Forecasting the Future with EarthPT
Explore EarthPT, an open-source Earth Observation pretrained transformer. Learn about its capabilities in predicting surface reflectances, vegetation indices, and potential applications in land use classification and crop yield forecasting.
Generative AI for Search
Explore the powerful role of generative AI in search, focusing on NLP and Vision. Discover key challenges and promising directions through anecdotes and organizing principles.
Generative AI for Product Builders
Explore generative AI's potential to enhance products, accelerate workflows, and unlock creativity. Learn about technical challenges and solutions in building AI-powered products.
Early Alignment in Two-Layer Networks Training: A Two-Edged Sword
Explore early alignment in two-layer network training, examining its dual nature as both beneficial and potentially problematic for neural network performance.
How to Finetune and Develop Your Own Large Language Model
Explore techniques for fine-tuning and developing custom large language models, enhancing your AI capabilities and understanding of advanced NLP concepts.
CyberMirage: AI DeepFake LIVE Demo
Witness a groundbreaking AI DeepFake LIVE demo showcasing the viral CyberMirage technology. Explore cutting-edge cybersecurity implications with seasoned expert Brandon Kovacs at HackMiami XI.
Accelerate AI Inference Workloads with Google Cloud TPUs and GPUs
Optimize AI inference using Google Cloud's TPUs and GPUs. Compare accelerators for various workloads, deploy efficiently, and implement cost-effective strategies for high-performance model deployment.
Accelerate AI Training Workloads with Google Cloud TPUs and GPUs
Explore key considerations for choosing TPUs and GPUs, optimize AI training workflows, and discover best practices for performance and cost-effectiveness on Google Cloud.
Take Large Scale AI from Research to Production with Google Cloud's AI Hypercomputer
Discover Google Cloud's AI Hypercomputer: a supercomputing architecture optimizing hardware, software, and consumption models for efficient AI deployment at scale. Gain insights from Kakao Brain and Nuro's experiences.
Non-convex SGD and Lojasiewicz-type Conditions for Deep Learning
Explore non-convex SGD and Lojasiewicz-type conditions for deep learning in this mathematical conference talk by Kevin Scaman at CIRM.
Frontiers of Foundation Models for Time Series
Explore foundation models for time series data, addressing challenges in science applications and discussing future research directions in deep learning for time series analysis.
Attention Is All You Need - A Landmark Paper in AI
Explore the groundbreaking "Attention Is All You Need" paper, its impact on modern AI, and the potential of transformer architecture in various applications beyond machine translation.
Building Threat Detection Systems - An MLE's Perspective
Explore threat detection systems from an MLE's perspective. Gain insights on rule engines, testing ML models, and the importance of writing for professional development in MLOps.
Systems Engineering in Machine Learning - Navigating Low-Level Challenges
Explore systems engineering in ML with Andrew Dye, discussing low-level work, blending disciplines, and ML infrastructure challenges. Gain insights on distributed training, managing scale, and bridging gaps between firmware and MLOps.
Explainability in the MLOps Cycle - MLOps Podcast Episode 138
Explore explainability in MLOps with Dattaraj Rao. Gain insights on rule-based systems, ML model deployment, and emerging trends in AI. Learn about responsible AI and practical applications in various industries.
Fine-Tuning LLMs: Best Practices and When to Go Small - Lecture 124
Explore best practices for fine-tuning LLMs, including strategies for improving performance, overcoming challenges, and determining when to use smaller models for specific tasks.
From Arduinos to LLMs: Exploring the Spectrum of ML - MLOps Podcast Episode 162
Explore MLOps spectrum from LLMs to TinyML. Gain insights on model deployment challenges, IoT integration, and strategies for constrained environments. Learn about the intersection of machine learning and electronics.
Evaluating LLM-based Applications - Part 2
Learn hands-on techniques for evaluating language models, including data sourcing, automated metrics, and human evaluation. Gain practical tools for assessing LLM-based applications effectively.
Ads Ranking Evolution at Pinterest - From Logistic Regression to Deep Learning
Explore Pinterest's ads ranking evolution, from logistic regression to deep learning transformers, incorporating sequential signals and multi-task learning. Gain insights on overcoming challenges and advancing ML platforms.
GenAI in Production - Challenges and Trends - Lecture 224
Explore challenges and trends in Generative AI production, including model size, context windows, multimodality, and regulation. Gain insights from Gemini 1.0 vs 1.5 comparisons and industry expert Verena Weber's experiences.
AWS Trainium and Inferentia - Enhancing AI Performance and Cost Efficiency
Explore AWS Trainium and Inferentia's AI accelerators for enhanced performance, cost savings, and seamless integration with popular frameworks. Learn about their benefits and implementation in ML workflows.