NEWS

UK - bottom of the class for AI?

Companies in the UK are lagging behind their global counterparts when it comes to artificial intelligence (AI) and machine learning (ML) implementation, with just one in ten organisations (10%) able to boast mature capabilities – compared to one in six (17%) worldwide.

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NEWS

AI solving real-world problems and AI ethics among top trends for 2021

Data science, machine learning, and AI experts highlight the top AI and ML trends they expect to shape the data science industry in 2021.

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NEWS

MInd the learning gap

Rackspace Technology has published the results of a global survey that reveals that the majority of organizations globally lack the internal resources to support critical artificial intelligence (AI) and machine learning (ML) initiatives.

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NEWS

Alteryx partners with Snowflake

New innovations and integrated offering provide organizations Alteryx automated analytics and machine learning on Snowflake.

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NEWS

Machine learning via managed service

Calligo launches 'world’s first' managed service to make machine learning accessible to any business.

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NEWS

IEEE highlights importance of AI, ML, 5G and IoT

Chief information officers and chief technology officers surveyed on 2021 opportunities, challenges and key technology trends.

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Two thirds of financial services executives say disruptive technologies will have a positive impact...
Amadeus Ventures will invest in the travel tech startup which uses machine learning to help...
Announces first commercial availability of key technologies from Project Debater.
Super Micro has introduced that it says is the industry’s broadest portfolio of validated...
Research from Blue Yonder, a JDA Company, in collaboration with Microsoft finds vast majority of...
86% of IT executives surveyed believe human work, AI systems, and robotic automation must be...
Latest Video

LinkedIn Automates All of the Easy Things, and Makes all of the Hard Things Easy

Hear LinkedIn’s senior SRE, Todd Palino, share how the company continually improves the state of its infrastructure, so that the developers who are rolling out applications have a framework that they can do it within, and they can do it safely. LinkedIn currently generates over 50 terabytes a day of unique metrics on applications. No human is going to look at 50 terabytes a day of data and get anything useful out of it, so LinkedIn relies on systems give them some useful signal out of all that noise. By moving down the road of machine learning, LinkedIn can now do anomaly detection using machine learning models.

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