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insideBIGDATA Guide to Optimized Storage for AI and Deep Learning Workloads

This new technology guide from DDN shows how optimized storage has a unique opportunity to become much more than a siloed repository for the deluge of data constantly generated in today’s hyper-connected world, but rather a platform that shares and delivers data to create competitive business value. The intended audience for this important new technology guide includes enterprise thought leaders (CIOs, director level IT, etc.), along with data scientists and data engineers who are a seeking guidance in terms of infrastructure for AI and DL in terms of specialized hardware. The emphasis of the guide is “real world” applications, workloads, and present day challenges.

AI in the Enterprise: Trends & Insights on Vendor Selection and Implementation

A new report was released by our friend over at Leverton, a data extraction startup recently acquired by MRI Solutions, titled “AI in the Enterprise: Trends & Insights on Vendor Selection and Implementation.” The report lends insight into the experiences and preferences of “leaders,” “lookers,” and “laggards” (defined below) when it comes to AI deployment.

DarwinAI Generative Synthesis* Platform and Intel® Optimizations for TensorFlow* Accelerate Neural Networks

DarwinAI, a Waterloo, Canada startup creating next-generation technologies for Artificial Intelligence development, announced that the company’s Generative Synthesis platform – when used with Intel technology and optimizations – generated neural networks with a 16.3X improvement in image classification inference performance. Intel shared the optimization results in this recently published solution brief. The complexity of deep […]

AI-Driven Data Catalogs for the Insights-Driven Enterprise: How to Find the Right Data Catalog

Data lakes have turned into data swamps. Metadata initiatives have derailed. As a result, data discovery and retrieval are ongoing, head-banging challenges. In the universal search for a workable solution, data catalogs are quickly rising to the top of the list. Download the new report from Io-Tahoe that outlines some of the major considerations to help you find the AI-driven data catalog that will work best for your organization. 

Intelligent Sensing: The Impact of AI on Sensor Capabilities

The rise of artificial intelligence (AI) is unlocking a wave of new sensor applications and driving market demand for intelligent sensing – the ability to extract insights from sensor data. To guide innovation and investment in this fast-evolving market, the team at Lux Research, a leading provider of tech-enabled research and advisory services for technology innovation, took a deep dive into how and where enhanced AI analytics are rapidly improving the […]

Alternative Data for Investment Management

From hedge fund managers to mutual funds and even private equity managers, alternative data has the power to improve valuation of securities and boost the clarity of the investment process.  Techniques like natural language processing and machine learning allow organizations to better capitalize on alternative data. These technologies enable processing of large, heterogenous, and unstructured sets at an extremely fast rate. A new report from SparkCognition explores the challenges for alternative data adoption, how to overcome them, and explores the potential of automation.

A Blueprint for Preparing Your Own Machine Learning Training Data

Download the new guide from Alegion that acts as a pre-flight checklist for data science teams that are contemplating preparing their own maching learning training data.

Four Types of Machine Learning Bias

AI models comprise algorithms and data, and they are only as good as their underlying mathematics and the data they are trained on. When things go wrong with AI it’s because either the model of the world at the heart of the AI is flawed, or the algorithm driving the model has been insufficiently or incorrectly trained. Download the new whitepaper from Alegion that can help AI project leads and business sponsors better understand the four distinct types of bias that can affect machine learning, and how each can be mitigated.

Four Real-Life Machine Learning Use Cases: A Databricks guide

Databricks Unified Analytics Platform is a cloud-service designed to provide you with ready-to-use clusters that can handle all analytics processes in one place, from data preparation to model building and serving, with virtually no limit so that you can scale resources as needed. Download the new guide that walks readers through four practical end-to-end Machine Learning use cases on Databricks.

Unified Analytics for Dummies: Accelerate AI Innovation

In this Databricks e-book, you not only discover how to avoid and overcome the most common challenges impacting AI success, but a new concept is also introduced. Download the new e-book that explores Unified Analytics, a concept that brings together solutions that unify data science and data engineering, making AI much more achievable for enterprise organizations and enabling them to accelerate their AI initiatives.