How I Learned to Stop Worrying and Love the Transformer - Stanford CS25 Lecture
Explore the Transformer's evolution and future directions with Ashish Vaswani, co-author of "Attention is All You Need". Gain insights into motivations, developments, and promising research areas in AI and NLP.
Aligning Open Language Models - Stanford CS25 Lecture
Explore the evolution of open language models, covering key techniques, datasets, and models like Alpaca and QLoRA. Gain insights into the future of aligning these models for easier use.
Intuitions on Language Models and Shaping AI's Future - Stanford CS25 Lecture
Explore intuitions on language models and the evolution of Transformer architectures with OpenAI researchers. Gain insights into next-word prediction, scaling laws, and the future of AI development.
Demystifying Mixtral of Experts - Stanford CS25 Lecture
Explore Mixtral 8x7B, a Sparse Mixture of Experts model, with Albert Jiang. Learn about its architecture, expert routing, and how it processes 47B parameters while using only 13B during inference.
Learn About: Google's AI-Powered Learning Tool - HAI Seminar
Explore Google's experimental AI learning tool, Learn About, combining search knowledge with Gemini's conversational abilities to revolutionize education through personalized, interactive learning experiences.
Intuitive Reasoning as Unsupervised Neural Generation
Explore intuitive reasoning in AI through neural generation, covering topics like common sense, language models, and multimodal information with researcher Yejin Choi.
Imitation vs Innovation: Large Language and Image Models as Cultural Technologies
Explore the impact of large language and image models as cultural technologies, examining the balance between imitation and innovation in AI development.
Writing Assistance or Plagiarism - How Language Models Are Changing Our View of Knowledge
Explore how language models are reshaping our understanding of knowledge, writing assistance, and plagiarism with insights from Anna Rogers in this thought-provoking discussion.
Language Models Could Learn Semantics - No Matter How You Define It
Explore how language models can acquire semantic understanding through form, entailment, and Gricean principles, with insights on practical limitations and future possibilities.
Imitation Versus Innovation - What Children Can Do That Large Language Models Can't
Explore the unique cognitive abilities of children in comparison to AI language models, focusing on imitation and innovation in learning and problem-solving processes.
What Do Our Machines Dream Of? Understanding Language Models and Their Reasoning Capabilities
Explore the fascinating world of AI language models, their capabilities, limitations, and potential for reasoning through experiments and demonstrations.
Cross-Domain Similarity Mapping: From Bananas to Cloudy Days - Cognitive Science Insights
Explore the intriguing world of cross-domain mappings and how humans draw connections between seemingly unrelated concepts, backed by studies and language model simulations.
CorpusLM: Towards a Unified Language Model on Corpus for Knowledge-Intensive Tasks - Lecture 1
Explore CorpusLM, a unified language model for knowledge-intensive tasks, combining LLM capabilities with efficient corpus search techniques.
Introduction to LangChain and Retrieval Augmented Generation (RAG)
Explore LangChain's core concepts and build LLM-based applications using Retrieval Augmented Generation for document-based question answering.
Supercharging Search with Language Models (LLMs)
Explore how Instacart revolutionized search using Language Models, enhancing user experience with personalized recommendations and improved results.
Making ChatGPT Funny with Prompt Optimization - MLOps World
Discover techniques to enhance ChatGPT's humor through prompt engineering, overcoming AI limitations and unlocking its comedic potential.
Synthetic Data: Generative AI for Enhanced Data Quality in the Era of Foundational Models
Explore synthetic data's transformative potential in AI, focusing on data quality, augmentation, bias, and privacy for foundational language models.
Towards Understanding Modern Alchemy - Transformers as a Computational Model
Explore in-context learning of formal languages, comparing Transformers to other models and examining specialized "n-gram heads" for improved performance in language modeling.
Interpretability Agents: Automating and Scaling Model Interpretation
Explore automated interpretability agents for scaling model interpretation, enabling efficient analysis of AI systems through hypothesis-driven experimentation and modular design.
Understanding and Improving Efficient Language Models
Explore efficient language models, focusing on associative recall's impact on performance. Learn about new hardware-efficient architectures expanding quality-efficiency frontiers in machine learning.
Using Recurrence to Achieve Weak to Strong Generalization
Explore recurrent architectures for weak-to-strong generalization in reasoning models, enhancing problem-solving capabilities beyond training data.