Using Ollama to try a couple of models right now for an idea. I’ve tried to run Llama 3.2 and Qwen 2.5 3b, both of which fits my 3050 6G’s VRAM. I’ve also tried for fun to use Qwen 2.5 32b, which fits in my RAM (I’ve got 128G) but it was only able to reply a couple of tokens per second, thereby making it very much a non-interactive experience. Will need to explore the response time piece a bit further to see if there are ways I can lean on larger models with longer delays still.
chiisana
It was never to your definition of free, so you were never going to be using it in the first place. Don’t need to say goodbye when you were never here.
For “larger” projects, they tend to follow semantic version best practices fairly well, so I tend to pin to minor (i.e. postgres:16.4
) and I get updates along the way, with minimal risk of it breaking from major changes.
For others, I pin to specific version and update on my own terms.
If you’re going to use it, you’d be paying for it one way or another; either through money or privacy. Par for the course.
This is Apple; they value different things than most people… sometimes warranted, results in offering a much better experience, and pushes everything forward (see MagSafe -> Qi2 for recent example), other times they’re just regarded as late adopters. The detraction of visual aesthetics from folding crease is apparently one of such things that they care about.
Amazing stuff. Thank you so much!
The LM password hash (predecessor to NTLM) was calculated in two blocks of 7 characters from that truncated 14 characters. Which meant the rainbow table for that is much smaller than necessary and if your password is not 14 characters, then technically part of the hash is much easier to brute force, because the other missing characters are just padded with null.
If memory serves, 175B parameters is for the GPT3 model, not even the 3.5 model that caught the world by surprise; and they have not disclosed parameter space for GPT4, 4o, and o1 yet. If memory also serves, 3 was primarily English, and had only a relatively small set of words (I think 50K or something to that effect) it was considering as next token candidates. Now that it is able to work in multiple languages and multi modal, the parameter space must be much much larger.
The amount of things it can do now is incredible, but our perceived incremental improvements on LLM will probably slow down (due to the pace fitting to the predicted lines in log space)… until the next big thing (neural nets > expert systems > deep learning > LLM > ???). Such an exciting time we’re in!
Edit: found it. Roughly 50K tokens for input output embedding, in GPT3. 3Blue1Brown has a really good explanation here for anyone interested: https://youtu.be/wjZofJX0v4M
The models are not wrong. The models are nothing but a statistical model that’s really good at predicting the next word that is likely to follow base on prior information given. It doesn’t have understanding of the context of the words, just that statistically they’re likely to follow. As such, all LLM outputs are correct to their design.
The users’ assumption/expectation of the output being factual is what is wrong. Hallucination is a fancy word in attempt make the users not feel as upset when the output passage doesn’t match their assumption/expectation.
The amount of confidently incorrect responses is exactly what one could expect from Lemmy.
First: TCP and UDP can listen on the same port, DNS is a great example of such. You’d generally need it to be part of the same process as ports are generally bound to the same process, but more on this later.
Second: Minecraft and website are both using TCP. TCP is part of layer 4, transport; whereas HTTP(S) / Minecraft are part of layer 7, application. If you really want to, you could cram HTTP(S) over UDP (technically, QUIC/HTTP3 does this), and if you absolutely want to, with updates to the protocol itself, and some server client edits you can cram Minecraft over UDP, too. People need to brush up on their OSI layers before making bold claims.
Third: The web server and the Minecraft server are not running on the same machine. For something that scale, both services are served from a cluster focused only on what they’re serving.
Finally: Hypixel use reverse proxy to sit between the user and their actual server. Specifically, they are most likely using Cloudflare Spectrum to proxy their traffic. User request reaches a point of presence, a reverse proxy service is listening on the applicable ports (443/25565) + protocol (HTTPS/Minecraft), and then depending on traffic type, and rules, the request gets routed to the actual server behind the scenes. There are speculations of them no longer using Cloudflare, but I don’t believe this is the case. If you dig their mc.hypixel.net domain, you get a bunch of direct assigned IP addresses, but if you tried to trace it from multiple locations, you’d all end up going through Cloudflare infrastructure. It is highly likely that they’re still leaning on Cloudflare for this service, with a BYOIP arrangement to reduce risk of DDOS addressed towards them overflow to other customers.
In no uncertain terms:
mc.hypixel.net
, but also have a SRV record for_minecraft._tcp.hypixel.net
set for 25565 onmc.hypixel.net
mc.hypixel.net
domain has CNAME record formt.mc.production.hypixel.io.
which is flattened to a bunch of their own direct assigned IP addresses.