Technology is not showing signs of slowing down any time soon. As we move into cloud computing, big data, natural language processing and artificial intelligence, the employment sector is gearing up for a big boost in the number of opportunities. Organisations such as Google, Microsoft, Facebook and Apple are aggressively hiring people with expertise in these domains, which makes them highly lucrative. Artificial intelligence is particularly on the cusp of a breakthrough. Technologies such as machine learning, neural networks, genetic algorithms and deep learning are receiving a lot of spotlight.

With the evolution of modern technology and wholesome digital transformation, there is enormous availability of the highest-paid jobs in technology. In the past career options were limited, there were only a few jobs in specific industries like medicine or IT. But now there are ample opportunities where one person can get certified even when they are still working. Want to give your career a good start and to make sure about your skillset? Here is the list of the top 10 highest-paid tech jobs for you.

Artificial Intelligence is all over the place. If you attended our post-summit AI symposium we held during Global Summit 2018 in San Antonio, you certainly got a taste of the varied use cases where AI can make a difference. But what does it take to build an AI-powered application? Do you start implementing tedious data-gathering processes for training your models? Or do you first scour the job market for a handful of those elusive data scientist unicorns, which itself may take years?

Recently deep learning has shattered all records when it comes to machine learning. In this short talk you will gain a basic understanding of the two simplest types of layers: the dense, and convolutional layer. Roland Meertens is Machine Learning Engineer at Autonomous Intelligent Driving. This video was recorded at QCon.ai 2018: https://bit.ly/2piRtLl The InfoQ Architects' Newsletter is your monthly guide to all the topics, technologies and techniques that every professional or aspiring software architect needs to know about.

Ritesh Madan shows how Celect uses the historical data (point of sales transaction, inventory, product attributes, product images, product descriptions) to build a SaaS solution that helps buyers and merchants predict the future demand of products for the upcoming season. The short talk covers the real life problem statement, high level ML frameworks, and how the product is used by buyers and merchants. This video was recorded at QCon.ai 2018: bit.ly/2piRtLl The InfoQ Architects' Newsletter is your monthly guide to all the topics, technologies and techniques that every professional or aspiring software architect needs to know about. Over 200,000 software architects, team leads, CTOs are subscribed to it.

In last article I tried to show my vision on what research areas are maturing and can grow big this year. Research is cool, but there must be something from AI world that became mature in 2017 and is ready now to be used in mass applications. This is what this article will be about -- I would like to tell about technologies that are good enough to be used in your current work or to build your own startup based on them. Important note: this is the list of AI areas, algorithms or technologies that are ready to use right now. For example, you can see time series analysis in the list, because deep learning is rapidly replacing previous state of the art in signal processing.