@mods in the Order Book graph ("Cumulative shares vs probability"), the green graph which shows the cumulative YES limit orders seems to be off. There are 2'383 YES limit orders in total, but the graph shows 140k?

Also, the user Mira does not exist anymore, but their limit orders are still listed.

@JonasSourlier The graph shows the total number of potential shares to be bought with the limit orders, while the order book shows the amount of potential mana required to buy the shares. For example, Mira’s 1001 mana order at 1% buys 100100 shares, and is listed as 1001 in one place and 100100 in the other.

I’m pretty sure it’s normal that the limit order of a deleted account is still there.

Let me know if you have more questions.

@JonasSourlier

There are 2'383 YES limit orders in total, but the graph shows 140k?

Note that the limit orders above are denominated in mana ("M"), while the chart below is denominated in "shares". Note that a 1M limit order at 1% is worth 100 shares.

Also, the user Mira does not exist anymore, but their limit orders are still listed.

FWIW the mods don't have direct input on how the site works (for feedback you can use the Discord)

@Ziddletwix lol

@bagelfan I was too slow!

actual inference spend seems to be extremely low

OpenAI was only collecting about $700m in inference revenue. Assuming that both Google and Anthropic have less inference revenue than OpenAI, we have less than $2.1bn total inference spend across all the major players.

Fascinating. You don't hear that figure in the news as much.

The gap is closed with 405b and we still got 1.5 years

That is, if either all the leaderboards are full of open-source LLMs with successors to GPT-4 or Claude being far behind

this seems very unlikely!

or if most of the business spending for inference seems to be on running AI models built on open-source foundation models

this seems less unlikely but still unlikely. Google, openai, and anthropic are still gonna be competing!

The second some VC AI companies fail H100s start to flood the market were gonna have Llama405b instances everywhere. And then? It would be the cheapest option by far.

Why won't google, openai, and anthropic match those prices?

(Also, aren't all of those actively developing better models?)

The open-source model Deepseek is currently the clear leader in cost-efficiency: (Screenshot from https://artificialanalysis.ai/)

https://github.com/cfahlgren1/natural-sql

https://twitter.com/rohanpaul_ai/status/1736827830971867312

GPT-3.5 class model with longer context size is offered at 1/3 of gpt-3.5-turbo price

@WieDan How is Gemini "open-source AI"?

@osmarks it's obviously not, but Gemini Ultra being barely better than GPT-4 arguably shows that having enormous resources and data doesn't really give you that much of an edge.

@BairAiushin My reading of that is just that Google is bizarrely incompetent some of the time.

@BairAiushin yeah i think we're deep in the s curve

@osmarks Google had an extra 9 months over GPT-4 + some open source knowledge, and still failed to make the gains we expected, even with delaying Ultra. This definitely is good news for YES betters here. Plus, open source is getting closer to gpt-4. I'm updating a bit towards open source seeing that it is progressing faster.

@ShadowyZephyr I haven't seen any open source models get remotely close to GPT-4, the best ones are just barely starting to get close to 3.5 Turbo.

@SemioticRivalry this is true but if the other models are going to slow down they have 2 years to catch up. In the scenario where everyone is blasting full speed ahead them catching up would not be nearly enough.

@SemioticRivalry Mixtral is reportedly better than GPT-3.5 on benchmarks.