https://www.ai-tech.io/EXECUTIVE SUMMARY
The parent company of Solidus Ai Tech Limited, “Solidus Technologies” were founded in December 2017 as a cryptocurrency mining firm with a particular focus on mining Ethereum (ETH) via GPU-based mining rigs. Before Solidus Technologies launched
they teamed with software development company Soft Galaxy International. Soft Galaxy assisted the establishment and maintenance many large-scale cryptocurrency mining projects throughout Europe.
Solidus Technologies raised around $5.7 million via their network
of investors during the cryptocurrency market downturn of 2018.
The bulk of the investment was used to purchase thousands of “ GPU Servers, which were installed in an unused facility to which
Soft Galaxy has access. The remainder of the funds were used
to build an 8,000 square foot purpose built state-of-the-art data centre in Bucharest.
Solidus Technologies has a long-term goal of Ethereum mining. In the present scenario, however, when Ethereum is running 100% on the proof of stake algorithm, Ethereum will no longer be mineable. This is due to the pending updates and developments in the Ethereum roadmap.
When Solidus Technologies launched in December 2017, the company was aware that Ethereum would very likely move from ‘proof of work’ to ‘proof of stake’ and would no longer be mineable largely due to the aforementioned pending updates and developments in the Ethereum roadmap. Furthermore, the recent EIP-1559 upgrade will eventually make Ethereum deflationary. The Solidus Technologies team knew that
this scenario was probable, and pre-emptively developed relationships with Governmental Authorities and Megacorps who would likely require AI services in the future.
During the financial crash of April 2020, the demand for AI services rose significantly due to COVID-19 restrictions. Across every industry, the adoption of AI has exceeded predictions for growth. AI is creating new products, boosting revenues, reducing costs and drastically improving efficiencies. The inexorable evolution of technologies has reached the point where there is an urgent need to solve problems with
high computational requirements, the solution of which cannot be provided by a single computing unit. To meet these requirements, Solidus Ai Tech has implemented heterogeneous distributed systems of unparalleled computational capacity and has secured a number
of partnerships with Governmental Authorities and Corporate Entities.
Solidus Technologies’ joint venture partner, Soft Galaxy International have been approved via the European Union for
a €3.5 million grant to help towards completing the existing data centre infrastructure and to scale up operations. Solidus Ai Tech will raise $43 million from this token offering to complete the project. A full breakdown of the how these funds will be utilized can be seen on pagcan be seen on page 19 (Fund Management).
When the data centre and IaaS platform is complete, Solidus
Ai Tech will begin generating revenue from Governmental Authorities, Megacorps, SMEs and professionals. The long-term plan is to scale up by building additional data centres nearby.
In preparation, additional land has been identified by our partner, Soft Galaxy International. All of our data centres will follow our unique protocol.
GENERAL OVERVIEW OF THE PROJECT
A wide variety of machine learning applications use HPC Servers, including deep learning, image recognition, autonomous cars, real-time voice translation, and more. Machine learning is not new, but the increase in available data and more powerful HPC Servers allow for faster and more efficient parallel computing. The processes involved in machine learning used to take a year to complete; now with HPC Servers, the same processes only take mere weeks or days. HPC appliances supporting multiple NVIDIA HPC Servers will allow machine learning to go even further.
In one of the greatest technological transformations ever undertaken, the AI revolution is happening right now. AI has an impact on cybersecurity, platform support, and HPC for industry. Solidus Ai Tech and its partners aim to become the leader of this democratisation of AI, building the technology that will make communities safer and more connected everywhere.
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SOLIDUS AI TECH WHITEPAPER 1.0
The deep learning with HPC computing applications that Solidus Ai Tech plans to implement are as follows:
♦ Voice-processing solutions for call centres, financial services, insurance, and other industries
♦ Deep learning-based software dedicated to industrial image analysis
♦ A development software solution based on a state-of-the-art set of algorithms in machine learning
♦ Geospatial visualisation of 3D and 2D data, mensuration, and mission planning
♦ Image processing and analytics with machine learning and deep learning
♦ Real-time full-motion video and wide-area motion imagery enhancement and computer vision-based analytics software for intelligence analysts
♦ Electromagnetic signals propagation modelling for complex urban and terrain environments
♦ The Automatic Spatial Modeler (ASM) is designed to generate 3D point clouds with accuracy similar to light detection and ranging (LiDAR), which can extract 3D objects from stereo images.
♦ Medical applications — AI-powered tools can be an extra set of ‘eyes’, helping clinicians to quickly read images, calculate measurements, monitor changes, and identify urgent findings to optimise workflows and enhance patient care. Image processing serves a crucial role in the aid of disease prevention, early detection, diagnosis, and treatment. Medical imaging procedures are often computationally demanding because of the large medical datasets required to process clinical applications. HPC Servers are massively parallel computational engines, ideal for computationally expensive tasks in a wide range of medical applications.
♦ Bioinformatics in medicine — The field of bioinformatics is used
in many different applications, including medicine. Bioinformatics enables advances such as drug discovery, diagnostics, and disease management. The methods of bioinformatics can be applied to diagnose cancer subtypes, predict the survival time of cancer patients, identify the mode of action of candidate drugs, model protein binding, and model drug target properties. In the future, doctors may be able to perform genomic analyses on cancer patients, and the results of those analyses could help them determine the drug treatments that will be the most effective for those particular patients. Speeding up bioinformatics with HPC Servers will hopefully help advance the field for the benefit of all.
♦ Research — Today’s research requires infrastructure that can handle large computational workloads to derive fast and accurate insights from vast amounts of data. Researchers are using OSS and NVIDIA platforms to expand breakthroughs in HPC, AI, and machine learning as well as data science in disciplines such as robotics, autonomous vehicles, and healthcare.
♦ Autonomous vehicle and ITS management using AI/deep learning
— The cars in these fleets need to be outfitted with specialised HPC equipment, including high bandwidth data ingest systems tied to the myriad of video, radar, and LiDAR sensors in the car, high-capacity and low-latency storage subsystems, and HPC engines that can perform the AI machine learning and inference tasks needed to enable the vehicle to see, hear, think, and make decisions just like human drivers.
♦ This project is designed to operate and help reform different branches of government services within the context of a digital transformation agenda.
AI is a core component of any digital transformation initiative today. This is witnessed in the rapid growth of the industry from $281.3 billion in 2020 to the forecasted $327.5 billion revenue
in 2021 and $554.3 billion in 2024. The core component of this growth is powered by the underlying, highly sophisticated AI hardware and infrastructure. None of the AI innovations would be possible without the simultaneous growth and innovation in AI hardware. From the humble CPU from just a few years ago, the industry has progressed to HPC, FGPA and yet a very hungry AI industry needs and demands so much power from its hardware.
Per the latest report from Stanford University, the speed of
AI computation power doubles every three months, basically outpacing the forecast of the well-established several-decades- old Moore’s Law, which states that ‘computation power would double every 24 months’. Furthermore, today, compared with 2012, the computing resources required to train cutting-edge AI models have grown over 300,000 times, while the transistor count has grown a mere four times in NVIDIA HPC Servers.
To address such hyper-aggressive demand for AI computer resources – which, soon, no single organisation will ever be able to fulfil internally – Solidus Ai Tech will be building one of the world’s finest state-of-the-art AI infrastructure data centres, starting in Europe and then expanding globally. These facilities will be offered to Governmental Authorities, Megacorps, SMEs and Professionals in a highly secure manner, enabling them to augment and protect their businesses.