The end of classical Computer Science is coming
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The end of classical Computer Science is coming
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Re: The end of classical Computer Science is coming
#2This keeps me awake at night I must admit. How do I best future proof my career?
I was sceptical about this until I started playing with GPT 3 and has it not only writen code for me, but also "explained" code to me. Sure, it's kind of limited right now, but it can only be a matter of time now before this all radically improves.
Maybe I should focus on system design and translating the messy real world into systems. That's the hardest bit of my job currently. I was also thinking of moving down the stack and getting deeply into security engineering or something like that (not that this is immune from AI either!!).
Re: The end of classical Computer Science is coming
#3This keeps me awake at night I must admit. How do I best future proof my career? I was sceptical about this until I started playing with GPT 3 and has it not only writen code for me, but also "explained" code to me. Sure, it's kind of limited right now, but it can only be a matter of time now before this all radically improves. Maybe I should focus on system design and translating the messy real world into systems. T…
You can't guess the future so future proofing is next to impossible. Providing solutions to people wants and needs is the way to go. There you focus on the problem and then you look at what tools are available to provide the needed solution. People will always need food,recreation,sex, a place to live and religion to name a few. Figure how to fill needs in those areas and you'll be ok.
Re: The end of classical Computer Science is coming
#4This keeps me awake at night I must admit. How do I best future proof my career? I was sceptical about this until I started playing with GPT 3 and has it not only writen code for me, but also "explained" code to me. Sure, it's kind of limited right now, but it can only be a matter of time now before this all radically improves. Maybe I should focus on system design and translating the messy real world into systems. T…
It was in 1982 that I for the first time heard about the fourth generation programming languages in which you only had to specify the problem and you would get the system for free. But now 40 years later, most of the programming is still done in third generation programming languages.
I am rather skeptical about the idea that AI is going to do away with programming soon. Yes, ML have shown some impressive results and will definitely show some improvements in the coming decades, but I think it will still take some time before the efficiency of electronic based ML systems will surpass that of organic based ML systems.
Please note that this blog post is from a start-up that aims to work at ML systems that aim at replacing programming. So, this blog is also in a sense a kind of job advertisement and/or investor pitch.
Re: The end of classical Computer Science is coming
#5> Fast forward to today, and I am willing to bet good money that 99% of people who are writing software have almost no clue how a CPU actually works
The fact that many people do not know exactly enough what they are doing can be seen in the result. The people whose goal is to write as robust and efficient software as possible still do have to know and control the details. It's like driving a car; you do not have to be a engineer to drive one; but the more you want to push the limits of performance, the more you need to know about the details. And as far as AI is concerned, despite the predictions and full-bodied promises, we are obviously still a long way from replacing humans as drivers. I see no reason why software development should be any different. There are so many very complex issues involved that are not mentioned in the article. Just understanding the requirements of software will stretch the capabilities of AI for a few more decades.
Re: The end of classical Computer Science is coming
#6It'll be interesting to see who's right: Matt or Brooks. Matt essentially argues that AI can be trained to take the responsibility of specifying a system, which is the opposite of what Brooks argues in his essay No Silver Bullet.
Of course, I'm assuming that we are writing programs to specify what and how a system should work. It could be that AI (but not AGI) is so advanced that specifying a system can be compressed into training a model.
Re: The end of classical Computer Science is coming
#7Writing a program is still the most efficient way to explain a lot of things, even to another human - I've been in plenty of meetings where hours of explaination and examples only added confusion, whereas 20 minutes of pseudocode or 5 minutes of real code made it very clear what we were talking about.
If you just want to do the same thing you currenty do but faster, AI will handle that. But modelling a business process properly and making it explicit will still bring huge value to those who care to put the effort in.
Re: The end of classical Computer Science is coming
#8> 99% of people who are writing software have almost no clue how a CPU actually works, let alone the physics underlying transistor design.
My undergraduate education was in the early 90s, and at no point in my life have I ever had much of a clue regarding the physics underlying transistor design.
EDIT: also at one time I probably did have a reasonably solid grasp on how CPUs work, there's been an awful lot of advancement in the field over the decades, and I won't describe my understanding as anything more than a cartoon model.
Re: The end of classical Computer Science is coming
#9> Fast forward to today, and I am willing to bet good money that 99% of people who are writing software have almost no clue how a CPU actually works The fact that many people do not know exactly enough what they are doing can be seen in the result. The people whose goal is to write as robust and efficient software as possible still do have to know and control the details. It's like driving a car; you do not have to b…
> we are obviously still a long way from replacing humans as drivers.
This is only because we as a society have an extremely low tolerance for errors in automated driving and essentially require by default superhuman performance (a self-driving car with an error rate of the median human would never be allowed to be set loose by itself). In scenarios where a 0.1% error rate, 1% error rate, or maybe even 10% error rate are acceptable, AI is making huge strides.
> Just understanding the requirements of software will stretch the capabilities of AI for a few more decades.
I hope so. I'm not sure. And for a variety of reasons that's scary. What gives you a timeline of a few more decades?
Re: The end of classical Computer Science is coming
#10There is a reason we are getting robot dogs with guns on their backs at the same time AI is advancing; because once AI crosses a certain line it is going to be powerful enough to nullify most jobs. It's not science fiction.
What happens when you have a NN that understands how to integrate new physical input and render usable actions for creating outputs without human intervention? That's where we get machines building machines.
What happens when we start using AI to find the best recreational drugs? How about recreational drugs designed for specific kind of Overdoses - like crumple zones on a car? Or using AI to find the best cocktail of psychedelics that allow us all to work stoned and to maximum benefit all day long without diminishing returns?
Finally, what happens when these AI can layer themselves together through transfer protocols and problem solving distribution without us telling them to? A self-analyzing, self-correcting and self-improving system can be considered a kind of life.
We really are very close now.