Conference Deep-Dive:

Machine Learning, Data Science & Artificial Intelligence 

Machine Learning, Data Science & Artificial Intelligence  

Take a deeper look machine learning, artificial intelligence and data science before heading to the summit with a selection of Gartner content including smarter with Gartner articles, webinars and predicts. 

 

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5 Ways Data Science and Machine Learning Impact Business 

Data science and machine learning are having profound impacts on business, and are rapidly becoming critical for differentiation and sometimes survival. Being able to quickly categorize the potential impacts into one of five categories, and communicate their potential, will help data and analytics leaders drive better results.

 

Gartner research director Erick Brethenoux explains the five categories of impact and provides real-world examples taken from the worlds of government, sport and business.

 

 

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Webinar: Key Trends in AI and Machine Learning 

No trend in the past 10-15 yrs has created as much buzz as artificial intelligence (AI) and machine learning (ML). During this webinar, we discuss the latest trends in how machine learning drives artificial intelligence, what is enabling AI, where the cutting edge is (including examples), and what the limitations are of current technology. We will also cover the complexities involved when organizations are trying to create their own ML / AI application from scratch and how to overcome them.

 

Watch On-Demand Webinar Here

 

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How to Get Artificial Intelligence ‘Right’

Given the pervasive nature of artificial intelligence (AI), the consequences of IT getting AI right or wrong are potentially profound. When used incorrectly, AI can unintentionally rinforce harmful biases, increase polarization and result in other damaging consequences.

 

To use AI accurately, companies need to build the case for data literacy as a new core competency for both creators and consumers of AI. Gartner advises leaders responsible for enabling AI initiatives to follow this three steps process: First, build AI right, then use AI right and ultimately keep AI right.

 

Read the three steps here

 

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Gartner Predicts:
  • By 2024, a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.
  • By 2020, 20% of citizen in developed nations will use AI assistants to help them with an array of everyday, operations tasks.
  • By 2022, enterprise AI projects with built-in transparency will be 100% more likely to get funding from CIOs.
  • In 2020, AI becomes a positive net job motivat4ed, creating 2.3 million jobs while only eliminating 1.8 million jobs

 

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