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Simplifying Big Data AI with Intel Analytics Zoo

Applying machine learning to distributed big data analytics plays a central role in today’s intelligent applications and systems. These problem settings have pushed the field to address issues of data scale that were almost inconceivable to AI researchers even a decade ago. To address these challenges, Intel has open sourced Analytics Zoo (https://github.com/intel-analytics/analytics-zoo), which allows […]

Intel Graph Analytics & AI: An Efficient Way to Analyze Massive Datasets

Graphs are playing a key role in big data analytics, providing insights in many domains through traditional graph algorithms and graph neural networks. As the size of these data sets increase, the computing power needed also increases and the software techniques to manage it becomes ever more critical. For example, there are Intel-based single node […]

MemVerge Big Memory Workbench: Multi-Stage Analytics

Yong Tian, Director, Product Management, presents MemVerge Big Memory Workbench. This enables users to interact with big memory using a GUI, CLI, or REST API to eliminate expensive file I/O and enable big memory analytics.

MemVerge In-Memory Snapshot Deep Dive

Yue Li, CTO, presents the MemVerge Memory Machine snapshot capability, putting it in context of challenges facing AI applications in the enterprise. He first presents the tiered memory allocation model and the use case for in-memory image recognition and virtualized servers. Then he discusses the potential for in-memory snapshots to support these applications, including the […]

Big Memory Computing with the MemVerge Memory Machine

Frank Berry, Vice President of Marketing for MemVerge, presents the changing computing landscape. With today’s AI and big data analytics challenges, companies are at an inflection point and looking to add more memory capacity and features. This “big memory” challenge is what the MemVerge Memory Machine is intended to address.

The Future is Bright with BrainChip

These are exciting times at BrainChip. Anil Mankar, Co Founder and Chief Development Officer, will highlight Brainchip’s proposed business models as well as highlight key areas of applications. Summarizing BrainChip activity with some key demonstrations of Akida in action and closing the session by addressing questions.

The BrainChip Advantage

BrainChip is uniquely positioned with it’s Neuromorphic Processor to address low power functionality while processing at the Edge without dependency of communicating with the cloud. This capability enables BrainChip to address key beneficial AI applications such as detecting Volatile Organic Compounds (VOCs) through exhaled breath and accurately determining various diseases and viruses. Presented by Anil […]

Making Edge AI Possible with BrainChip

Anil Mankar, Co Founder and Chief Development Officer, BrainChip, will discuss how to make AI at the Edge possible by leveraging BrainChip’s Akida Neuromorphic Processor and it’s capabilities. In this session Anil will highlight Facial Detection and Object Detection at the Edge.

Unlocking Dynamic AI On-Prem with Liqid

Liqid CDI is built from the ground up to manage AI+ML workloads for maximum operational performance and footprint efficiency for accelerated time-to-value in AI+ML environments. Exponentially increase value of existing resources and deploy disaggregated resources for GPU-intensive AI+ML workloads. Learn how Liqid CDI can scale for multitenancy workloads and dominate the data center. Build a […]

How Liqid Addresses Infrastructure Challenges Facing On-Prem AI

Liqid provides composable disaggregated infrastructure (CDI) solutions that optimize AI+ML operations by providing adaptive architecture that can manage resources like NVIDIA GPUs, intelligent networking, NVMe, and other accelerators. Liqid CDI software addresses the limitations of traditional on-prem infrastructure for AI such as limited GPU config options, limited change readiness of existing static architecture, and poor […]

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