Every Monday, we take a step back and look at all the cool stuff that went down during the previous week. Last week, we spoke to Red Hat’s Jan Wildeboer about open source software development, interviewed the creator of Eclipse Theia, and learned how to combat bias in AI algorithms. Let’s take a closer look.
When artificial algorithms are biased, this can create unethical results, which in turn can lead to PR disasters for businesses. In this article, you will learn about three different types of AI bias – algorithmic, technical, and emergent – and what measures can be used to limit them.
We’re going to need high dimensional probability and statistics and model it in high dimensional geometry. This is why AIOps is inevitable. This article examines four of the reasons why people distrust AI and what properties define big data.
Take a look at our brand new ML Magazine, in which the authors will give you a full idea of the cutting edge of machine learning—from tutorials for certain tools to insights about the relationship between AI and ethics. Don’t miss our first issue that includes an interview with Noam Chomsky.
How can machine learning and artificial intelligence change the landscape of manufacturing? According to reports by Deloitte and McKinsey, machine learning improves product quality and has the potential to double cash flow. Let’s take a look at three global manufacturers who are already on board.
Demucs is a new research project by Facebook AI. It is designed to separate musical tracks into different instruments or vocals, similar to how a human can detect the specific instruments, and solve the problems of existing approaches. In the long run, Demucs could be applied to other AI tasks as well.
AI is finding a wide variety of uses for images and video, including auto-cropping and resizing, automating image tagging, and creating video auto-previews. This article examines five examples of how AI is used to enable image and video management at scale at Cloudinary.
Humans are introducing their own biases and prejudices into machine learning. As advanced as AI can be, having been built by humans, it can still share some of our own ethical shortcomings. The usage of proper databases during training is one of the ways to help prevent biases from developing within artificial intelligence.
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…
Artificial intelligence is complex, and as integration with businesses continues, certain areas will impact enterprises. We are seeing a rise in integration, especially in regards to apps relying on API for combining services and data from different systems. This article explores four scenarios that will be affected by AI and integration in the year 2020 and beyond.
In the bigger picture, big data services companies are providing better-integrated Data analytics services and an AI scale to accelerate innovation. What is unified data analytics? Read about the Unified Data Analytics platform and the benefits of AI and big data analytics solutions.
Manual efforts to gather such a huge amount of information could eat up a lot of time. Hence, AI is leveraged to automate the stage and deliver flawless results while saving a lot of time and resources. Embedded AI and ML can help security testing teams in delivering greater value through automation of audit processes that are more secure and reliable.
