• The Essential Guide: Machine Scheduling for AI Workloads on GPUs

    This white paper by Run:AI (virtualization and acceleration layer for deep learning) addresses the challenges of expensive and limited compute resources and identifies solutions for optimization of resources, applying concepts from the world of virtualization, High-Performance Computing (HPC), and distributed computing to deep learning.

Featured Stories

  • Do Business Intelligence Providers Trust Domain Experts? It Certainly Doesn’t Seem Like It

    n this special guest feature, Rob Woollen, CEO and Co-Founder of Sigma Computing, asks why rely solely on data analysts when you have a full team of experts that know their domain? Instead of simply sitting back and hoping for a eureka moment for your business, it’s time to level out the playing field for empowered data discovery — across all business teams.

  • Columbia University DSI Alumni Use Machine Learning to Discover Coronavirus Treatments

    Two graduates of the Data Science Institute (DSI) at Columbia University are using computational design to quickly discover treatments for the coronavirus. Andrew Satz and Brett Averso are chief executive officer and chief technology officer, respectively, of EVQLV, a startup creating algorithms capable of computationally generating, screening, and optimizing hundreds of millions of therapeutic antibodies. They apply their technology to discover treatments most likely to help those infected by the virus responsible for COVID-19.

  • Supercomputers vs Superviruses: Why Tech is Our Best Hope in the Coronavirus Pandemic

    In this contributed article, Golnar Pooya, a partner with IBM Digital Strategy practice, and an advisor at 7 Gate Ventures, suggests that in light of the global pandemic, AI gives us an incredible chance to protect life and we must arm it with the information it needs to do so. This outbreak only confirms the position of technology as mankind’s most important tool in protecting global health.

Featured Resource

NVIDIA’s New Data Science Workstation – a Review and Benchmark

This new whitepaper from NVIDIA’s Authorized Channel Partner, PNY Technologies, tests and reviews the recently released Data Science Workstation, a PC that puts together all the Data Science hardware and software into one nice package. The workstation is a total powerhouse machine, packed with all the computing power—and software—that’s great for plowing through data.

All Recent News

Industry Perspectives

  • For Service Providers, Big (network) Data is the New “Oil”

    In this special guest feature, Alex Pavlovic, Director, Product Marketing, Nokia Deepfield, discusses “Data is the new oil,” a phrase coined by The Economist, that has become the mantra for describing the platform-based economy driven by hyperscale players such as Google, Facebook, Amazon, Microsoft and Netflix. To reach their global audience, these webscale giants need the ubiquitous connectivity provided by service providers and their networks. These networks generate and store vast amounts of data on networks, infrastructure and services.

  • Lowering the Barrier to Entry for Cloud Computing is the Key to Scientific Discovery

    In this special guest feature, Ivan Ravlich, Co-Founder and CEO of Hypernet Labs, points out how the cloud industry needs to offer more accessible options to scientists and researchers who need to process large amounts of data. Containerizing scientific applications is a major step forward.

RSS Featured from insideHPC

  • NVIDIA Adds GPU and AI Expertise to COVID-19 HPC Consortium
    A task force of NVIDIA computer scientists has joined the COVID-19 High Performance Computing Consortium, which brings together leaders from the U.S. government, industry and academia to accelerate research using the world’s most powerful HPC resources. "The consortium’s objective is to accelerate development of effective methods to detect, contain and treat the coronavirus. It will […]

Editor’s Choice

  • What is the Difference Between Business Intelligence, Data Warehousing and Data Analytics

    In this contributed article, Christopher Rafter, President and COO at Inzata,, writes that in the age of Big Data, you’ll hear a lot of terms tossed around. Three of the most commonly used are “business intelligence,” “data warehousing” and “data analytics.” You may wonder, however, what distinguishes these three concepts from each other so let’s take a look.

  • COVID-19 Dashboard Uses Machine Learning to Track Global Pandemic

    Anodot, the company pioneering the autonomous monitoring space, has launched a public service including a machine learning driven analytics dashboard that monitors locally reported COVID-19 cases, and notifies users when a particular region’s numbers change significantly.

  • The insideBIGDATA IMPACT 50 List for Q1 2020

    The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting [READ MORE…]

  • Field Report: KDD 2019

    As a very long time member of the ACM and their SIGKDD group, I’d always wanted to attend a KDD conference (first one occurred in 1995). This year I received a gracious invitation to attend KDD2019 in Anchorage, Alaska, August 4-8. It satisfied two of my bucket list items: witnessing a KDD first-hand and also visiting Anchorage. I was not disappointed with the experience! What follows is my “Field Report,” a travel log if you will, chronicling my observations, both technical and cultural. KDD is touted as being “the premier interdisciplinary conference bringing together researchers and practitioners from data science, [READ MORE…]

  • The Harvard Data Science Initiative and The MIT Press Launch the HARVARD DATA SCIENCE REVIEW

    The Harvard Data Science Initiative (HDSI) and the MIT Press are pleased to announce the launch of the Harvard Data Science Review (HDSR). The multimedia platform will feature leading global thinkers in the burgeoning field of data science, making research, educational resources, and commentary accessible to academics, professionals, and the interested public. With demand for data scientists booming, HDSR will provide a centralized, authoritative, and peer-reviewed publishing community to service the growing profession.

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