Thought Leader Interview with Dr. Steve Deng of Matrix AI Network

Thought Leader Interview with Dr. Steve Deng of Matrix AI Network

This week in our Thought Leader interview series we spoke to Dr. Steve Deng, Chief AI Scientist for MATRIX AI Network (MAN), a global open-source, public, intelligent blockchain-based distributed computing platform and operating system that combines artificial intelligence (AI) and blockchain.  MATRIX AI Network was created to make blockchains faster, more flexible, more secure, and more intelligent.

Professor Deng is an Associate Professor at the School of Software, Tsinghua University, where he has served as a faculty member since 2008.

Professor Deng’s research interests include machine learning, industry data analytics, and computer architecture.  He has authored over 50 papers. His textbook, “Structural VLSI Design and High-Level Synthesis,” is used by Tsinghua and other universities.

Professor Deng has served as Principal Investigator (PI) and Co-PI for numerous national-level research projects.  Since 2016, he has served as Vice Principal Architect of China Railway Rollingstock Corporation’s Prognostics Health Management for High-Speed Trains Project.

Professor Deng’s work on deep-learning based image detection was ranked #1 in many prestigious challenges including PASCAL VOC and VSCOCO; beating out teams from Google, Intel, Facebook, and Microsoft.  He has received numerous awards including “Best Paper” at the International Conference on Computer Design in 2013, the “NVIDIA Partnership Professor” Award and the Tsinghua University “Key Talent” Award.

Check out our exclusive interview below to learn a little more about AI, blockchain, and the present and future of Matrix AI Network.

Tell us a little bit more about the launch of the Matrix main net?

Our AI server allows users to directly process AI tasks over the blockchain using a simple interface.  The first wave of AI services on our main net includes image recognition models based on the same technology that won first place in the 2017 PASCAL Visual Object Classes (VOC) challenge and 2017 Microsoft COCO international competitions.  The AI features pose detection, AI-assisted cancer diagnosis, and 3-D model reconstruction of CT scans to assist in the diagnosis of rib fractures.

Our green mining machine is an AI accelerator, FPGA optimized to run a subset of deep learning models, that integrates with the blockchain consensus over the blockchain. We have used MCMC, or Markov Chain Monte Carlo methods in the past, which is one useful class of algorithms. At Tsinghua University my laboratory has developed a Bayesian computer to accelerate the MCMC algorithm. We have shifted our focus to deep learning.

Our main net has the capacity for DApps development, integration with the interplanetary filing system (IPFS) and cloud storage. We are also able to support AI-powered industrial IoT applications integrated with ERP systems, production line management, and ticketing systems.  This is invaluable for risk management, predictive analytics, visualization, and reporting tools.

How do you see blockchain and AI evolving into other industries?  Like VR and AR, for example?

The industry applications for blockchain and AI are well documented. AI applications in consumer applications are well-funded and relatively saturated. We’re focused on areas with high-impact, high specialization, and low adoption in industries with a high growth ceiling. Our current focus is on AI IoT applications in renewable energy and public safety, as well as a new computer and data-pooling solutions for AI-assisted medical diagnosis.

Tell us a little about what Matrix AI is doing in the healthcare technology space?

We are working with several highly regarded Chinese hospitals to develop early cancer diagnostic systems for lung, thyroid and liver cancers.  We have received detailed data relating to over 2,000 patients provided by top medical experts. The information covers all areas from early screening to CT imaging to biopsy data.  We are working now to expand the number of participating institutions and experts, for additional high-quality data, with the goal to develop more accurate AI models, a promising area of valuable research.

Tell us a little about what Matrix AI is doing in shipping and logistics?

We recently announced a collaboration with the OGI Ocean Gate Transportation Company to develop an intelligent global freight shipping application platform that will operate on Matrix AI Network’s blockchain and integrate big data information processing, smart contracts, DApps, financial services, and payment systems.

What can be done to help convince industries that are still reluctant to embrace AI and blockchain?

AI and blockchain are not monolithic ideas that can be sprinkled onto business services. They are an integral part of new powerful and sophisticated solutions, which require business needs analysis, an evolving data strategy, and management workflow closely tailored operational and market use.

Now that the main net is live, what is next for Matrix AI Network?

We are aggressively building out industry solutions in high impact areas; specifically, AI and industrial IoT and medical assisted diagnosis.

Where do you see Matrix AI Network in 5 years?  In 10 years?

Safely and effectively connecting and powering large-scale public/private partnerships in data management. This will support a thriving ecosystem of participants to strike a balance between business models, privacy, and scale of data that will make AI more pervasive and effective.

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