
5 Step Guide to AI-Driven Fraud Detection with Unified Data Intelligence
Financial fraud is an unchecked epidemic, draining billions from the global economy while leaving businesses, taxpayers, and consumers to foot the bill. In 2023 alone, global payment card fraud losses…
A Guide to Solving 5 of Common AI Infrastructure Challenges
Maybe your applications seem to be running fine, but since when has “fine” been good enough? Instead of celebrating the new business value of AI, you find yourself resetting expectations.
Accelerate Artificial Intelligence Initiatives with DDN and NVIDIA at Any Scale
Data now plays such a prominent role in determining business success that 98% of organizations surveyed by ESG are in some phase of data-driven digital transformation.
Accelerating AI Networks with DDN’s Data Intelligence Platform and NVIDIA Spectrum™-X for Storage
Abstract As AI models continue to grow in complexity and scale, delivering high-performance infrastructure becomes critical. Traditional Ethernet-based storage networks, while sufficient for general workloads, struggle to keep up with…
Accelerating Life Sciences Innovation with Trusted AI Infrastructure
Executive Summary: Scaling AI in Life Sciences with Trusted Data AI is rapidly transforming life sciences from accelerating drug discovery to improving diagnostics and personalizing care. But while the pace…
AI Engineering: A New Discipline
AI engineering is an emerging discipline that focuses on applying tools, systems, and processes to enable AI to perform effectively.
AI Infrastructure for Financial Services: Powering Profit & Trust
Financial services are undergoing rapid transformation, driven by artificial intelligence (AI) and powered by modern AI Infrastructure. From microsecond gains in high-frequency trading (HFT) to real-time fraud detection, institutions are…
Architect’s Guide to AI-Driven Systemic Risk Mitigation in Post-Trade
By Moiz Kohari, VP Enterprise AI In today’s markets, post-trade isn’t a back-office formality – it’s a real-time battleground for systemic stability. Regulators demand faster answers. Traders want real-time…
DDN Infinia: The Foundation for Enterprise AI Success
DDN Infinia gives fluid control of data from edge to core and core to cloud, while maximizing the capabilities of the underlying infrastructure, including storage, network and compute.
Delivering the AI Edge for High-Frequency Trading
In recent years, the financial sector has witnessed a significant surge in the adoption of artificial intelligence (AI), with high-frequency trading (HFT) firms leading the charge. As of 2024, 72%…
Evaluating Infrastructure Options for Enterprise Development
Although the promise and attraction of AI is well appreciated by IT and business decision-makers alike, it’s far less clear how organizations should begin their journey to enterprise-class AI.
How to Build an AI Center of Excellence
Organizations need to adopt a disciplined approach to implementing and measuring the outcomes of AI projects.
Large Language Models
In this white paper, we take a platform approach to accelerate LLMs and show how GPU, memory, and storage collectively contribute to overall LLM performance.
LLM Checkpointing Efficiency is a Critical Blocker to AI Productivity
In the race toward more useful and more intelligent AI systems, high-performance computing (HPC) continues to be the backbone of AI development
Maximizing ROI on Your AI Infrastructure
Executive Summary Generative AI is the hottest topic in every corporate strategy meeting today – evaluating the market opportunities, outlining new business models, and looking for the right entry points…
Streamlining AI Data Management
For supreme AI data management, the AI data lifecycle needs a clear, continuous flow, both for training of AI models, and for applying AI models to real time decision making.
The AI Data Factory
Data monetization is now led by market-driven business priorities and outcomes, expressed as measurable results that affect the bottom line.
The Next AI Breakthrough Won’t Come from Compute -It’ll Come from Faster Data
In the relentless pursuit of artificial intelligence (AI) advancement, organizations often focus on model architectures, algorithm optimization, and computational power. Yet, a critical component remains under-appreciated: the efficiency of data…