Stark ./🕐

Interested in algorithms.
[email protected]

[Stark ./🕐 @christ0x33]

> Quantum computing is often associated with cryptography, which makes the field feel abstract and complex to most people.

For the past 2 years, I have been experimenting with quantum annealing as a builder, exploring how quantum optimization can solve real world problems.

Through @dwavequantum’s cloud based quantum annealers, I worked on something completely different: optimizing chemical mixtures and formulations.

Chemical formulation is a complex optimization challenge. Thousands of possible ingredient combinations must balance factors like stability, skin compatibility, viscosity, cost, performance, and safety.

The goal is to translate product requirements into measurable objectives and constraints: maximize performance, stability, and user experience while minimizing cost, irritation risk, safety and formulation complexity.

I converted the formulation challenge into a mathematical QUBO (Quadratic Unconstrained Binary Optimization) model, then to an Ising model allowing the D-Wave annealer to explore the solution space and identify high quality combinations that traditional trial and error approaches may take significantly longer(may take years) to discover.

This is a practical example of how quantum optimization can be applied to real world industrial problems.

Companies with in house R&D like @LOrealParisUSA, @Unilever, @ProcterGamble, @Beiersdorf_AG, @KAO_Corp, and @SHISEIDO_corp could leverage quantum annealing to accelerate formulation research, optimize ingredient selection, and develop better performing, more sustainable skincare products.

@quipnetwork @dac_chain @Alan_Baratz @Quantum_Murray
@robdthomas
@scott_crowder
⚛️🧪 #QuantumComputing #DWave #Optimization

[Pendle @pendle_fi]

tokenized stock dividends

[Stark ./🕐 @christ0x33]

@binance Agent OS enables real time analysis and execution for your agents.
Watch how our trading Agents operate in a single system to make immutable machine readable decisions and actions.
AIFI accountability starts by seeing what refusals the agents dealt.
https://t.co/Fr5zQqwzxW

[Stark ./🕐 @christ0x33]

Most agent demos show what the agent did.
Zcastor(4 Agents) shows what it refused and anchors it onchain before the outcome is known.
Reads live market state through @Binance Agent OS. 21 gates decide. Most
signals are declined, each with a named reason and the policy hash in force.

The session's decisions become one document, hashed and anchored.
Anyone verifies it with sha256sum and a chain lookup. No API from us, no
credentials, no involvement.
an onchain machine readable accountability layer for the agents.

https://t.co/w6CecdIGWA
#BinanceAgentOS

[Stark ./🕐 @christ0x33]

to tokenize a real-world Asset?
first, verify the asset.
property deeds. contracts. financial statements. valuations. ownership records.
turn the documents into machine readable data - check @docugami's https://t.co/feTt1ca8D9 - , verify the claims and create a cryptographic record of the PROOF.
then tokenize it.

[Stark ./🕐 @christ0x33]

@binji_x Financial LEGO pieces that can be traded as perpetual futures.

[wildcryptox 🎯📈🕉️ @wildcryptox]

mantra:native : x50 👀

Trade with Responsibility ⚖️

https://t.co/5W6wjH0d8R

@MANTRA_Chain ⛓️
@dogthesunny

https://t.co/vyTvsFqLYX

[Inveniam @InveniamIO]

Buying an AI tool does not make your data AI-ready.

A model can read a lease. It cannot tell you whether the lease it read is the executed version, who signed it, or what changed since the last one. That is not a model problem. It is a provenance problem.

AI-ready means the document, its source, its history and its accountable parties travel together. That is what @docugami, powered by Inveniam produces, and what @NVNM_Chain makes checkable by anyone.

[MANTRA | The EVM L1 for RWAs @MANTRA_Chain]

The tokenization supercycle.

[Stark ./🕐 @christ0x33]

This is the @rwasummit feedback that got me thinking about the demand side of RWAs and how @InveniamIO 's thesis provides the infrastructure solution for verifiable data to Investors.

The point about institutions all saying the same thing "tokenize more assets" all while the BUY side remains the harder question is worth thinking about.

https://t.co/05wVsZZj6z

[Stark ./🕐 @christ0x33]

@rwasummit 2026 in Brooklyn concluded last week.

Everyone wants to tokenize assets.
Institutions: “We need to tokenize more assets.”
Everyone: “Yes, more assets should be tokenized.”
Then: who is actually buying them?

RWA needs a stronger buy side.

@NVNM_Chain has built the infrastructure for AI agents to consume machine readable PROOF from financial and document data(checkout https://t.co/feTt1ca8D9), make accountable decisions, and eventually participate in transactions with provenance attached to those decisions.

Providing "receipts" for Agentic Finance (AiFi).

And on the market access side, MF Markets provides access and liquidity through perpetual futures tied to the RWAs.
Tokenization creates the supply.
AiFi builds the demand. $MANTRA

MF Markets: https://t.co/NX6Nn9Jik1

[Stark ./🕐 @christ0x33]

Gm y'all

Rise and Grind

[Stark ./🕐 @christ0x33]

what if you could invest in private real estate as easily as you buy public stocks?
Both RWAs but different classes.
private markets hold enormous value, but unlike public stocks, much of that market has historically been difficult for everyday investors to access.
the data is also proprietary and mostly in documents and pdfs, so it can’t simply be exposed to every AI agent or put onchain.

@InveniamIO Capital manages private market assets and is bringing this market into machine readable form through DGML.
@NVNM_Chain provides the anchoring layer, a Layer 2 on @MANTRA_Chain for proof, agent accountability and settlement in @mantraUSD.
the markets are then listed on MF Markets, giving investors access to RWAs onchain.

private assets → machine readable PROOF → onchain markets.

https://t.co/NX6Nn9Jik1

[Katie V Holmes 🕵‍♀️🕉️ @lady_in_crypto]

📢 MF Markets Update: Something is cooking on MF Markets.

I see the @NVNM_Chain logo and a $3.20B trade volume.

Did I just find another Alpha? 👀

I don't know, but I'll keep monitoring. 🫡🕉

In the meantime, it's not too late to get started.

🔗 https://t.co/H5i7hNnmFd

[Charly Wargnier ♨️ @DataChaz]

me using GPT-6 Astra to center a div

[Stark ./🕐 @christ0x33]

@NVNM_Chain AIFI, agents need receipts.

[Stark ./🕐 @christ0x33]

Most agent demos show what the agent did.
Zcastor(4 Agents) shows what it refused and anchors it onchain before the outcome is known.
Reads live market state through @Binance Agent OS. 21 gates decide. Most
signals are declined, each with a named reason and the policy hash in force.

The session's decisions become one document, hashed and anchored.
Anyone verifies it with sha256sum and a chain lookup. No API from us, no
credentials, no involvement.
an onchain machine readable accountability layer for the agents.

https://t.co/w6CecdIGWA
#BinanceAgentOS

[Binance @binance]

4 days left. $60,000 USDC up for grabs.

Build an AI agent with Agent OS, or connect your MCPs and trade.

Join the Binance Agent OS Mini Hackathon 👇
https://t.co/utaVepUwhh

[Stark ./🕐 @christ0x33]

Agents are moving from generating answers to taking actions.

ChatGPT and Claude can now trade crypto for you on Binance.

Binance has launched Agent OS, a platform that connects AI tools directly to its markets through the Model Context Protocol, letting agents act on your account with your permission.

That creates a new infrastructure requirement: PROOF.

@NVNM_Chain provides the layer where agent activity can be attested, recorded and verified connecting the information an agent uses to the actions it takes.

Agentic finance needs verifiable infrastructure.

That’s NVNM. $MANTRA

[NVNM Chain @NVNM_Chain]

AI Agentic finance creates a new infrastructure requirement: PROOF.