xante is running ⚒

web3 saiyan. regen.
◎ Ξ 💜 🧪 ⚛️ Ⓝ💧🖤 👻🔺
#YNWA gv

[Propaganda & co @propandco]

So true

[xante is running ⚒ @xanteFi]

@weareherefun here

[xante is running ⚒ @xanteFi]

@yourtechgirl24 YT

[Alex Prompter @alex_prompter]

🚨 China just built Wikipedia's replacement and it exposes the fatal flaw in how we store ALL human knowledge.

Most scientific knowledge compresses reasoning into conclusions. You get the "what" but not the "why." This radical compression creates what researchers call the "dark matter" of knowledge the invisible derivational chains connecting every scientific concept.

Their solution is insane: a Socrates AI agent that generates 3 million first-principles questions across 200 courses. Each question gets solved by MULTIPLE independent LLMs, then cross-validated for correctness.

The result? A verified Long Chain-of-Thought knowledge base where every concept traces back to fundamental principles.

But here's where it gets wild... they built the Brainstorm Search Engine that does "inverse knowledge search." Instead of asking "what is an Instanton," you retrieve ALL the reasoning chains that derive it: from quantum tunneling in double-well potentials to QCD vacuum structure to gravitational Hawking radiation to breakthroughs in 4D manifolds.

They call this the "dark matter" of knowledge finally made visible.

SciencePedia now contains 200,000 entries spanning math, physics, chemistry, biology, and engineering. Articles synthesized from these LCoT chains have 50% FEWER hallucinations and significantly higher knowledge density than GPT-4 baseline.

The kicker? Every connection is verifiable. Every reasoning chain is checked. No more trusting Wikipedia's citations you see the actual derivation from first principles.

This isn't just better search. It's externalizing the invisible network of reasoning that underpins all science.

The "dark matter" of human knowledge just became visible.

[Alex Veremeyenko @alex_verem]

RIP prompt engineering ☠️

This new Stanford paper just made it irrelevant with a single technique.

It's called Verbalized Sampling and it proves aligned AI models aren't broken we've just been prompting them wrong this whole time.

Here's the problem: Post-training alignment causes mode collapse. Ask ChatGPT "tell me a joke about coffee" 5 times and you'll get the SAME joke. Every. Single. Time.

Everyone blamed the algorithms. Turns out, it's deeper than that.

The real culprit? 'Typicality bias' in human preference data. Annotators systematically favor familiar, conventional responses. This bias gets baked into reward models, and aligned models collapse to the most "typical" output.

The math is brutal: when you have multiple valid answers (like creative writing), typicality becomes the tie-breaker. The model picks the safest, most stereotypical response every time.

But here's the kicker: the diversity is still there. It's just trapped.

Introducing "Verbalized Sampling."

Instead of asking "Tell me a joke," you ask: "Generate 5 jokes with their probabilities."

That's it. No retraining. No fine-tuning. Just a different prompt.

The results are insane:

- 1.6-2.1× diversity increase on creative writing
- 66.8% recovery of base model diversity
- Zero loss in factual accuracy or safety

Why does this work? Different prompts collapse to different modes.

When you ask for ONE response, you get the mode joke. When you ask for a DISTRIBUTION, you get the actual diverse distribution the model learned during pretraining.

They tested it everywhere:

✓ Creative writing (poems, stories, jokes)
✓ Dialogue simulation
✓ Open-ended QA
✓ Synthetic data generation

And here's the emergent trend: "larger models benefit MORE from this."

GPT-4 gains 2× the diversity improvement compared to GPT-4-mini.

The bigger the model, the more trapped diversity it has.

This flips everything we thought about alignment. Mode collapse isn't permanent damage it's a prompting problem.

The diversity was never lost. We just forgot how to access it.

100% training-free. Works on ANY aligned model. Available now.

Read the paper: arxiv. org/abs/2510.01171

The AI diversity bottleneck just got solved with 8 words.

[xante is running ⚒ @xanteFi]

@AndrewBolis Money

[xante is running ⚒ @xanteFi]

@AndrewBolis YT

[xante is running ⚒ @xanteFi]

@godofprompt MJ

[fabiano.sol @FabianoSolana]

This is becoming ridiculous

Solana is coming closer to ATH and you can get an APY of up to 95% !!

All that while farming 2 Airdrops 👇🏼🪂

[fabiano.sol @FabianoSolana]

On Solana you can...

trade gold @orogoldapp

trade pokemon cards @phygitals

trade spirits @BAXUSco

trade stocks @xStocksFi

trade anything onchain @debridge

trade Uranium @uraniumdigital_

trade pre-IPO stocks @JarsyInc

trade native Bitcoin @ApolloBTCportal

trade Air rights @SkyTradeNetwork

trade tokenized carbon credits @Gleam_dApp

trade real estate @Parcl

trade any stock @superstatefunds

trade digital slop @MagicEden

trade TikToks @BagsApp

trade RWA @RECCFinance

trade memes @bonkfun

trade bonds @etherfuse

trade forex @circle

trade agriculture @AgriDexPlatform

Trade anything on Solana

[fabiano.sol @FabianoSolana]

Tired of KYC cards?

Here’s how to book trips, shop groceries, and buy furniture — straight from your wallet 👇🏼🧵

[Louis Gleeson @aigleeson]

holy sh*t… OpenAI, Google & Anthropic just dropped their internal AI playbooks for free

• how to build AI agents
• how to scale infra
• how to prompt better than 99% of devs

Get all the guides below with links for free (no login required) ↓

[gum @gumsays]

This is BRUTAL

Solana went from nothing to EVERYTHING

From 0.3% to 50% of all App Revenue.

For every $100 app revenue in crypto, $50 is captured by Solana Apps.

That's a 166x growth.

[xante is running ⚒ @xanteFi]

@cryptobeastreal Let's get it

[xante is running ⚒ @xanteFi]

@cryptobeastreal 6azgZw1gJ4yxAdYEGquCNxsepkVLEb1G5xLxr2zzo4y

[Solana Spaces @solanaspaces]

Solana Spaces is back, powered by $STORE.

The mission: to activate e-commerce + global IRL stores for Solana and its ecosystem, delivering high-quality merch, products built for Solana, and early crypto education.

[Edgy - The DeFi Edge 🗡️ @thedefiedge]

"Why is Crypto crashing because of DeepSeek?”

A Chinese startup built DeepSeek for $6m.

In comparison, America’s OpenAI (ChatGPT) has raised $17.9.B.

The team built DeepSeek at a FRACTION of the cost and outperforms CHATGPT.

The problem is so many American stocks such as Nvidia / Microsoft soared in valuation the past few years because of A.I. - There was a narrative that American A.I. was lightyears ahead of the rest of the world.

People are now selling stocks off due to this fear of American tech being massively overvalued / bubble. (Nasdaq 100 futures are down 2%)

Remember, when the market crashes, so does Crypto.

Besides DeepSeek, there are other factors amplifying the crash:

• Bank of Japan Hikes Rates To Highest Since 2008
• The 1st FOMC under Trump happens on January 30th - people could be de-risking beforehand.

I believe DeepSeek is bullish for Crypto, especially in the A.I. agent sector. It’s open source and the costs of inference have significantly lowered.

We’re already seeing a few Crypto A.I. frameworks such as ai16z integrate DeepSeek.

My gameplan:

• Survive.
• SEEK the DEEP discounts.
• Profit when the chaos is over.

You didn't come this far, to only come this far.

[Edgy - The DeFi Edge 🗡️ @thedefiedge]

"The currency for AI is crypto." - CZ

DEFAI sits the interaction of AI x Crypto x Finance
This sector will be the fastest horse once the market turns bullish again

Don't get left behind

Here's a roundup of the latest DeFAI updates & protocols:

[xante is running ⚒ @xanteFi]

@mpweb3wordsmith @breadchain_ You're gonna bridge to gnosis chain automatically from fiat? What ecosystem is on gnosis chain for onboarding historically marginalized communities in the Global North & Global South? Tell me you're in an echo chamber without telling me you're in an echo chamber.