text. There are no guarantees that the output makes sense and the AI community is not even close to developing techniques that limits generated output to only sensible ones (or throw up an error if there is no good answer).

And more importantly, given how easy it is to generate output, the real challenge is to not get lost in a world of simulation and to keep it real.

Thank you!

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No matter how complex the idea, you can explain them in simple terms if they have fundamental merit. Use the Feynman technique.

You might be right. By the time 2030 kicks in, there will probably be a wide spread disruption of society like we saw in 1929-30.

Every system, organic or synthetic, is imperfect. What are the imperfections of singularity? Would it kill other species for its own existence?

We have some pretty amazing technology right now. Does that mean that people can afford homes, cars, relaxation or raising a family? It’s the other way around. If we achieve singularity it will come with a winner-takes-all situation. It’s not good for society in general.

I am postulating something in the opposite direction of your thesis. The limitations of LLMs and modern AI are so much that the best it can do is enhance human productivity. But its not enough to replace it. So we’ll see a general improvement in the quality of human output but I don’t foresee a large scale unemployment anytime soon. There maybe a shift in the employment workforce (eg. A car mechanic maybe forced to close shop and operate alongside robots at the Tesla giga factory) but large scale replacement of human labor will take a lot more advancement in AI. And I have doubts if society will even accept such a situation.

The problem is often the last mile issue. Say you use LLMs to generate a T-shirt style or a customer service response. Can you verify correctness? Can you verify that the response is acceptable (eg., not offensive)? Can you ensure that it isn’t biased in its response? Can you make sure it’s not misused by bad actors?

You can’t represent all that with just patterns. You need reasoning. LLMs are still a tool to be exercised with caution by a human operator. It can dramatically increase the output of a human operator but it’s limitations are such that it’s still bound by the throughput of the human operator.

The problems we have with AI is akin to the problem we have with the internet. Internet was born and adopted in a hurry but it had so many side effects (eg. Dark web, cyber attacks, exponential social convergence, counduit for bad actors, etc). We aren’t anywhere close to solving those side effects. LLMs are still so limited in their capabilities. I hope the society will choose to be thoughtful in deploying them in production.

I think you understand the limitations of the approaches that you’ve discussed. Generating intermediate results and trying out possibilities of outcomes is not reasoning. It’s akin to a monte carlo simulation. We do such reasoning every day (eg. Is there time to eat breakfast or do you have to run to office for the meeting, do you call the plumber this week or do you wait till next month for the full paycheck, etc). LLMs are just repeating patterns and that can only take you so far.

I know what LLMs are. They are a surprising development but the history of technology is littered with surprising discoveries and inventions. But there are very few inventions of the earth shattering variety. And I don’t believe that LLMs are of that variety for the reasons I stated. CNNs were all the rage before LLMs. And respected giants in the field such as Yann LeCun have also stated that LLMs are important but they aren’t everything.

LLMs are not the be all and end all. It’s good for understanding context when generating content. But can it reason by itself without seeing pattern ahead of time? Can it distinguish between the quality of the results it generates? Can it have an opinion that’s not in the mean of the output probability distribution?

There is a lot more to intelligence than finding patterns in a context. We agree that we are on a non-linear path of AI advancement. But a lot of that has to do with advancement of GPUs. That’s kinda stalled with the death of the Moore’s law. We are nowhere close to simulating 100 trillion neural connections that we have in a human brain.

Experience is a necessity for intelligence. All AIs are trained with real world data which is an experience of reality.