model_tar_gz
You misspelled pencil in this context. I believe you meant “a fuckin’ pencil”.
And you just reminded me of a movie from a show and let’s just say I recommend both.
My use case will be to remove the looping bland house music from tech product demos. I really don’t understand why every tech company needs to make me feel like I’m at a club when I’m just there to learn about a new feature in their product and how I can use it.
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.
The UPS driver that delivers to my home office a bag of electronic goodies every week couldn’t care less about what OS I use. I mean I even tried to tell him about all the awesome Minty Pops and Arches and all he had to say was “that Fedora looks fucking dope, bro. Say, do you listen to Hannah Montana?”
With a high-vis vest and a clipboard, you can get almost anywhere.
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.
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.