Generative AI and large language models are stirring change across industries — but according to NVIDIA Senior Product Manager of Developer Marketing Annamalai Chockalingam, “we’re still in the early innings.”
In the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with Chockalingam about LLMs: what they are, their current state and their future potential.
Describing LLMs as a “subset of the larger generative AI movement,” Chockalingam says they can do five things with language: generate, summarize, translate, instruct or chat. With a combination of “these modalities and actions, you can build applications” to solve any problem, he said.
Enterprises are tapping LLMs to drive innovation, develop new customer experiences and gain a competitive advantage, he said. They’re also exploring what safe deployment of those models looks like, aiming to achieve responsible development, trustworthiness and repeatability.
New techniques like retrieval augmented generation could boost LLM development. RAG involves feeding models with up-to-date data sources or third-party APIs to achieve “more appropriate responses,” Chockalingam said — granting them current context so that they can “generate better” answers.
Chockalingam encourages those interested in LLMs to “get your hands dirty and get started” — whether that means using popular applications like ChatGPT or playing with pretrained models in the NVIDIA NGC catalog.NVIDIA offers a full-stack computing platform for developers and enterprises experimenting with LLMs, with an ecosystem of over 4 million developers and 1,600 generative AI organizations. To learn more, register for LLM Developer Day on Nov. 17 to hear from NVIDIA experts about how best to develop applications.
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