Oh sweet! When can skip the bullshit puzzle phone screens?
Ali Group CAPTCHA's or Android unlock?
Competitive Programming with AlphaCode
321–330 of 415 posts
Re: Competitive Programming with AlphaCode
#322Earlier quoted context omitted.
I think programmers are relatively "safe" from AI for the simple reason they are the ones who talk to AI. The job of programmers is to have machines do stuff so that humans don't have to, and of course, they do it for themselves too. Scripts, libraries, compilers, they are just tools to avoid flipping bits by hand. If something like copilot is not embraced by all programmers, it is that it is often less than helpful,…
there will always be someone who tells the computer what to do Until the computer starts telling people what to do
That actually gave me chills. We're doomed!
Re: Competitive Programming with AlphaCode
#323I sometimes read these and wonder if I need to retrain. At my age, I’ll struggle to get a job at a similar level in a new industry. And then I remember that the thing I bring to the table is the ability to turn domain knowledge into code. Being able to do competitive coding challenges is impressive, but a very large segment of software engineering is about eliciting what the squishy humans in management actually want…
AI might take over management quicker than you think. If the objective is to get the rocket into space, AI might know the requirements better than humans at this rate.
Re: Competitive Programming with AlphaCode
#324What I always find missing from these Deep Learning showcase examples are an honest comparison to existing work. It isn’t like computers haven’t been able to generate code before.
Maybe the novelty here is working from the English language specification, but I am dubious just how useful that really is. Specifications are themselves hard to write well too.
And what if the “specification” was some Lisp code testing a certain goal, is this any better then existing Genetic Programming?
Maybe it is better but in my mind it is kind of suspicious that no comparison is made.
I love Deep Learning but nobody does the field any favors by over promising and exaggerating results.
Re: Competitive Programming with AlphaCode
#325I sometimes read these and wonder if I need to retrain. At my age, I’ll struggle to get a job at a similar level in a new industry. And then I remember that the thing I bring to the table is the ability to turn domain knowledge into code. Being able to do competitive coding challenges is impressive, but a very large segment of software engineering is about eliciting what the squishy humans in management actually want…
Have you tried out Github Copilot yet? I find it super interesting. It turns writing code into more of a write some comments, let it write the code, review the code, realize what I actually need it to do, revise the comments, then tighten up the generated code.
Most surprisingly I can quickly tackle domains that require libraries I don't know because a combination of code generation and IDE hinting means I can write comments and pseudo code and the tool then provides at least a first pass best method to use.
Can't say if I write better code with Copilot but it's worth experiencing!
Re: Competitive Programming with AlphaCode
#326What I always find missing from these Deep Learning showcase examples are an honest comparison to existing work. It isn’t like computers haven’t been able to generate code before. Maybe the novelty here is working from the English language specification, but I am dubious just how useful that really is. Specifications are themselves hard to write well too. And what if the “specification” was some Lisp code testing a c…
Specs are hard to write because the person interpreting them may not understand you, but it's the iteration time and cost that kills you.
Make me a sandwich -> two weeks and $10k isn't viable
Make me a sandwich -> 2 seconds and free, totally viable
Re: Competitive Programming with AlphaCode
#327What I always find missing from these Deep Learning showcase examples are an honest comparison to existing work. It isn’t like computers haven’t been able to generate code before. Maybe the novelty here is working from the English language specification, but I am dubious just how useful that really is. Specifications are themselves hard to write well too. And what if the “specification” was some Lisp code testing a c…
I have fiddled with genetic programming. I don't think there is a good solution for a useful metric for comparing one code generator against another, so I don't think DeepMind should care.
Most of the genetic programming results code generated by my algos doesn't compile. Very occasionally the random conditions exist to allow it to jump over a "local maxima" and come up with a useful candidate source code. Sometimes the candidates compile, run, and produce correct results.
The time it takes to run varies vastly with parameters (like population, how the mutation function works, how the fitness function weights/scores, etc).
Personally I really like that these DeepMind announcements don't get lost in performance comparisons, because inevitably those would get bogged down in complaints like "the other thing wasn't tuned as well as this one was". Let 3rd party researchers who have access to both do that work, independently.
Re: Competitive Programming with AlphaCode
#328Earlier quoted context omitted.
What do you think then is the difference between going from 50th to 99.9th percentile in their other domains? Is there something materially different between ago, protein folding, or coding? (I don’t know the answer, just curious if anyone else does)
Well with respect to Go the fundamental difference afaict is that you can apply self-supervised learning, which is an incredibly powerful approach (But note e.g. that even this approach wasn't successful in "solving" Starcraft). Unfortunately it's extremely difficult to frame real-world problems in that setting. I don't know anything about protein-folding and don't know what Deepmind uses to try to solve that problem…
That’s not entirely correct, as I know of at least one approach to neural program synthesis that employs self supervised learning.
https://arxiv.org/abs/2006.08381
It’s a slightly different, easier problem: generating programs based on example outputs, rather than natural language specifications.
Re: Competitive Programming with AlphaCode
#329I sometimes read these and wonder if I need to retrain. At my age, I’ll struggle to get a job at a similar level in a new industry. And then I remember that the thing I bring to the table is the ability to turn domain knowledge into code. Being able to do competitive coding challenges is impressive, but a very large segment of software engineering is about eliciting what the squishy humans in management actually want…
Have you tried out Github Copilot yet? I find it super interesting. It turns writing code into more of a write some comments, let it write the code, review the code, realize what I actually need it to do, revise the comments, then tighten up the generated code. Most surprisingly I can quickly tackle domains that require libraries I don't know because a combination of code generation and IDE hinting means I can write…
I've been playing with Copilot as well.
It's very good at handling boilerplate and making contextual suggestions.
I don't see it eating my cake, but it's definitely a very useful tool for saving time.
Re: Competitive Programming with AlphaCode
#330I sometimes read these and wonder if I need to retrain. At my age, I’ll struggle to get a job at a similar level in a new industry. And then I remember that the thing I bring to the table is the ability to turn domain knowledge into code. Being able to do competitive coding challenges is impressive, but a very large segment of software engineering is about eliciting what the squishy humans in management actually want…
I agree with you on this, since we humans want things in a vague form, and it's still very hard for computers to infer insights from those ambiguous requirements. Not very easy to do that by taking derivatives of function compositions.