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Building vs. buying AI News
June 30, 2021
Dell Technologies spotlighted its open source Omnia software as part of its latest initiatives to ease the deployment and management of HPC, AI and data analytics workloads.
June 09, 2021
The market is ripe for more AI M&A deals as enterprise demand for AI talent, MLOps and vertical applications rose during the pandemic.
March 31, 2021
A new OSDU standard aims to bring information from oil, gas, wind, solar and other sources into a single data platform to help energy companies address future demand.
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.
Building vs. buying AI Get Started
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Executives are aware of the value artificial intelligence in its many forms can bring to enterprises yet devising a viable AI strategy can be as complex as the technology itself. Continue Reading
Making machine learning more accessible and helping developers with AWS SageMaker training is at the core of Julien Simon's book, 'Learn Amazon SageMaker.' Continue Reading
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
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Business leaders should consider their employees' technical expertise, technology budgets and regulatory needs, among other factors, when deciding to build or buy AI. Continue Reading
Enterprises are adopting machine learning technologies at rapid rates. In this machine learning guide, we break down what you need to know about this transformative technology. Continue Reading
In the past year, AI hyperscalers got serious about their machine learning platforms, expectations were reset and transformer networks empowered the GPT-3 language model. Continue Reading
Manage Building vs. buying AI
Learn to apply best practices and optimize your operations.
Maximizing the value of insights into your business, industry and competition requires a thoughtful, creative, experimental, incremental and team approach to deploying AI. Continue Reading
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