AI Catalyst Conference: Building Commercially Successful LLM Applications
Category: Tutorials
- views: 80
- date: 16 November 2023
- posted by: mitsumi
AI Catalyst Conference: Building Commercially Successful LLM Applications
Released 11/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 2h 49m | Size: 583 MB
What you'll learn
Unlock profits and monetize generative AI with insights from industry leaders.
Master the details of LLM selection, benchmarking, and the powerful Langchain library.
Explore ethical AI and real-world solutions to address ethical concerns in generative AI.
In an era in which artificial intelligence is revolutionizing industries, this event is a pivotal opportunity for professionals to stay ahead of the curve. The half-day conference cuts through the noise, delivering critical know-how on optimizing profits, technical implementation, and ethical considerations in the rapidly evolving landscape of Large Language Models (LLMs) and Generative AI. Whether you're a developer, data scientist or entrepreneur, this event offers an invaluable blend of expertise and actionable strategies to help you navigate the complexities and opportunities in commercial AI applications. You'll come away empowered to accelerate the deployment of profitable Generative AI models.
AI Catalyst Conference
The AI Catalyst Conference from Pearson brings together fresh voices in AI to make complex topics understandable and actionable. Host Jon Krohn guides the conversation and explains how to bring state-of-the-art methods into practice. Gain new information or a different perspective to make an impact in your job and in the world.
What you'll learn and how you can apply it
Monetization: Grasp the strategies to make AI and LLMs profitable.
Technical Criteria: Know how to evaluate LLMs for your specific needs.
Ethical Concerns: Understand the social impact of AI deployments.
And you'll be able to
Implement Langchain: Utilize the new Python library for seamless LLM integration.
Benchmark Models: Conduct performance tests to ensure optimal LLM functionality.
Build Trust: Apply open-source tools to manage ethical concerns in AI.
This course is for you because.
You are a data scientist, software developer, ML engineer or other technical professional who would like to be able incorporate profitable state-of-the-art LLMs into real-world applications.
You're an entrepreneur, intrapreneur or other professional who's keen to accelerate commercial innovation and profitability at your firm.
Prerequisites
All you need is an interest in how AI can impact you and your organization.
Feel free to bring questions for the experts.
Recommended Follow-up
Attend: Large Language Models in 3 Weeks by Sinan Ozdemir
Attend: Optimizing Large Language Models by Shaan Khosla
Read: Quick Start Guide to Large Language Models by Sinan Ozdemir
Watch: Quick Guide to ChatGPT, Embeddings and Other Large Language Models by Sinan Ozdemir
Read: Designing Machine Learning Systems by Chip Huyen
For technical deep-dives, read David Foster's Generative Deep Learning, 2nd Edition and Lewis Tunstall et al.'s Natural Language Processing with Transformers, Revised Edition
For a more general introduction to deep learning, check out the Deep Learning: The Complete Guide playlist by Dr. Jon Krohn:https://learning.oreilly.com/playlists/a40ea8fe-994d-4370-8b29-0d6c0f519a89/
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