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The following tables compare notable software frameworks, libraries, and computer programs for deep learning applications. ... Vertex.AI, Intel: 2017 Apache 2.0: Yes
With AI systems increasingly employed into critical frameworks of society such as law enforcement and healthcare, there is a growing focus on preventing biased and unethical outcomes through guidelines, development frameworks, and regulations. Open-source AI has the potential to both exacerbate and mitigate bias, fairness, and equity, depending ...
In the context of AI, it is particularly used for embedded systems and robotics. Libraries such as TensorFlow C++, Caffe or Shogun can be used. [1] JavaScript is widely used for web applications and can notably be executed with web browsers. Libraries for AI include TensorFlow.js, Synaptic and Brain.js. [6]
1 the Road, the first novel marketed by an AI. [75] AlphaFold is a deep learning based system developed by DeepMind for prediction of protein structure. [76] Otter.ai is a speech-to-text synthesis and summary platform, which allows users to record online meetings as text. It additionally creates live captions during meetings.
Analysts at International Data Corp. (IDC), a provider of market intelligence, predict that worldwide revenues for the AI market could reach $900 billion by 2026, logging a compound annual growth ...
It is designed to follow the structure and workflow of NumPy as closely as possible and works with TensorFlow as well as other frameworks such as PyTorch. The primary functions of JAX are: [71] grad: automatic differentiation; jit: compilation; vmap: auto-vectorization; pmap: SPMD programming
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