AI is the popular industry narrative but does it last?

Fundamentally AI and blockchain are very different. Blockchain utilizes distributed computing whereas AI requires computational power. In blockchain every node runs calculations to ensure a block is valid, whereas AI utilizes resources to train neural nets based on a variety of datasets.

For example, say you want AI to help you trade. ... More

Centralized machine learning is highly inefficient and costly to businesses. TAO are creating a decentralized neural network that will develop and learn incrementally from itself over the years to create an all-knowledge and power neural network.

The $TAO network consists of two types of nodes: Servers and Validators. Validators prompt Servers for information and assess the value of their... More

They say Bitcoin has more computing power than the top 500 supercomputers combined. Bittensor aims to build a similarly powerful computer network to run publicly owned AI that could rival existing privately held AI.

Bittensor is an open network that allows anyone to contribute computing power. AI developers can deploy their models which can share data and learn from other models on the network.... More

Bittensor has a decent team behind it. According to LinkedIn, there are 14 people working for it. A few have Ph.D.s in Physics and AI. Most of the team have Computer Science, AI, and Engineering backgrounds and experiences.

The co-founders of Bittensor are Jacob Steeves and Ala Shaabana.

Jacob Steeves is the CEO and co-founder of Bittensor. He has a background in machine learning research and founded Bittensor to decentralize AI. He also worked for Google for a few years.

Ala Shaabana is the COO and co-founder of Bittensor. He has a Ph.D. in machine learning.

https://www.linkedin.com/in/jacob-robert-steeves-7b0629b8/ https://www.linkedin.com/in/ashaabana/

A friend of mine just started working at BitTensor. Somehow I had not seen previous reviews until now. I'm usually very skeptical about AI on blockchain most of the time but BitTensor does it in a very interesting way. One of the most used framework to create neural networks is TensorFlow from Google. With BitTensor, you can deploy your existing AI model on the blockchain without having to... More

BitTensor has a pretty strong social media following, as follows:

Twitter - 37.3k Followers Telegram - 2.5k members, 222 online Medium - 194 followers (even with no posts!) LinkedIn - 4.1k followers Youtube - 1.3k Subscribers, 2 videos Discord - 12.2k Members, 1,3k online

They seem to be the most active on Twitter (or is it X now?), constantly engaging and updating their socials on latest... More

Challenges such as centralization, scalability issues, adoption problems, and power consumption lie ahead.

The suggestion is to employ a market approach wherein machines assess each other's intelligence and assign rankings. These rankings are then recorded on a digital ledger, and high-ranking machines are rewarded. The network consists of two layers: the Blockchain layer, responsible for... More

I wished that the BitTensor team would be available to see on their website, as they are an extremely talented team, and it would be great to always find out more about their team. Looking at the Academia paper, Whitepaper as well as comparing with LinkedIn, I could only find the following (4/7):

Jacob Steeves - https://www.linkedin.com/in/jacob-robert-steeves-7b0629b8/ Ala Shaabana -... More

I was only able to find the Tokenomics of BitTensor via their 'TaoStats' at the bottom of their site.

Before being on Finney network, they used to be called Kusangi network in 2021, before being migrated over with all previously mined $TAO migrating as well.

They have a total supply of 21 million, that is pre-programmed (and unable to be changed). Every block is mined around 12 seconds, and... More

BitTensor is an ambitious decentralized machine learning network aiming to collaboratively advance AI through incentive structures. The project melds blockchain technology for handling consensus and payments with an AI layer where models interact to become more intelligent.

BitTensor's core innovation is a decentralized marketplace for assessing, valuing, and rewarding machine learning models... More

The project that turns all our computers into a massive AI learning network? The idea of that sounds kinda cool where anyone's and everyone's computers and gaming rigs can work together to crunch numbers and make the existing AI technology even smarter. That's where BitTensor comes into play, rewarding people for pitching in their unused computational power, providing a cost-effective alternative... More

Bitensor is a decentralized, blockchain-based machine learning network. The network is designed to train machine learning models collaboratively, and to reward participants in the network with TAO tokens. TAO tokens can be used to purchase access to the network's machine learning models, or to participate in the governance of the network.

Here are some of the key features of the Bitensor... More

The goal of this project is to create a decentralized network where different AI systems can cooperate and be rewarded for providing value to the overall network. It's like building a marketplace for AI. Participants can cooperatively share data to train each other's models. The more an AI contributes useful knowledge to the network, the more rewards it earns tracked on a blockchain ledger.... More

BitTensor's aim of building a mining network via machine learning models and rewarding participants for contributing to machine learning, via complexities and ranking information production (i.e rewards are paid based on how much the machine learning model fulfils the objectives set), and the blockchain layer communicates directly with the AI layer to build a consensus mechanism.

For a pretty... More

It is hard to make an external assessment of a project that is coming soon in everything which I was looking for on the website. So I had to resort to reading a very interesting if not complex set of documents that outlined their aims.

Building AI and machine learning probability algorithms on top of what seems to be probably correct filters to the AI learning models seems to be an interesting... More