because the secret is that the web runs on advertising/targeted recommendations. Brezos(tm) wants you to actively browse Ramazon so he can harvest your data, search patterns etc. Amazon and most sites like that are very not crawl friendly for this reason. Why would Brezos let Saltman get all the juicy preference data?
On the foundational level, test time compute(reasoning), heavy RL post training, 1M+ plus context length etc.
On the application layer, connecting with sandboxes/VM's is one of the biggest shifts. (Cloudfares codemode etc). Giving an llm a sandbox unlocks on the fly computation, calculations, RPA, anything really.
MCP's, or rather standardized function calling is another one.
Also, local llm's are becoming almost viable because of better and better distillation, relying on quick web search for facts etc.
Their page itself looks classic v0/ai generated, that yellow/orange warning box, plus the general shadows/borders screams LLM slop etc. Is it too hard these days to spend 30 minutes to think about UI/user experience?
I actually like the idea, not sure about monetization.
It also requires access to all the data?? And it's not even open source.
> I actually like the idea, not sure about monetization.
To be fair, we're not sure about monetization either :) We just had a lot of fun building it and have enjoyed seeing what people make with it.
> It also requires access to all the data??
Think of us like Tampermonkey/some other userscript manager. The scripts you run have to go through our script engine. That means that any data/permission your script needs access to, our script needs access to. We do try to make the scripting transparent. If you're familiar with the Greasemonkey API, we show you which permissions a given script requests (e.g. here https://www.tweeks.io/share/script/d856f07a2cb843c5bfa1b455, requires GM_addStyle)
I'm working on Flavia, an ultra-low latency voice AI data analyst that can join your meetings. You can throw in data(csv's, postgres db's, bigquery, posthog analytics for now) and you just talk and ask questions. Using cerebras(2000 tokens per second) and very low latency sandboxes on the fly, you can get back charts/tables/analysis in under 1 second. (excluding time of the actual SQL query if you are doing bigquery).
She can also join your google meet or teams meetings, share her screen and then everyone in the meeting can ask questions and see live results. Currently being used by product managers and executives for mainly analytics and data science use cases.
We plan to open-source it soon if there is demand. Very fast voice+actions is the future imo
Great feedback thanks! We have added a synthetic e-commerce dataset as an example when you sign up so you can test it without your data first. Will also add a demo video ASAP.
What kind of plan do you have with Cerebras? It seems like something like that would need one of the $1500/month plans at least if there were more than a handful of customers.
They introduced pay as you go recently. The limits on that is similar to the plans, 1 million tokens per minute, so if you stack a few keys and do a simple load balancing with redis, can cover a decent amount of traffic with no upfront cost. Eventually we would have to go enterprise though yes!
ok.. when I tried to use pay-as-you-go it was unusable for me because there were a ton of 429s and 503s. one test it was just constant for a few seconds when I tried it, 429 or 503.
I am using it for a voice application though so retrying causes a delay for the user that they don't expect. especially if it stays unavailable for a few seconds.
It is special because of what is being discussed here: it attempted (pretended?) to do so as a non-profit, which arguably gave it early support by people who otherwise may not have provided it. None of the other players you mention did so, which to me makes it an unfair advantage. Or not, given that it seems that anything is fair that you can get away with these days.
Everyone. People are becoming dependent on chatgpt. They literally cannot function professionally or even socially without it. They will pay their last 20-30 dollars if needed. It's literally like a drug especially when it's asking you if you want to followup/continue.
Everyone also uses Google, YouTube or Instagram. No one would ever pay for any of it though and it is financed through ads. So far it is unclear, if this is also a viable option for chatgpt.
Out of about 2.7 billion users. So about 5% of all users are subscribed to YouTube.
If the same were true then Open AI at 1 billion weekly users they should have about 50 million subscribers. Right now that numbers sits at 20 million though and growth is slowing down. [1]
So people are more willing to pay for YouTube than ChatGPT and that is ignoring that YouTube is still largely relying on ad revenue and can only allow itself to have more and more ads as there are no alternatives. Open AI has plenty of competitors that would love to offer users free access if ChatGPT were to start showing you ads.
> Everyone also uses Google, YouTube or Instagram. No one would ever pay for any of it though and it is financed through ads.
A lot of people already pay for YouTube since the introduction of Premium. Google/Facebook don't push for paid versions of these products because the data from billions of "free" users is more valuable to them than payments from millions of paid users.
If Google search were paywalled (pre-AI) the most likely outcome would be a separation of consumers into "premium" customers paying for Google, some people paying for cheaper but not quite as good alternatives, and everyone else getting by with the free alternatives. There would also likely be some kind of enterprise tier for indexing your corporate resources or some such.
There's a reason Adobe is still extracting billions from its ~~victims~~ users despite many great free (or reasonably priced) alternatives existing.
This has nothing to do with what i said. I said they are addicted. The free limits are designed this way. If openai suddenly removed the free plan, i guarantee you a lot of people would buy. They dont have an alternative they cannot think independently anymore
At least one of us is inside a bubble. Nobody I interact with regularly uses chatgpt for anything more than novelty. Even people who used it as glorified google for looking up things reduced their use.
There are definitely big?bubbles where everyone has outsourced their thinking to AI. I’d like to think it’s mostly at the lower end of “knowledge work” - think Deloitte, but it seems that even people / orgs that you would expect more critical thinking of are using it uncritically.
Of course this all occurs in a very small segment of society, I think the majority of people don’t really use it, and certainly haven’t moved any of their day-to-day thinking over to it.
If my mom gives me 1000 dollars for 1% of my lemonade stand, that doesn't mean my stand is worth 100k. Tether is in talks with investors to mayb raise 20b at a 500b valuation. Keep in mind also that crypto investors overvalue companies to create the hype and then lobby for better regulations etc. It doesn't mean at all that someone would be interested to buy 100% of tether for 500b. Now, if they were public is a different story, like Tesla etc
The whole point of embeddings and tokens are that they are a compressed version of text, a lower dimensionality. now, how low depends on performance, lower amount of vectors=more lossy (usually). https://huggingface.co/spaces/mteb/leaderboard
You can train your own with very very compressed, i mean you could even go down to each token=just 2 float numbers. It will train, but it will be terrible, because it can essentially only capture distance.
Prompting a good LLM to summarize the context is probably funnily enough the best way of actually "compressing" context
Additionally, depending on round, they also have multiples, like 2x meaning they get at least 2x their investment before anyone else gets anything