Nyquist Limit:The frequency of changes in tech is invalidating our understanding
Posted by evakhoury 1 day ago
Comments
Comment by menaerus 21 hours ago
And we're already there, it's beyond our cognitive capacity to fully understand the (AI) produced volume of work for given unit of time.
In order to really mitigate the human bottleneck, we will either have to reach the AGI, which might not come in the next 10 years or so, or change the form of how we're doing work, review included.
Comment by wrs 21 hours ago
But also yes, the whole time I read the article, I was really hoping the 2X part wouldn’t be presented literally, because that makes no sense.
Comment by TimTheTinker 19 hours ago
The main problem is that shannon-nyquist is concerned with discrete representation of a continuous/analog signal. But TA is applying it backwards: software is discrete and human understanding is analog. So human "sampling" of software is not something an A->D theory can speak to.
Comment by somethingsome 22 hours ago
I don't like the analogy, it supposed that AI generated code will always be badly organized underneath if it is automatic, however, as time goes, I find the code better and better..
Comment by 4star3star 21 hours ago
Comment by yfw 21 hours ago
If its a straight line you need 2 samples.
If its not you probably need more.
Id argue codebase understanding is neither of these simplifications
Comment by esafak 21 hours ago
Comment by waffletower 21 hours ago
Comment by ironmanszombie 20 hours ago
It would be really interesting to see an AI create a new kernel for Linux that every piece of it's code was written and verified-secure by having it analyzed and exploited simultaneously.
We, humans, don't need to be as fast as our tools.
On a personal note, I can't wait to see new silicone and operating systems made specifically for AI. That will be cool!
Comment by vr46 21 hours ago
LLMs plus continuous delivery - what a gruesome twosome.
Comment by frangonf 20 hours ago
But overall cool read to make you think, where you can see a dev brain as an ADC, design paradigms or microservices as band pass filters, apis as low pass, frameworks as downsampling, legacy code as DC signal that you don't touch, etc.
Comment by Scramblejams 21 hours ago
Comment by smitty1e 18 hours ago
Comment by science4sail 22 hours ago
AI advocates nowadays are calling for abolishing human code review. So code moves from read-often-write-rarely to read-once-write-once to read-never-write-often. The assumption is that we can rely on the agents to decipher the code if needed.
My feeling is that software "engineering" in the future will be basically a cargo cult or the Adeptus Mechanicus from Warhammer 40k: all detailed technical knowledge comes from the gods, humans only manage the rituals around technology.
Comment by nemo44x 21 hours ago
I have to say I mainly agree in a way I wouldn’t have 1 month ago. We are now starting to see bugs creep above our baseline. This is only what we are detecting. At least in certain critical areas we are not removing strict human review.
One theory is our codebase (which is large and mature) was very coherent. As we moved to more autonomy and needed generated code in the base has grown and is less mature now and likely not as coherent. The LLM has to cope with this.
Comment by FLeXMurphy 21 hours ago