ThirdAI
ThirdAI (pronunciation: /THərd ī/ Third eye) is a cutting-edge Artificial intelligence startup carving scalable and sustainable AI. ThirdAI accelerator builds hash-based processing algorithms for training and inference with neural networks. The technology is a result of 10 years of innovation in finding efficient (beyond tensor) mathematics for deep learning. Our algorithmic innovation has demonstrated how we can make Commodity x86 CPUs 15x or faster than most potent NVIDIA GPUs for training large neural networks. The demonstration has shaken the common knowledge prevailing in the AI community that specialized processors like GPUs are significantly superior to CPUs for training neural networks. Our innovation would not only benefit current AI training by shifting to lower-cost CPUs, but it should also allow the “unlocking” of AI training workloads on GPUs that were not previously feasible.
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Latent AI
We take the hard work out of AI processing on the edge. The Latent AI Efficient Inference Platform (LEIP) enables adaptive AI at the edge by optimizing for compute, energy and memory without requiring changes to existing AI/ML infrastructure and frameworks. LEIP is a modular, fully-integrated workflow designed to train, quantize, adapt and deploy edge AI neural networks. LEIP is a modular, fully-integrated workflow designed to train, quantize and deploy edge AI neural networks.
Latent AI believes in a vibrant and sustainable future driven by the power of AI and the promise of edge computing.
Our mission is to deliver on the vast potential of edge AI with solutions that are efficient, practical, and useful. Latent AI helps a variety of federal and commercial organizations gain the most from their edge AI with an automated edge MLOps pipeline that creates ultra-efficient, compressed, and secured edge models at scale while also removing all maintenance and configuration concerns
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TFLearn
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorial and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, metrics. Full transparency over Tensorflow. All functions are built over tensors and can be used independently of TFLearn. Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs, and optimizers. Easy and beautiful graph visualization, with details about weights, gradients, activations and more. The high-level API currently supports most of the recent deep learning models, such as Convolutions, LSTM, BiRNN, BatchNorm, PReLU, Residual networks, Generative networks.
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Zebra by Mipsology
Zebra by Mipsology is the ideal Deep Learning compute engine for neural network inference. Zebra seamlessly replaces or complements CPUs/GPUs, allowing any neural network to compute faster, with lower power consumption, at a lower cost. Zebra deploys swiftly, seamlessly, and painlessly without knowledge of underlying hardware technology, use of specific compilation tools, or changes to the neural network, the training, the framework, and the application. Zebra computes neural networks at world-class speed, setting a new standard for performance. Zebra runs on highest-throughput boards all the way to the smallest boards. The scaling provides the required throughput, in data centers, at the edge, or in the cloud. Zebra accelerates any neural network, including user-defined neural networks. Zebra processes the same CPU/GPU-based trained neural network with the same accuracy without any change.
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