MSP Channel Insights

What will the New Year hold for the world of AI and ML?

Posted 6 years ago in by Phil Alsop

2018 was huge for technology, but now that we’ve rung in the new year, it’s time to turn our attention to 2019 and what this coming year will bring. As we are heading towards a world of driverless cars and smart cities, artificial intelligence (AI) and machine learning (ML) is starting to impact almost every aspect of our lives. With this in mind, four IT and data experts have come together to share their thoughts on how these advances will further impact the technology landscape in 2019.

BLOG

Four key considerations for enterprises starting their journey into machine learning

Posted 6 years ago in by Phil Alsop

Machine learning is having a profound impact on many organisations. It is enabling functionality ranging from personal shopping recommendations to automated customer support through to financial fraud detection and compliance. Ninety per cent of CIOs using machine learning expect it to help them drive greater top-line revenue growth. By Joe Hellerstein, Co-Founder and Chief Strategy Officer, Trifacta and Jim Gray Chair of Computer Science at UC Berkeley.

BLOG

Is your automated technology a threat to customer relationships?

Posted 6 years ago in by Phil Alsop

We’ve all been there: trying to call our bank, GP, or utility provider, and having to press an infinite number of keys to get through to an automated voice that will make us wait on the line while letting us know that we’re number 20 in the queue. Companies claim that automating communication with the customer is making their journey much more efficient and streamlined. But is that really the case or are companies just putting a barrier between them and their customers? By Neil Hammerton,...

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.

Read more