Mikey

[Mikey @0xMkzys]

This Bullrun is shit thanks to all these scam KOLs who support these bullshit memes or AI’s with no tech or future. This is why $ALCH @alchemistAIapp and $Chaos @divinediarrhea who actually have tech and a great dev/team get less hype. People are investing is litteral crap! and losing all their money. Invest in real tech, invest in something you believe and stop swing trading listening to these loser KOLs who just want a quick bag and then sell without letting their followers know. If you don’t have conviction, you will lose. DYOR

[Mikey @0xMkzys]

@hwailoveyou @VALORANT You must be our reyna lol

[Tsotchke Corporation @tsotchkecorp]

Today we were able to run a Quantum Gate Operations performance comparison.

Python has extremely efficient memory cleanup, so it sets a high bar for us. We benchmark against TensorFlow because it’s a very good library and outperforming means our QLLM will do everything we say it will.

[Tsotchke Corporation @tsotchkecorp]

So our library outperforms, what does it mean? It means we’ll be able to offer an LLM that will be superior on all fronts.

[Tsotchke Corporation @tsotchkecorp]

A very thorough thread on our Tensor Library.

Eli and many others have now run our open source code on their own computers yielding the same results we’ve marketed. This will keep happening.

Builders build.

[Eli5DeFi @Eli5defi]

The race for decentralized quantum supremacy has been unfolded.

Introducing Quantum Geometric Tensor (QGT) by @tsotchkecoin.

Want to know what it is and how it might reshape the future as we know?

We'll explain it simply in an easy-to-understand way.

Let's dive in ⚛️

...

— 📌 Before We Move On

We encourage you to check out our previous post explaining why Tsotchke is a one-of-a-kind project and why no other project comes close:

➡️ Tsotchke Overview
https://t.co/NtioXD6nYm

➡️ QRNG
https://t.co/4DDPWbvK6h

...

— 📌 WTH is QGT?

QGT is essentially a tensor library (TL), a machine learning framework for manipulating multi-dimensional data structures.

The most used TL is Google's TensorFlow. It supports complex numerical computations, aiding in machine learning and AI development.

Unlike conventional TLs, Tsotchke's QGT primarily utilizes principles from quantum mechanics, focusing on Quantum Geometric Learning and Algebraic Topology.

While I won't delve into the nuances, this approach aids machines in effectively dealing with data that's complex and multidimensional more accurately.

It allows for analyzing intricate structures, networks, and curved data spaces allowing machine learning to learn with:

🔹 Higher efficiency
🔹 Better accuracy
🔹 Less computational demand compared to conventional TLs.
🔹 Large-scale ML training supports

...

— 📌 Can Anyone Use It?

Absolutely.

@tsotchke QGT works great on regular computers. @BearStorm86 even ran it successfully on a 2009 Mac and got impressive results.

https://t.co/KYuN5JWU6u

Tsotchke's QGT provides advanced features to optimize and enhance AI training:

🔹 Aggressive algorithm optimization
🔹 Adaptive memory and efficiency improvements
🔹 Distributed training with multi-GPU support
🔹 Advanced hardware utilization through hybrid classical-quantum optimization

These features boost system performance, enabling faster training and efficient resource use, optimizing computational output.

Enhanced scalability manages increasing workloads and data, while robust error management ensures reliability by promptly addressing issues.

...

— 📌 Quantum Natives Hardware Support

As quantum computing advances, QGT also supports quantum hardware systems natively.

It handles different quantum hardware challenges by using special methods that improve speed and performance:

🔹 Hardware-native operations
🔹 Geometric protection
🔹 Resource-efficient methodologies

These methods help overcome resource limits and integration issues, resulted in superior computational outcomes.

When used with quantum computers, a special process further optimizes the system. This approach dynamically improves circuit complexity, gate efficiency, and overall computational resources.

Currently, QGT supports quantum systems from IBM, Rigetti, and D-Wave. More hardware support is expected as the quantum computing field continues to grow rapidly.

...

— 📌 How it Perform?

Based on the benchmark shared using Google's TensorFlow as reference baseline they achieved total execution time 0.169 ms for QGT and 11.53 ms for TensorFlow.

That's ~68.2x improvement compared to the baseline!

Find more benchmark test details here ⤵️
https://t.co/ly0c8Phupg

P.S.: I tried to run the test myself and got impressive 0.19 ms utilizing Apple M4 Chip, I suggest for you to run it by yourself using your hardware to check and verify.

https://t.co/nlBNgDGcud

...

— 📌 Wrap-Up

Tsotchke's QGT is already a robust and fully realized system, boasting an impressive codebase of over 100,000 lines.

Even in its pre-release state, the architecture demonstrates remarkable completeness and functionality. We can anticipates that future optimizations will further elevate its already exceptional performance.

The system definitively outperforms TensorFlow across critical benchmarks, seamlessly bridging classical and quantum computing paradigms.

This breakthrough positions QGT as a pioneering force in open-source innovation, potentially marking a transformative moment for decentralized quantum computing that could reshape the technological landscape.

[KOKO @Bayc364]

Today @tsotchke released tech that can revolutionize the world and is at 30m mc

Undervalued is an understatement

[Tsotchke Corporation @tsotchkecorp]

tensor mog

[Tsotchke Corporation @tsotchkecorp]

Quantum Geometric Tensor initialized successfully ✅

[Tsotchke Corporation @tsotchkecorp]

https://t.co/FZhb9p2N7L

[Tsotchke Corporation @tsotchkecorp]

coming soon to your computer

[Unipcs (aka 'Bonk Guy') 🎒 @theunipcs]

it's interesting watching people do a lot of mental gymnastics to paint President Donald Trump's launch of $TRUMP as bearish for memecoins and crypto

make no mistake:

IT IS NOT

this is akin to the 2021 GameStop moment, where meme stocks like $GME experienced an insane, retail-fueled mania for weeks and sucked liquidity out of everything

the Gamestock pump and squeeze started in early January and resulted in $GME peaking at $483 per share on January 28—an impressive 2,300% pump in one month

the media, along with almost everyone else, made it seem as if the GME movement would collapse the markets, with talking heads claiming it was bearish for crypto

yet $DOGE began its explosive rally and pumped 1,000% in the span of 24 hours—from January 28-29—exactly a day after GME topped

$BTC also made a new ATH of $40,000 in the same January and went on to hit $64,000 in April

i expect $TRUMP to play out in a similar same way

BILLIONS of people who have never heard the term 'memecoin' will see every TV channel and news outlet talking about how the President of the United States launched his own memecoin, which rocketed to tens of billions of dollars in market cap within hours

i'm struggling to wrap my head around how anyone could consider this a bearish event

many of these people will come on-chain to buy their very first memecoin and a significant portion of them will enter the rabbit hole of crypto and memecoins for the very first time

of course, the overwhelming majority of them will use Solana

so this is incredibly bullish for $SOL

it is also bullish for $BONK as the main memecoin and mascot of the Solana blockchain

but it is just as bullish for all of our other memecoins

this short-term pullback on memecoins is worth buying IMO

i think $TRUMP should run a bit more and capture mindshare/liquidity

then it should be party time for the rest of our memecoins as an army of retail investors starts looking for what to bid on shortly afterward

[JoshXT @JoshXT]

I've spent most of my life without money or in debt. Building open source with an MIT license means you're doing it for the world.

[Eli5DeFi @Eli5defi]

The dream of truly powerful quantum computing feels like it's still decades in the making.

Even NVIDIA's CEO, Jensen Huang, agrees.

But what if a hybrid alternative could revolutionize the landscape sooner and bring the products on the consumer-level?

@tsotchkecoin is aiming for this by integrating spin-based quantum mechanics with a semi-classical computing approach.

This isn't just another vaporware product—it might be the dawn of a new era that will reshape the fabric of society.

Let's dive in 🧵

...

— 🛑 Before We Move On

For a quick primer on classical vs. quantum computing (QC), check our previous post here:

https://t.co/PUph6hiHXk

...

— 📌 Bottleneck in QC

As of now, QC is largely seen as impractical due to a range of formidable obstacles.

A primary challenge is the current state of quantum hardware, plagued by high error rates, limited coherence times, and poor qubit connectivity.

Quantum systems are exceedingly vulnerable to noise and errors from environmental disturbances, which can lead to an accumulation of mistakes and a decline in computational quality.

Furthermore, many quantum algorithms remain inefficient or impractical for real-world issues, creating a significant gap between theoretical potential and practical application.

These constraints pose significant hurdles in scaling quantum systems for real-world use.

...

— 📌 What is Tsotchke?

Tsotchke is a DeSci project focused on developing scalable quantum computational architectures and algorithms for the consumer market.

The ultimate goal of Tsotchke is to bring QC to consumers without requiring specialized, large-scale equipment such as cryogenic systems to maintain stability - think about Raspberry Pi version for QC.

The brilliance of Tsotchke lies in its integration of classical and quantum computing, enabling current classical machines to leverage hybrid algorithms and synergize with QC once available.

...

— 📌 How it Works

Tsotchke's approach to quantum computing mainly focuses on using silicon for quantum processing, specifically through:

🔹 Controlling quantum spin states
🔹 Integrating neuromorphic architecture
🔹 Using advanced entropy modeling

This method uses microwave pulses to carefully control the spin of electrons and techniques like spin resonance for manipulating quantum states.

It achieves more than 99% accuracy and maintains stability for milliseconds at room temperature.

On the other hand, neuromorphic computing architectures enable faster and more flexible machine learning directly on quantum hardware.

Tsotchke leverages established semiconductor production techniques, particularly proprietary modular CMOS (Complementary Metal-Oxide Semiconductor) processes.

This approach presents a cost-effective solution that is easily scalable and compatible with existing manufacturing frameworks, enabling widespread production and utilization.

...

— 📌 Practical Implementations

The practical implementations of Tsotchke QC focus primarily on two main areas:

🔹 Quantum Random Value Generation/ QRNG

QRNG generates true entropy for high-quality randomness, applicable to:

• Cryptographic key generation
• Statistical simulations (e.g., Monte Carlo)
• Optimization of AI modeling and training processes
• Advanced modeling that requires reliable randomness

To understand about QRNG and Entropy, please check here: https://t.co/4DDPWbvK6h

🔹 Quantum-Enhanced Language Model / qLLM

qLLM use quantum-classical hybrid processing to enhance traditional language models such as:

• Improved text generation with better probability sampling for coherent outputs.
• Enhanced pattern recognition for natural language understanding.
• Faster, accurate model training via quantum acceleration and optimized parameters.

...

— 📌 So, When?

Tsotchke QC devices will be developed in three main phases:

🔹 Phase I (Foundations)

Establish open-source core prototype of QRNG, Quantum-based Tensor Library, qLLM and QC processors.

🔹 Phase 2 (Advanced Developments)

Enhance and optimizing QC processors, scaling the architecture, integration of neuromorphic computing, and launch commercial products.

🔹 Phase 3 (Universal Quantum Computing/ UQC)

Achieve universal quantum computing, fully integrate neuromorphic technology, and develop distributed quantum computing with advanced algorithms, while expanding product presence.

...

— 📌 Wrap-Up

The field of quantum computing is new and developing quickly, but it is still in the early stages, so the conversation around it will reflect that. Right now, I won’t predict the future and will focus on the first phase of Tsotchke.

So far, Tsotchke has launched and made the qRNG open-source, qRNG-based website (soft launch) and it will soon release a quantum-based tensor library (TL).

All of these codes are open-source and compatible with existing classical computing, facilitating its adoption.

The last preview of the Tensor Library created a huge buzz online because it offers significant improvements over TensorFlow.

https://t.co/Se2lvVPKPZ

This has drawn a lot of attention, and many people are skeptical about whether the results are valid and reproducible.

Once the TL is publicly available, we can test it. If the improvement matches the initial preview, it will mark a new beginning for everything.

Be ready, Anon. 👀

[evee @evee0x]

#tsotchke + $tetsuo = Future

Keep building ,

[Tsotchke Corporation @tsotchkecorp]

You can purchase Tsotchke on MEXC, Moonshot, OXFun, Bitmart, and now CoinEx.

The marathon continues.

[Robert Scoble @Scobleizer]

CES report #23: Don’t push the robot!

[Tsotchke Corporation @tsotchkecorp]

The future is what we make it, so let’s make it what we want.

[Mikey @0xMkzys]

👀

[Tsotchke Corporation @tsotchkecorp]

This is your last chance. After this, there is no turning back.