Introduction to Generative AI by Numa Dhamani: New

Introduction to Generative AI by Numa Dhamani: New

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Generative AI, also known as generative adversarial networks (GANs), is a fascinating subset of artificial intelligence that has gained significant attention in recent years. In this post, we will explore the basics of generative AI and how it works, with insights from Numa Dhamani, an expert in the field.

Generative AI refers to AI systems that can create new data or content that is similar to, but not exactly the same as, the input data they were trained on. This is in contrast to discriminative AI, which focuses on categorizing and classifying data. GANs, a type of generative AI, consist of two neural networks – a generator and a discriminator – that work together to produce realistic outputs.

Numa Dhamani explains that the generator network creates new samples that are then evaluated by the discriminator network. The generator aims to produce data that is indistinguishable from real data, while the discriminator aims to differentiate between real and generated data. Through this adversarial training process, both networks improve their performance over time.

Generative AI has a wide range of applications, from generating images and videos to creating music and text. It has also been used in fields such as healthcare, finance, and security for tasks like data augmentation, anomaly detection, and fraud prevention.

Overall, generative AI is a powerful tool with the potential to revolutionize many industries. Stay tuned for more insights from Numa Dhamani on this exciting technology.
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