Alice, the making of: Behind the scenes with the new AI assistant from Yandex
Did you ever wonder what it's like to build an AI personal assistant, or to bridge the language gap? Hint: There's big data and machine learning involved.
Read More →Insight platforms as a service: What they are and why they matter
The convergence of cloud, automation and collaboration has created a new class of offerings for data driven insights. We take a look at their defining characteristics, featuring analysis from Forrester and commentary from Qubole.
Read More →Raiders of the storm: The data science behind weather prediction
What kind of data and techniques are used to model and predict weather and climate? How do you reduce uncertainty and communicate complexity? Are Harvey and Irma signs of climate change, and is it going to get worse?
Read More →In-memory architecture + streaming data = Digital Twins?
The Digital Twin is a buzzword in its prime time infancy. We take a look at what it is and how it relates to modern data architectures, examining ScaleOut's adoption and implementation and comparing with other alternatives.
Read More →Supercharging your image: Machine learning for photography applications
Advanced capabilities for image retrieval and processing are relatively new and powered to a large extent by advances in machine learning technology. We present a brief history of this space, and share the story of how Shutterstock has embraced this technology and what it does for them.
Read More →Will the real Elon Musk please stand up? Autonomous bots and synthesized speech in the public domain
The ability to create virtual clones that appear to think and talk like the real thing is very much real, as it has been done for Elon Musk and Barack Obama. We discuss techniques and potential with the people behind them.
Read More →Alibaba: Building a retail ecosystem on data science, machine learning, and cloud
What does it take to compete in a global arena in which retail and cloud are increasingly intertwined? Domain-specific data science and machine learning for the masses, according to Alibaba.
Read More →NBA analytics: Going data pro
For the NBA, like every other sports league, awards are important. They can generate attention, spur debate, make money, and involve fans, players, and experts, among others. Is there data science and analytics behind them — can there or should there be? We picked the NBA Most Improved Player award as an example to analyze some aspects of data-driven culture.
Read More →Kafka: The story so far
Hard problems at scale, the future of application development, and building an open source business. If any of that is of interest, or if you want to know about Kafka, real-time data, and streaming APIs in the cloud and beyond, Jay Kreps has some thoughts to share.
Read More →Artificial intelligence on Hadoop: Does it make sense?
MapR just announced QSS, a new offering that enables the training of complex deep learning algorithms. We take a look at what QSS can offer, and examine AI on the Hadoop landscape.
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