During the SXSW 2024 event, Wei Li presented on AI Everywhere with Software and Hardware. In this episode of the AI Today podcast we interview Wei Li. He is VP/GM of the AI Software Engineering Team at Intel.
He shares with what insights from that talk and what he means by AI being everywhere in both hardware and software.
Continue reading AI Everywhere with Software and Hardware: Interview with Wei Li, Intel [AI Today Podcast] at Cognilytica.
AI Today Podcast: Digitizing the Mind: Interview with Dmitry Shapiro, YouAi
AI Today Podcast – AI Glossary Series: Transformer Networks
AI Today Podcast: AI Glossary Series – Boltzmann Machine
AI Today Podcast: AI Glossary Series – Encoder-Decoder, AutoEncoder, and Generative Adversarial Network (GAN)
AI Today Podcast: AI Glossary Series – Convolutional Neural Network (CNN)
AI Today Podcast: AI Glossary Series – Recurrent Neural Networks (RNN) and Long-Short Term Memory (LSTM)
AI Today Podcast: AI Glossary Series – Feed-Forward Neural Network
AI Today Podcast: AI Glossary Series – “Ground Truth” Data and Synthetic Data
AI Today Podcast: AI Glossary Series – Pre-Trained Model and Transfer Learning
AI Today Podcast: Why Data Storage Matters When it Comes to AI: Interview with Justin Emerson, Pure Storage
AI Today Podcast: AI Glossary Series – CPU, GPU, TPU, and Federated Learning
AI Today Podcast: AI Glossary Series – Tokenization and Vectorization
AI Today Podcast: AI Glossary Series – Training Data, Epoch, Batch, Learning Curve
AI Today Podcast: AI Glossary Series – Backpropagation, Learning Rate, and Optimizer
AI Today Podcast: AI Glossary Series – Loss Function, Cost Function and Gradient Descent
AI Today Podcast: AI Glossary Series- Hidden Layer and Deep Learning
AI Today Podcast: AI Glossary Series – Perceptron
AI Today Podcast: AI Glossary Series – Bias, Weight, Activation Function, Convergence, and ReLU
AI Today Podcast: AI Glossary Series – (Artificial) Neural Networks, Node (Neuron), Layer
AI Today Podcast: AI Glossary Series – Feature Reduction, Principal Component Analysis (PCA), and t-SNE
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