Carahsoft, in conjunction with its vendor partners, sponsors hundreds of events each year, ranging from webcasts and tradeshows to executive roundtables and technology forums.

Events and Resources

Events

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NVIDIA

Real-Time Disaster Response Leveraging Artificial Intelligence with NVIDIA and CrowdAI


Event Date: October 08, 2019

In the face of increasingly destructive natural disasters, human-machine teaming is essential to helping first responders save lives. Automation of high-skill, labor-intensive tasks can act as a force multiplier by reducing cognitive burden while extracting meaningful insights about a disaster, allowing first responders to focus on higher-order challenges, like decision making. Critical to effective response efforts, machine learning algorithms leveraging the power of NVIDIA GPUs can provide first responders with accurate insights in near-real-time. 

In this webinar, participants discovered how CrowdAI identifies countless features from still imagery and full-motion video to support humanitarian assistance and disaster response, such as wildfires, flooding, hurricanes, and more. To build effective models, CrowdAI trained on multiple imagery types from the world’s leading satellite and aerial data vendors on NVIDIA GPUs.

During this webinar, attendees learned: 
  • Lightweight models that can deploy to a customer cloud or on-prem to process data in situ
  • Scalable solutions that can reduce a week’s work into minutes or an hour’s work into milliseconds
  • Models that are trained on GPUs to solve specific problems on customer’ proprietary and/or sensitive imagery and video sources
  • Models that are designed for seamless compatibility across a variety of imagery sources
  • Role of NVIDIA GPU’s in training the algorithms and performance gains.
Explore how CrowdAI has produced some of the industry’s most accurate, light-weight models on the market!

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Resources

Using AI Agents to Accelerate Discovery
Infographic

Using AI Agents to Accelerate Discovery

Agentic learning is when AI agent improve their performance over time by learning from completed tasks. Finch AI uses this approach to power agents that automatically discover, research, and create entries for new entities. These agents work together to validate information, summarize findings, and suggest related entities, delivering increasing value as they learn.


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