At ISC High Performance 2024, Intel announced in collaboration with Argonne National Laboratory and Hewlett Packard Enterprise (HPE) that the Aurora supercomputer has broken the exascale barrier at 1.012 exaflops and is the fastest AI system in the world dedicated to AI for open science, achieving 10.6 AI exaflops. Intel will also detail the crucial role of open ecosystems in driving AI-accelerated high performance computing (HPC).
Search Results for: modeling
Heard on the Street – 5/9/2024
May 9, 2024 by
Welcome to insideAI News’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.
Avoid these 8 Data-related Mistakes on Data Projects
April 29, 2024 by
This article is excerpted from the book, “Winning with Data Science: A Handbook for Business Leaders,” by Howard Friedman and Akshay Swaminathan with permission from the publisher, Columbia Business School Publishing. The article covers how to avoid 8 data-related mistakes on data projects
How to Use Raw Data in Web Analytics
April 25, 2024 by
In this contributed article, Mateusz Krempa, Chief Operations Officer for Piwik PRO, explores the benefits and challenges of using raw data in analytics, and discusses its potential use cases for gaining valuable insights.
Nature Communications Publishes Zapata AI Research on Generative AI for Optimization
April 23, 2024 by
Zapata Computing Holdings Inc. (Nasdaq: ZPTA), the Industrial Generative AI company, announced that its foundational research on generator-enhanced optimization (GEO) has been published in the esteemed Nature Communications journal. The research, titled “Enhancing Combinatorial Optimization with Classical and Quantum Generative Models,” introduces Generator-Enhanced Optimization (GEO), a novel optimization method that leverages the power of generative modeling to suggest high-quality candidate solutions to complex optimization problems.
Avoid these 7 Common Business-related Mistakes On Data Projects
April 16, 2024 by
This article is excerpted from the book, “Winning with Data Science: A Handbook for Business Leaders,” by Howard Friedman and Akshay Swaminathan with permission from the publisher, Columbia Business School Publishing. The article covers how to avoid 7 common business-related mistakes on data projects that all stem from failures in planning, preparation and communication.
The Data Disconnect: A Key Challenge for Machine Learning Deployment
March 25, 2024 by
This article is excerpted from the book, “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment,” by Eric Siegel, Ph.D., with permission from the publisher, MIT Press. It is a product of the author’s work while he held a one-year position as the Bodily Bicentennial Professor in Analytics at the UVA Darden School of Business.
The Infrastructure behind the Outputs: Cloud and HPC Unlock the Power of AI
February 19, 2024 by
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.
Navigating the AI Landscape in 2024: Prioritizing Ground-Truth Data, Developer Enablement, and Consumer Privacy
February 7, 2024 by
In this contributed article, Jason Hudak, SVP of Engineering at Foursquare, explores four pivotal aspects shaping the AI landscape: the imperative role of quality ground-truth data, the proliferation of developer enablement, the renewed focus on consumer privacy in the midst of an election year, and the role LLM’s and NLP’s will play in data democratization.
Sony AI Big Data Industry Predictions for 2024
February 5, 2024 by
Our friends over at Sony AI have prepared a special set of compelling technology predictions for the year ahead. The Sony AI team is comprised of researchers and leaders with backgrounds in deep reinforcement learning, data science, law, privacy and security, and more. They each offer different perspectives on topics related to AI ethics and policy, the use of AI to augment creativity and scientific research, emerging AI training methods, and more. From the company’s point of view 2024 should be quite a year! Enjoy these special perspectives from one of our industry’s best known movers and shakers.
