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Kubernetes Bytes
Byte-sized: Exploring the Basics of AI in Plain English
Dec 8, 2023
The hosts of the podcast discuss the basics of Artificial Intelligence, Machine Learning, and Deep Learning, exploring terms, differences, and approaches. They also cover topics such as power consumption in AI applications, AI chat bots streamlining processes, and the benefits of using Kubernetes for AI and ML workloads.
01:00:18
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Quick takeaways
- Kubernetes provides a platform for running AI and ML workloads, offering shared infrastructure access, GPU resource management, and portability.
- Vector databases can be used to retrieve current and accurate information, ensuring that generated responses are based on real data, mitigating the issue of hallucinations in language models.
Deep dives
AI and ML in the World of Kubernetes
Kubernetes provides a platform for running AI and ML workloads, offering shared infrastructure access, GPU resource management, and portability. Projects like Kubeflow, MLflow, and Hugging Face provide tools for building and deploying machine learning pipelines, managing experiments, and sharing models. Other projects like Qubr and Q help with scaling AI workloads, and Q with managing batch scheduling. The ecosystem is rapidly evolving, making it an exciting space to explore and contribute to.
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