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Cerebras Wafer-Scale Cluster Brings Push-Button Ease and Linear Performance Scaling to Large Language Models

Cerebras Systems, a pioneer in accelerating artificial intelligence (AI) compute, unveiled the Cerebras Wafer-Scale Cluster, delivering near-perfect linear scaling across hundreds of millions of AI-optimized compute cores while avoiding the pain of the distributed compute. With a Wafer-Scale Cluster, users can distribute even the largest language models from a Jupyter notebook running on a laptop with just a few keystrokes. This replaces months of painstaking work with clusters of graphics processing units (GPU).

ACH Fraud and AI/ML – Much Work to be Done

In this article, I give focus to the situation with the financial services industry embracing AI/ML to a high degree in so many areas, one would think AI/ML would be used to detect and prevent ACH fraud, but this is not generally the case. Even the largest banking institutions seem to wash their hands with regards to ACH fraud, leaving their customers to absorb the losses.

“Above the Trend Line” – Your Industry Rumor Central for 9/14/2022

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.

How to Optimize the Modern Data Stack with Enterprise Data Observability

In this sponsored post, our friends over at Acceldata examine how in their attempt to overcome various challenges and optimize for data success, organizations across all stages of the data journey are turning to data observability where they can get a continuous, comprehensive, and multidimensional view into all enterprise data activity. It’s a critical aspect of optimizing the modern data stack, as we’ll see. 

Contextualizing Pattern Recognition to Drive Business Insight

It’s time to decouple artificial intelligence from individual applications. Dr John Bates, CEO of SER Group contends that the time is ripe to shift from simple process automation to enterprise contextual intelligence.

TOP 10 insideBIGDATA Articles for August 2022

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.

China’s Plan To Be The AI Leader Makes Headway; Can The U.S. Thwart That Plan?

In this contributed article, Erika Twani, Co-founder and CEO of Learning One to One, discusses the global AI industry and how China’s plan to be the AI leader is making headway; and also how the U.S. can thwart that plan.

The Missing Puzzle Piece of the Modern-Day Enterprise: Responsible AI

In this contributed article, Kirti Dewan, VP of Marketing of Fiddler AI, discusses how a central problem with AI remains the same: a lack of model transparency. Many of the AI models businesses deploy today are considered to be opaque, which often leads to issues being detected after decisions have been made and people have already been affected

Heard on the Street – 8/30/2022

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.

Building an AI Culture – Your Roadmap to the Future

In this contributed article, Vrinda Khurjekar – Sr. Director – AMER Business – Searce, believes that companies struggling to improve operational processes need to adopt an AI-driven culture to survive. However, they shouldn’t rush. Instead, they must dedicate time in the design and planning phase to create holistic approaches that will stand the test of time.