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
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— 📌 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
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— 📌 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.
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— 📌 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.
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— 📌 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
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— 📌 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.
We just pushed another hotfix for $sbot regarding our /scan mechanic!
now Solana contracts will link bubble maps when scanned.
More frequent updates soon to come 🍓
GM FAM ❤️❤️
🥳1st ANNIVERSARY WOHOO NFT🥳
Today is February 2, exactly one year ago @WohooNFTs was born 🥳🥳🥳
It has been a very beautiful journey in these last 365 days, some mistakes have been made and other great successes. In this year Wohoo NFT has formed a large and united family where everyone is excited to grow more and more in the Solana space
They do not hesitate to pass alpha so that we are all up to date. We are all learning how to print money every month
Lets gooo 🎉🎉Happy Anniversary to Wohoo NFT🎉🎉
It's time to blow everything up this year 🚀🚀
To recognize a project that is truly rewarding its holders with solid, consistent payouts, I’ve changed my pfp to @pioneerlegendio.
Another week, another awesome payout. Thanks to @Legacyzzzzz and @pioneerlegendio for the amazing work being done.
Special 3333 Collection .05 mint. Art by
@theHome113. Majority of mint funds used in investments streams. 50% profits generated goes to saga treasury forever.
@SagaMobileDAO see you tomorrow 😘
@theHome113@phantsocietynft@bam19221 @frenchy1478 Every single one is awesome. Thanks so much for working on these. Hope you will be creating the next 50.
Another week, more passive income, if your not making money while you sleep your just another slave to the system @phantsocietynft Making money is the Utility
GM Fam, Happy Day ❤️
Wohoo NFT It's burning, a lot of fire and new members very inspired to make money and grow all together in this space🚀🚀
Our time is here💸
Big shoutout for some of our members 🔥🔥