Lecture Collection

Lecture Collection - Natural Language Processing with #DeepLearning (Winter 2017) [Stanford]

  • Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication.
  • This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation.

Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture s…
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Boeing Takes Stake in AI, Machine Learning Tech Developer

Boeing Takes Stake in #AI, #MachineLearning Tech Developer-  #ArtificialIntelligence

  • “SparkCognition is at the forefront of a technological shift in machine learning and artificial intelligence that will revolutionize every aspect of industry,” according to Boeing CTO Greg Hyslop.
  • Boeing’s stake was placed through HorizonX, a venture it set up recently to direct investment capital for technology commercialization and new market access.
  • SparkCognition develops “machine learning technology” — i.e., artificial intelligence — particularly for applications in information technology, energy, oil-and-gas, manufacturing, finance, aerospace, defense, telecommunications and security.
  • Reportedly, several of the initial investors investors joined Boeing and Verizon Ventures in the new funding.
  • “SparkCognition is at the forefront of a technological shift in machine learning and artificial intelligence that will revolutionize every aspect of industry.

Boeing is investing in SparkCognition, a developer of “machine learning technology” for IT, energy, manufacturing, aerospace, defense, and other sectors.
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Semiconductor Engineering .:. A Learning Machine For Machine Learning -Semiconductor Engineering

A Learning Machine For #MachineLearning --  #ArtificialIntelligence #AI

  • Many of these systems will need to work in real time, and that requires massive local processing capability.
  • Many options, but only one chance to pick the right combination to hit the power, performance and area (PPA) target of the final system.
  • To begin, you need a massive knowledge base of all combinations of process technologies, technology options, IP and package configurations.
  • You also need to capture the profiles of CPU, disk, memory and I/O bandwidth required for many types of advanced designs, and for the various steps in the design process.
  • A system that designs machine learning systems is still on the horizon, but using machine learning to help build machine learning chips is very real.

Building the systems that power machine learning is an immensely complex task.
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