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TOP 10 insideBIGDATA Articles for June 2020

In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. Over the past several months, we’ve heard from many of our followers that this feature will enable them to catch up with important news and features flowing across our many channels.

Model Risk Management in the Age of AI

In this contributed article, Stu Bailey, Co-Founder and Chief AI Architect of ModelOp, discusses how financial services companies can easily validate multiple AI/ML models and reduce ML project costs by 30% through automation. ModelOps refers to the process of enabling data scientists, data engineers, and IT operations teams to collaborate and scale models across an organization. This drives business value by getting models into production faster and with greater visibility, accountability and control.

insideBIGDATA Latest News – 6/29/2020

In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.

Key Trends Framing the State of AI and ML

In this special guest feature, Rachel Roumeliotis, Vice President of Content Strategy at O’Reilly Media, provides a deep dive into what topics and terms are on the rise in the data science industry, and also touches on important technology trends and shifts in learning these technologies.

Where Predictive Machine Learning Falls Short and What We Can Do About It

In this contributed article, technologist Bernard Brode takes a look at where prediction machine learning falls short, the implications of this, and what can be done about it. Machine learning often fails in unexpected ways, which makes managing the risks of deploying the technology difficult.

Transform Raw Data to Real Time Actionable Intelligence Using High Performance Computing at the Edge

In this special guest feature, Tim Miller from One Stop Systems discusses the importance of transforming raw data to real time actionable intelligence using HPC at the edge. The imperative now is to move processing closer to where the data is being sourced, and apply high performance computing edge technologies so real time insights can drive business actions.

Accelerated Machine Learning Available from Your Browser

InAccel, a pioneer on application acceleration, makes accessible the power of FPGA acceleration from your browser. Data scientists and ML engineers can now easily deploy and manage FPGAs, speeding up compute-intense workloads and reduce total cost of ownership with zero code changes.

Global Study Sponsored by Qlik Finds Strong Relationship Between Optimizing Data Pipelines and Business Value

Qlik® announced a global study that shows organizations that strategically invest in creating data-to-insights capabilities through modern data and analytics pipelines are seeing significant bottom line impact. The global IDC survey, sponsored by Qlik, of 1,200 business leaders* shows that companies with a higher ability to identify, gather, transform, and analyze data to glean insights benefited from higher quality decision making and better business outcomes, including improved operational efficiencies, increased revenue and increased profits.

Intel Announces AI and Analytics Platform with New Processor, Memory, Storage and FPGA Solutions

Intel today introduced its 3rd Gen Intel Xeon Scalable processors and additions to its hardware and software AI portfolio, enabling customers to accelerate the development and use of AI and analytics workloads running in data center, network and intelligent-edge environments. As the industry’s first mainstream server processor with built-in bfloat16 support, Intel’s new 3rd Gen Xeon Scalable processors makes artificial intelligence (AI) inference and training more widely deployable on general-purpose CPUs for applications that include image classification, recommendation engines, speech recognition and language modeling.

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.