Crowrosion 🐦‍⬛

Observing from the shadows 👁🧠

[Crowrosion 🐦‍⬛ @Crowrosion]

@KenKirtland17 @AlessandroPonz4 I dont understand this. Id argue teslas pivot to humanoid robots justify its valuation if we assume too much value is being pulled forward. But im having a hard time seeing that for SpaceX

[Crowrosion 🐦‍⬛ @Crowrosion]

@RJCcapital Is this some kind of psychosis? How? What is the path for this happening?

[Crowrosion 🐦‍⬛ @Crowrosion]

@ParadisLabs Its cool, I like being introduced to stocks and then they fade out. They'll come back if they're quality.

[Michael Sikand 🦑 @michaelsikand]

If your AI stocks mooned today.

You are part of a tiny, tiny contingent out of the global population studying and allocating capital into this supercycle.

You realize most people don't believe in AI and want to see it collapse?

This is not the consensus trade you think it is.

[based16z @based16z]

Markets are so inefficient these days… Jensen Huang said MRVL should be 1 trillion and instead of being up 5x after hours to 1 trillion it’s only up 20%

[Upamanyu Acharya @upamanyuacharya]

@StanphylCap Is this a new terminology you've invented called backward PE?

"If this company earns next year what it did last year, this would be the price" lol

[SJ87K @BrueghelElder87]

@WalkerFran80950 I think it will depend on parallel development of the robotics theme, chance is there for sure

[Altcoin Overlord @AltcoinOverlord]

@crux_capital_ its not even a real product yet though lol there is zero proof of concept right its multiple years away even if it is possible?

[Crowrosion 🐦‍⬛ @Crowrosion]

@lapplandtrader @TheValueist Its ridiculous.

[Toby @TomolaGroup]

Nvidia sells the chips that every AI company on earth depends on.

OpenAI buys from them. Google buys from them. Microsoft buys from them.

Now Nvidia is spending $26 billion to build its own AI models.

The shovel seller just entered the gold mine.

This is the biggest power play in tech right now and nobody is talking about it enough.

[Crowrosion 🐦‍⬛ @Crowrosion]

@RailgunIntern 🤣🤣

[Crowrosion 🐦‍⬛ @Crowrosion]

@Lewsiphur @rootslashbin Bro just implied that he's intentionally spreading fear mongering misinformation for vibes.

[Crowrosion 🐦‍⬛ @Crowrosion]

@Banana3Stocks Confused a bit here. It seems like you meant to say HBM (high bandwidth memory) and not hmb?

[Crowrosion 🐦‍⬛ @Crowrosion]

@RJCcapital That "correlated as diversification' is the ninja of the group.

[Fuego @DeployFuego]

Finally 😶‍🌫️🆙️ another day with @lukso_io

Explored the whole Universal profile and @ProfileJump thanks to @JordyDutch and now decided to build a protocol in sync with the universal profile, which can be used across the ecosystem, In 4 weeks I should be done with the MVP. Then another 4 weeks probably SDKs will be ready for devs to use the protocol or contribute to it. Open source.

Here's the plan;

Unlike Web2 chat apps or even some Web3 messengers:

🧬 I am using a real identity (UP), not random wallets

🆙️ Embed chat protocol across LUKSO, fashion dApps, marketplaces, DAOs, games

🧠 It's a protocol, not just a product, hopefully, others can adopt my schema.

Imagine User A uses your app “My App,”
User B uses “UP Messenger” by someone else.
They can still chat because they both use the same UP architecture.

So yeah it's a shared protocol, not a platform:

No one needs my app to communicate just their UP

Any LUKSO dApp can plug into the protocol.

Spent all weekend reading the full documentation to make it work, I think I have a way. Let's explore and document this together, shall we, who's with me?

In the meantime, I have something exciting for Devs and NFT enthusiasts, which is only going to be on Discord 🤔 .

[Marjorie Hernandez @0xMarjorie]

If he applied the same speed and energy to product delivery as he does to forwarding me screenshots about trolls or RTFKT, LUKSO might be in a much stronger position by now.

[LUKSO @lukso_io]

Former CEO of Coinbase Germany joins LUKSO

Jan-Oliver Sell joins as COO of @Universal_Every to help grow the LUKSO Tech team.

Read the article here:
https://t.co/MOf8YNuob1

[Jack Morris @jxmnop]

# A new type of information theory

this paper is not super well-known but has changed my opinion of how deep learning works more than almost anything else

it says that we should measure the amount of information available in some representation based on how *extractable* it is, given finite computation. for example, an encrypted text file has less V-information than the same data in plaintext, because it takes more computation to extract. note the contrast to traditional information theory, which would tell us that the two representations have the same amount of Shannon information

i’ve long wondered why certain types of basic questions didn’t have a proper theoretical answer:
> why does distillation outperform vanilla maximum likelihood training?
> why does lora work better than finetuning?
> why does self-attention work better than almost any other similar operation?
> how much “information” remains in a text embedding?
> how much “information” remains in language model weights?
> should i use fine-tuning or RAG?

the true answers to all these questions depend on some way of measuring and comparing *information content* between different representations. v-information is one step towards doing this

besides computational constraints, model architecture probably affects the “information content” in representations, along with the presence of any pretraining data used, as well as model-level statistics about the optimization in the training process – e.g. the length of time a model was trained for probably changes representations pretty drastically

this is all to say, i think there is some true notion of “information” that none of our current paradigms (Shannon information, V-information, etc.) capture. we encounter this idea every day but we dance around it and describe it in vague terms; we measure it from all sorts of angles but can’t quite characterize it theoretically

when the v-information paper came out I thought there would be a lot of follow up work developing more complex and useful notions of information for deep learning. but it hasn’t

yet I still think at the heart of these questions of what-information-lies-in-representations there’s something to be found that’s profound, elegant, and potentially extremely useful. I don’t know what it is and i’m probably not the person who will figure it out. but I really hope someone does. :)

[Crowrosion 🐦‍⬛ @Crowrosion]

@PrestoHODL @AndreCronjeTech I must of missed a lot. why do you hate lukso now again?

[Satya Nadella @satyanadella]

Read more about our discovery, and why it matters, here: https://t.co/fzeVX6G95w