Introduction to Artificial Neural Networks - JSALT 2023
Explore artificial neural networks: fundamentals, architectures, and applications in this comprehensive introduction from JSALT 2023 workshop.
Toward Length Extrapolatable Transformers
Explore innovative techniques for enhancing transformer models' ability to handle longer sequences, improving their performance and scalability in natural language processing tasks.
In Search of Invariance in Brains and Machines
Explore mathematical frameworks for robust AI perception, focusing on Lie theory to model hierarchical structures and transformations in real-world object recognition.
Programming with Neural Surrogates of Programs
Explore neural surrogates for program optimization, including case studies on CPU simulators and techniques like the Renamer and Turaco for constructing efficient program surrogates.
Understanding the Visual World Through Naturally Supervised Code
Explore symbolic structure inference from visual data using neuro-symbolic methods. Learn to leverage natural supervision for discovering repetitive patterns, object intrinsics, and grounded visual concepts.
Can Democracy Handle AI? - The Impact of Artificial Intelligence on Political Campaigns and Misinformation
Explore AI's impact on democracy, political campaigns, and misinformation. Learn about deepfakes, fact-checking, and building resilience against AI-generated content in the digital age.
Machine Vision vs Deep Learning in Cancer Detection
Explore machine vision and deep learning applications in cancer diagnosis, comparing their strengths and limitations. Gain insights into innovative computer-aided methods for analyzing microscopic images of breast cancer tissue.
Свёрточные нейронные сети - Анализ изображений петрографических шлейфов
Изучите анализ изображений петрографических шлейфов с помощью свёрточных нейронных сетей для геологических исследований.
Finite Neuron Method - Lecture 2
Explore finite neuron method, covering electrical entropy, curse of dimensionality, neural networks, and approximation properties. Gain insights into deep learning concepts and techniques.
AI-900 Study Guide: Non-Generative AI Fundamentals - Lecture 1
Explore AI fundamentals, machine learning, deep learning, and Azure's AI services. Master key concepts and prepare for the AI-900 exam with practical insights and exam tips.
Generative AI Based on Transformer Neural Networks - Fundamentals, Implications and Trends
Explore fundamentals, implications, and trends of generative AI using transformer neural networks in this comprehensive Stanford Otolaryngology grand round.
Building a Computerised Maintenance Management System with Hyperledger Fabric and Firefly
Explore building a Computerised Maintenance Management System using Hyperledger Fabric and Firefly. Learn from an expert about blockchain applications in operations and maintenance.
Adventures in Building CLIP and Other Large Language Models
Explore insights on building CLIP and large language models, AI integration, and balancing tech career with family life. Gain valuable perspectives from a seasoned Deep Learning Engineer.
The Centralization of Power in AI - MLOps Podcast Episode 181
Explore AI power centralization, language limitations, and open-source initiatives. Gain insights on AI transparency, accountability, and the evolving landscape of machine learning frameworks.
Introduction to Artificial Intelligence - Neural Networks - Lecture 18
Explore neural networks' fundamentals, structure, and applications in AI problem-solving, with hands-on assignments applying techniques to simple games.
Introduction to Artificial Intelligence: Neural Networks - Lecture 19
Explore fundamental concepts of neural networks in AI, including structure, functionality, and applications in modern problem-solving environments.
Intro to Artificial Intelligence - Deep Neural Networks - Lecture 20
Explore deep neural networks, their architecture, and applications in AI. Learn key concepts and techniques for implementing advanced machine learning models.
Introduction to Artificial Intelligence: Neural Networks - Lecture 20
Explore fundamental concepts of neural networks, their structure, and applications in AI problem-solving environments.
Understanding and Mitigating Loss of Control in AI Systems
Explore AI control challenges and mitigation strategies with Professor Yoshua Bengio's keynote on understanding and addressing potential loss of control in artificial intelligence.
Democratizing Deep Learning with DeepHyper
Explore DeepHyper: Automate DNN design for scientific data using scalable neural architecture and hyperparameter search. Learn to generate DNN ensembles for uncertainty estimation in various applications.
A Chiplet-Based Generative Inference Architecture with Block Floating Point Datatypes
Explore a chiplet-based architecture for generative inference, featuring block floating point datatypes and optimizations for large language models in AI accelerated computing.