Social encounters

Q1: What is Epicognition and how does it help Matrix?

EpiCognition is a new research institute headed by Professor Deng. It aims to boost the adoption of AI and IoT technologies in manufacturing and transportation industries, specifically. They will specialize in custom sensor networks and AI models to deliver a complete range of prognostic health management solutions, operational status monitoring and prediction, fault prediction, and remaining useful life prediction. Epicognition will help Matrix secure projects and partners to use Matrix’s blockchain and AI solutions.

Q2: It was previously mentioned that we might see up to 10 DAPPS by end of the year. Is this still on track?

This is still in the right ballpark, though its not 100% guaranteed of course. Some are developed in-house, some are developed by outside developers — we can only control in-house. That being said, 10 is still a reasonable estimate.

I’ll also add that some of these DAPPs may not technically be DAPPs by the end of the year. Some may still be “APPs” or “DAPP/APP” hybrids at that time depending on how testing goes. All will be DAPPs in their final form, though.

Q3: What percentage of Professor Deng’s time is devoted to Matrix? Does he continue teaching as a Professor?

Professor Deng is absolutely still an active professor at Tsinghua University (one of the top 2 Universities in China). He is also still actively heading the AI side of the Matrix AI Network. These two positions work in concert as most of our AI employees are his former students.

In terms of time-split, it’s hard to say. The balance of his schedule is up to him. When its busy at the university, he may spend less time in the Matrix offices — and vice versa.

However, it feels like this question is asking to what extent Professor Deng is involved with the Matrix AI Network. To that, I’ll say he is fully involved and is an active participant/leader. Despite being in different offices, I see him at least weekly — if not several times a week. He still actively leads Matrix’s AI team and is the final decision-maker on all things AI.

Q4: In general, which members of the Matrix Management team are full time?

All of them.

Q5: Could you please provide an update as to the progress of natural language smart contracts? When is this platform likely to be live?

As far as I know, progress has been slow but steady. We hope to release an open, public demo in September.

Q6: Could you try to release a PDF for each Masternode GMAN release with a technical FAQ?

Sure! No problem. We will do so for the next update — and for subsequent updates.

Q7: What is happening with Huobi?

I know everyone wants us to be able to say… it will be done of XXXX date. Unfortunately, I can’t.

All I can say is that we’ve been in contact with them throughout — as recently as the past few days. As of right now, they are not ready to do it. My best estimate is Q4. But we are keeping on them to get it done as soon as possible.

Q8: When will the android wallet be released? Owen said June? Is that on track?

Yes, the wallet will release by the end of the month. Both Android and IOS versions. My apologies to Windows Phone owners~

Q9: Do you have a plan to fix the incredible amount of read/write caused by running Masternodes?

Yes

Q10: Can we have some details on how the devs will reduce the blockchain size?

Combine this with the above question — the tech team has a plan in place to address the blockchain size as well as the read/write frequency. They aren’t ready to share specific technical details yet but say that they will roll out the change in an update about 2 months from now. They want to let the chain get bigger before rolling out this change/update.

I’m combining a few questions in this next one… the original questions might not be specifically answered but they all relate to disatisfaction with LevelDB.

Q11: Will Matrix consider switching from LevelDB?

The team has heard that there is disatisfaction among the community regarding the use of LevelDB. They are currently evaluating/testing alternatives. Currently, they are deciding between RocketDB and Redis+mysqlserver.

Q12: Can you share any more info regarding the development with the office in the USA? Any timeline or something?

As mentioned previously, we have successfully registed for a business license in silicon valley. A few of my colleagues are heading down there next week to get some facetime with a few of our business partners.

Once open, this office — as mentioned last time — will focus on AI model research and development. Its secondary function will be to faciliate forming business cooperations with entities in that part of the world.

Q13: Whats the formal process for hospitals and other companies inside China to use the AI services provided by Matrix?

Currently, there are two major ways. First, before formally becoming a partner, they can access some basic functions on our web wallet.

The second and “more formal” option is that use on-site terminal equipment. This is the case with current partner hospitals using our AI services.

Q14: When can we expect AI services to be used? I presume not until the hardware farms are organized?

Also replying to Anu — AI services are already being used/tested in our partner hospitals.

Rolling out to much larger scale also requires our compute and data attribution solutions to be put into place. Once that development is completed, they it can really take off.

Q15: Is is possible to filter dates when viewing the hashrate chart of tom.matrix.io? We would like to check further bacl than 2 days.

Currently, this was limited to 2 days as loading in that much data was making tom.matrix.io too slow. I’ve let the tech team know that there’s demand for this information. They responded that they will look into offloading this data onto a separate webpage for interested parties to access/peruse.

Q16: Will there be tools to check how our nodes are doing? For example, a tool to check my personal mining hashrate etc.

This is part of the long-term plan but is currently considered a low-priority item, to be honest.

Q17: In a future release, GMAN could introduce a “call home” feature that is transported across port 50505. This would allow the ability to keep tabs on what nodes are and are not online and report on. Will this kind of feature be introduced?

Similar to above, this kind of feature is not imminent. Currently, this can basically be accomplished by pinging your node via ICP from a computer on a different network. Not exaclty what’s being asked for in this question (and lacks UI), but a possible workaround~

Q18: What private chain developments have been made? What’s the story here?

There are some projects interested in private chains that have opened discussions, but they are not yet been developed. We’re not ready to talk about these yet.

Q19: Can we see the promised smart city fire demo?

We still have some work to do on this. We will discuss with our partners to try and determine a specific time to share more.

Q20: What functionality has Matrix implemented to ensure there isn’t a possibility of a one-to-many validator or miner scenario, where a single master wallet can control many masternodes?

The situation with miners and validators is different.

We actually have no problem with a single person/entity controlling several Mining Masternodes. We’d consider this a good thing. It is quite the opposite with Verification Masternodes. We don’t want large Verification Masternodes to stake several smaller ones.

Part of our reward design disincentivizes this behavior by increasing the selection rate on the basis of stake and by giving guaranteed selection to truly gigantic Verification Masternodes that exceed 1/19th of the total network stake. It is not in a large V node’s interest to divide itself and stake several smaller Verification Masternodes.

We can say that with Mining Masternodes — the more the better. With Verification Masternodes, we’d rather have fewer, more stable nodes.

Q21: What measures are being taken to support Matrix’s developer community?

There is still a lot of work to do on this front. As I understand it, after the next gman update, the team plans to open an RPC port for community developers. After that, they will prepare formal developer documentation then start actively reaching out and making overtures.

Q22: How much computational power is currently distributed through the Matrix AI Network? Is this measurable?

Currently not. This function will be rolled-out alongside our compute and data attribution solutions.

Q23: How are you pricing private token sales?

I have no details to share about this besides to say large private sales are always on a case-by-case basis. All will have lock-up periods.

Q24: Can you run through some of the teams plans to lower the barrier of entry to mining?

This ties a little bit into a previously asked question about community developers. A Matrix core-team developed 1-click solution/executable to launch a Matrix Masternode is not imminent. We’ve talked with the tech team about this before — right now, they are still focused on improving and expanding the underlying tech.

Q25: What about the Bloomberg Article (When Bloomberg)?

Actually, this was a video interview. It was for a programme called Beyond Innovation. As I understand it, between the filming date and air date, the relationship between Beyond Innovation and Bloomberg changed. Beyond Innovation is now best described as a programme that airs on Bloomberg TV.

A brief snippet of the interview with Matrix CEO Owen Tao was featured in Episode 25: Burger-Flipping Robots, Intent-Based Networking, Smart City Technology & More. It aired on Bloomber TV during the May 11–12 weekend.

In this interview Dr. Steve Deng, Chief AI Scientist for Matrix AI Network, speaks on how this company is using blockchain to transform the healthcare business, and what the future of the industry holds.

1. What’s the story behind MATRIX AI Network? Why and how did you begin?

Dr. Steve Deng began his academic career as a computer scientist with a focus on computer aided design of integrated circuits, but gradually migrated to high-performance computer architectures and GPU based parallel computing. Since 2013 Dr. Steve Deng’s group has been conducting advanced research in various areas of artificial intelligence, including industry data mining, deep learning, and brain-inspired computer architecture. As a result its work on deep learning-based object detection has been ranked number one in several prestigious machine learning challenges such as PASCAL VOC 2017, COCO 2017 and CVPR WAD 2018

2. Please describe your use case and how MATRIX AI Network uses blockchain.

>> The first wave of AI services includes our image recognition models. It also has pose detection, AI-assisted cancer diagnosis, and a 3-D model reconstruction of CT scans to diagnose rib fractures.

>> AI, in coordination with blockchain, has the potential to improve the accuracy of medical diagnoses, detect diseases and medical conditions at an earlier stage, and limit the variability in the quality of care a patient receives; just to name a few obvious advantages. We are targeting several challenging healthcare-related problems that are dependent on treatment records and laboratory testing we are collaborating with leading hospitals to develop cutting-edge research.

>> One of MAN’s most distinct advantages is its access to high quality patient data from early screening, to CT imaging, until biopsy. Currently, Matrix has the data of over 2,000 patients and all data labeled by top physicians in China.

3. Could you share a specific customer/user that benefits from what you offer? What has your service done for them?

Matrix is building a diagnosis and treatment solution to assist in the diagnosis of thyroid cancer and liver cancer. The deep learning capability provided by MAN’s Bayesian Proof of Work algorithm is ideally suited for this development. It will help with the daily work of pathologists which require extraordinarily high levels of concentration and an extremely diverse knowledge base, it also facilitates a greatly increased accuracy and efficiency with pathological diagnoses.

4. What other blockchain healthcare use cases are you excited about?

>> Technological solutions to respond to the healthcare needs of a growing global population, and blockchain technology and AI are uniquely able to meet this challenge.

>> Technology can be adapted toward streamlining the health insurance space, pharmaceutical logistics, maintaining the safety and integrity of drugs from manufacture to distribution, sales and more.

5. Where will MATRIX AI Network be in five years?

>> The first level of applications is to leverage the power of AI to make better blockchains. For instance, MATRIX already developed tools to automatically identify the bug recently found in the EOS chain.

>> The second level is AI applications running on top of a blockchain. Such AI apps may or may not use the data stored in the blockchain. And the payment has to be made in the corresponding tokens. One such application Matrix is working on is medical image processing.

>> The third level of applications is to export the computing power of nodes in a blockchain network for real-world applications. The idea is to replace the Hash computations, which have no value outside the cryptocurrency, with a new mining function that creates values beyond the cryptocurrency. One such example is the training of deep neural network. Of course, the training procedure may not be a pure stochastic gradient descent one. Instead, Matrix will introduce new mechanisms such as the evolution algorithm.

To sum up, modern society, computing is becoming a basic human need, something similar to bread and butter. So, the computing power is a new resource. Blockchains offer a brand-new opportunity to mobilize such a global resource to build the biggest computer ever. By properly designing the incentive mechanism, personal computers, tablets, and even cell phones can be connected into the network and provide computing power.

The article covers deeper background on Matrix’s AI work and the future of Matrix AI Network.

“We’re a unique platform for incubating AI capabilities with our AI server and green mining AI accelerators.” Dr. Steve Deng

>> 48% of global funding for AI start-ups came from China in 2017.

>> The national Made in China plan aims to grow AI to 150 billion RMB by 2020.

Alibaba, Baidu, Tencent and JD have led the charge. Who is next?

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