Google's DeepMind has developed a groundbreaking tool called GNoME that utilizes deep learning to expedite the process of uncovering new materials. This innovative technology has the potential [...]
Tech leaders need to put AI and its subcategories into practice--and into common business vocabulary that everyone can understand.
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Keras sequential models make deep neural network modeling about as simple as it can be
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Deep learning is the state-of-the-art method for many AI challenges. Companies are failing to adopt it because of these four key challenges.
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Global Deep Learning Market size is expected to reach $256.2 billion by 2023, rising at a market growth of 31% CAGR during the forecast period.
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A team of researchers from Nvidia have developed a new deep learning technique that allows robots to be taught to mimic human actions just by observing how people perform certain tasks. This technology can greatly reduce the amount of time…
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To assess the true opportunities for AI, and to distinguish the hype from the reality, one must understand this algorithm category and what makes it revolutionary.
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There’s a lot of confusion out there about deep learning performance. How do you measure it? What should you measure? The simple answer: PLASTER. The not so simple reality: “Hyperscale data centers are the most complicated computers the world has ever made — how could it be simple?” NVIDIA CEO Jensen Huang explained at NVIDIA’s Read article >
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Insight Engine Smart Data Platform™
Fullstack AI ( Augmented Intelligence) One of the most challenging issues facing organizations is deriving insights from complex heterogeneous data. While it can be challenging to simply store the sea of data available today, the real value is derived when understanding
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Combining Natural Language Processing with Deep Learning integrated with Search allows users to train Vertical Knowledge Sets while they work.
