The online version will remark free and available. The in-person, for credit course is being discontinued. Unless you are an incoming Harvard student, this won’t affect you.

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I could really go for some Æthermelon right about now.

… said the Joker to the Thief.

You misspelled pencil in this context. I believe you meant “a fuckin’ pencil”.

Look up the kanban method. It’s really commonly used in software engineering because there’s always so many tasks to do and very often we discover other tasks to do while in the midst of another task—natural task stacking. I’ve taken to using it in my day to day life and it’s the only way I’ve found that actually keeps some sanity to the chaos. Also, it improved my family relationships when I finally got everyone on board with it.

Up

And you just reminded me of a movie from a show and let’s just say I recommend both.

https://youtu.be/X1DcKBwliAw

Anything Goes!

Sure, but $120k is definitely not FAANG-tier base comp in SF. Not even close. Maybe it’s on the low side of scrappy startup/scaleup comp.

I relatively recently tried to replay Goldeneye. It was shocking—controller and FPS mechanics have evolved so much since then it was honestly not fun to play. While it was breakthrough tech at the time it just did not age well.

So many hours of fun into that game though; I’ll never not hold a special place in my heart for it even if it’s unplayable nostalgia now.

FPS keyboard+mouse shooters of that era have aged much better. I can still play Marathon (+2 + Infinity) (Bungie’s precursors to Halo) and have an enjoyable gaming session.

I love selecting text on a page or different file then middle-clicking at the target for a quick copy-paste that bypasses the typical clipboard ctrl-c/ctrl-v pattern.

Is he related to Nebraska Spider-Man?

I use cloud computing to run a lot of my computer stuff. Not a PC. I self-host some services on a home-server. Also not a PC. I can install a GUI on these if I want and RDP into them, still doesn’t make these PCs.

I can use my personal laptop as a server if I want (and I have!) with remote-access enabled; so it is both a PC and a not-PC?

I think we have to settle on PC being usecase-driven; not hardware-defined. Which is what I think you were trying to get at, but abstracting too far.

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.

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.

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.

You seem like a good person and I wish Lemmy had a way to follow people. Need more positivity in the feed. Keep it up, friend.

I listen to Stellaris OST a lot these days. Turns out that good music to plan galactic domination is also good music to design and build software.

Don’t really play the game much anymore though. That was one of my main pandemic games.