Safety in data: Implementing data-driven road safety
Using data to improve road safety sounds like a good idea, but the devil is in the details.
Read More →The new Cloudera-Hortonworks Hadoop: 100 percent open source, 50 percent boring
How do you bring Hadoop to the AI, hybrid, and multi cloud era, making it so easy to use and reliable that it's boring? How do you build a sustainable business doing that, while switching to a 100-percent open source model? The new Cloudera raises more questions than it offers answers at this point
Read More →Nvidia GPUs for data science, analytics, and distributed machine learning using Python with Dask
Nvidia wants to extend the success of the GPU beyond graphics and deep learning to the full data science experience. Open source Python library Dask is the key to this.
Read More →Salesforce Research: Knowledge graphs and machine learning to power Einstein
Explainable AI in real life could mean Einstein not just answering your questions, but also providing justification. Advancing the state of the art in natural language processing is done on the intersection of graphs and machine learning.
Read More →Graph data standardization: It’s just a graph, making gravitational waves in the real world
AWS, Google, Neo4j, Oracle. These were just some of the vendors represented in the W3C workshop on web standardization for graph data, and what transcribed is bound to boost adoption of the hottest segment in data management: Graph.
Read More →Open source AI chips making Green Waves: Bringing energy efficiency to IoT architecture
What if machine learning applications on the edge were possible, pushing the limits of size and energy efficiency? GreenWaves is doing this, based on an open-source parallel ultra low power microprocessor architecture. Though it's early days, implications for IoT architecture and energy efficiency could be dramatic.
Read More →Habana, the AI chip innovator, promises top performance and efficiency
Habana is the best kept secret in AI chips. Designed from the ground up for machine learning workloads, it promises superior performance combined with power efficiency to revolutionize everything from data centers in the cloud to autonomous cars.
Read More →Confluent shows open source, paradigm shifts, cloud, and commercial success can all co-exist
Confluent just became a unicorn. We discuss why, what happens from now on, and how this is significant for the entire data ecosystem and the world at large with CEO Jay Kreps
Read More →Start the reskilling revolution without me: Future of Work trends and soft data on soft skills
As work is being redefined by automation as well as changing economy and social norms, how can technology help us stay abreast, discover, hone and document our skills, and match labor demand and supply?
Read More →Beyond experts: Jobs, tasks, and skills for a data driven Future of Work
Understanding and keeping track of the relationship between jobs, tasks and skills is essential for the future of work. If current efforts fall short, how can we do this going forward?
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