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cover of episode 886: In Case You Missed it In April 2025

886: In Case You Missed it In April 2025

2025/5/9
logo of podcast Super Data Science: ML & AI Podcast with Jon Krohn

Super Data Science: ML & AI Podcast with Jon Krohn
AI Deep Dive Transcript
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Sharish Gupta
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Sama Bali: 我将首先介绍 NVIDIA AI Enterprise，这是一个端到端的 AI 软件开发平台，它不仅可以加速数据科学流程，还可以帮助构建下一代 AI 应用。它包含 NIM 微服务，这是一种将各种 AI 模型作为容器化微服务交付的方式，方便开发者快速切换模型。此外，它还包含 Nemo、AI Blueprints 和 CUDA 库等组件，以加速 AI 应用开发和推理。CUDA 库，例如 Rapids 和 QML，可以显著加速数据科学任务。 Emily Weber: AWS 致力于为客户提供选择，包括在加速硬件方面。Annapurna Labs 开发的 Graviton CPU 和 Trainium 2 芯片是 AWS 在 AI/ML 领域的重要产品，提供高性能、高性价比和高能效的计算能力。Trainium 2 是 AWS 上最强大的 AI/ML EC2 实例。 Greg Michelson: Zerve 通过内置的 API 构建器和 GPU 管理器，降低了 AI 模型部署的难度，使数据科学家能够更轻松地将模型部署到生产环境中，无需依赖软件工程师。它处理了依赖项管理、模型序列化和基础设施问题，使数据科学家能够专注于模型构建。 Sharish Gupta: 使用人工智能个人电脑 (AIPC) 进行本地推理比依赖云计算具有诸多优势，AIPC 具有加速、个性化、私密和低成本等特点，适用于各种应用场景。AIPC 可以降低延迟，提高性能，保护数据隐私，并降低成本。

Deep Dive

Shownotes Transcript

Our In Case You Missed It episode for April has clips on NVIDIA’s and Dell’s product and service offers including an overview of NVIDIA’s GPUs, AI Enterprise, and its microservices. You’ll also hear about AWS’ focus on bringing choice to customers and the incredible power of its Graviton CPU, how Zerve opens access to AI deployment, Merck KGaA, Darmstadt, Germany’s multi-chip integration, and why reliance on the cloud might soon become a practice of times past.

Additional materials: ⁠www.superdatascience.com/886⁠)

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