compare this to Electronic engineering, we are not making chips by hand, It is impossible to squeeze too many transistors in such a small space, we just create the circuit designs. I believe writing the code is heading in the same direction as well, you don't write too much code now, but you have to design the architecture and connect things. But it does not mean that you don't need to understand the code, now of all the times people who understand code are more important. Many below par devs will loose jobs for sure.
Exactly. Chips are incredibly expensive and extremely complex—containing billions of transistors and you can't realistically build them at home. Memory is a good example: it keeps growing in both capacity and cost.
The same thing will happen to software. Eventually, the sheer volume and diversity of code will exceed human comprehension and only massive data centers will be able to process it. We'll reach the point where software complexity and programmer capabilities hit an economically practical limit. The next-gen Moore's Law for AI?
Today, chips are designed largely through automated processes and software is increasingly being created the same way. The main difference is the timescale: software evolves billions of times faster than hardware.
> >layoff developers
for now we are not sure what is gonna happen. Big tech is surely reducing headcount to invest more in AI. but with recent downtime of github/AWS and them not blaming AI but humans, says a lot about that they will go to any extent to prove AI is bringing value enough to fire human engineers.
if we think, what is accountability? if a human would do a mistake, you would as an employer do two things: either teach him what not to do, or fire him.
Same thing can be done with AI agents, if you decide to stay with the agent then teach it what not to do, this might not work 100% but to a certain level for non critical things it would work.
Agents should ofc not be given consequential actions like deleting accounts at will.
But the point is, once a mistake is done, it is done, be it human or an agent, you gotta teach or fire something.
I don't think any other way to solve this problem
Intelligent people see and understand the world deeper, more than an average person can, They see the world in all its forms, good and bad, understanding too much does not bring happiness but gloom. existence seems to be absurd, the more we understand existence the more one believes that it shouldn't have existed at the first place.
"happiness in intelligent people is the rarest thing I know" is a quote by Hemingway.
Also intelligent people overthink about a particular situation, while its better for survival but it can reduce happniess.
as good as it may sound, but this will never happen.
People will never pay for everything, majority don't even buy PC games, they use pirated one's. This is how humans are designed, and this is what which keeps the market afloats.
I cannot make out anything from this. what are you trying to say? AI agents's fundamental task is to implement stuff, or in technical terms tool calling, computer use etc. they take input from user in natural language, and everything is perfectly defined in the prompt. The LLM is instructed to ask whenever not sure, so bootstrapping from hallucinations only happens when the implementation of AI agent is poor.
The entire paper demonstrated the results of the simulation or whatever they did. They did not mention how did they achieve this simulation. running 500-1000 LLMs parallely, will take too much computing resources, neither did they prove the claim they made about their parallel architecture. I remeber there was the paper published about an AI town, in which they mentioned clearly how they implemented it. they also released a recording of the simluation along with the real data of the results. If anyone got how they implemented this paper, please tell me.
Hi guys, I made a completely multiplayer programming game for C++ and python, started it to learn graphics, multithreading and all. ended up creating a small game engine for my game (included a lot of game maths), learnt multithreading and multiprocessing deeply. the game is originally programmed in c++, so had to do everything from scratch. Later ported it to python using pyBind11, wrote the langauge bindings for python. For the multiplayer part, which took the most of the time, ended up creating my own networking protocol( over UDP) according to the game needs.
you can see the project here at my website: https://aiplaygrounds.in
