One of the biggest narratives, not only in crypto, is AI/ML.
I think I found the next Unicorn in the making, combining AI with blockchain to create the largest neural network: $TAO.
Although already a midcap, $TAO could still do a #x100 from here.
A🧵
1) Problem
Today AI is inefficient, non-transparent and incredibly expensive.
The AI models are developed in centralized data silo’s by the likes of Google, IBM, OpenAI and Microsoft.
Google alone spends 75% of their electrical cost on machine learning. The usage of a machine learning model like GPT3 costs $12 Million per hour!🔥💵
Small players don’t have access to, nor the money for these operations, putting the power in the hands of a few, not the many.
Furthermore, a new model (GPT3) has to relearn everything that the old model (GPT2) already learned.👀
This relearning process occurs very often because AI research doubles every year. This makes the AI sector extremely inefficient.
2) Use case
@bittensor_ is an open-source protocol that powers a scalable, globally-distributed, decentralised neural network focused on AI/ML.
The interesting thing here is that the goal is to create a network on which information compounds, which means a new model doesn’t have to relearn everything a previous version of the same model already learned.
Furthermore, when using the bittensor network there is also a value transfer from other models that don’t exist in a centralized AI silo.
The new model is basically learning from all the models and their data available in the neural network.
One of the Co-founders, Jacob Steeves, called it ‘a continues machine learning library’.
This library is accessible for everyone in a truly decentralized manner and will accelerate the adoption of AI.
3) Consensus mechanism
The consensus mechanism of $TAO can be best explained by following the same path that the data follows when added to the network. These 4⃣ steps involve different parties with different roles in the process.
Lets dive in🏊♂️
1⃣ A company, that producing knowledge in the form of AI/ML models, contributes to the network by uploading this data.
If the data is valuable, they will be rewarded in $TAO.
2⃣ Various AI companies will validate the quality of this uploaded AI/ML models.
They validate it by using the models to solve specific problems. Once they reach consensus, they will get rewarded with TAO tokens.
Who gets rewarded in these first two steps is based on information significance measurement, it is like a matrix with contributors and validators getting a share of the rewards based on their "usefullness" ranking.
This first part of coming to consensus happens like smart contracts on a L2 and only when consensus is reached the information is added to the L1 PoS blockchain of $TAO.
3⃣ The third step is executed by the validators of the PoS blockchain, validating the blocks of the "L1" PoS blockchain.
This party doesn’t need any knowledge about AI. But to be eligible to become a validator, you need 1024 $TAO and computing power to validate the blocks.
4⃣ After the AI models with value are added to the blockchain, this data is ready to be utilized by the end consumers, mainly AI companies running new models.
The capacity on the network is owned by the $TAO holders and they can utilize it to fulfill their needs.
So, accessing the @bittensor_ network can be done in two ways; The company has to hold $TAO to gain access or the company has to pay someone with $TAO, that is not using its full capacity on the network, to gain access.
If the network reaches its full potential, I can see $TAO wars happening just like what happened with $CRV in the curve wars 🔥
The beautifull thing with BitTensor is that not only big companies, like IBM, Google or Microsoft, but also smaller ones can use this sophisticated library full of interesting AI/ML models and data for their own projects.
4) Team
Jacob Steeves and Ala Shaabana CO-founded BitTensor.
They both have great academic backgrounds and working experience in the sector, working for Google and the likes.
The next 💎 I am adding to my long-term portfolio is $DNX
The world’s first decentralised neuromorphic supercomputing platform, @dynexcoin
Wanna know why this could be a generational opportunity🔥
A 🧵
1) Use case
$DNX is a next-gen platform that bundles neuromorphic computing, creating a neuromorphic supercomputer that is capable of performing computations at unprecedented speed and efficiency.
With this, $DNX will become the base layer for two things.
1⃣ $DNX will become a L1 where applications and algorithms can be built on top of their consensus mechanism.
2⃣A marketplace for clients/customers that want to utilize the computing power and pay for it in $DNX.
Absolutely love the Decentralized Autonomous Brand concept and the team has been building nonstop.
Some very interesting fundamentals and recent updates!
Let’s dive in, a 🧵
1) Decentralized Autonomous Brand (DAB) concept
In this new exciting business model the token holders have direct control over the real-life product through voting. This includes, the use of funds, product development, product design and product distribution.
Basically everything can be decided by the token holders through proposals and voting.
This concept truly gives the holders a stake in the company 🎯
If you missed #Bitcoin early on, don’t miss this next generation PoW blockchain that solves the shortfalls of $BTC. I am talking about @KaspaCurrency, I’ll show you why I am so bullish.
A $KAS 🧵
1) Problem
Satoshi’s vision of #Bitcoin was that it became a peer-to-peer electronic cash system, but bitcoin turned out to be a store of value, or e-gold. This is an enormous achievement but leaves some room for improvement.
$KAS is aiming to fill this gap. Lets dive in🧐
2) Use case
$KAS is in line with Satoshi’s vision and the fastest PoW coin (Nakamoto consensus) on the planet. It’s aiming to become a L1, like $ETH, $BNB, $ADA, $SOL and $MATIC. Except it will solve the blockchain trilemma, something I have not seen a PoW blockchain do before.