Avatar Intelligence: The Next Stop in the Web3 World

Matrix AI Network
10 min readFeb 9, 2023

What is AvI (Avatar Intelligence)?

Thanks to technological advancement, AI can do more and more incredible things. As early as 2011, IBM’s supercomputer Watson defeated two of the best human players, Brad Rutter and Ken Jennings, in a trivia show called “Jeopardy!” In this competition, Watson scored higher than the scores of the two players combined.

Watson’s knowledge was not coded into its memory. Instead, it had educated itself by reading Wikipedia and several other encyclopedia websites (all natural language source materials). However, Watson didn’t need to read through all web pages as a human would. After reading one page, it might have already reached itsconclusion that, for instance, the probability of Argentina winning the World Cup is 36%. You might also read the same page and conclude the probability is 80% because you are better at reading comprehension. Watson, on the other hand, compensated for its disadvantage in reading by absorbing way more source materials. It has an excellent Bayesian inference system that could integrate all the indexed information to reach a more reasonable conclusion, which takes little time.

Bayesian inference systems have played a crucial role in the development of AI since. Whether it’s AlphaGo or ChatGPT, we can see a glimpse of Bayesian inference in them. These AI technologies have expanded our horizons, enabling virtual worlds such as Web3 and the Metaverse.

Today, when we talk about the Metaverse and Web3, one fact we cannot ignore is we are all carbon-based organisms and cannot live forever in a virtual world completely detached from reality. We need a way to exist in the virtual world for longer than our physical existence, or even indefinitely. There needs to be a solution that turns the virtual world depicted in the Matrix films into a reality, which brings us to AvI (Avatar Intelligence).

AvI stands for Avatar Intelligence. While traditional AI focuses on training algorithms to achieve abilities like those of humans, Avatar Intelligence aims to recreate the Matrix films by uploading our consciousness to the network or building a program to replicate the thought patterns of users. This means that each person will have a unique digital avatar in the Metaverse or Web3, which can perform various tasks independently under users’ authorization. This will be the ultimate use scenario for Web3.

Avatar Intelligence vs Mind Uploading

Before Matrix proposed the concept of Avatar Intelligence, another idea that is quite popular is Mind Uploading.

Mind uploading uses brain scanning and conjecturing to simulate the brain’s state in computers. The computer will simulate how the brain processes information and how the entire neuronal system works to generate a level of awareness like the human brain.

Problem One: Scanning

The first step is to recreate the interconnected state of all the neurons of the brain. To do this, the brain has to be sliced into pieces a million times thinner than a slice of orange. Information from the brain is stored in every nook and cranny of the physical connection among neurons. Their size, shape, and the number and location of the connections are all relevant to the information we are trying to retrieve from the brain. We have to obtain all these data to create a computer simulation of the whole brain’s neuronal state.

Cutting the brain carries high risk, and even if there are users who agree to have their brains sliced into pieces, it would be difficult to perfectly reassemble them back to their original state. Thus, it is difficult to imagine this technology being widely adopted.

Problem Two: Neuron Simulation

If we want to create a computer that operates like the human brain, it must be able to access all stored data in a short amount of time, which means the data have to be stored in RAM rather than on hard drives.

In our experiments, if we try to store data collected from lab mice in RAM, it would require a storage space 12.5 times that of the largest single-memory computer (a device built for storage rather than processing) in history. Not to mention that the human brain contains roughly 100 billion neurons, which is as many as the number of stars observable in our galaxy and a million times the number of neurons in a lab mouse’s brain. This difference is even wider when it comes to the number of connections, which is equivalent to how manygrains of sand there are in a one-kilometre long and two-metre deep sand beach.

To further complicate matters, we don’t even know how much information the human brain can store, not to mention what it would take to transfer such information to a computer. We need to transcode the information first and keep it in some kind of storage for computers to access. Any errors in this process would be fatal. If we don’t know how much information needs to be stored before the transfer process begins, we may use up all storage space before the transfer is finished so that the information sequence may become damaged and unusable. Furthermore, since this is the equivalence of uploading someone’s life, we must have at least two (if not three) backups. Otherwise, the consequences of losing such data could be catastrophic.

All this is to say that in the short term if we truly want our digital avatars created in a swift and convenient way to explore all the wonders of Web3 and the Metaverse, we must enlist the help of AI, and thus Avatar Intelligence.

Technical Path of Avatar Intelligence

In light of the difficulties of Mind Uploading, AI offers us a glimpse of hope in a new direction. Semantic Pointer Architecture Unified Network (Spaun) is a masterpiece by a team of theoretical neuroscientists from the University of Waterloo in Canada led by Chris Eliasmith. Although Spaun only contains 2.5 million virtual neurons, far fewer than the 86 billion in the human brain, it is capable of processing large amounts of information and performing simple arithmetic and basic reasoning. This provides a completely new solution to the fundamental problems of Mind Uploading. AI algorithms are similar to the human brain in that they are opaque boxes whose contents are totally unknown to us. However, we can train an AI software brain that will deliver the same reactions as the human brain would when stimulated by the same data input. In our current simulations, the resources required for such an AI model are far less compared to Mind Uploading.

In order to behave like a human, the software brain must also acquire basic human behavioural patterns, as well aspersonalities, memories, emotions, beliefs, attitudes and values. This can be achieved by creating a mind file and writing a mind algorithm. By sufficiently training the mind algorithm, we will get a user’s Avatar Intelligence.

Given what we’ve already achieved with AI, it’s only a matter of time before a brain simulation software will surpass the complexity of human brains in psychological, perceptive and spiritual aspects. In its ultimate form, Avatar Intelligence will consist of two core parts: one for data collection and one for data processing.

In MATRIX 3.0, the brainwave data of users will be collected, and a personalised dialogue assistant will be built using a pre-trained method based on the current semantic pointer architecture unified network, utilizing personalised sparse data. This is done by adopting an encoder-decoder framework and using a pre-trained language model to initialise the encoder and decoder. Property embedding is added in encoding to capture rich personalised features when modelling conversation history, and an attention routing mechanism is built in the decoder to integrate the target personalised properties into the decoding process.

Using multiple attention paths will enhance the training result. Each path will have a certain feature source, such as the target personality, chat history or previously decoded tokens. A dynamic weight predictor will be established to measure the output of each route so that each target feature’s contribution in the final output will be balanced.

The current semantic pointer architecture cannot simulate human emotions, but it has replicated many quirks of human behaviour, such as a tendency to only remember the beginning and the end of a list of things. With how fast technologies are developing, future iterations can definitely make the impossible possible.
scenarios, the emergence of AvI will play a very important role in the MATRIX ecosystem.
First of all, AvI requires a large amount of decentralized computing power to support it, which will bring widespread demand to MANTA. At the same time, AvI will generate a large amount of data, all of which will become important digital assets for further development of artificial intelligence on MATRIX. More importantly, the generation of these demands and values will bring huge demand to MAN, further enhancing its circulation and playing an invaluable role in the overall value enhancement of the MATRIX ecosystem.
AvI will become the fast train towards the movie “MATRIX”, leading all Web3 enthusiasts into the future!

AvI’s Use Scenario

AvI will revolutionise Web3 in the following ways.

The ‘Real’ DAO

True DAO will only be possible after the arrival of AvI. Yes, you heard that right.

DAO is short for decentralised autonomous organisation, sometimes also referred to as distributed autonomous organisation. It is an organisation based upon open and transparent computer codes and governed in a decentralised way where token holders get to make decisions.

The governance rules of DAO are often in the form of open-source software, and anyone can participate by either buying shares of a DAO or providing services. To a certain degree, a DAO can be viewed as a fully automatic robot that willcontinue to operate following predefined rules once everything is set up. It can also continuously maintain and upgrade itself to adapt to changing circumstances. Undoubtedly, DAO is a new form of organization native to Web3, and so farvarious types of DAO have been built. In a sense, the consensus mechanism of various public chains, including Matrix, can be seen as a type of DAO. However, our physical limitations prevent us from creating true Web3 DAO, as we cannot participate in every voting session. Nor can we check every transaction that is happening on-chain to vote against transactions that we wouldn’t approve.

AvI is the perfect solution to these problems. When we duplicate our personalities and thoughts onto AvI, it can monitor the entire network’s situation on our behalf, including every proposal, every transaction, as well as every on-chain contract and app. AvI can also make decisions and take actions based on our values. This is what the era of Web3 DAO will look like. The entire network will be managed and governed by a group of advanced AvI, which will be the foundation of a decentralized Web3 society.

The Real Metaverse

Despite all our longings for life in the Metaverse, as carbon-based organisms, we cannot stay in the Metaverse forever. How do we continue to create value in the Metaverse while we are offline? As the Metaverse is a far broader world than our real world, we need inhabitants to populate it. If people can’t be online 24/7, then much of the Metaverse would be underpopulated and a lot less fun. Moreover, since in the Metaverse information is exchanged at an unbelievable speed, limitations in human beings’ capacity for acquiring information may hinder the development of the Metaverse.

Although populating the Metaverse with bots may be a temporary solution, the Metaverse won’t be truly immersive until we have AvI. After a user logs out, their AvI can continue working and living in the Metaverse on their behalf. Since AI-powered AvI can process large amounts of information simultaneously, it will empower users to experience more things and live a better life in the Metaverse. Freed from the limitations of our physical bodies, we can dedicate ourselves to creating more value for the Metaverse.

Web3 Search Engine

Whether it’s Web3 or the Metaverse, the gigantic amounts of information available in the digital world will be beyond any human being’s ability to process. Without a way to ramp up our capacity for information gathering and processing, we can’t say we have tapped the full potential of Web3, nor the true creativity of our brains.

AvI provides the perfect solution. Since AvI is based on the personalities and preferences of each individual user, it can utilise Web3 computing power to help users to search through the overwhelming amounts of information for what they truly need.

AvI and the Matrix

Of course, besides the above, AvI will expand into many more use scenarios in the future. It will also play a major role in the Matrix ecosystem.

First of all, AvI requires large amounts of decentralized computing power to support its functions, which will createdemand for MANTA. Secondly, AvI will generate large quantities of data, all of which are valuable digital assets for the development of AI on Matrix. Finally, as the Matrix ecosystem becomes more valuable and more people use Matrix services, there will be greater demand for MAN, further increasing MAN’s liquidity, and this will in turn make the Matrix ecosystem more valuable.

AvI is the fast track for our eventual migration into the Matrix. Web3 users, fasten your seat belts!

The Matrix AI Network was founded in 2016. In 2023, we enter Matrix 3.0 blending neuroscience with our previous work to realize the vision of the Matrix films.


Website | GitHub | Twitter | YouTube

Telegram (Official) | Telegram (Masternodes)

Owen Tao (CEO) | Steve Deng (Chief AI Scientist) | Eric Choy (CMTO)



Matrix AI Network

The Matrix AI Network was founded in 2017. In 2023, we enter Matrix 3.0 blending neuroscience with our previous work to realize the vision of the Matrix films.