ML Developer Workshop 4: Enterprise GPT Language Modelling, with SambaNova Systems | Kisaco Research

Accelerating the enterprise adoption of state-of-the-art natural language processing (NLP) techniques is a full-stack endeavor. Within the modern NLP system stack, the hardware, software, machine learning and solution layers are all critical parts for the time-to-deployment. In this workshop, we will lead you through our full-stack vertical NLP solution – the Enterprise Large Language Model available only through SambaNova’s Dataflow-as-a-service (DaaS). We first discuss the new turn-key development paradigm for adopting enterprise-grade large language models. In such a paradigm, developers can build solutions and integrate into business workflows with DaaS as a NLP application store via easy-to-use APIs. To materialize a concrete view on this paradigm, we showcase prototyping enterprise semantic search and legal compliance analysis solutions built on top of our Dataflow-as-a-service APIs. This is followed by some entertaining text generation live trials to shine the excitement of modern large language modeling technologies.

Developer workshops are restricted to machine learning practitioners from research institutions and enterprises who are interested in learning how to port code onto novel AI platforms and want to get hands-on access to hardware and SDKs. 

Workshops are application only and subject to eligibility and availability. The workshops are free, and lunch, shared networking sessions, and access to the Meet and Greet function and keynote is included in the developer pass. If you're a machine learning engineer / AI application developer, please apply using the form in the registration section of the website or by emailing [email protected]. There are approximately 30 spaces available.

Session Topics: 
Developer Efficiency
NLP
Novel AI Hardware
Sponsor(s): 
SambaNova
Speaker(s): 

Author:

Jian Zhang

Director, Machine Learning
SambaNova Systems

Jian Zhang

Director, Machine Learning
SambaNova Systems
Session Job Focus: