Matrix Ai Network

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                                                                                       Staking UI Improvement



Dear Matrixian,

With reference to our announcement on UI improvement of Staking/Unstaking published on 8 April, (https://www.matrix.io/blog/Staking_Unstaking_UI_Improvement_160.html), we are glad to share with the community that the relevant UI has been updated.

When you try to stake, you can select a duration or time limit for your fixed stake. Available options are, 30-Day, 90-Day, 180-Day and 360-Day. See below screen cap.




                                                        



When you try to use your web wallet to check the status of your staking, you can find the relevant staking duration too.



                                                        



We believe this will be more intuitive for users.

As always, MATRIX welcomes suggestions and insights. Please do submit them to https://docs.google.com/forms/d/e/1FAIpQLSfAioEUFqwYi_av9DbsT11KXqA0HDzWws8LcwDKnx79vLOb-Q/viewform




                                                            https://www.matrix.io/blog/Staking_UI_Improvement_169.html

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                                                                                                         MATRIX Fact Sheet 2



12.












Meet the AIRTIST

https://www.instagram.com/p/Ccd1gj-MqZZ/



13.























The internet, which has transformed into completely different phases since the day it came to our homes, has passed through which phases and what has changed in these phases.

One of the hottest topics of recent times.

https://www.instagram.com/p/CckVh1-okbb/



14.








MANAS (MATRIX AI Service Open Platform), the AI Service Platform built on MATRIX’s High-Performance Blockchain, is about to arrive.

https://www.instagram.com/p/Ccn7pVloh4_/



15.








Exciting waits for #AIRTIST.

https://www.instagram.com/p/Ccs2Dl4obRo/



16.








Guess our next tag on @coinmarketcap?

https://www.instagram.com/p/CcvvK4RISdP/



17.









Mobile man wallet with all features.

https://www.instagram.com/p/Ccx1rvvIoij/








                                                                            https://www.matrix.io/blog/MATRIX_Fact_Sheet_2_170.html

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                                                                                 The Past and Present of AI Art （1/2）




Let’s take a look at a work of art.











This is a work by Refik Anadol using machine learning to go through and sort out 1.7 million files. The interactive relationship of all their multidimensional data was actualized into an immersive media format. This experiment was done as part of a Google project called Artists and Machine Intelligence, which gathers artists and engineers together to explore the possibilities of machine intelligence. This new collaborative way of art creation could pioneer brand new use scenarios for AI systems.

When art meets big data, we are sure to witness the birth of new ways of artistic expression no one could ever dream of. Are technologies tools for artists, or are they part of the art? History might shed some light.

The Creative Power of AI

Despite all the hype about AI, it is still far from being capable of thinking and learning on its own as depicted in sci-fi novels. But in the past several decades, AI has already integrated into every aspect of our lives. For one reason or another, more and more artists have decided to incorporate AI into their works.

- Some like to try out the most futuristic technologies;

- Some experiment with AI to explore new ways to create art;

- Some believe that AI can greatly enhance their current workflow.

Can AI truly have creative power？

- Opinion One

Machines can’t truly possess creative power.

There is a stereotypical belief about creativity thinking that it is unique to human beings. In the Origins of Creativity, Edward Wilson proposed that creativity is born from an impulse. Machines are lesser than humans in terms of creativity, because machines don’t ever make mistakes. Even by introducing chance into AI, it won’t deviate much from the input value, provided that the program is running as it’s supposed to do. Humans, on the other hand, are totally different. After all, to err is human.

- Opinion Two

Whether AI can be creative actually depends on what we mean by creativity.

In Minds, Brains, and Programs, John Searle introduced a thought experiment: the Chinese Room. A native English speaker who doesn’t know Chinese at all sits in a room with only two windows. He has an English instruction manual with him in the room, as well as a bunch of written Chinese characters. Someone outside the room keeps passing in questions written in Chinese, and the guy in the room tries to arrange the Chinese characters in the room into an answer to give back, using the instruction manual for guidance.

John thinks that in the ideal situation the guy in the room can totally pass as a Chinese native, even though he doesn’t understand Chinese. In this thought experiment, the guy outside the room is like a programmer, and the guy inside is like a computer, while the manual is like a computer program.

Just as the guy in the room doesn’t have to truly understand Chinese, but only relies on the manual to complete tasks. Computers won’t truly understand human thoughts, but they might appear to humans as if they did.

Therefore, it’s actually pointless to require machines to be creative in a true philosophical sense. As long as machines can “fake” a semblance of that, it would make no difference.

If by creativity we mean the ability to constantly improve, then with adequate access to quality data, AI will be able to self-improve.

Twitter : https://twitter.com/MatrixAINetwork/status/1519224001595416578?s=20


Medium : https://matrixainetwork.medium.com/the-past-and-present-of-ai-art-1-2-1abb0ceeb6ff

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                                                                                      The Past and Present of AI Art (2/2)




A Brief History of AI Art

AI wasn’t born out of nothing in the 21st century. It grew from a number of roots.

3000 BC — the Talking Nodes of Quipu

Quipu is a method for keeping and passing information used by the Inca people in ancient times. Quipu uses nodes of different colors and materials. Sometimes there can be hundreds of nodes that were tied in different ways and at different heights to express differences in meaning. Quipu can not only record date, number and account balance but also serve as the medium for abstract thoughts and record the folklore and poetry of local cultures.









3000 BC - the Talking Nodes of Quipu

Quipu is a method for keeping and passing information used by the Inca people in ancient times. Quipu uses nodes of different colours and materials. Sometimes there can be hundreds of nodes that were tied in different ways and at different heights to express differences in meaning. Quipu can not only record date, number and account balance but also serve as the medium for abstract thoughts and record the folklore and poetry of local cultures.

Without resorting to an alphabetic writing system, Quipu can record large amounts of information with decent accuracy and flexibility. When nodes of different colours are added to make even more combinations possible, the potential is limitless.

1842 - Poetical Science

Analytical engines can execute mathematical calculation orders on punctured cards. In 1836, a portrait of Joseph Marie Jacquard, inventor of the first weaving machine, was woven using 24,000 punctured cards. In a sense, this portrait is the world’s first digital image.

In 1842, Ada Lovelace wrote the first computer program in history. Her friend Charles Babbage designed the very first system of algorithms for his analytical engine inventions.







The first published computer algorithms are Charles Babbage’s Analytical Engine Sketches (1842).

The way analytical engines weave algebraic patterns is just like how a weaving machine weaves flowers and leaves. Ada called this poetical science. Imagine if a computer can do more than computing. Can computers be used to make art? At a time when art and science are in two totally separate camps, her goal was to integrate the accuracy of science and the flexibility of art.







The basis of this belief is that our world is built upon mathematical laws. Here is an example:

Rose curve formula: ρ=a*sin(nθ), a being a fixed length, n being an integer. We can use this formula to draw a rose.







Mathematics holds the key to a lot of visually pleasing shapes and patterns. Since AI is based on mathematics, the beauty it can create is limitless.

1929 - A Machine That Could See

In 1929, Austrian engineer Gustav Tauschek invented the photoelectric reading machine.







This contraption has letter/number-shaped holes on a wheel. When light reflecting off a letter or number passes through a lens and hits the wheel, the wheel will receive the most amount of light if the shape of the letter/number matches that of the hole. When this happens, the photosensitive module on the wheel will send a signal, and the reading machine will register the correct letter or number.

The photoelectric machine is human beings’ first attempt at giving machines the power to recognize things. The method it adopted is called “template matching”, which is also the first practical recognition method.

What does it mean for humans to see through the eyes of a machine? And what does the machine actually see?

1950 - The Imitation Game

In 1943, the concept of an AI neural network was first raised. Combining algorithms and mathematics, it uses “threshold logic” to simulate the thought process of human beings. The gate to AI was thus pushed open.

Alan Turing developed the Turing test, also called the imitation game. This is a benchmark test used to show that machines can conduct intelligent behaviour indistinguishable from humans. Can machines think? Under the influence of Turing, many artists began designing similar “games” during this period of time.







                                                                                                                Turing Test







                                                                                                         Self-destructive Art

Jean Tinguely used one piano, two electric power engines, one balloon and over 20 bicycle wheels to make a chaotic structure. This contraption is capable of a series of unpredictable actions that will eventually lead to its own destruction.

1953 - Reactive Machines

Gordon Pask was one of the early pioneers of cybernetics. As a psychologist and educator, his research involved bio-computing, AI, cognitive science, logic, linguistics, psychology and artificial life. He incorporated information from various media sources into his cybernetic theories and expanded the scope of the study.

In a famous exhibition: Surprising Discoveries of Cybernetics, Gordon Pask displayed a work titled The Colloquy of Mobiles. This is a type of reactive machinery capable of emitting lights in response to sounds made by human performers.







In 2020, a duplicate of Gordon Pask’s 1968 The Colloquy of Mobiles was displayed at Center Pompidou Gallery.

1968 - Cybernetic Serendipity

In the 1960s, under the influence of cybernetic art, many artists started creating “artificial life” artworks drawing their inspiration from animal behaviour, or viewing the system itself as art.

The exhibition Cybernetic Serendipity was held in the Institute of Contemporary Arts in 1968. In the exhibition, Jean Tinguely displayed two of his drawing machines. These are dynamic sculptures. Visitors can choose a pen of any colour or length and at any location, and the machines can create a brand new piece of abstract art with it.







                                                                                                           Cybernetic Serendipity (1968)

1973 - An Autonomous Picture Machine

More artists began to try using machines to create art. Some of their ideas still influence present-day art.







Picture: Untitled 1972, an early example of computer art, made by the first code-based drawing program developed by Vera Molnar

In 1973, Harold Gohen developed an algorithm named AARON, which allowed machines to draw irregular drawings like the human hand. Although AARON is only limited to a certain drawing style coded by Cohen, the fact that it can create a limitless number of works in this style makes its works the first-generation computer art.







                                                                                                        040502 by AARON (2004)

The Age of Deep Learning

By the late 20th century, thanks to the popularization of personal computers, this industry began its fast development. More and more artists started using software programs. Into the 21st century, the availability of free learning materials for programming in combination with open-source projects on Github helped the industry grow.

In addition, researchers are building and publishing large databases, such as ImageNet, which can be used for training algorithms in categorizing and recognizing images. AI visual programs such as DeepDream are easily available to artists and the general public so that everyone can experiment with how well computers can understand different forms of visual expressions.

With all these innovations, AI art to this day has gone through three stages:

- Chatting bots

- Generative art

- Beyond generative art

Chatting bots

1995 - A.L.I.C.E

Released in 1995, Richard Wallace’s famous chatting bot A.L.I.C.E was able to learn how to speak from a corpus of natural human language gathered from the Internet.

2001 - Agent Ruby

Lynn Hershman Leeson created Agent Ruby.







                                                                                                         agentruby.sfmoma.org
                          
2020 - Expanded Art

Since then, many more artists have created chatting bots. Martine Rothblatt modelled his bot Bina48 after his wife’s personality. Martine Syms developed an interactive chatting bot to be her digital avatar. The bot is named Mythicbeing and was designed to be a black, upward, violent, solipsistic, anti-social and gender neutral woman.







                                                                                                    A virtual friend in your iPhone

Generative Art

Artists can collaborate with AI in various ways, using neural networks and machine learning to create artworks. Examples of this include Neural Style Transfer, Pix2Pix, CycleGAN and Deep Dream. So far generative adversarial network is the technology most relevant to AI art.

2014 - Generative Adversarial Network

Generative adversarial network is a term coined by Ian Goodfellow in a 2014 thesis. He believes that GAN will be the next step for neural network, as the technology can be used to create visual effects that were possible before.



https://www.matrix.io/assets/img/blog/AI_Art_19.png



                                                                                        Anna Ridler, Tulips from Mosaic Virus (2018)







                                                                                       GAN used to generate landscape paintings

2017 - GANism was born

Around 2017, artists began testing this technology.







                                                                                               GANism Is The New Art Trend

2018 - A Milestone of Auctioning

The most well-known example of GAN-generated art is a portrait by Obvious which sold for 432,000 at Christie’s in 2018.







Obvious Art’s [ ())] + [( − (()))], Portrait of Edmond de Belamy, Generative Adversarial Network print on canvas (2018).







Two types of algorithms are used here to create these high-resolution artworks: GAN and super-resolution algorithms. More interestingly, the authors have used arithmetic functions to sign their works.

Beyond Generative Art

In recent years, more and more artists see the purpose of AI as not merely to create images, but also to put an end to the innate prejudice people hold against AI. How this movement is carried forward will have long-lasting influences on social justice, equality, tolerance and many other important issues.





                                                                 https://www.matrix.io/blog/The_Past_and_Present_of_AI_Art-2_172.html

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                                                                                     MATRIX AI NETWORK BI-WEEKLY REPORT



                                          



Mainnet Performance

Validation node: 93

Mining node: 1138

New wallets added: 149

Project Update

2.1 Work with mature platforms for NFT trading

• Estimated Progress: 60%

• Updated the IPFS port and NFT protocol of the Mainnet to support minting algorithms and data on the Mainnet IPFS into NFT on Ethereum/BSC/HECO as well as the smooth circulation of NFT assets among these platforms;

• Updated the IPFS port and NFT protocol to support minting algorithms and data on the Mainnet IPFS into NFT on OpenSea and other mainstream platforms for trading.

• Goals for the next phase:

o To support NFT minting on Solana and Polygon;

o To support more mainstream NFT platforms.

2.2 An ecosystem of NFT for the trading of computing power, algorithmic models and data

• Estimated Progress: 35%

• Support minting algorithms and data into digital assets to go in circulation;

• Introduced the first ecosystem app featuring NFTized algorithm/data/computing power as well as equity split;

• Focuses of the next phase:

o Releasing open computing power accessing features to allow non-miner computing power to join in;

o Developing more ecosystem apps using these features and seeking more partnerships.

2.3 Generalized Software Solution compatible with mainstream machine learning hardware

• Estimated Progress: 30%

• Completed the grid deployment of MANTA on Matrix’s miner network, and finished some of the testing work;

• Finished the compatibility expansion design for MANTA;

• Completed the structural design for deploying MANTA tasks onto more nodes;

• Focuses of the next phase:

o Development and testing of multi-node task deployment;

o Development and testing of compatibility with mainstream hardware;

o Compatibility with any universal machine learning algorithm.

3. Others

o Compatibility of MANTA with AIRTIST (demo);

o Finger vein recognition for NFT digital authentication;

o Structural design and development of the new smartphone wallet app by the Matrix ecosystem developer team.

Twitter: https://twitter.com/MatrixAINetwork/status/1519933331663728641?s=20

Medium: https://matrixainetwork.medium.com/matrix-ai-network-bi-weekly-report-1f2e267067b8

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                                                                                                     Release of AIRTIST Website










Release of AIRTIST Website

Dear Matrixian,

We just published a series article this week introducing the past and present of AI arts. Please refer to below two links for details:

https://www.matrix.io/blog/The_Past_and_Present_of_AI_Art-1_171.html

https://www.matrix.io/blog/The_Past_and_Present_of_AI_Art-2_172.html

Art—an expression of human creativity—has always been at the centre of human culture. For centuries, humans have created arts that express thoughts, imaginations, ideas, and memories. These artistic expressions have allowed humans to study history and realise its progress through time.

And as computers increase their capabilities and AI becomes widely deployed, AI-based painting and music composition have emerged in the past few years. And recent breakthroughs in GANs and deep learning networks (DNNs) provide insights into the future of creativity and possibilities.

AIRTIST is a Blockchain-powered platform populated with deep neural networks (DNN) that allow users to generate their own computerised artists via GAN models. The platform uses large data sets and GAN algorithms to train a piece of software with associated data that resembles a latest red-hot artist or famous deceased master like Pablo Picasso and Van Gogh.

Using AIRTIST, any participants can create and trade their NFTs—whether Artist NFTs or Artwork NFTs— on the platform and obtain token derivatives that can be exchanged directly.

Today, we are glad to announce that the official website of AIRTIST is ready and you can access simply clicking the link below: https://airt.ist

You can read the business deck, whitepaper and the founding team members plus roadmap at the website.

Our ecosystem partner will have the phase 1 function ready and we will keep you informed.

This is definitely exciting and inspiring. Enjoy the adventure with MATRIX.

Twitter: https://twitter.com/MatrixAINetwork/status/1520331658439892993?s=20

Medium: https://matrixainetwork.medium.com/release-of-airtist-website-af3d33085899






                                                                     https://www.matrix.io/blog/Release_of_AIRTIST_Website_175.html

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                                                                                                        Matrix AMA — April 2022






                                                                         




Link to the AMA video: https://youtu.be/npIKueVugo4

Eric: Hello Owen, good morning.

Owen: Hi, good morning Eric.

Eric: Okay and also good morning to our Matrixians across the globe. Greetings from Hong Kong and also greetings from Beijing. Owen I heard some cases about the Covid-19 in Beijing, is it serious there? And does it have any effects on our colleagues?

Owen: In fact it’s not that serious but everyone in Beijing needed to do the Covid test every two days.

Eric: Okay, and does it have any effect on our colleagues, on our office operation there?

Owen: Not yet, yeah.

Eric: Oh yeah okay, and hopefully no, okay. I heard in Shanghai they are facing kind of serious situations there, but they are determined to have the Covid-19 settled there.
So again, today is the 26th of April and we are shooting the AMA video for April, and as usual: Hello Matrixians.

So today we are going to have live questions from the members and I would love to have our CEO Mr Owen Tao to share his insight or answers on some timelines, and also his insight on these questions. And Owen, are you ready for these questions?

Owen: Okay I’m ready.

Eric: Okay that’s good, let’s kick some ass then!
Okay the first question comes from Boz_Kurt, this is about mining the question is like this: “If a corporation set up their own miners, let’s say 50 miners for AI computing can they delegate those 50 miners to serve only their need?” (This meaning to serve this company alone) “Sorts of dedicated AI miners for their business needs.
Have the tools been developed for all these companies to dedicate their miners for their own tasks?”

Owen: Yeah, our plan… That’s a new function we want to edit our new versions for MANTA and the mining system. In our plan, our cooperators who will use MANTA or our AI mining, they can add their own miners or their computing powers to our MainNet. And also they can delegate their own computing powers to only serve their own tasks. So yes, in our plan we will add this function in our assistance, yeah.

Eric: Okay that’s great! So both good, we think ahead of yours, and thanks for your questions. And Owen, do you mind sharing if there is any rough timeline for this new function?

Owen: Yeah, this function is also with our MANTA system so I think in this quarter we will start to invite some collaborators who will join our testing to use this function. And we would like to open it to the public.

Eric: Okay so within this quarter, meaning Q2, we will start to look into this function, but the exact schedule we have to study or investigate further, and then to advise the community.

Owen: Yes this function, I think this function will take a long time, a longer time than our MANTA and the GPU mining, because this is not a key function for this system, so we’ll spend some time to develop it and spend more time to test it because in this way we’d like to ask to new collaborators who will add their own computing powers to join our system, not as a miner, just as computing power, so I think it will take more time to do the testing work.

Eric: Okay, so the simple answer to this question is yes, we will be looking at this function and we’ll be starting to look at this function within this quarter, but it will take a long time to finish it because we have other more [important] tasks that are more prioritized than this one. But we will keep updating the community about the timeline for this function as well. So this answers the first question, and shall we go on to the second question?

Owen: Okay

Eric: Okay good, so the second question is from TheElk:
“Hi Owen, in a previous AMA you said a new version of the GMAN miner software will be released to miners during Q2, are you still on track with that timeline?”

And then, there are two follow-up questions:
“Will this new version of GMAN support multiple GPUs?” Question one. Question two:
“Will we, in the community, be able to participate in a testing of the new GMAN version to help the team find bugs?”

So actually there are three questions: number one is “Are we still on track for the Q2 to have the GMAN miners software released?”

Owen: Yeah, this is still on track. And of course it will support multiple GPUs, because you can see it already, we’ve already added this function in our test version of MANTA. You can check on our TestNet, you can use the multiple GPUs servers to join this system yes. And of course after our testing we will open a public testing task, and we would like to invite our community to join this test work and the fun bargain. Maybe we will make a bounty for that, yeah.

Eric: Okay that’s good. So Elk, [the answers to] your questions are all positives, so I think you’ll be happy with that. And I know you have further questions:
“Hi Owen, now that Matrix chose to not use FileCoin but instead Matrix own IPFS servers, can the community contribute by joining this IPFS network to be able to decentralize it further and to secure the uploaded data?”
Yeah, Owen?

Owen: The thing is, we haven’t opened this function to the public because we haven’t encouraged systems into our IPFS system, so if you provide the storage to other people you can’t get rewards right now. So that’s why we haven’t opened this to the people, because if you want the contributors who will support a stable and good storage in our IPFS system, you need to give them rewards, so maybe after we finish the design for the Tokenomics for this functions, we will open it to the public and ask the community to make their own storage to our system.

Eric: Okay, I think that makes a business sense. I think that people are driven by the interest of the rewards, particularly for the miners or service providers. So when it is ready then we will invite people to join these IPFS network servers, things like that, to further decentralize and to securely upload the data.

Okay, and then we go on with Kacawote: “When will Matrix be able to make transactions of 1 million TPS or more?”

Owen: We have mentioned that in our plan, we designed the Matrix network which kind of supports 1 million transactions per second. But it’s in theory, because we haven’t good enough hardware right now, such as we haven’t got enough bandwidth for that. We have tested our network in the laboratory, in lab, and the most TPS we can achieve is about 100,000. But we still can’t achieve the 1 million which is our theory TPS, but I think in the future when the hardware will get better and better, and the bandwidth will get bigger and bigger, I think maybe we will achieve this number someday, but not now.

Eric: Okay, so I think our current TPS is about 14,000. And also in the lab test, we can reach up to over 100,000 TPS. And the MainNet is scalable, but we have to take a progressive approach. Meaning to say, even if we had the 1 million TPS right now, we don’t have that many transactions, so it’ll be a waste of those bandwidths, hardware, mining things, etc, etc. So we take kind of a progressive approach, so when there is a need for more TPS, or higher TPS, it is there, because we are scalable.

Okay that’s good, and that is the part one about the technical or technology side, and may I move on to a product side, this is from Sbblc, Owen: “Do you have plans to bring out a wallet app in the App Store?”

Owen: Yes, last time, I have mentioned that right now we are working on that to offer a new version of a world app (application), but of course we will offer an Android version first, and then the iOS version. I think in the near future you will find a wallet app which supports Matrix and MAN in the App Store, which will be developed by one of our ecosystem team.

Eric: Okay, that’s good, that’s good, that’s good. So hopefully we can see the upgraded Android wallet app soon, and then after some tests we can then apply to be uploaded to the PlayStore of Android.
That’s good, and the second question about the product side, again from TheElk: “Hi Owen, will MANAS and MANTA be fully released on MainNet during Q2?”

Owen: Yeah, in this Q2, in this quarter, I think the madness will be fully released on the MainNet. Right now we have already put all the AI services on our MainNet right now. But for MANTA, in this quarter I think we will start it. Of course we will release it on our MainNet, and we will invite some collaborators to do the tests first. After the testing we would like to open it to the public.

Eric: Okay that’s good. So MANAS will be released to the MainNet, and MANTA we finish 2 Quarter, we will invite some partners to test first and then release to the public. I think that makes sense. So kind of very good signs for this and I hope TheElk you are satisfied with this one.

And then we move on to 2 questions about… Actually three, so this one is from Omer55yuksel about Twitter:
“Even CZ tweets 10 tweets a day.. Wouldn’t it be better if you were a little more active on Twitter and announced the developments?”

So I think he’s asking if you can, I mean if your personal twitter can be more active. I know you are busy, and because of language issues, but can you please try to answer this one please?

Owen: Okay, I think it’s a good suggestion, and right now we have the most things [going on] about our project, we will announce them in our official Twitter account. And I think your suggestion is very good, and I’d like to be more active in the future and share more information on my own twitter account. I will try my best.

Eric: Okay, good. So, for tweets, it may be relatively difficult because you have to write, but I think a quick way will be to have more interaction with the tweets from the official Twitter account. So you can say for example like a retweet, things like that, that will be easier for you.

Owen: Okay.

Eric: Okay, yeah. And then from EbMagic: “Do we have a developer space on Discord, Slack, or anywhere where we can learn to use all of the Matrix AI tools with some practical cases?”

Owen: Yeah, that’s a good suggestion too, and we will have our Discord channel and I think in the future after we finish most of our development work in our roadmap, maybe we would like to ask one or two technologies staff who will be in charge of building this channel, we can discuss more things about our technological things in Discord, yeah. It will happen, but not now. We will finish our development work first and then we will do better and more things for the developers in our community.

Eric: Okay, so it will take a while EbMagic, but before that you can visit the website. I think there is a place at our website with all the technical details you can refer to.

And last question, this is from Snoeks78. A bit long. The question is like there’s a lot of statements, it’s like this:
“Although I’m still testing, I find that the APY is more like 2–3% on an annualized basis than the suggested 10–11%.”
Okay. Before I go on to other questions, Owen, do you have any comments on this one? He’s getting 2 or 3% instead of just 10 to 11%, do you have any comment on this part?

Owen: In fact the subject of the APY is calculated as an average reward for all the miners, and the delegates know. So ,because you know, there are some very big delegates, that’s why they can gain more percent rewards then. And also the little delegate nodes will gain less. So the number you have seen is an average number. That’s why maybe it’s something not exactly equal to the suggested numbers. And also if you are a miner and the APY for you… First every miner has the same chance to be selected, but how many rewards they will gain depends on your computing power and your bandwidth and lots of things. So you can’t say “I have joined as a miner in the Matrix network, I will gain the most rewards”, you need to improve maybe your hardware and your bandwidth, or something else to… I’ll say to add more rewards.

Eric: Okay, thanks. Snoeks78, because you have a very long statement, so I will cut the… you have some suggestions on the UI etc. So I think we have done some improvements on those and see if that fits your needs. And allow me to go to the last bit of your statement, which is about “can we have a simple staking guide so that the process is clearer to understand, especially in regards to the APY, 10 to 11% is okay, 2 or 3% is not that interesting especially for crypto. So, cut it short, can we provide some simple staking guide?”
I think we do have this staking guide in place, but I’m not sure what exactly do you want us to improve on that. Yeah perhaps you can Snoeks78, could you please DM me directly so that we can understand your list better, and then after we are clear and then I’ll pass the message to Owen for his comments and to see how we can help the miners all together.

And Owen I think you have addressed the nine questions that we selected from the pool. Thank you very much for your time, and you take care of yourself and also of your family in Beijing.

And I think that concludes our AMA today. And thanks Owen, and again and thanks Matrixians for supporting and sharing your concerns, asking your questions, submitting your suggestions, thanks for that. And I think this is a good one because we will have MANAS to be released in Q2 and we do think ahead of some functional features but we still cannot give a very exact timeline to fully realize those functions. But we’ve already taken those into consideration and we will keep updating the community.

Okay and I think that concludes the AMA today, thanks everyone, bye.

Owen: Bye.







                                                                  https://www.matrix.io/blog/Matrix_AMA%E2%80%94April_2022_176.html

[karametade]

 


                                                                                            Award-winning Matrix Quiz Event





                      





Dear Matrixians,

“Award Quiz Event” to introduce our Ecosystem project AIRTIST and to make people aware of it’s awesome utility in terms of art creation, NFT generation and trading and how Matrix is associated with it.

A. Event Details

Our event starts on Wednesday, May 4, 2022 at 17:00 (UTC).

Event period : May 4 — May 30, 2022 (12 Prize Questions)

Every Wednesday, Friday and Monday at 17:00 (UTC) throughout May.

Prize: $10 MAN/day — Total=$120 MAN will be distributed.

Date of Winner Announcement : 3 June

Date of Prize Distribution : about 5 June, 2022

Those who give the first correct answer to the question of the day in our 12 planned events will win a $10 MAN.

At any time from 5pm(UTC) chat in the Matrix AI Network Global channel will be muted for the question, once it is finished chat will be unmuted to receive answers. First correct answer will be rewarded. So stay alert!

B.Tasks

Join the Matrix Global Telegram Channel at t.me/matrixainetwork

Retweet the announcement tweet.

C.Rules

We will ask one question per event.

A person can win up to 3 prizes.

The first to write the correct answer and the fastest will win the prize.

MATRIX reserves all rights in this events.

Terms and Condition is subject to change without prior notice.





                                                                 https://matrixainetwork.medium.com/award-winning-matrix-quiz-event-d802c3f1a337

[karametade]

                                                                                   AIRTIST—Matrix’s Great Venture into AI Art (1/4)




What is AI art?

In recent years, as a novel form of art, AI art has caught more and more mainstream attention. AI is short for artificial intelligence. If computer-generated imagery can be called digital art version 1.0, and art created by people on the Internet is version 2.0, then the emerging AI art may bring us into the third iteration of digital art. From 1.0 to 3.0, digital art is constantly upgrading and revolutionizing itself. As we have witnessed, CGI-based digital films, anime and online games are some of the most powerful driving forces of digital art. Internet art based on various interaction mechanisms are also gaining huge traction.

AI is the technology that makes machines capable of performing cognitive tasks as humans do. These include playing chess, image recognition, translating, searching for the best candidate among heaps of resumes, etc. We can extend this concept to art by having computers learn the techniques and styles of classical artists and create works that pass as from the same period in the eyes of art history scholars.

In fact, this is similar to the idea behind the famous Turing test. If artworks created by AI after training can pass as works from a certain historical period in the eyes of art history scholars, and these works are not simple modifications of their source data, then these AI artists have passed the “Turing AI Art Test”. All this sounds simple enough, so we can use it as our fundamental definition of AI art. Under this definition, AI art is any artworks considered legitimate classical or contemporary art by experts in the relevant academic fields.



                                                            



In today’s world technologies are developing at a breakneck speed, and the definition and boundary of AI art are also changing and becoming clear. On the one hand, people are beginning to try using AI as a tool to assist humans in art creation. On the other hand, people are also using the latest technologies, such as generative adversarial networks to help AI understand art in order to enhance their mastery.


Portrait Of Edmond de Belamy: A Milestone of AI Art

In October 2019, Portrait Of Edmond de Belamy (2018) the first-ever AI artwork was sold for 350,000 USD after a heated six-minute auctioning, smashing previous estimations. This transaction was settled at 432,500 USD including commission, which was more than 43 times the estimated price.







Starting from this, more and more AI artworks have entered the global spotlight. In March 2019, Sotheby’s sold Mario Klingemann’s Memories of Passersby I for 51,012 USD. In the spring of 2018, HG Contemporary Art Center held the first gallery exhibition dedicated to AI artists in Chelsea, Manhattan. Among the exhibits was a work called Faceless Portraits Transcending Time, a collaborative work between AI and Ahmed Elgammal, professor of computer science at Rutgers.

Renowned art institutions and collectors alike are closely following this new form of art. Marisa Kayyem, director of Continuing Education at Christie’s Education, said: If we look at what is happening in the art world from a broader perspective, instead of just fixing our attention on sales, we will realize the things that are happening are powered by strong momentum and backed by large institutions. More and more collectors are getting used to AI art.

Many professionals in art-related industries still hold a degree of suspicion towards AI art, thinking that the word could be misleading or has too narrow a reference. Like other artists who are also programmers, Klingeman prefers to use the word generative art, which refers to all works created using algorithms. Klingeman’s works have been put on the auction block at Sotheby’s, while the origin of generative art can be traced to the late 1950s.

Jason Bailey, founder of Artnome, said: AI art is actually a word made up by media in the recent three to five years. He thinks that using this word will mislead people into thinking these are art created by machines. The majority of artists I know don’t like being called AI artists, he said, but like it or not, the word is quite commonly used.



                                                                



Although Edmond de Belamy is the most well-known AI artwork, for people getting to know this art form for the first time, the work might be a bit distracting. Edmond de Belamy was created using generative adversarial networks (GANs), which was trained using a set of artworks to learn to create a similar style and use all the knowledge to create something new while retaining certain elements from the original images.


NFT and the Metaverse: New Opportunities for AI Art

2021 was the year NFT gained serious traction along with everything related to the Metaverse. Top-notch teams from all over the world have entered the scene, and the Metaverse also saw the very first influx of new users. Although the hype has died down a bit since then, this doesn’t change the fact NFT is getting increasingly accepted by the general public, especially with the setting up of infrastructure such as Opensea, Huahe, Jingtan, etc. The enthusiasm with which people can accept something revolutionary like NFT is beyond expectation, while profile picture NFTs are leading the industry in terms of creativity and growth speed.



                                                                        



Some eye-catching success stories of NFT include Mike Winkelmann’s Everydays: The First 5000 Days, which sold for an astonishing 69.3 million USD, setting a record for digital artworks. Jack Dorsey sold his very first tweet for more than 2.9 million USD. Even more insanely, British contemporary artist Banksy’s Morons was bought at 95,000 USD, and the original work was destroyed intentionally after being converted into an NFT version, which sold for 380,000 USD.

Most people would find it difficult to make sense of all this. But the fact that NFT can attract so much hot money is all thanks to the hype about the Metaverse. In March last year, Roblox was listed on New York Stock Exchange and immediately favoured by market capital. This incident popularized the concept of the Metaverse like never before, and as the fundamental technology of the Metaverse, NFT has come to be known as the key to the digital world. If the Metaverse is a parallel universe to ours, then NFT is the bridge between the real and the virtual worlds.

AI art is a fast-growing new industry with limitless potential. The popularity of the Metaverse and NFT will create more opportunities for everyone involved.





                                                     https://www.matrix.io/blog/AIRTIST%E2%80%94Matrix_s_Great_Venture_into_AI_Art_178.html

[karametade]

                                                                                 AIRTIST—Matrix’s Great Venture into AI Art (2/4)



What is AIRTIST?

AIRTIST is the combination of two words: AI and artist. As the name suggests, AIRTIST is an AI artist, a distributed program that uses AI algorithms for art creation. We use deep neural networks to create AIRTIST, and every AIRTIST is operated by an independent deep neural network. To guarantee AI artists and their works are decentralized, these deep neural networks will be deployed on the blockchain.







After an AI artist has been created, users can use distributed computing power to run the DNN corresponding to the AI artist to create artworks.

Depending on the type of art, AIRTIST will create four kinds of AI artists: PAINTER, MUSICAIN, DESAIGNER and WRAITER. AI artists will branch out into more art forms in the future.

Why do people need AIRTIST?

AIRTIST will transform the current art NFT market in three ways:

1. Solving the problem of trust between online and offline parties which troubles conventional art NFTs:b Conventional art NFT are created by human artists in the real world. Therefore, both the digital artworks and their artists are centralized. The transactions of these artworks invariably take place at centralized exchanges, which is at odds with the ideal of decentralization that blockchain represents. On the contrary, AI artists’ works, from their creation to their storage and transaction are all decentralized, which perfectly solves the problem of trust during NFT trading.

2. Lowers the entry barrier for the NFT market: In the current art NFT market, artworks are created by a minority of people, while the average person has no way to own an artwork except by paying the costly price to buy one. The arrival of AIRTIST allows everyone to own his/her independent artist. Besides buying and selling, oridinary users can create their own art NFTs, which will find their way into the market. This is expected to make the current market size many times larger.

3. Bringing deceased masters back to life: Through machine learning, AIRTIST can master the styles of deceased artists such as Van Gogh or Monet. The world will marvel at new masterpieces from these deceased giants.







Work by an AI Artist trained using Vincent van Gogh’s works

AIRTIST and Matrix

AIRTIST has three core components: AI artist, art creation and art circulation (minting NFTs, buying and selling). Among these, AI artists and art creation will happen on the Matrix Mainnet, while the circulation part will take place on Ethereum.







Why choose Matrix?

Matrix AI Network is a highly efficient blockchain empowered by AI. Here are some of Matrix’s features that will benefit AIRTIST as well as AI art creation.

1. Compatibility with IPFS: Distributed storage is the fundamental storage facility for NFT, and the Matrix Mainnet is already perfectly compatible with IPFS. Through future protocol updates, Matrix will also support Filecoin and other distributed storage platforms.

2. Distributed Computing Power Platform: Matrix provides a distributed computing power platform, which will guarantee sufficient high-quality computing power for the creative work of AI artists.

3. Algorithm Authentication Platform: The Matrix Mainnet supports algorithm authentication and minting algorithms into NFTs, which protects the intellectual property of AI artists who train DNN.

IRTIST—Matrix’s Great Venture into AI Art (1/4)

Twitter: https://twitter.com/MatrixAINetwork/status/1522446576345571328?s=20

Medium: https://matrixainetwork.medium.com/airtist-matrixs-great-venture-into-ai-art-2-4-b3230fbb9fa1




                                           https://www.matrix.io/blog/AIRTIST%E2%80%94Matrix_s_Great_Venture_into_AI_Art_2_179.html

[karametade]

                                                                                       How important DID is…exactly why I keep emphasizing it
                                                                                          Eric Choy
                                                                                          @MATRIXCMTO



                                                          




 Decentralized Identity (DID)
 Essentially, a decentralized identity is a digital identity document that is not issued by central authorities.
 In this day and age, managing one's digital identity can be quite difficult for many people with different accounts on different platforms, each with their own complex authentication process.  The author has at least more than a hundred accounts and often forgets the password of rarely used accounts, such as a social security card or residence card.
 By creating a single digital identification system that is reliable enough to be used across all platforms, we can eliminate the need to open a new account each time we access new platforms.
 Decentralized identity has a number of advantages, and if the above isn't enough motivation to move to a DID system, the following should provide more support.
 Privacy: Smart contracts, targeted authorization, etc.  With the help of mechanisms, exclusive access to certain services can be provided.
 Efficiency: If a single identification method can be used across platforms, no one needs to be bothered by the complex registration requirements each company has.
 DID still goes beyond that.  A decentralized identification system will inform the service provider whether the user's identity information is authentic or not without providing personal information.  For example, if an exchange needs to verify your identity, the DID system can do the verification work and report back to the exchange without letting it get your ID card/passport number.  As crypto investors, we all get scam calls from time to time.  You can ask how the scammer got your information.  They know our names and phone numbers, even the fact that we invest in cryptocurrency.  It goes without saying that we have been betrayed by the cryptocurrency exchanges we are registered with.
 With DID, one will no longer have to worry about their privacy.
 But one thing DID, with all its obvious advantages, cannot do is verify someone's identity, and if the credential entered into the system is wrong in the first place, the rest becomes meaningless.  Therefore, centralized identification, although inefficient, is still indispensable, as the authorities behind it lend credibility to their conclusions.  Therefore, while the Matrix Bio-Wallet was created as the perfect solution, reliability remains DID's biggest obstacle.  Bio-Wallet uses finger vein recognition to authenticate users.  It is both reliable and decentralized.  Since every Bio-Wallet is a container containing the user's DID information, a system of them can provide accurate identification while ensuring confidentiality and ease of use.

MATRIX BIO WALLET point based finger vein recognition wallet to store your crypto assets.

Its a container containing user's DID information providing accurate identification ensuring confidentiality




                                        




                                                                             https://twitter.com/matrixcmto/status/1523189663913025536?s=21

[karametade]

                                                                                           AIRTIST—Matrix’s Great Venture into AI Art (3/4)




How to create an AI artist?

To create an AI artist is essentially to train a DNN, which uses the same methods as training generative adversarial networks. Here we need two deep neural networks. One is called AIRTIST-DNN and imitates the creative process of artists. The other is called Discriminator and serves to improve the quality of the art. The relationship between the two networks is illustrated below. On the bottom left corner is AIRTIST-DNN, and Discriminator is in the middle. An AI artist needs to be trained before it can create art. The two networks are deployed on the Matrix Mainnet using distributed computing, and we need a group of artworks of a certain style. Before training begins, the weighting of the two networks are set to random. AIRTIST-DNN is built using a generative model, which can mirror a set of random numbers onto an artwork. Of course, in the beginning, the results may not look like art by any means. But in the meantime, Discriminator will also start training, using preselected art samples and works created by AIRTIST-DNN as sample data. The target of training is to be able to tell which one is the real artwork and which one is generated by AI. In the process, the weighting of the two networks is constantly readjusted to get the statistical distribution of AIRTIST-DNN-generated data as close as possible to that of real art. This training process can be seen as a game where two players compete with each other. The quality of generated works will match up to real ones when Nash equilibrium is reached.







How to create AI artworks using AI artists?

Let’s use the process of AI artists creating a painting as an example to illustrate how AIRTIST works.

A fully trained AIRTIST deep neural network will have multiple layers of neurons, each with large quantities of weighting parameters, which reflects the statistical distribution of specific artworks. To create an artwork, first, we need to enter a theme. After semantic analysis, the theme will be converted into a group of preliminary parameters to be sent to AIRTIST-DNN. After the data input, neurons of the hidden layer will calculate the data and weighting parameters level by level. Finally, the output layer will receive the final result, which is the end product of the AI artwork. In fact, a deep neural network is an all-powerful tool that can mirror data input onto any data output. The process of training is to adjust the mirroring function of the network to match the target art style, and the creative process is to generate a set of data (i.e. the artwork) based on the distribution style reflected by network topology and weighting parameters. As a deep neural network will have millions of weighting parameters, there will be a degree of randomness in the reflection of specific distributions. This randomness is a manifestation of the artist’s free will.







After a work has been created, it is authenticated through blockchain and saved on the distributed storage to be a digital asset.

https://www.matrix.io/blog/AIRTIST%E2%80%94Matrix_s_Great_Venture_into_AI_Art_178.html

https://www.matrix.io/blog/AIRTIST%E2%80%94Matrix_s_Great_Venture_into_AI_Art_2_179.html







                                                      https://www.matrix.io/blog/AIRTIST%E2%80%94Matrix_s_Great_Venture_into_AI_Art_3_180.html

[karametade]

                                                                                   AIRTIST—Matrix’s Great Venture into AI Art (4/4)




Why is AIRTIST important for Matrix?

Both AI art and NFT are practical use scenarios for Matrix. Before the AIRTIST team joined, Matrix had already been planning to build its own AI art platform, which attests to how important AIRTIST is for the Matrix ecosystem.

1. The First Important Use Scenario for MANIA

Every AI artist is an independent AI algorithm model, and AI artists themselves can be minted into NFTs to go into the market. All these are thanks to MANIA’s innovations. As the first major application of MANIA, AIRTIST’s impact on the AI art scene and the NFT market will likely create more use scenarios for MANIA. The integration of AI models and NFT will spark more innovations in the whole industry.

2. More Demand for MANTA

Whether it’s training AI artists, or creating art using these AI artists, distributed computing power will be necessary. AIRTIST will be one of the earliest projects to be granted access to computing power from MANTA. AIRTIST will create more demands for the distributed computing power produced by Matrix, and this in turn will make it more profitable for Matrix miners to output computing power.

3. More Liquidity for MAN

Matrix services and products offered through MANIA and MANTA will be paid for in MAN, so the popularity of AIRTIST will create more liquidity for MAN.

4. A More Mature Matrix Ecosystem

The integration of AI and NFT plus the introduction of AIRTIST under DAO will diversify the Matrix ecosystem and bring about more opportunities. Creations of artists on AIRTIST could be packaged into an AI service offered on MANAS. There could even be professional AI art critics trained by MANTA.

The Future of AIRTIST







NFT is being accepted by users at an unprecedented speed. OpenSea’s daily active users hit a new high at the beginning of this year. According to Dappradar, the volume of transactions on OpenSea reached 4.491 billion USD in January 2022, up 102% month on month. The number of transactions rose to 2.8163 million, a 95% increase month on month. Its daily active users registered 46,800, achieving a historic high and a 86% increase month on month. This data shows that more and more users are starting to not only accept NFTs as digital assets but also trade and hold them.

After over a year’s fast growth, the NFT application ecosystem has developed into six main areas: collectibles, artworks, game equipment, virtual lands, practical NFT and financial NFT. Of them, collectibles, artworks, game equipment and virtual lands account for the largest market share.

Based on data about all NFT-related niches, collectible NFT has become the predominant use scenario. The transaction volume of collectible NFT this March has reached 995 million USD, and the volume for the first quarter registered 4.134 billion USD, up 67% from the 2.461 billion USD of the previous quarter. The hot collectible NFT market is the primary force in helping the NFT industry recover since the beginning of the year. Starting from July last year, the turnover of collectible NFTs has been sharply on the rise, and its proportion in the entire NFT market rose from 28% to 84% by March.

AIRTIST will effectively lower the entry barrier to NFT and greatly expand its market size. Thanks to AIRTIST, the NFT market will welcome a new round of explosive growth, and AIRTIST will benefit from being the pioneer of a new age.






Users will have diverse demands for art in the Metaverse, and the majority of these artworks will be created by AI. This will mean huge demands and growth potential for AIRTIST.

The arrival of AIRTIST could mean a crisis for the current art market as well as some artists, but in the eyes of many event organizers, institution managers and academics of the art industry, AI will create countless opportunities by being a new player in the game. Human artists may engage in a battle of imitation and counter-imitation. Some human artists will begin to use AIRTIST as an innovative art creation tool to achieve unique styles, just like skilled photographers are able to get creative visual effects in their photos by adjusting the technical parameters of their equipment. Who is to say this won’t be the beginning of a dozen new schools of art?



                                           https://www.matrix.io/blog/AIRTIST%E2%80%94Matrix_s_Great_Venture_into_AI_Art_4_181.html

[karametade]

                                                                                                   User Guide for Matrix IDE





Matrix IDE is an online integrated development environment built on the Matrix Mainnet supporting the use of Solidity to develop, compile, deploy and interact with Matrix smart contracts online.

Layout



                                                                



1. Icon Panel: Click to choose which plugin to show in the Side Panel

2. Side Panel: A graphical user interface to show icons

3. Main Panel: A work area for editing files

4. Terminal: The area to show results

Icon Panel



                                      



The Icon Panel contains the file explorer, the compiler, deploy & run functions, tools, settings and other useful features.

The File Explorer

The File Explorer is a tool for browsing files saved in the local storage. By default, it contains two test contract files and one Matrix address converter.



                                      



Click + on the upper left corner to create a new Solidity contract file. Let’s name the file test.sol in the window that pops up.



                                                              



Click OK, and you will see hello.sol under Browser in the File Explorer on the left side panel.

Simultaneously, a newly created file will open in the Editor. At this point, the file is still empty.

Next, write some simple Solidity codes.

Add a local file.

You may select files from your local storage to load onto the IDE explorer.

Editor

You can edit codes here.

Select the newly created hello.sol file and enter a simple string of codes.



                                                            



Let’s use the simplest codes we can think of, as in the example above. The function of echo () is to return any string of codes that is entered.

The Terminal

The Terminal is mainly for showing the results of running a contract or a static analysis.

The Compiler

You may click the box right next to Compiler to choose which version of Solidity compiler you wish to use.



                                                            



Click Start Compiling to compile the currently selected code file in the Matrix IDE Compiler. In this case, the file is hello.sol.

If no error is found after compiling is done, you will see Hello in the dropdown menu under Compiler Configuration.



                                          



Deploy & Run

On the Deploy & Run page, you may deploy a compiled contract as well as run already deployed contracts.



                                          



Three options are offered under Environment.

· Java Script VM is a virtual machine in Java Script. It operates in your explorer so you don’t have to worry about Java Script node configuration or losing ETH. This environment is most suitable for learning and prototype testing.

· If you have your own node, you may select Aiman Provider to connect IDE to your node. However, please note that if a node is connected to the Mainnet, any transaction will be charged a transaction fee.

· Use the contract function of the Web Wallet to compile the tested contract into byte codes and deploy it onto the Mainnet (wallet.matrix.io) or the test chain (wallettest.matrix.io).



                                                            



Example

In the image above, the selection box is set to Hello. The selection box will contain a list of compiled contracts. Click Deploy to deploy the selected contract. After mining, newly created items will be added, which may take a few seconds. Please note that if the constructor contains parameters, then they will need to be specified.

At Address can be used for viewing deployed contracts. This is assuming the provided address is an item under the selected contract. Please note that this feature does not currently offer security checks. Make sure you are using a trusted contract address.



                                        



Now we can see our contract under Deployed Contracts. Click our contract.



                                                    



As we can see, the echo method set out in the Hello contract automatically shows up.

The return value is the same as the parameters we entered. We have achieved our goal.

Address Converter

address_conversion.sol is a library file for swiftly migrating Ethereum contracts to the Matrix Mainnet.

toMan converts an Ethereum address to an Matrix address.

toAddress converts an Matrix address to an Ethereum address.

Tools

This section contains some useful tools you may need on the Matrix Mainnet.



                                                          



Settings

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                                                                        https://www.matrix.io/blog/User_Guide_for_Matrix_IDE_182.html

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                                                                                                How to Create a Matrix Smart Contract






1. Create a smart contract

Use Matrix IDE to develop, compile, test and adjust contracts. Details can be found in the User Guide.

Visit：ide.matrix.io







2. Deploy the contract

● Use Matrix IDE to connect your node and deploy the contract.







● Use the contract features on the Matrix Web Wallet to publish the compiled byte codes onto the Matrix Mainnet or the test chain.









                                                              https://www.matrix.io/blog/How_to_Create_a_Matrix_Smart_Contract_183.html

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                                                                                           The impact of AI on the gaming industry






Artificial Intelligence has elevated  gaming into a high-end experience. Here are some of the top applications of AI in making games fun and versatile.


Better level progression: Game AI can detect a player’s skill level and emotional state and tailor the game accordingly. This might also incorporate dynamic game difficulty balancing, which alters the game’s difficulty in real-time depending on the player’s skill level. The AI in the game may even aid in identifying the player’s intent. Thus, as players ascend to higher levels, AI assists in making the games more challenging

Imparting skills to NPCs: NPCs, or non-player characters, are the most typical targets for Game AI. These are intelligent game characters who act as though they are controlled by human players. Artificial intelligence algorithms and engines determine how these characters operate. The behavior of these NPCs is typically governed by decision trees. However, making NCPs raises the skills of the player.

Improving user journeys: Gamification is a process of leveraging game design elements in a business operation. The goal is to create habit-forming commodities that encourage long-term retention and engagement. It is an excellent motivator and engagement enhancer. Gamification elicits human feelings such as enjoyment, interest, and excitement. Positive user experiences lead to increased engagement, loyalty, and business growth.

Increasing engagement in education: AI games have acquired popularity as a new paradigm in education. Digital games may be played by anybody, and they have the potential to be used for large-scale teaching and learning. There has been an increase in interest in digital games to encourage computational thinking and programming in pre-college and K-12 schools in recent years.

Immersive training modules: Using games, business leaders can design engaging training modules for employees that simulate real-life situations and enable employees to improve their skills in virtual environments. Learning their work through games gets employees interested and aid in retention. It’s also a fun way to keep getting better and picking up new skills. AR/VR-based games powered by AI are the most useful in these scenarios.

Artificial intelligence has a significant impact on the advancement of AI games and their adaptation to the preferences of players. AI is the most often used innovation in this regard. Essentially, the AI gains from the enormous number of games, creates inferred representations of the games, and then continues to recombine the information from this representation and apply the extension to create new games.
AI has brought about significant changes in the gaming industry, and its influence is growing at a rapid rate. It would not be startling to see AI used significantly more in the gaming industry in the near future, given how it aids in the production of extremely intense and believable game experiences.

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                                                                                    MATRIX AI NETWORK BI-WEEKLY REPORT




Mainnet Performance

Validation node: 92

Mining node: 1126

New wallets added: 69

Project Update

Work with matured platforms for NFT trading – 70%

—Added more compatible NFT platforms;

—Began the development work for compatibility with Solana ports and IPFS upgrade;

Focus of the next phase:

—Supporting NFT minting on Solana;

—Supporting Polygon and other public chains;

—Supporting more mainstream NFT platforms.

An ecosystem of NFT for the trading of computing power, algorithmic models and data – 45%

—Deployed the first ecosystem app (demo) featuring NFTized algorithms/data/computing power and equity split;

—Upgraded the distributed storage format for algorithms and data to improve their security;

Focus of the next phase:

—Allowing computing power from devices other than mining machines to enter the ecosystem in future updates;

—Developing more ecosystem apps and finding more partnerships based on the above feature.

Generalized automatic machine learning – 35%

—Assisted in the deployment of the first distributed AI computing ecosystem app (demo);

—Completed the optimization and upgrading work of MANTA to support DNN models;

Focus of the next phase:

—Developing and testing multi-task deployments;

—Developing and testing compatibility with mainstream hardware;

—Upgrading to support any universal machine learning algorithm.

Others

—Introducing finger vein recognition for signing algorithms and personal data;

—Mobile wallet app (alpha version) completed by our ecosystem team and about to enter the first round of testing.



                                                                                    https://www.matrix.io/blog/BI-WEEKLY_REPORT_185.html

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                                                                                                          MATRIX Fact Sheet 3












18- https://www.instagram.com/p/Cc3hfKNIuA2/

Matrix Bio-Wallet is a point-based finger vein recognition wallet to store your crypto assets. It will support various features built on Matrix Mainnet.

Matrix Bio-Wallet outperforms other crypto wallets in terms of security, efficiency, and transaction fees. It is clear that the Bio-Wallet will be an important part of the Matrix ecosystem and will guarantee a secure transaction and identification for services on the Matrix platforms.







19- https://www.instagram.com/p/Cc8wc5yoIr2/



























20- https://www.instagram.com/p/Cc-T4fGoioQ/ (video)







21- https://www.instagram.com/p/CdBqK6fIc4V/

The Matrix eco-system is getting stronger！






22- https://www.instagram.com/p/CdG5l4IIDEd/

AIRTIST delivers the power of the NFTs into your pocket by combining AI, crypto-wallet, and other web 3.0 technologies. Blockchain-powered decentralized art platform.







23- https://www.instagram.com/p/CdJedxDI6OP/

MAN's new ecosystem project AIRTIST is a decentralized platform for creation and ownership of robotic artists (AI Artists) and digital artworks generated by AI Artists.


24- https://www.instagram.com/p/CdTZ4MOIOBW/

Matrix AI Network works in harmony with other popular blockchains.

MAN is building the future of blockchain. Stay tuned





                                                                            https://www.matrix.io/blog/MATRIX_Fact_Sheet_3_184.html

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                                                                                                                  AIRTIST



AIRTIST is a Blockchain powered platform filled with deep neural networks (DNN) that allows users to create their own computational artists through GAN models. The platform uses large datasets and GAN algorithms to train a piece of software with associated data that resembles a trendy artist like Pablo Picasso and Van Gogh or a famous deceased master.
The resulting artist created through GAN algorithms is an AI Artist or robotic artist. Using GANs, the platform can import styles from existing datasets and create new ones with all-new AI Artists.
The end products can have enormous potential value, as users devote a lot of computational effort and resources to training such AI Artists. This value found in Artificial Intelligence Artists is transferred to the Blockchain as NFTs through a mintage process. As such, users can print AI Artists as Artist NFTs on the AIRTIST platform after they are created, allowing them to trade these digital assets.
When AIRTIST is trained with different algorithms and datasets, it can create digital artists and artworks of different styles and genres. Because an AI Artist is programmed to respond to user interactions via computer, users can always modify the inputs to create various works of art. Like AI Artists, users can print their artwork to create Artwork NFTs.
Using AIRTIST, any participating platform can create and trade their NFTs (Artist NFTs or Artwork NFTs) and receive directly exchangeable token derivatives. For example, anyone can trade an Artist NFT for other valuable assets on the platform, such as common cryptocurrencies, or exchange it for native AIRT tokens.
Our AI-powered web 3.0 compatible platform aims to redefine experiences and streamline the entire creation process for digital arts, leveraging NFTs to monetize such arts seamlessly and securely.


Airt is a platform dedicated to AI related NFT assets generation and authentication.. used in art digital art work, painting, music and literature


AIRT is a decentralised platform for creation and ownership of robotic artists (AI Artists) and digital artworks generated by AI Artists. AIRTIST uses generative adversarial networks (GANs) to allow users to create their own digital artists using datasets from existing art pieces (in digital form) of contemporary or deceased famous artists The platform liberalises the ownership of digital arts by allowing users to create their own AI Artists and artworks and using Blockchain’s inherent properties (transparency, security, and immutability) to store their arts their mission is to decentralize the ownership of digital arts, allowing artists or novices to create, share, and monetise their creations

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                                                                                          MATRIX AI NETWORK BIO WALLET



After completion of finger vein registration features such as wallet creation, wallet login, wallet import, wallet backup, signing transactions, balance check, transaction history check, etc will all be supported




                                                            



                                                                 https://twitter.com/MatrixAINetwork/status/1526453723106578433?s=20