Today at NVIDIA GTC, Hewlett Packard Enterprise (NYSE: HPE) announced updates to one of the industry’s most comprehensive AI-native portfolios to advance the operationalization of generative AI (GenAI), deep learning, and machine learning (ML) applications.
Hitachi Vantara, the data storage, infrastructure, and hybrid cloud management subsidiary of Hitachi, Ltd. (TSE: 6501), today announced a collaboration with NVIDIA to create a new generation of transformational artificial intelligence (AI) solutions. Hitachi Vantara will develop a portfolio of solutions, Hitachi iQ, to drive targeted AI outcomes by layering industry-specific capabilities on top of its AI solution stack, so outcomes can be more specific and relevant to an organization’s business.
Today, at NVIDIA GTC, a global AI conference, Lenovo announced new hybrid AI solutions, built in collaboration with NVIDIA, that deliver the power of tailored generative AI applications to every enterprise and cloud, bringing transformational capabilities to every industry.
Pure Storage® (NYSE: PSTG), the IT pioneer that delivers advanced data storage technology and services, today announced new validated reference architectures for running generative AI use cases, including a new NVIDIA OVX-ready validated reference architecture. As a leader in AI, Pure Storage, in collaboration with NVIDIA, is arming global customers with a proven framework to manage the high-performance data and compute requirements they need to drive successful AI deployments.
Tokenizing time series data and treating it like a language enables a model whose zero-shot performance matches or exceeds that of purpose-built models.
In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, explores the origins of NumPy and SciPy with their creator, Dr. Travis Oliphant. Dr. Oliphant shares his journey from personal need to global impact, the challenges overcome, and the future of these essential Python libraries in scientific computing and data science.
How can we effectively generate missing data trans-formations among tables in a data repository? Multiple versions of the same tables are generated from the iterative process when data scientists and machine learning engineers fine-tune their ML pipelines, making incremental improvements. This…
Zapata Computing, Inc., the Industrial Generative AI company, announced that its scientists, in collaboration with Insilico Medicine, the University of Toronto, and St. Jude Children’s Research Hospital have demonstrated the first instance of a generative model running on quantum hardware outperforming state-of-the-art classical models in generating viable cancer drug candidates. The research points to a promising future of hybrid quantum generative AI for drug discovery using today’s quantum devices.
Snowflake partners with Landing AI to integrate advanced computer vision capabilities into its Data Cloud, unlocking new possibilities for enterprises to harness the potential of visual data across industries.
Join leaders in Boston on March 27 for an exclusive night of networking, insights, and conversation. Request an invite here. For OpenAI CTO Mira Murati, an exclusive Wall Street Journal interview with personal tech columnist Joanna Stern yesterday seemed like a slam-dunk. The clips of OpenAI’s Sora text-to-video model, which was shown off in a […]
Second-order optimization methods, such as cubic regularized Newton methods, are known for their rapid convergence rates; nevertheless, they become impractical in high-dimensional problems due to their substantial memory requirements and computational costs. One promising approach is to execute…
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.
Given a node-attributed graph, and a graph task (link prediction or node classification), can we tell if a graph neural network (GNN) will perform well? More specifically, do the graph structure and the node features carry enough usable information for the task? Our goals are (1) to develop a fast…
Sellers on online marketplaces such as Amazon.com use a variety of retail and retail media advertising services to improve their brand performance, including awareness, consideration, and revenue. But how can they measure their progress and drive these metrics? For 122,000 brands, we measure Amazon…
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.
In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by Lisa Cohen, Google's Director of Data Science and Engineering, to discuss the capabilities of the cutting-edge Gemini Ultra LLM and how it stands toe-to-toe with GPT-4.
In this contributed article, technical leader Kamala Manju Kesavan believes it is essential to periodically reassess your database strategy to ensure that it continues to meet your organization's evolving requirements. If migrating to another database solution is deemed necessary, approach the process methodically, leveraging best practices and stakeholder collaboration to maximize success and drive business value.