All current Conference Talks courses in 2024
731 Courses
When Knowledge Graph Meets TTPs - Automated and Adaptive Executable TTP Intelligence for Security
Explore automated TTP intelligence for security assessments using knowledge graphs, enhancing breach simulation with adaptive attack chains to evaluate defense capabilities effectively.
EINNET - Optimizing Tensor Programs with Derivation-Based Transformations
Optimizing tensor programs for deep neural networks using derivation-based transformations, outperforming existing optimizers by leveraging a larger search space and automatically creating new operators.
Integrated Information Theory of Consciousness in Conventional Computing
Exploring how computer programs influence cause-effect structures in integrated information theory, challenging assumptions about consciousness in simulated systems.
Learning to Predict Requires Integrated Information
Exploring how Integrated Information Theory quantifies consciousness in neural networks and its relationship with embodied intelligence and predictive learning in AI agents.
Insights from the Conscious Turing Machine - A Machine Model for Consciousness
Explores puzzling phenomena of consciousness using the Conscious Turing Machine model, including pain's impact on sleep, experiences vs. simulations, illusions, dreams, and free will.
Brainish - Formalizing a Multimodal Language for Intelligence and Consciousness
Explores Brainish, a multimodal language for AI consciousness, building on the Conscious Turing Machine. Discusses its syntax, semantics, and implementation for advancing machine intelligence and consciousness models.
On the Link Between Conscious Function and General Intelligence in Humans and Machines
Exploring the connection between consciousness and intelligence in humans and AI, examining theories and proposing a unified model for developing more advanced artificial agents.
Consciousness Meets AI for a New Paradigm
Exploring connections between consciousness and AI, combining theories like Global Workspace Theory with deep learning to develop a new paradigm for general-purpose intelligence and brain-to-brain communication.
Towards an NP-Hard Model of Consciousness
Exploring computational complexity of consciousness, analyzing arguments for non-computability, and proposing conditions for implementable conscious systems in artificial intelligence.
To What Extent Are Machines Conscious?
Exploring machine consciousness: challenges, theories, and implications. Analyzes information, computation, and phenomenal experience in AI, discussing strong vs. weak machine consciousness and their achievability.