Meta Llama 3 Fine-Tuning, RAG, and Prompt Engineering for Drug Discovery
Explore advanced techniques to enhance Llama 3's performance in drug discovery using fine-tuning, RAG, and prompt engineering. Gain insights into improving domain-specific AI responses for pharmaceutical research.
Meta Llama 3 for Drug Discovery - Generative AI Assistant Developments
Explore advanced techniques for modifying Meta Llama 3 for drug discovery, including fine-tuning, RAG implementation, and agentic behavior enhancement for improved accuracy and capabilities.
LangChain Suite for Advanced Drug Discovery Generative AI Workflows
Explore advanced drug discovery using LangChain's AI tools. Compare GPT models, optimize workflows, and leverage generative AI for pharmaceutical innovation.
How to Develop APIs for Generative AI Drug Discovery Production
Explore platforms for creating APIs from Large Language Models to enhance drug discovery workflows. Learn to increase efficiency, reduce errors, and lower costs through synchronization and automation.
C++ Generative AI Inference - Production Ready Speed and Control
Optimize C++ for generative AI inference, enhancing speed and control. Explore techniques to boost performance and gain precise command over AI model execution in production environments.
GenAI Multimodal, RAG, RAPTOR, Agent, and Finetuning - Live Coding Demonstration
Explore cutting-edge GenAI techniques through live demos of RAG, RAPTOR, Agent, and Finetuning. Witness multimodal capabilities and gain hands-on experience with advanced AI models and tools.
Live Python Demos - Generative Artificial Intelligence
Explore local hosting of generative AI models, comparing LLMs and LMMs for image processing, code generation, and multimodal tasks using various platforms and tools.
Prompt Tuning Explained
Explore prompt tuning techniques for optimizing pre-trained language models. Learn about soft prompts, gradient descent, and improving performance on downstream tasks while maintaining model efficiency.
Torch.fx Explained - Accelerating ML Code with PyTorch
Explore PyTorch's torch.fx toolkit for accelerating ML code through symbolic tracing, program manipulation, and optimization of neural network modules.
Llama 2 Explained - Safety and Ethical Considerations - Part 3
Explore Llama V2's safety features in this concluding session. Gain insights into Meta AI's latest language model iteration and its focus on secure AI development.
Segment Anything Model (SAM) Explained
Explore SAM, a versatile image segmentation model by Meta AI. Learn about its multitask capabilities, zero-shot transferability, and applications across various scenes and objects.
The Emergence of Essential Sparsity in Large Pre-trained Models
Explore essential sparsity in large pre-trained models, examining efficient handling of complex transformers and the impact of weight removal on performance.
Distill Whisper Explained - Robust Knowledge Distillation for Speech Recognition
Explore Distill-Whisper: a compact, efficient speech recognition model. Learn about its robust knowledge distillation, large-scale pseudo labelling, and performance compared to the larger Whisper model.
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models
Explore OpenMoE, an open-source Mixture-of-Experts language model series. Discover its cost-effectiveness, routing mechanisms, and key insights in comparison to dense LLMs.
LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding
Explore LayerSkip, an LLM acceleration method that speeds up inference by strategically restricting model layers, achieving 2x speed-ups on various tasks through innovative techniques.
ReFT: Representation Finetuning for Language Models Explained
Explore ReFT, a novel approach to fine-tuning language models by modifying internal representations, achieving efficiency with fewer parameters than traditional methods.
Towards Monosemanticity: Decomposing Language Models with Dictionary Learning
Explore monosemanticity in neural networks through sparse autoencoders. Learn how extracting interpretable features enhances understanding of language model behavior and improves reasoning capabilities.
Complex Agentic RAG Systems - Overcoming Limitations of Traditional RAG
Explore advanced agentic RAG systems with expert Atita Arora, overcoming traditional limitations and revolutionizing information retrieval for AI and machine learning applications.
Hierarchical Prompting Taxonomy - A Universal Evaluation Framework for Large Language Models
Explore a universal evaluation framework for large language models using Hierarchical Prompting Taxonomy. Gain insights into assessing dataset complexity and model capabilities.
Knowledge Circuits in Pretrained Transformers Explained
Explore knowledge circuits in pretrained transformers, uncovering computational mechanisms behind language models' articulation of specific knowledge. Gain insights into AI's inner workings.
The Future of Imaging Informatics - Enabling the Quintuple Aim in Healthcare
Explore imaging informatics with Dr. Tessa Cook, covering its role in healthcare's quintuple aim, hot topics, cutting-edge research, and strategies for improving patient care and physician experience.