Adopting artificial intelligence (AI) has become a strategic imperative. Early adopters are achieving massive returns, while those who wait run the risk of falling behind. In order to empower more decision-makers across business units, it is essential for organizations to embrace democratization of both data and AI.Companies seeking to democratize the entire AI lifecycle are mobilizing new data. However, a key challenge is that internal data is often siloed and restricted, which makes discovery and deployment harder than ever.
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Anaconda
Data scientists love the wealth of awesome capabilities offered by Python packages like Numpy, Pandas, and scikit-learn. However, these capabilities historically have been limited to data that can fit on a single machine. In Scaling Python with Dask, Lead Dask Developer Matt Rocklin will show how simple Dask makes scaling beyond a single machine while supporting the packages you’re already using.
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Infovista
95% of IT Decision Makers say their network is important or critical to their company’s digital transformation. Unfortunately, today’s digital enterprise can no longer be supported by yesterday’s enterprise network! SD-WAN promises to deliver business agility and improved application performance, but recent commissioned research conducted by Forrester Consulting for Infovista shows only 22% of enterprises not using SD-WAN expect to achieve better consistency in end-user application experience.
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AI Trends
AI is a red-hot topic, even overhyped, some say. We will show why the latter group may well be right–about general AI, anyway. One thing’s for sure: we’re not going to have personal AI assistants anytime soon. Narrow AI applications–that is, practical, focused ones–are a different matter altogether. We believe such applications in business will deliver on their promise and revolutionize the world as we know it.
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