Network Traffic Analysis (NTA) is a key component of modern cybersecurity in companies. With machine learning and artificial intelligence solutions, the sheer amounts of data to analyze is an asset to be used rather than, as was once the case, a challenge to overcome.
While making predictions may be easy, delivering accurate ones is an altogether different story. That’s why in this column we won’t just be looking at the most important trends of 2020, but we’ll also look at how the ideas we highlighted last year have developed.
Where there is a show, there must also be a backstage. The more sophisticated the show, the more powerful the backstage will have to be to support it. IT operations are effectively the backstage of all business.
ICLR (The International Conference on Learning Representations) is one of the most important international machine learning conferences. It’s popularity is growing fast, putting it on a par with such conferences as ICML, NeurIPS or CVPR.
September brought us two interesting AI-related stories, both with a surprising social context. Despite its enormous impact on our daily lives, Artificial Intelligence (AI) is often still regarded as too hermetic and obscure for ordinary people to understand.
With chatbots powering up customer service on one hand and fake news farms on the other, Natural Language Processing (NLP) is getting attention as one of the most impactful branches of Artificial Intelligence (AI).
With this edition of AI Monthly Digest, we have now for a full year been bringing readers carefully selected and curated news from the world of AI and Machine Learning (ML) that deepsense.ai’s team considers important, inspiring and entertaining.
Monitoring brand visibility is an important business problem. We describe our solution for logo detection and visibility analytics with deep learning.
AI models are skilled in Chess, Go, StarCraft and, since July, six-player Texas Hold’em Poker. But the hunt for inhuman players has begun.
Computer vision enables machines to perform once-unimaginable tasks like diagnosing diabetic retinopathy as accurately as a trained physician or supporting engineers by automating their daily work.