What will 2020 look like in terms of AI and AIOps? I thought I’d break this down into three distinct areas: technology, market and users. For each of these I’ve come up with five major trends which I think will have significant impact on how AIOps, and AI in general, evolves over the next twelve months. At the outset I’d like to say that the most significant changes will be seen in user behaviors and user practices, this is the year where we will see substantial transformation. Let’s finish this series with five user trends…

What will 2020 look like in terms of AI and AIOps? I thought I’d break this down into three distinct areas: technology, market and users. For each of these I’ve come up with five major trends which I think will have significant impact on how AIOps, and AI in general, evolves over the next twelve months. At the outset I’d like to say that the most significant changes will be seen in user behaviors and user practices, this is the year where we will see substantial transformation. Now, let’s continue where we left off with the five market trends…

What will 2020 look like in terms of AI and AIOps? I thought I’d break this down into three distinct areas: technology, market and users. For each of these I’ve come up with five major trends which I think will have significant impact on how AIOps, and AI in general, evolves over the next twelve months. At the outset I’d like to say that the most significant changes will be seen in user behaviors and user practices, this is the year where we will see substantial transformation. But, let’s start with the five technology trends…

During 2020, deployment of AIOps functionality will migrate to an approach that delivers all algorithmic functions from a logically centralized platform. AIOps can be defined as the sequenced application of algorithms for data selection, pattern discovery, inferencing, communications, and robotics – applied against varied IT Operations use cases. Up to now, solution delivery has largely been piecemeal and data domain specific, an extension of existing management technologies and disciplines.

Neural networks have peaked in their ability to deliver effective and meaningful results. There are four big developments that will happen with AI. A crossover with computational neuroscience will happen soon. What will be the impact of this crossover? There will be an increasing focus on how AI algorithms interact with one another.

In this article, Will Cappelli explains why any business that does not deploy AI will either be afflicted with making really terrible decisions or being drowned by the fixed costs of making good decisions.

With IoT, you are giving devices, vehicles, buildings the ability to host algorithms and perform functions which can only be driven by software. Therefore, AI software is a must when you need to handle the complexity of the Internet of Things. In this article, Will Cappelli explores two major intersections of AI and IoT.