287 karma · joined December 22, 2023
It's absolutely just sampling with temperature or top_p/k, etc. Beam searches would be very expensive, I can't see them doing that for chatgpt which appears to be their "consumer product" and often has lower quality results compared to the api.
The old legacy had a "best_of" option but that doesn't exist in the new api.
That said it appears they also released the base checkpoints that aren't fine-tuned for alignment
Are there plans for MoE or 70B models?
What they actually said (abbreviated) was anything with more then
> "600 Gbyte/s [memory transfer speed]" or 4800TOPS
Page 103 https://public-inspection.federalregister.gov/2022-21658.pdf
They set very specific performance restrictions, not a general "don't sell fast stuff plz"
It's like putting up a speed limit sign that says "55mph" and then ticketing them for speeding going "53mph".
If they want people to go 35mph, they should just made the limit 35mph!
It's like putting up a speed limit sign that says "55mph" and then ticketing them for speeding going "53mph"
They should have just written this in the regulations.
Instead they're making nvidia waste resources making a product that complied with regulations.
I've had queries of copy+pasted errors with zero results, but playing around with it a bit just to find a github result that was only like two words off.
> it’s terrible but far better than getting 100’s of irrelevant results because
Surely the similarity to the one on github would still have it ranked on the first page?
That's what I said. "then evaluate the query anyway." I should have added "original" to that statement
> If that is nothing, that's what it should show. It should not show me entirely unrelated results, ads, or what it "think" I meant. Not its job.
I'm saying I don't want similarity cutoffs. Most FTS methods involve a similarity score, I'm saying I don't want only results with > 0.1 similarity. I want all of them that were returned.
I'm NOT saying it should somehow inject results that didn't originate from the original FTS query.
I'm saying if you have a query that returns a similarity score, I don't want only results with > 0.1. I want all the results returned
I'm saying I don't like high cutoffs of similarity scores. I have no idea what you're talking about.
Very very few queries should have _literally zero results_. Surely you have at least a few words in common with something
Then it should suggest a better one and then evaluate the query anyway.
> This is what any decent search engine should do -- return nothing
WHY?! That's the opposite of it's job!
I have an account with a username that is spelled very similarly to a real word. Google will suggest searching for the real word instead. If you do that though, you'll never find the username!
I'm tired of people saying the computer should not do what I tell it to. It's like children who won't even attempt a multiple choice test because they aren't 100% sure
Uh sorta but not like parent described at all. You have multiple "experts" and you have a routing layer(s) that decide which expert to send it to. Usually every token is sent to at least 2. You can't just send half the tokens to one expert and half to another.
Also the "experts" are not "domain experts" - there is not a "programming expert" and an "essay expert".
If it was as simple as dropping 10's millions on compute they could do that, yet google's bard/gemini have been a year behind GPT4's performance.
That said I do agree that it's a moat for the startups like stability/mistral, etc. They also have access to $/compute, albiet a lot less. And you can see this in their research, as they've been focused on methods to lower the training/inference costs.
*I'm measuring performance by the chatbot arena's elo system and r/locallama
He didn't seem to have specific definition at all really.
I think most people attribute it to a "secret sauce technology" in the case of OpenAI, I'm not sure if "finances to lease a huge cluster of GPUs" makes sense here because the main competitors (Google, AWS, Apple, etc) also have access to insane compute as well yet have struggled to get close to GPT4's performance in practice.
That said I do agree that it's a moat for the startups like stability/mistral, etc. They also have access to $/compute, albiet a lot less. And you can see this in their research, as they've been focused on methods to lower the training/inference costs.
The flipper is just some common off-the-shelf radios and microcontroller, albiet in a nice package. That's it. Like common radios found in your everyday stuff, like say a garage door remote.
Would regulations affect every product using these? I assume they'd have to in order to have any teeth? Would this impact a developer who wants to buy an cc1101 evaluation board for development?
Don't MoE's route tokens to experts after the attention step? That wouldn't solve the n^2 issue the attention step has.
If you split the tokens before the attention step, that would mean those tokens would have no relationship to each other - it would be like inferring two prompts in parallel. That would defeat the point of a 10M context
ZeroWater uses an ion exchange filter - It's my understanding that many (most?) micro plastics are not dissolved and/or are not charged meaning it won't effectively filter most microplastics.
Similarly they aren't designed to filter bacteria.
> The current system is meant to be used with municipally treated, potable water as the current filter will not remove microbiological contaminants.
There's few things that destroy them further.
That and many of the effects may not occur until a sufficient amount of microplastics have accumulated which we may only now be approaching.
The biggest issue is that they break down so poorly. Even if we stopped all plastic production today, the total amount of microplastics will only accumulate
Yes, very suspicious that he didn't want to issue CVEs for
checks notes
Two DOS attacks that only apply to users that explicitly enabled experimental QUIC support (by default it's disabled)
You're looking at 10k to file it, and then all it gives you is the ability to sue. If [insert company] violates it, you could easily be looking at 100k+ for litigation that you may or may not win.
> So if I invent something
My problem is you don't need to "invent" anything. You just need to be the first to file the paperwork (and have the cash to do so).
"[sensor] on [smartwatch, glasses, goggles, belts, chairs, whatever]" and now nobody else can do it for 20 years. Even if it's blatantly obvious that an chair can sense if you're sitting in it to turn on the tv automatically.
I'd be more on-board with the idea if non-software patents only had say a 5 year lifespan
Comcast is 180 days - https://www.xfinity.com/-/media/4231839e374c4f618b2d34004d50...
I could not find a specific number for Frontier - https://content.frontier.com/-/jssmedia/documents/corporate/...
Generally people refer to this as Enshittification
> if you ruin the experience for the user then you've ruined your own product, thus defeating the shareholder.
Enshittification is literally the opposite of this.
That's not true, you can request/compel Frontier to tell you what specific customer that IP was assigned to at a given time.
> and they're typically shared among many others so an IP is not a guaranteed signal that it was 'you' who pirated stuff.
Most residential ISPs in the states have 1 ipv4 (and possibly ipv6) assigned per customer and don't CGNAT, from my brief research Frontier doesn't seem to use CGNAT at least for residential internet.
Depends on the file/directory structure. Traditionally back in the CGI days URI's were links to files on a server. They often still are for static files. If you know the path to a file then the lookup should be very fast.
But yeah any other type of index other then the path isn't really possible.