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Is there a More Environmentally Friendly Way to Train Artificial Intelligence?

In this special guest feature, Omri Geller, Co-founder and CEO at Run:AI, takes a timely and interesting look at one of the most pressing issues facing the computing industry by an accomplished data scientist. The issue relates to how machine learning is developed. In order for machine learning (and deep learning) to be able to accurately make decisions and predictions, it needs to be “trained.”

Gaining the Enterprise Edge in AI Products

In this contributed article, Taggart Bonham, Product Manager of Global AI at F5 Networks, discusses last June, OpenAI released GPT-3, their newest text-generating AI model. As seen in the deluge of Twitter demos, GPT-3 works so well that people have generated text-based DevOps pipelines, complex SQL queries, Figma designs, and even code. In the article, Taggart explains how enterprises need to prepare for the AI economy by standardizing their data collection processes across their organizations like GPT-3 so it can then be properly leveraged.

“Above the Trend Line” – Your Industry Rumor Central for 3/30/2021

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.

Book Excerpt: Real World AI

This article was adapted from the recently released best-selling book, Real World AI, written by Alyssa Rochwerger and Wilson Pang. Alyssa is the director of product at Blue Shield of California and has previously served as VP of product for Figure Eight (acquired by Appen), VP of AI and data at Appen, and director of product at IBM Watson. Wilson is the CTO of Appen and has over nineteen years’ experience in software engineering and data science, having served as the chief data officer of Ctrip and the senior director of engineering at eBay.

What’s So Great about AIOps

In this special guest feature, Gerry Miller, CEO at Cloudticity, takes a look at the emerging technology dubbed “AIOps.” AIOps, according to Gartner, “combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” The basic operating model for AIOps is Observe-Engage-Act.

Microsoft Azure AI for Health Initiatives

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insideBIGDATA Latest News – 3/22/2021

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.

Professionalize AI to Maximize Investment

In this special guest feature, Fernando Lucini, global lead, data science and machine learning engineering, Accenture Applied Intelligence, reviews the four steps organizations can use to professionalize AI. If AI is formalized within an organization as a trade, including proper training and standards, it can be strategically scaled to ensure it’s maximizing the best results for an organization and, in turn, providing the best return on investment.

ACM Issues Computing Competencies for Undergraduate Data Science Curricula

Recognizing the explosive growth of data science as a field, as well as the demand for data science training at the undergraduate level, a Data Science Task Force convened by the Association for Computing Machinery’s Education Board recently released “Computing Competencies for Undergraduate Data Science Curricula.” The ACM report seeks to define what the computing/computational contributions are to this new field, as well as to provide guidance on computing-specific competencies in data science for departments offering such programs of study at the undergraduate level.

Innovative AI Edge Device Cuts Costs and Delivers Faster Performance

Leopard Imaging has been working to address the need for affordable multiprocessing power in deep learning applications. Using Socionext’s SC2000 image signal processor and the Hailo-8™ M.2 AI acceleration module, Leopard Imaging’s EdgeTuring™ consumes less power, performs at a higher level, and ensures greater reliability for video analytics and privacy at the edge than alternative solutions.