Machines Behaving Badly: The Morality of AI
Explore ethical considerations and unexpected consequences of AI, including racism in AI assistants, robot rights, self-driving car accidents, and facial recognition limitations.
Cloud AI 100 High Performance Cloud-Edge Inferencing
Explore Qualcomm's Cloud AI 100 accelerator for high-performance cloud-edge inferencing, featuring leadership-class performance, power efficiency, and comprehensive software tools for production deployment.
SAT Net: Issues with Symbol Grounding - Part 2 of 3
Explore critiques of SAT Net, focusing on the symbol grounding problem in neurosymbolic reasoning. Gain insights from Paulo Shakarian's lecture on this advanced AI topic.
SAT Net: Resolving Symbol Grounding - Part 3
Explore symbol grounding in SAT Net through follow-on work, addressing key challenges in neurosymbolic reasoning and artificial general intelligence.
Training Logical Neural Networks via Primal-Dual Methods - Part 1
Explore primal-dual methods for training Logical Neural Networks in neuro-symbolic reasoning, based on Lu et al.'s 2021 IBM research paper.
Training Logical Neural Networks via Primal-Dual Methods - Part 3
Explore primal-dual methods for training Logical Neural Networks in neuro-symbolic reasoning, concluding a series on Lu et al.'s 2021 IBM research paper.
Introduction to NeuPSL - Part 1
Explore NeuPSL, a neurosymbolic framework combining probabilistic soft logic with deep learning for end-to-end training and logical constraint enforcement. Learn its fundamentals and applications in AI.
NeuPSL: Training and Inference - Part 2
Explore NeuPSL's training and inference processes, combining probabilistic soft logic with deep learning for end-to-end training and logical constraint enforcement in neurosymbolic AI.
NeurASP: Model Training - Part 2
Explore NeurASP's end-to-end training process, connecting ASP programs to neural architectures for gradient flow. Learn model training techniques in this neuro-symbolic framework.
Backpropagation: Training Deep Neural Networks
Explore backpropagation, a crucial technique for training deep neural networks through gradient descent, with insights from ASU's Paulo Shakarian.
Technical Shortcomings of Deep Learning - Part 1
Explore technical challenges in deep learning, including data hunger, limited transfer capacity, open-ended inference, and explainability. Gain insights from Gary Marcus's critical appraisal.
Technical Shortcomings of Deep Learning - Part 2
Explore technical challenges in deep learning, including integration with prior knowledge, correlation vs. causation, and data distribution issues. Gain insights into limitations and potential improvements.
Deep Ontological Networks: Experimental Evaluation - Part 3
Explore experimental evaluations of Deep Ontological Networks, covering datasets, results, and comparisons with classical approaches. Gain insights into scaling, challenges, and visualizations.
Five Overlooked Neuro-Symbolic AI Papers from 2022
Explore five overlooked neuro-symbolic AI papers from 2022, covering topics like Logic Tensor Networks, knowledge base completion, symbolic regression, and neural ILP architectures.
Differentiable Inductive Logic Programming - Part 6: Q&A
Explore Q&A session on differentiable inductive logic programming, discussing key concepts and applications in neuro-symbolic AI with Prof. Paulo Shakarian.
Deductive Reasoning for Cross-Knowledge Graph Entailment - Part 1
Explore deductive reasoning for cross-knowledge graph entailment, covering inference types, embedding methods, memory networks, and model architecture for AI and machine learning applications.
Introduction to Propositional Logic for AI
Explore propositional logic fundamentals, including syntax, semantics, and key concepts for AI applications. Gain insights into logic programming and its role in neuro-symbolic AI.
Evaluating ChatGPT on 1,000 Math Word Problems
Explore ChatGPT's performance on 1,000 math word problems through in-depth experiments, revealing its capabilities and limitations in mathematical reasoning.
Learning Logical Relationships with Neural Networks - Part 3
Explore experimental evaluation of Differentiable Inductive Logic Programming for Structured Examples, examining its application in learning logical relationships using neural networks.
Inference in Propositional Logic: From Basics to Lattice Theory Applications
Explore propositional logic inference, including lattice theory and fixpoint operators for entailment queries. Gain insights into logic programming and knowledge reasoning fundamentals.
Deep Symbolic Regression - Petersen et al.'s 2021 ICLR Paper
Explore deep symbolic regression through Petersen et al.'s 2021 ICLR paper, covering innovative techniques at the intersection of symbolic methods and deep learning.