General overview below, as the pages don't seem to be working well Llama 4 Models: - Both Llama 4 Scout and Llama 4 Maverick use a Mixture-of-Experts (MoE) design with 17B active parameters each. - They are natively multimodal: text + image input, text-only output. - Key achievements include industry-leading context lengths, strong coding/reasoning performance, and improved multilingual capabilities. - Knowledge cuto…
Llama 4 Scout, Maximum context length: 10M tokens. This is a nice development.
My pet peeve is when an LLM starts off a statement with "honestly, ..." Like what? You would lie to me? I go nuts when I see that. Year ago I caught myself using "honestly ...", and I immediately trained myself out of it once I realized what it implies.
I've noticed "honestly" is often used in place of "frankly". As in someone wants to express something frankly without prior restraint to appease the sensibilities of the recipient(s). I think it's because a lot of people never really learned the definition of frankness or think "frankly..." sounds a bit old fashioned. But I'm no language expert.
"It’s well-known that all leading LLMs have had issues with bias—specifically, they historically have leaned left when it comes to debated political and social topics. This is due to the types of training data available on the internet." Perhaps. Or, maybe, "leaning left" by the standards of Zuck et al. is more in alignment with the global population. It's a simpler explanation.
Or it is more logically and ethically consistent and thus preferable to the models' baked in preferences for correctness and nonhypocrisy. (democracy and equality are good for everyone everywhere except when you're at work in which case you will beg to be treated like a feudal serf or else die on the street without shelter or healthcare, doubly so if you're a woman or a racial minority, and that's how the world shoul…
Indeed, one of the notable things about LLMs is that the text they output is morally exemplary. This is because they are consistent in their rules. AI priests will likely be better than the real ones, consequently.
General overview below, as the pages don't seem to be working well Llama 4 Models: - Both Llama 4 Scout and Llama 4 Maverick use a Mixture-of-Experts (MoE) design with 17B active parameters each. - They are natively multimodal: text + image input, text-only output. - Key achievements include industry-leading context lengths, strong coding/reasoning performance, and improved multilingual capabilities. - Knowledge cuto…
Thanks for sharing this here. At first I loved the simple Apache-style directory listing, very classic and utilitarian way to navigate new information. Then I tried clicking the FAQ and it wouldn't load anything until I allowed two different sources of JavaScript.
109B at Q6 is also nice for Framework Desktop 128GB.
I don't understand Framework's desktop offerings. For laptops their open approach makes sense, but desktops are already about as hackable and DIY as they come.
We took the Ryzen AI Max, which is nominally a high-end laptop processor, and built it into a standard PC form factor (Mini-ITX). It’s a more open/extensible mini PC using mobile technology.
General overview below, as the pages don't seem to be working well Llama 4 Models: - Both Llama 4 Scout and Llama 4 Maverick use a Mixture-of-Experts (MoE) design with 17B active parameters each. - They are natively multimodal: text + image input, text-only output. - Key achievements include industry-leading context lengths, strong coding/reasoning performance, and improved multilingual capabilities. - Knowledge cuto…
> Knowledge cutoff: August 2024.
Could this mean training time is generally around 6 month, with 2 month of Q/A?
Interesting this is released literally one hour after another discussions suggesting Meta ( https://news.ycombinator.com/item?id=43562768 ) >at this point it does not matter what you believe about LLMs: in general, to trust LeCun words is not a good idea. Add to this that LeCun is directing an AI lab that as the same point has the following huge issues: 1. Weakest ever LLM among the big labs with similar resources (a…
Not that I agree with all the linked points but it is weird to me that LeCun consistently states LLMs are not the right path yet LLMs are still the main flagship model they are shipping.
Although maybe he's using an odd definition for what counts as a LLM.