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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.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – May 2020

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

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.

“Above the Trend Line” – Your Industry Rumor Central for 6/15/2020

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.