[Beyond GPU] Solutions for AI Hardware Challenges from Infrastructure to Deployment - with Mark Heaps of Groq
The AI in Business Podcast
00:00
Challenges in Model Deployment for AI and Machine Learning
The challenges in model deployment in 2023 revolve around the shift from training to inference, where the focus is on delivering services to end users. This shift represents the crossroads where business leaders need to adapt to model deployment. Additionally, the rapid development of AI models poses a challenge for enterprises, as the constant evolution of AI models requires continuous reworking and investment, making it difficult to keep up with the market's pace. Business leaders are concerned about the risk of investing in a model that may become outdated in a short time, leading to significant downtime. The need for real-time adaptability and the ability to react to market changes is crucial in the area of model deployment.
Transcript
Play full episode
