With AI Training Net, real-life AI training commences on the DeepBrain Chain computing power network
DeepBrain Chain, the world’s first AI computing platform powered by blockchain, today announced the commencement of its AI Training Net in preparation for creating a truly worldwide AI cloud-computing services platform. For context, the computing power needed for AI development has grown exponentially in recent years, currently doubling every three and a half months. Unfortunately, such exponential growth has become the chief bottleneck constraining AI’s development. DeepBrain Chain is endeavoring to build an affordable network in which spare capacity can be bought and shared, allowing this exciting field to continue to flourish.
AI Training Net is the precursor to full commercialization of the DeepBrain Chain platform: AI companies can now start to use the DeepBrain Chain system to train their models. In celebration of Training Net’s launch as well as to spark the DBC ecosystem, DeepBrain Chain will distribute DBC tokens to universities and research institutes working in AI for these pioneers to purchase AI computing power on the DBC network.
At present, among other projects being trained on DeepBrain Chain’s AI Training Net are multiple AI and machine-learning programs in the areas of Natural Language Processing, voice recognition, driverless cars, medical imaging, and more. Tech giants across the globe have been rushing to enter AI computing, but have failed to leverage blockchain-token incentives, which DeepBrain Chain has utilized to attract idle, high-quality computing power from around the world at an affordable price.
Advantages of DeepBrain Chain’s AI Training Net
- Optimized neural network computing performance: Currently, most AI products’ core algorithms are deep neural networks, so DeepBrain Chain has optimized operations on top of CUDA GPUs in order to support mainstream deep-learning frameworks, including but not limited to TensorFlow, Caffe, and CNTK.
- High concurrency: DeepBrain Chain’s unique load-balancing technology coordinates node containers in sharing the concurrency pressure to support massive numbers of AI enterprise users, who expect high-performance computing solutions.
- Low latency: Each DeepBrain Chain module utilizes as few resources as possible in order to ensure the fastest response to user requests.
- Privacy protection: Through encryption algorithms, DeepBrain Chain is able to protect the privacy of each participant in the ecosystem.
- Flexible supply: DeepBrain Chain’s flexible scaling technology allows for automatic container deployment so that content in a container can be quickly copied and deployed onto other idle containers during peak times.