#machine learning

People-centric and smart space tech

Adopt these 10 strategic technologies in 2020

Take a look into the crystal ball. What does Gartner predict for 2020? Here are ten strategic trending technologies that tech leaders should have on their radar in the coming years. Augmented and virtual reality might train employees in the future, voting might become based on a blockchain, and AI security might become the most important factor in risk management.

Achieving efficiency

The impact of ML and AI in security testing

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.

What we learned at ML Conference 2019 in Berlin

Saving lives with deep learning, creating smarter chatbots and more: 10 takeaways from ML Conference 2019

ML Conference 2019 had lots of exciting talks and insights to offer. How can we make chatbots smarter and provide machines with abilities such as ethical values or emotional intelligence—and how can deep learning help save lives? We’ve collected 10 takeaways to share some highlights of our Berlin conference.

Exploration, training and deployment

Why Kubernetes and containers are the perfect fit for machine learning

Both machine learning and the use of cloud-native environments built on containers are becoming more commonplace in the enterprise. Luckily, Kubernetes and containers are a perfect match for ML. The cloud-native model has many advantages that can be brought over to machine learning and other forms of artificial intelligence for more effective, practical business strategies.

Interview with Xander Steenbrugge

Generative Adversarial Networks: “GANs can create new ‘realities’ that never existed”

Generative Adversarial Networks (GANs) have recently sparked an increasing amount of interest, as they can generate images of faces that look convincingly real. What else are they capable of, what risks could they pose in the long run, and what do they have in common with the emerging internet in the 1990’s? We interviewed ML Conference speaker Xander Steenbrugge.