Robot Learning in the Era of Large Pretrained Models - Stanford Seminar
Exploring interactive robot learning with large pretrained models, focusing on visual representations, data collection strategies, and leveraging language models for robotics applications.
SleepFM - Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals
Explore SleepFM, a groundbreaking multi-modal foundation model for sleep analysis, leveraging brain, cardiac, and respiratory data to improve sleep stage classification and disorder detection.
Could a Purely Self-Supervised Foundation Model Achieve Grounded Language Understanding?
Exploring the potential of self-supervised foundation models for grounded language understanding, discussing semantics, multi-modal streams, and causal abstraction in large networks.
Are Foundation Models Castles in the Air?
Explore the trustworthiness and effectiveness of foundation models in AI with Stanford professor Percy Liang, examining their potential and limitations for human-computer interaction and continuous learning.
AI Transformation in Enterprise Data Strategies - Snowflake CEO Sridhar Ramaswamy
Explore the transformative impact of AI on enterprise data strategies in this 56-minute video featuring Snowflake CEO Sridhar Ramaswamy. Delve into Ramaswamy's journey from Google to Snowflake, the evolving role of foundation models, and Snowflake's AI s…
New Perspectives on Harnessing Foundation Models for Robot Learning
Explore innovative approaches to integrating foundation models in robotics, focusing on multi-robot collaboration and articulated object reconstruction for enhanced real-world applications.
Foundation Models for Therapeutic Design and Treatment Prediction
Explore foundation models for therapeutic design and treatment prediction, focusing on novel insights in biomedical research and machine learning advancements.
Beyond the Model Zoo - Optimizing Foundation Models for Your Application
Optimize foundation models for specific applications, exploring techniques beyond pre-trained models to enhance performance and efficiency in machine learning projects.
Reproducibility and Data Version Control for LangChain and LLM/OpenAI Models
Explore reproducibility and data version control for LangChain and LLM/OpenAI models using lakeFS. Learn to manage large datasets efficiently and achieve reproducibility in LLM applications.
Understanding Foundation Models: A New Paradigm for Building and Productizing AI Systems
Explore foundation models as a new AI paradigm. Learn practical ways to leverage these models in building and productizing AI systems for your company.
Uber's Journey in Building Multi-Modal Foundation Models
Dive into Uber's approach to developing in-house multi-modal foundation models, optimizing earner onboarding and screening processes globally using Ray for distributed training and deployment.
Foundation Models in Drug Discovery - Ray Summit 2024
Explore how foundation models are revolutionizing drug discovery across multiple biological domains. Gain insights into Recursion's large-scale approach using GPUs, robotics, and petabytes of data to transform pharmaceutical innovation.
From Risk to Resilience - Risk Assessment, Safety Alignment, and Guardrails for Foundation Models
Explore comprehensive safety evaluation and enhancement strategies for foundation models, focusing on risk assessment, alignment techniques, and practical guardrail implementation for AI systems.
Azure ML: Fine Tune Foundation Model con Python SDK para LLama2
Aprende a realizar fine-tuning de modelos de lenguaje como Llama2 para clasificación de texto utilizando el SDK de Python de Azure ML Studio.
Azure Machine Learning - Fine Tune Foundation Model for Text Classification
Aprende a realizar fine-tuning de modelos BERT para clasificación de texto utilizando Azure Machine Learning, mejorando tus habilidades en IA generativa.
Azure ML: Punto de Inferencia Q&A con Foundation Model
Crea un punto de inferencia en línea para modelos QA utilizando Azure Machine Learning Studio y el SDK de Python. Explora el catálogo de modelos base.
Differentially Private Synthetic Data Generation via Foundation Model APIs
Explore generating high-quality differentially private synthetic data using foundation model APIs, overcoming challenges and achieving state-of-the-art results without accessing model weights.
A General-Purpose Robotic Navigation Model
Explore advancements in general-purpose robotic navigation models, including data sharing across robots, generalization capabilities, and applications like kilometer-scale navigation and open-vocabulary instruction following.
From Words to Actions - Foundation Models for Generalist Robot Brains
Explore the potential of Foundation models in robotics, discussing lessons from scaling robot data collection and strategies to leverage these models for practical applications.
Foundation Reward Models for General Robot Skill Acquisition
Explore foundation reward models for general robot skill acquisition, leveraging non-robot data to enhance adaptability in unstructured environments.
Building Adaptable Generalist Robots
Explore cutting-edge approaches for building adaptable generalist robots, focusing on in-context learning, unsupervised reinforcement learning, and leveraging foundation models for improved generalization and task versatility.