Heard on the Street – 3/7/2024

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.

Hammerspace Unveils the Fastest File System in the World for Training Enterprise AI Models at Scale

Hammerspace, the company orchestrating the Next Data Cycle, unveiled the high-performance NAS architecture needed to address the requirements of broad-based enterprise AI, machine learning and deep learning (AI/ML/DL) initiatives and the widespread rise of GPU computing both on-premises and in the cloud. This new category of storage architecture – Hyperscale NAS – is built on the tenants required for large language model (LLM) training and provides the speed to efficiently power GPU clusters of any size for GenAI, rendering and enterprise high-performance computing.

Using Clinician Big Data to Alleviate a Struggling Workforce

In this contributed article, Charlie Lougheed, CEO and co-founder of Axuall, explains why healthcare needs to adjust its thinking and in what ways clinician big data can make impactful changes throughout the healthcare industry, from credentialing to attrition.

Heard on the Street – 2/29/2024

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.

NEW RESEARCH: Growing Database Complexity Will Fuel Significant Skills Gaps in 2024

Increasing complexity, the rapid adoption of emerging technologies and a growing skills gap are the biggest concerns facing IT leaders in 2024, according to The State of the Database Landscape, a major new survey from end-to-end Database DevOps provider Redgate. 

A Brief Overview of the Strengths and Weaknesses Artificial Intelligence 

In this contributed article, editorial consultant Jelani Harper suggests that since there are strengths and challenges for each form of AI, prudent organizations will combine these approaches for the most effective results. Certain solutions in this space combine vector databases and applications of LLMs alongside knowledge graph environs, which are ideal for employing Graph Neural Networks and other forms of advanced machine learning.

The Future of Computing: Harnessing Molecules for Sustainable Data Management

In this contributed article, Erfane Arwani, founder and CEO of Biomemory, discusses how molecular computing (using molecules rather than traditional silicon chips for computational tasks) could be a critical component in revolutionizing data storage, despite the exponential growth of AI.

Heard on the Street – 2/22/2024

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.

The Infrastructure behind the Outputs: Cloud and HPC Unlock the Power of AI

In this contributed article, Philip Pokorny, Chief Technology Officer for Intelligent Platform Solutions/Penguin Solutions at SGH, provides insights regarding the relationship between high-performance computing (HPC) and generative AI and his expert point-of-view of the growing market. The increasing momentum behind generative AI in recent months has raised the prospective capabilities of enterprise businesses. At the forefront of this technology will be those that leverage HPC to create their solutions.

Video Highlights: Data Science Trend Predictions — with Sadie St. Lawrence

In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by Sadie St. Lawrence to analyze last year’s predictions and delve into the emerging technologies reshaping the field. They cover a range of topics, including the rise of AI hardware accelerators, the evolution of large language models into operating systems, and the potential impact of generative AI on data analysis roles.