Building vs. buying AI News
May 18, 2018
A new developer kit from Intel seeks to lower the bar for doing deep learning on CPUs and other types of chips to extract more intelligence from video.
July 31, 2017
Think before you act on artificial intelligence technologies to ensure that your efforts to become a "cognitive business" lead you in the right direction.
Building vs. buying AI Get Started
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Deep learning is powering the development of AI. To build your own neural network, start by understanding the basics: how neural networks learn, correlate and stack with data. Continue Reading
AI encompasses a wide range of disciplines, from advanced math to application development, and building a strong AI team starts with incredibly skilled data scientists. Continue Reading
Before AI can revolutionize business processes or decision-making, companies need a strong foundation. These tools, platforms and applications help enterprises get started with AI. Continue Reading
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GPUs are often presented as the vehicle of choice for running AI workloads, but the push is on to expand the number and types of algorithms that can run efficiently on CPUs. Continue Reading
MLaaS allows companies to add machine learning capabilities without software development. There are still some barriers to entry, however, and providers are not one-size-fits-all. Continue Reading
Before autoML can improve model building and deployment, enterprises need to choose a platform. Here, we evaluate autoML platforms by category, key features and accessibility. Continue Reading
Manage Building vs. buying AI
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As standardized NLP framework evaluations become popular, experts urge users to focus on individualized metrics for enterprise success. Continue Reading
A shortage of data for machine learning training sets can halt a company's AI development in its tracks. Turning to external sources and hidden data can solve the problem. Continue Reading
Problem Solve Building vs. buying AI Issues
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Most data science projects end up facing similar problems, such as lack of robustness and data quality issues. In this feature, experts offer tips on how to overcome these challenges. Continue Reading