That’s fair. I see what I see at an engineering and architecture level. You see what you see at the business level.

That said. I stand by my statement because I and most of my colleagues in similar roles get continued, repeated and expanded-scope engagements. Definitely in LLMs and genAI in general especially over the last 3-5 years or so, but definitely not just in LLMs.

“AI” is an incredibly wide and deep field; much more so than the common perception of what it is and does.

Perhaps I’m just not as jaded in my tech career.

operations research, and conventional software which never makes mistakes if it’s programmed correctly.

Now this is where I push back. I spent the first decade of my tech career doing ops research/industrial engineering (in parallel with process engineering). You’d shit a brick if you knew how much “fudge-factoring” and “completely disconnected from reality—aka we have no fucking clue” assumptions go into the “conventional” models that inform supply-chain analytics, business process engineering, etc. To state that they “never make mistakes” is laughable.

Absolutely not true. Disclaimer, I do work for NVIDIA as a forward deployed AI Engineer/Solutions Architect—meaning I don’t build AI software internally for NVIDIA but I embed with their customers’ engineering teams to help them build their AI software and deploy and run their models on NVIDIA hardware and software. edit: any opinions stated are solely my own, N has a PR office to state any official company opinions.

To state this as simply as possible: I wouldn’t have a job if our customers weren’t seeing tremendous benefit from AI technology. The companies I work with typically are very sensitive to CapX and OpX costs of AI—they self-serve in private clouds. If it doesn’t help them make money (revenue growth) or save money (efficiency), then it’s gone—and so am I. I’ve seen it happen; entire engineering teams laid off because a technology just couldn’t be implemented in a cost-effective way.

LLMs are a small subset of AI and Accelerated-Compute workflows in general.

I like to splurge on a Shackshackshack from time to time.

We’re looking at this from opposite sides of the same coin.

The NN graph is written at a high-level in Python using frameworks (PyTorch, Tensorflow—man I really don’t miss TF after jumping to Torch :) ).

But the calculations don’t execute on the Python kernel—sure you could write it to do so but it would be sloooow. The actual network of calculations happen within the framework internals; C++. Then depending on the hardware you want to run it on, you go down to BLAS or CUDA, etc. all of which are written in low-level languages like Fortran or C.

Numpy fits into places all throughout this stack and its performant pieces are mostly implemented in C.

Any way you slice it: the post I was responding to is to argue that AI IS CODE. No two ways about that. It’s also the weights and biases and activations of the models that have been trained.

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Neural nets are typically written in C; then frameworks abstract on top of that (like Torch, or Tensorflow) providing higher-level APIs to languages like (most commonly) Python, or JavaScript.

There are some other nn implementations in Rust, C++, etc.

Costco’s soft-serve is way better than McD’s and actually is cheap.

Bullshit. Developers never make mistakes. N.E.V.R.

No, but it’s basically a “I can use it to build my billion-dollar business and keep the profits if I want” license. The only real catch is that if I decide to modify the code and distribute it, I’m required by the license to share those changes with whoever gets the modified version. There’s nothing in the GPL that stops me from being a downstream freeloader, and I can stay on whatever version I like—no one’s forcing me to update to newer ones with terms I don’t agree with. Forking and modifying for my own needs is totally fine, as long as I slap the same GPL on the changes if I hand them out.

You can scan before the encryption step. It defeats the purpose of the encryption such that only the privileged actor gets plaintext while everyone downstream gets encrypted bytes, but technically it’s possible.

It’s only a matter of time until a vulnerability in the privilege is found and silently exploited by a nefarious monkey, and that’s precisely why adding backdoors should never be done.

Can’t wait for Nintendo to sue Microsoft because VS Code can be used to edit save files.

The funny thing here is that there are many good distributions that are based on Ubuntu. I’m a Pop!_OS fanboy, many of my colleagues enjoy Mint. Yet, almost everyone I know in the Linux world despises Ubuntu.

If I want to wear my sunglasses while I’m watching a movie in the cinema because I have a light-sensitivity condition—usagenof the sunglasses alters my perception of the film without changing the permanent media storage of the film—am I cheating and subject to copyright infringement action?

Stop giving me Thermo nightmares; I lived through that shit already I don’t need to sleep through it too.

How are you planning on handling the induced phase shifts due to the rapid polarity reversals that occur in the transgravitational electron flux arrays? I mean, this is a nonstarter if you can’t get that to work—the electropositron fields are going to decay too quickly to be useful otherwise and the quite-expensive phosphokinesis-generator will be wasted.

A enterprise company that has 10k developers should just invest in their own image hub. It’s not really that hard to do. Docker even open-sourced it under Apache2.0.

Fair enough. I agree for what it’s worth—just have yet to find a browser that meets my needs for both usability and privacy. Always happy to explore options and I do sometimes. Just always end up back with Brave because everything else I try ends up annoying me in some way or the other.

You can turn the crypto part off you know. They even tell you how to do it.

Gonna go ahead and be downvote sponge here: Brave. Its privacy features and integrated Adblock have no peer that I’ve found yet, and easy bookmark/history syncing across multiple devices.

Yeah the CEO is a POS. Find me a tech CEO that’s not, besides Meredith Whitaker.

The most annoying thing about a lot of these is that tutorials are “minimal viable setup” sorta things. Like “now you have it setup, make sure you tune it for production”

Dude I’m already in pain from trying to serve these models and you just have to go rub salt into my eyes. “Simplify your stack with <Tech>” they said. “Share your resources effectively and easily with <Tech>” they said. “Here’s your fuckin’ ‘Hello, World’ now GRTFM and buzz off” they said.

Working close to the metal do be like that.