SONM Hardware AI Neural Network
It is evident great changes will come to our society over the coming years. Neural network and artificial intelligence are two very exciting industries. At the same time, the hardware we use every day becomes smarter and more powerful. Fog computing will benefit tremendously from all of these breakthroughs and eve introduce a new wave of innovation over the coming years.
Solving The Cloud Server Computing Focus
Although technology enthusiasts have made great progress with deep learning an AI so far, one glaring issue remains. To be more specific, the vast majority of hardware sued for these developments revolves around cloud server computing. While that is not necessarily a bad idea, it introduces some new problems that will eventually hinder growth and development of these industries.
To be more precise, cloud server computing is sued for both training and executing of deep learning models. Right now, that is a viable business structure, although it can come at a rather expensive price. Unfortunately, it does not allow for much customization, and forces developers to sign up for lengthy contracts they may not need right now.
Some of the AI-based projects relying on cloud server computing include AlphaGo and NVIDIA’s surveillance project. Additionally, newly announced UK startup Graphcore is looking to build their Intelligent Processor Unit. However, all of these projects will eventually be hindered by the lack of proper scaling provided by cloud server computing. Moreover, there is always the risk of putting proprietary information in the hands of a third party, which creates a major security risk.
To be more precise, cloud server hardware is definitely evolving in the right direction. New chip designs improve memory bandwidth, and introduce computation on graphs rather than relying on vectors or scalars. In the long run, speed and efficiency of all cloud server computing process should be improved. Changing the fundamental data structure sued in cloud computing is a big deal, although it is not hard to see why graphs are the superior solution.
AI And Neural network Continue To Evolve
To ensure AI solutions and neural networks can evolve, the solutions will need to return more and better results in the future. A faster and more efficient model training will lead to a better user experience and an increased level of engagement between the user and the AI or neural network. This is the logical chain of evolution to make AI and neural networks more robust, smarter, and more attractive.
These concepts require larger data sets, which are provided by this logical evolution of AI and neural networks. In the end, it allows developers to optimize their model performance, which will be of great value to our society as a whole. In the end, it will come down to providing better and more efficient AI solutions compared to anyone else active in the same industry.
The SONM Multi-Agent System
This is where fog computing comes into the picture, as it can solve all of the problems found in traditional cloud computing. SONM Has been working on a multi-agent system to promote everlasting learning conception. To be more specific, every piece of information shared through the network will be distributed to all agents, creating a larger data set for companies and startups to use for their own offerings.
The team is confident machine intelligence is the future of computing. However, a graph-based processing approach will be the future of computers as a whole. There is a dire need for new and better machine learning hardware right now. SONM is on the right track to provide that solution to companies and individuals all over the world.
More importantly, the project revolves around decentralized fog computing, which allows users to harness computing power of nearby devices to complete tasks. This will provide a lot of useful data for artificial intelligence and neural networks moving forward. In the end, this will result in the creation of decentralized and powerful supercomputers, while harnessing the power of artificial intelligence at the same time.
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