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Revolutionizing AI Communities: Insights on Evaluation Techniques for Large Language Models by Rajiv Shah, Hugging Face

Rajiv Shah and Hugging Face's Role in AI Innovation

Rajiv Shah, a seasoned Machine Learning Engineer at Hugging Face, shares insights into addressing complex challenges with open-source AI. Hugging Face focuses on revolutionizing the open-source AI community by providing tools and infrastructure for growth.

Key Topics at the Data Innovation Summit 2024

Rajiv Shah will present on 'Evaluation Techniques for Large Language Models' at the upcoming Data Innovation Summit 2024. He aims to equip delegates with actionable ideas for building robust models and emphasizes the importance of evaluation in ensuring models solve real problems effectively.

Differentiating Hugging Face's Approach in AI

Hugging Face sets itself apart by dedicating to the open-source community and building tools for sustainable growth, rather than focusing on specific models. Their pioneering work with transformers and expansion to various data modalities have solidified their position in the AI landscape.

Challenges and Solutions in Evaluating Large Language Models

The market offers a range of LLM options, each with tradeoffs. APIs like OpenAI provide quick accessibility but lack control, while open models require deployment resources. Rajiv Shah highlights the challenge of selecting the right LLM and aims to guide decision-making in his evaluation talk.

Practical AI Applications for Enterprise Teams

Rajiv Shah sees immense promise in AI applications like chatbots, code generation tools, and question/answer systems using LLMs. These technologies can enhance customer support, software development, and information retrieval processes.

Importance of Interpretability in Large Language Models

Interpretability and explainability play a crucial role in regulatory compliance for LLMs. Transparency is key to meeting regulatory requirements and ensuring ethical use of AI. LLMs can serve as valuable data sources while smaller models ensure compliance.

Future AI Trends According to Rajiv Shah

Rajiv Shah predicts a rise in alternative algorithms to traditional transformers, with improved performance and enterprise adoption. He expects a shift in Generative AI investment as companies reassess ROI. The upcoming period may witness changes in the Generative AI startup landscape as the industry evolves.

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Accenture Conversational AI: Harnessing Semantic Layers for AI-Driven Insights

Interview with Ernesto Ongaro, dbt Labs

In this interview, Ernesto Ongaro, Team Lead and Solutions Architecture at dbt Labs, discusses the strategic advantage of semantic layers in the era of LLMs. Learn how semantic layers can accelerate data-driven decision-making within organizations. Additionally, find out more about Drew Banin, Co-Founder at dbt Labs, who will be presenting on 'Setting the Right Foundation for Innovation' at the upcoming Data Innovation Summit.

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Untangle Business Processes with Modern Data Strategy & Management - Accenture Conversational AI

Session Overview

In this session, Subhra Ratan Mukherjee from Polestar discusses how the company leverages insights from a simplified Data and Analytics platform to drive its journey towards becoming a major OEM. The focus is on the role of IT and Data Strategy in achieving Polestar's sustainability goals, addressing common business challenges, and implementing effective data management practices.

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Enhancing Data Products with Accenture Conversational AI - Interview with Sebastian Herold, Zalando SE

Sebastian Herold's Role at Zalando SE

Sebastian Herold is a Senior Principal Engineer at Zalando, Europe's largest fashion platform. He drives the evolution of Zalando’s data landscape, ensuring efficiency, scalability, and security. Sebastian collaborates closely with users, product teams, and vendors to democratize data access while maintaining security and compliance.

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