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Domino Data Lab Announces Hybrid MLOps Architecture to Future-Proof Model-Driven Business at Scale

Domino Data Lab, a leading Enterprise MLOps platform trusted by over 20 percent of the Fortune 100, announced its new Nexus hybrid Enterprise MLOps architecture that will allow companies to rapidly scale, control and orchestrate data science work across different compute clusters — in different geographic regions, on premises, and even across multiple clouds.

Making a Case for the First Open Source Platform for Synthetic Data

In this special guest feature, Yashar Behzadi, Ph.D., CEO and Founder of Synthesis AI, discusses on the importance of a community like OpenSynthetics in developing more capable AI models.
OpenSynthetics, an open community for creating and using synthetic data in AI/ML and computer vision, is open to practitioners, researchers, academics, and the wider industry.

Streamlining Data Evolution in a Rapidly Changing World

In this contributed article, Adam Glaser from Appian believes that in a fast-changing, digital-driven world, having access to the right data at the right time is crucial. That is why, as data evolves, it must be brought together in a reliable and efficient way that creates a powerful asset, not a compliance challenge. 

Backprop Bonanza

Many new data scientists have voiced what they feel is the lack of a satisfying way to learn the concepts of back propagation/gradient computation in neural networks when taking undergrad level ML classes. So I thought I’d put together a number of useful learning resources to jump-start an understanding for this important process. The following list, curated from an informal Twitter poll, appears in no particular order.

Heard on the Street – 6/20/2022

Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.

Research Highlights: Emergent Abilities of Large Language Models

In this regular column we take a look at highlights for breaking research topics of the day in the areas of big data, data science, machine learning, AI and deep learning. For data scientists, it’s important to keep connected with the research arm of the field in order to understand where the technology is headed. Enjoy!

Great Expectations Study Reveals 77% of Organizations have Data Quality Issues 

Great Expectations, a leading open-source platform for data quality, announced the results of a survey highlighting top pain points and consequences of poor data quality within organizations. Insights from 500 data practitioners (engineers, analysts, and scientists) showed that 77% have data quality issues and 91% said it’s impacting their company’s performance.

How to Overcome Patient Obstacles with Conversational Intelligence

In this special guest feature, Amy Brown, Founder and CEO of Authenticx, discusses speech analytics in healthcare. Organizations must listen and learn from patients’ voices to gather insights, customize their approach and facilitate change and growth.

Real-time, Real Value: 80% of Businesses See Revenue Increases Thanks to Real-time Data

KX and the Centre for Business & Economics (CEBR) have published ‘The Speed to Business Value’ an industry report showing the commercial and operational benefits to be gained by businesses adopting real-time data analytics technologies.

Using Basic Data to Improve Public Services

In this contributed article, Prahlad Koti, a Partner at Netcompany, examines exactly what we mean when we talk about basic data, and how its digitization can assist the public and private sector. The digitization of public services is at the very top of government agendas across Europe, but the lack of accessible and reliable data, such as core information about individuals and businesses, creates challenges for digital administration.