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A 4-Step Approach to Building your Predictive Analytics Stack

In this special guest feature, Slava Koltovich, CEO at EastBanc Technologies, speaks to the infinite possibilities of cloud-based predictive analytics and provide key strategies companies should consider when building a predictive analytics stack.

H2O.AI Brings Lightning-Fast Machine Learning to Enterprises with NVIDIA GPU Acceleration

[GPU Technology Conference Coverage], today announced that it has collaborated with NVIDIA to offer its best-of-breed machine learning algorithms in a newly minted GPU edition. In addition, H2O’s platform will be optimized for NVIDIA® DGX-1™ systems.

Interview: Jennifer Marsman, Principal Software Development Engineer at Microsoft

In this podcast interview, I caught up with Jennifer Marsman, Principal Software Development Engineer at Microsoft, to find out what it’s like to be a data scientist at Microsoft and get her take on the upward trajectory of AI and deep learning that we’re seeing in the industry today.

Data Science And Deep Learning Application Leaders Form GPU Open Analytics Initiative

[GPU Technology Conference Coverage] Continuum Analytics,, and MapD Technologies have announced the formation of the GPU Open Analytics Initiative (GOAI) to create common data frameworks enabling developers and statistical researchers to accelerate data science on GPUs. GOAI will foster the development of a data science ecosystem on GPUs by allowing resident applications to interchange data seamlessly and efficiently.

Neurala Announces Deep Learning AI for Self-Driving Cars, Drones, Toys and Other Machines That Can Learn on the Device Without Using the Cloud

[GPU Technology Conference Coverage] Neurala announced a major advance in deep learning with software that can learn with or without the cloud and eliminates the risk of forgetting its previous knowledge. The new patent-pending approach means that for the first time a self-driving car can be personalized by each owner or dealer to a specific neighborhood; a parent can teach a toy to recognize a child, without infringing on privacy; and industrial machines can be updated in the field for specific tasks.

Kinetica and Fuzzy Logix Partner to Bring GPU-Accelerated Advanced Analytics to Market

[GPU Technology Conference Coverage] Fuzzy Logix, Inc., provider of high performance, advanced analytic solutions and Kinetica, provider of the fast, in-memory analytics database accelerated by GPUs, today announced a partnership to offer a joint solution that will allow customers of both companies to leverage high performing advanced analytics with acceleration of 100-500x over CPU-only solutions.

Mobilizing PostgreSQL Databases for Realtime Applications

In this special guest feature, Andrew Konoff, Technical Evangelist at Realm, discusses the benefits of mobilizing Postgres SQL databases for realtime applications.

Medable Launches Cloud-Based Machine Learning Solution for Healthcare

MEDABLE Inc., a leading application and analytics platform for healthcare, announced Cerebrum, the first cloud-based machine learning solution created specifically for healthcare apps. Cerebrum leverages data gathering smartphones with a first-of-its-kind machine learning engine, resulting in health events becoming more easily predicted, such as warning an elderly relative when he is at greatest risk of a fall, or preventing an asthmatic child from triggering a life threatening episode.

GPU Technology Conference 2017 in Silicon Valley, May 8-11

GTC is the largest and most important event of the year for GPU developers. GTC and the global GTC event series offer valuable training and a showcase of the most vital work in the computing industry today – including artificial intelligence and deep learning, healthcare, virtual reality, accelerated analytics, and self-driving cars. The event is hosted by GPU giant NVIDIA,

The Hidden Costs of Bad Data

In this contributed article, Arvind J. Singh, CEO, Chairman, and Co-Founder of Utopia, Inc., looks at how data continues to be the basis of many top decisions made by every business. By learning by the mistakes other have made in the past, we can help bad data from having a costly impact in the future.