SE Radio 661: Sunil Mallya on Small Language Models

Software Engineering Radio - the podcast for professional software developers

SE-Radio Team에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 SE-Radio Team 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

6M ago 59:28

MP3•에피소드 홈

Sunil Mallya, co-founder and CTO of Flip AI, discusses small language models with host Brijesh Ammanath. They begin by considering the technical distinctions between SLMs and large language models.

LLMs excel in generating complex outputs across various natural language processing tasks, leveraging extensive training datasets on with massive GPU clusters. However, this capability comes with high computational costs and concerns about efficiency, particularly in applications that are specific to a given enterprise. To address this, many enterprises are turning to SLMs, fine-tuned on domain-specific datasets. The lower computational requirements and memory usage make SLMs suitable for real-time applications. By focusing on specific domains, SLMs can achieve greater accuracy and relevance aligned with specialized terminologies.

The selection of SLMs depends on specific application requirements. Additional influencing factors include the availability of training data, implementation complexity, and adaptability to changing information, allowing organizations to align their choices with operational needs and constraints.

This episode is sponsored by Codegate.

1044 에피소드