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Recorded 24 February 2026. Smita Krishnaswamy of Yale University presents "Inferring Dynamic Cellular Trajectories and ...

Princeton Professor Tom Griffiths talks to @JonKrohnLearns about his new book, The Laws of Thought, which grapples with the ...

St. Petersburg, a city of imperial grandeur and complex geography, historically struggled with urban management due to its ...

Industrial digital twins are evolving from static simulations into intelligent, real-time systems. At the heart of this transformation are ...

More than a first look at the Valeton GP-50 because in this video I compare them as players of NEURAL AMP MODELS ( NAM ...

In this AI Research Roundup episode, Alex discusses the paper: 'Cut Less, Fold More: Model Compression through the Lens of ...

Artificial intelligence is revolutionizing clinical trials, making them faster, smarter, and more inclusive. In this video, we explain how ...

Recorded 24 February 2026. Smita Krishnaswamy of Yale University presents "Virtual Talk: Inferring Dynamic Cellular ...

By embedding these physical priors directly into neural networks, models can achieve generalizable performance even when ...

Beliefs must shift; neurological science reveals how habits, residing in neural networks, are physiological. Neurobiological events ...

In this episode, we'll talk about the Gemini neural network, specifically how to use Google Gemini. Anyone who hasn't used it ...

From the pixels of the Utah Teapot to the neural networks of ChatGPT, this is a story of vision, cutthroat competition, and the ...

AI for Science at Scale: Transforming Discovery at NERSC In this session of UC Berkeley's AI & Climate Symposium, we explore ...

Learn how to build, train, and evaluate Neural Networks using Python, TensorFlow, and Keras in this complete step-by-step deep ...

What are Transformers? what is Activation function? What is loss function, stochastic Gradient Descent? How to evaluate AI Model ...

... RNNs, self-driving cars, image recognition & more ✓ Neural Networks – perceptrons, backpropagation, advanced architectures ...

I. Disclaimer - AI-generated content reviewed by a PhD Biomedical Science & Neuroscience researcher. Brenna Bray, PhD. II.

Building the AI's Brain: How Artificial Neural Networks (ANN) learn from "Golden Settings"—the perfect historical machine data for ...

... approximately 20% of the population) Sapolsky, R. Stanford University research on neural networks during projection episodes.

In this session of the BIDMaP Seminar Series, we explore the intersection of machine learning and structure-based drug discovery ...