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 […]
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.
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.
HP Amplify — NVIDIA and HP Inc. today announced that NVIDIA CUDA-X™ data processing libraries will be integrated with HP AI workstation solutions to turbocharge the data preparation and processing work that forms the foundation of generative AI development.
Federated Learning (FL) is a popular algorithm to train ma-chine learning models on user data constrained to edge devices (for example, mobile phones) due to privacy concerns. Typically, FL is trained with the assumption that no part of the user data can be egressed from the edge. However, in many…
Large Language Models (LLMs) trained on large volumes of data excel at various natural language tasks, but they cannot handle tasks requiring knowledge that has not been trained on previously. One solution is to use a retriever that fetches relevant information to expand LLM’s knowledge scope.…
Recent advances in tabular data generation have greatly enhanced synthetic data quality. However, extending diffusion models to tabular data is challenging due to the intricately varied distributions and a blend of data types of tabular data. This paper introduces TABSYN, a methodology that…
Generative AI has created a profound and positive shift inside of Citi toward data-driven decision-making, but for now Citi has decided against an external-facing chatbot because the risks are still too high.
In this contributed article, George Davis, founder and CEO of Frame AI, howlights how we find ourselves at an early, crucial stage in the AI R&D lifecycle. Excitement over AI’s potential is dragging it into commercial development well before reliable engineering practices have been established. Architectural patterns like RAG are essential in moving from theoretical models to deployable solutions.