Тёмный

Ontologies for Enabling Automated Graph LLM Workflows 

SWARM Community
Подписаться 256
Просмотров 750
50% 1

ABOUT THE WEBINAR:
This webinar will address the means of leveraging the combined benefits of both Large Language Models (LLMs) and Ontologies so that fact-based information retrieval can be leveraged from Retrieval Augmented Generation (RAG) solutions.
To provide further context, LLMs generate language based on prompt inputs, but the generated output language tends to not fit the context into which it is received. It behooves the receiver of a prompt, the context to interpret and correct.
We need to overcome the lack of context and provenance in each input / output pairings so that this technology can be routinely used by humans in real-world scenarios. Ontologies are the key for enabling the development of automated workflows.
Prasad has spent the better part of 4 years developing a platform called TextDistil, a modern NLP, Deep Learning, and Semantic Technology based platform used to extract knowledge from unstructured text and populate an ontology within an industry standard RDF triple store.

Наука

Опубликовано:

 

19 апр 2024

Поделиться:

Ссылка:

Скачать:

Готовим ссылку...

Добавить в:

Мой плейлист
Посмотреть позже
Комментарии    
Далее
AI and Ontologies as Standards
27:09
Просмотров 100
Building Production-Ready RAG Applications: Jerry Liu
18:35
QVZ PREMYER LIGA
00:18
Просмотров 841 тыс.
Unleashing the Synergy of LLMs and Knowledge Graphs
1:03:44
How to Build, Evaluate, and Iterate on LLM Agents
1:02:12
Without Ontology LLMs are Clueless  by JohnSowa
41:34
Stanford CS25: V3 I Retrieval Augmented Language Models
1:19:27
НОВЫЕ ФЕЙК iPHONE 🤯 #iphone
0:37
Просмотров 97 тыс.