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XAI: Are We Looking Before We Leap?

This four part report from our friends over at SOSA highlights the challenges and advances when it comes to regulations, relevant use-cases, and emerging technologies taking the mystery out of AI.

Driving ROI Through AI

This new report from ESI ThoughtLab was conducted alongside our friends over at DataRobot as well as a coalition of other AI leaders. The report shows that despite high adoption rates of AI in enterprises, ROI in AI still remains a work in progress and will take skill, scale, and time.

How big data works? How we use it at FunCorp, and why it’s one of our most important tools

The latest report on big data from FunCorp discusses how an increased usage in smartphone users has also led to a rising demand for better mobile apps. These modern apps also use tremendous amounts of data, and thus, a robust management tool for analyzing and managing this data has become a necessity. This is where the use of Big Data comes in (this includes FunCorp too). The company develops apps and has relied heavily on big data. Read this report to learn how.

Be (More) Wrong Faster – Dumbing Down Artificial Intelligence with Bad Data

In this white paper, our friends over at Profisee discuss how Master Data Management (MDM) will put your organization on the fast track to automating processes and decisions while minimizing resource requirements, while simultaneously eliminating the risks associated with feeding AI and ML data that is not fully trusted. In turn, your digital business transformation will be accelerated and your competitive edge will be rock solid.

The Real AI Revolution: Machines That Learn Like Scientists

In this compelling white paper, our friends over at causaLens highlight how ML has wrongly become synonymous with AI. We must shake off this misconception to start  the real AI revolution. Data science must forgo its reliance on curve-fitting ML and return to its roots; to put the science back into data science. causaLens is a major contributor to this new science of causality. And it is the company’s mission to help  organizations of all types to benefit from it.

The Future Starts Now – Achieving Successful Operation of ML & AI-Driven Applications

Operationalizing AI and ML has become an unavoidable need in business, as various industries heavily rely on large volumes of real-time data as input to automated decision-making processes to yield the best results. Use cases in the data science field have shown that ML models and AI have few tangible business benefits until they are operationalized. In this e-book, our friends over at MemSQL show us how to successfully deploy model-driven applications into production.

Building Powerful Enterprise AI Infrastructure: How to Design Enduring Infrastructure for AI

Our friends over at cloud-neutral colocation data center company Interxion have published a whitepaper titled, “Building Powerful Enterprise AI Infrastructure: How to design enduring infrastructure for AI,” which details the requirements of an ideal infrastructure environment when it comes to reaping the benefits of today’s growing volume of data and enabling AI at scale.

Enterprise Search in 2025

This white paper by enterprise search specialists Lucidworks, discusses how data is eating the world and search is the key to finding the data you need. The enterprise search industry is consolidating and moving to technologies built around Lucene and Solr. In the next few years we’ll see nearly all search become voice, conversational, and predictive. Search will surround everything we do and the right combination of signal capture, machine learning, and rules are essential to making that work. Fortunately, much of the technology to drive this is available to us today!

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.

Machine learning for all: the democratizing of a technology

In this short eBook, you’ll discover automated machine learning using H2O.ai. H2O.ai has dedicated itself to democratizing all aspects of AI, including machine
learning. H2O Driverless AI is a machine learning solution that automates AI for nontechnical
users. So-called “AutoML” solutions like H2O Driverless AI are rising in popularity for enterprises across a wide range of industries. With it, users can build robust, fast, and accurate machine learning solutions. It also includes visualization and interpretability features that explain the data modeling results in plain English, fostering further adoption and trust in AI.