I went through this a few months ago in Rust. I wrote all the code by hand, no LLMs. Then I went ahead and added a small "game" on top, plus some special effects like pixelization shaders and chromatic aberration at the edge of a flashlight.
if anyone is interested! The repo has lots and lots of in-progress screenshots so you can see the renderer come to life, plus all the hilarious visual bugs along the way.
I learned a lot! My biggest lesson, other than the specifics of how rendering works, was that modern CPUs are really fast: a single-threaded CPU renderer can definitely run an interactive 3D game with some fancy special effects.
Java LSPs are essentially the same approach, headless Eclipse JDT or NetBeans.
While Metals for Scala was an overhaul from the former Eclipse plugin (and Ensime) plus early experiments embedded in the Scala 3 compiler. And Metals v2 is yet another rewrite.
They're not jumping through any hoops, I think they're simply complying with reporting requirements. It's not on their balance sheet because being recorded as strait debt would itself be misleading. My understanding is that these sort of off-balance sheet "debt" is mostly in the form of deal terms that may or may not be expressed at some point in the future.
An analogy that comes to mind is when companies used to book future sales in the present. They got in trouble for this and is now forbidden. I recall reading that one deal had terms that transferred assets if certain conditions were not met. If terms-based debt should be booked now, then terms-based assets should as well. This stuff makes my head hurt.
Either way, as long as it's not hidden (and it's not for the public companies), then it's fine.
I have ~100 repos on github and only a few of them with LLM assistance. Aside from a few comments and a PR here and there throughout the years nobody cares about them. I have to assume it's the same for the majority of developers.
> But this went out of the window when some genius decided that usernames were too complicated, so Passkeys had to be discoverable, which means they have to be fully stored token-side. Which of course has the nice side benefit of essentially killing hardware tokens and forcing people into using their Android/iOS/Windows device for it.
This part of your comment is incorrect. Discoverable Webauthn absolutely can be used with hardware tokens like Yubikeys.
> It's interesting that it cares about formatting choices like bullet points.
Since AI I have noticed a lot of sudden bulleted lists appearing in pretty benign forum posts. That along with "You are right" "You are correct" "you're right" as the response.
I don’t understand this modern trend where people will put pictures of someone’s menu up, roast them, fall all over themselves talking about how over the food and still hit publish. What is the fucking point?
They only reason that they are retaining value is there was not so much demand for GPUs in 2021 as there is today. Once the demand drops you will find then in dumpsters across our barren, burning dystopia.
No one knows. There's a known bullwhip effect in supply chain [0], and DRAM makers are pretty far out along the supply chain. Just like it ramped up wildly it will stop even faster.
Unlike Claude Fable, once an open weights model is released, it's available forever (or at least until every copy is lost or deleted, which won't be soon).
Open weights models are already great, and the ones that are already released will continue to be just as good as they are today even if newer versions are released at a different speed in the future.
I didn't join the chat so I don't know that. It's final now anyway, nobody can change the text (next year you can propose another vote). No idea what the point would be of ephemeral conversations about it
The math looks good on paper, but in reality enterprise AI is hard, most companies are realizing they are actually not seeing ROI from AI. One of my customers took about 8 months to rollout an AI initiative that by the time it launched and people got trained on it, it was already legacy. Also if you are 10x more productive with AI that doesn’t necessarily increases your billable output. There could be some super models like Mythos aimed at very specific hard tasks like drug development, but we have not seen any of that yet, and the clock is ticking.
Forced labour? Poland has doctors on 32 hour shifts. Worker comes on monday morning, leaves tuesday evening. The night is spend on ER, with a few naps between patients. Perfectly legal!
Yes, you don't rely on an LLM solely for medical advice. You use it to get orientation to look at other sources. In my friend's case, I was relaying to him what I learned when taking a similar drug, my doctor's cautions on stopping the drug, what the manufacturer says about stopping the drug, and the published dosing schedule.
I guess you're right about me having zero qualifications. I only have a lifetime of experience with treatments for the various conditions I live with and the dozens of drugs that have failed to treat these conditions. I've been forced into self-education (learning how to read the research papers and the manufacturer info sheets) just like any patient with a complex medical situation needs to do for self-advocacy. This knowledge has helped me catch doctors' prescribing mistakes. I wish I'd had the skill before one such mistake toasted my kidneys.
One thing this implies is that the escape velocity of such objects increases linearly with mass, so the surface temperature they can sustain without losing mass increases quadratically with their mass. Massive super-jovian planets can orbit close to their star, limited only by tidal disruption. Some could even orbit within the outer envelope of the star for quite some time.
You could say this but the previous administration was not talking about taking a 10% share in both companies; this one is (thanks to Sam Altman's very personal lobbying of the president)
(edit: sorry, re-reading your comment you were more directly referring to the AI companies and this context, I interpreted this more generally on my first glance)
I mean that if fine / E[N_f] < battery_cost / E[N_b], where E[N_] is an expected number of rides before a fine / battery expire, then I save money per ride. In your example, you just pick the values such that the relation becomes '>'.
I’m saying there is no proof that companies _paying for AI_ are seeing a positive effect to their ROI. If you have such a proof, please share, that would be a massive news
Not to mention that tying your insurance to your job is a *huge* pain. If you switch jobs or get fired you need to deal with coverage gaps, considering individual coverage for the duration, you may need to switch care providers depending on what your new coverage is.
https://github.com/kshitijl/tinyrenderer-rs
if anyone is interested! The repo has lots and lots of in-progress screenshots so you can see the renderer come to life, plus all the hilarious visual bugs along the way.
I learned a lot! My biggest lesson, other than the specifics of how rendering works, was that modern CPUs are really fast: a single-threaded CPU renderer can definitely run an interactive 3D game with some fancy special effects.