The mechanism that makes Generative AI possible.
A fundamental block of Reinforcement Learning.
The challenge of organizing data in high-dimensional spaces.
A web of interconnected neurons that learn and predict.
The powerful trio: Efficient, Effective, Ensemble.
The AI that drives LLMs and Diffusion models.
Generating text and images that make us question reality.
Humans and machines work together to solve complex problems.
Connecting the 'what' to the 'why' in AI.
Uncovering insights and connections in your data.
A mathematical technique that estimates the true state of a system.
A super smart neural network that stores relevant information.
The wild idea of giving computers some form of self-awareness.
Creating robust AI systems with neural networks and symbolic reasoning.
Why intelligence and motivation don’t go hand in hand for AI.
AI’s way of learning from the past.
Leveraging the principles of quantum mechanics to enhance AI.
Ensuring that AI is ethical, transparent, and accountable.
LLMs that generate human-like text, but don’t actually understand it
A battery of tests to validate if AI is really sentient.
A system’s inability to recognize or understand its own limitations and biases.
An advanced ML technique that enhances the representation and generation of complex data.
Testing AI for common sense via Google-proof free-form conversations.
Transforming convolutional neural networks with depth wise separable convolutions.
Transforming the way machines perceive reality, one swift glance at a time!
Can AI predict the unknown without training? AI’s Evolution.