Dec 3, 2024
Webinar - Beyond Text: Multimodal AI Evaluations
Shohil Kothari
Head of Growth
Shohil Kothari
Head of Growth
While text-based LLMs drove the first wave of enterprise GenAI adoption, multimodal models and systems are increasingly popular for their versatility across a variety of complex use cases.
But before enterprise AI teams can deploy multimodal AI in production, they must implement a comprehensive multimodal evaluation framework to ensure model performance and accuracy, identify biases or blindspots, increase trust and transparency, and ultimately enable continuous system improvement.
Watch our webinar with Cloudflare to learn:
Key concepts behind multimodal AI evaluation
Why multimodality is more challenging than text-based evaluations
What to consider in your evaluation framework
While text-based LLMs drove the first wave of enterprise GenAI adoption, multimodal models and systems are increasingly popular for their versatility across a variety of complex use cases.
But before enterprise AI teams can deploy multimodal AI in production, they must implement a comprehensive multimodal evaluation framework to ensure model performance and accuracy, identify biases or blindspots, increase trust and transparency, and ultimately enable continuous system improvement.
Watch our webinar with Cloudflare to learn:
Key concepts behind multimodal AI evaluation
Why multimodality is more challenging than text-based evaluations
What to consider in your evaluation framework
While text-based LLMs drove the first wave of enterprise GenAI adoption, multimodal models and systems are increasingly popular for their versatility across a variety of complex use cases.
But before enterprise AI teams can deploy multimodal AI in production, they must implement a comprehensive multimodal evaluation framework to ensure model performance and accuracy, identify biases or blindspots, increase trust and transparency, and ultimately enable continuous system improvement.
Watch our webinar with Cloudflare to learn:
Key concepts behind multimodal AI evaluation
Why multimodality is more challenging than text-based evaluations
What to consider in your evaluation framework
While text-based LLMs drove the first wave of enterprise GenAI adoption, multimodal models and systems are increasingly popular for their versatility across a variety of complex use cases.
But before enterprise AI teams can deploy multimodal AI in production, they must implement a comprehensive multimodal evaluation framework to ensure model performance and accuracy, identify biases or blindspots, increase trust and transparency, and ultimately enable continuous system improvement.
Watch our webinar with Cloudflare to learn:
Key concepts behind multimodal AI evaluation
Why multimodality is more challenging than text-based evaluations
What to consider in your evaluation framework