The actual paper for DALL-E was released only a few days after we published our episode 2, so in this episode we re-visit DALL-E in its full published glory. Joining us as a special guest for this episode is Aditya Ramesh from OpenAI, the lead author of DALL-E. DALL-E blog post: https://openai.com/blog/dall-e/  DALL-E paper: https://arxiv.org/abs/2102.12092  DALL-E code (encoder/decoder model only, so far): https://github.com/openai/dall-e Deep Learning Deep Dive is also available on YouTube, where we scroll through relevant parts of the paper and code while talking about them: https://www.youtube.com/watch?v=PtdpWC7Sr98 We reached out and collected written consent from all participating audience speakers.

The actual paper for DALL-E was released only a few days after we published our episode 2, so in this episode we re-visit DALL-E in its full published glory. Joining us as a special guest for this episode is Aditya Ramesh from OpenAI, the lead author of DALL-E. DALL-E blog post: <a href="https://www.youtube.com/redirect?event=video_description&amp;redir_token=QUFFLUhqazJYZWFlN1RwSi1QRFdVelNGeVlDMTQxOUVSd3xBQ3Jtc0ttSjd0T3dodUkxMllFOVh6a0R5bnFFSHhmY24xNWpmQno3QTV4bzFIZjRTMDJHQ3B2SmNIcGVXbjE4Y0tLVzF3Qmo1aEZOcDZxS1NPUVZNc29kV1J0ZDVtdHBNQ3RqWnZIVl9NWGMyU2J0UzdtSkZ1RQ&amp;q=https%3A%2F%2Fopenai.com%2Fblog%2Fdall-e%2F" rel="nofollow" target="_blank">https://openai.com/blog/dall-e/</a> DALL-E paper: <a href="https://www.youtube.com/redirect?event=video_description&amp;redir_token=QUFFLUhqbkd0eGthSzd1Rjh4amJidGlvNFVTYUhXSmZNd3xBQ3Jtc0tuNEVqZzVqWmE5ZDlyUnhmOUYxcDdVd1VlXzhRZ3hqVFlpT0NaWFVvLUZFcmtzUFVJcUh6ZlNfUjFrZy1ibkI3LUFjcnowOFNaM3h2X3NNMzloVlVtcXhWbHNxbDlTMHhwMjFyWGZ0WHQ2ZUtBT2ZWMA&amp;q=https%3A%2F%2Farxiv.org%2Fabs%2F2102.12092" rel="nofollow" target="_blank">https://arxiv.org/abs/2102.12092</a> DALL-E code (encoder/decoder model only, so far): <a href="https://www.youtube.com/redirect?event=video_description&amp;redir_token=QUFFLUhqazZTall0Z1Q5ckxzYmYxZEZSbExHdFZKRnhLZ3xBQ3Jtc0tuZmtaUXNFZFp6VmluRmpVWGRDRjVBRWlSejNlZHlXR1R4MjhVei1KN09BZ2ZDbEYyOFBmdnN3Zk5GdGVYSllPaGN6V1RHa3ZGSGx5bXlnU21BQ1EwNGZ3d2c0ZVpqRG53N3lHWnVRVHIwOXV6a2lRNA&amp;q=https%3A%2F%2Fgithub.com%2Fopenai%2Fdall-e" rel="nofollow" target="_blank">https://github.com/openai/dall-e</a> Deep Learning Deep Dive is also available on YouTube, where we scroll through relevant parts of the paper and code while talking about them: <a href="https://www.youtube.com/watch?v=PtdpWC7Sr98" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=PtdpWC7Sr98</a> We reached out and collected written consent from all participating audience speakers.

Episode #3: DALL-E in depth

Andrej Karpathy and Justin Johnson deep dive into OpenAI's DALL-E and use it as an anchor point to recurse into some of the recent work in AI on image generation. Approximate agenda: DALL-E Blog Post: https://openai.com/blog/dall-e/ ImageGPT https://openai.com/blog/image-gpt/ VQ-VAE https://arxiv.org/abs/1711.00937 VQ-VAE-2 https://arxiv.org/abs/1906.00446 Gumbel-Softmax / Concrete Distribution https://arxiv.org/abs/1611.01144 https://arxiv.org/abs/1611.00712 VQGAN https://arxiv.org/abs/2012.09841 Andrej's attempted re-implementation of VQVAE and GumbelSoftmax: https://github.com/karpathy/deep-vector-quantization/blob/main/model.py You can see a video version of this episode on YouTube: https://www.youtube.com/watch?v=gMc90bqHMSM We reached out to all speakers and obtained their written consent to appear in this recording.

Andrej Karpathy and Justin Johnson deep dive into OpenAI's DALL-E and use it as an anchor point to recurse into some of the recent work in AI on image generation. Approximate agenda: DALL-E Blog Post: <a href="https://openai.com/blog/dall-e/" rel="nofollow" target="_blank">https://openai.com/blog/dall-e/</a> ImageGPT <a href="https://openai.com/blog/image-gpt/" rel="nofollow" target="_blank">https://openai.com/blog/image-gpt/</a> VQ-VAE <a href="https://arxiv.org/abs/1711.00937" rel="nofollow" target="_blank">https://arxiv.org/abs/1711.00937</a> VQ-VAE-2 <a href="https://arxiv.org/abs/1906.00446" rel="nofollow" target="_blank">https://arxiv.org/abs/1906.00446</a> Gumbel-Softmax / Concrete Distribution <a href="https://arxiv.org/abs/1611.01144" rel="nofollow" target="_blank">https://arxiv.org/abs/1611.01144</a> <a href="https://arxiv.org/abs/1611.00712" rel="nofollow" target="_blank">https://arxiv.org/abs/1611.00712</a> VQGAN <a href="https://arxiv.org/abs/2012.09841" rel="nofollow" target="_blank">https://arxiv.org/abs/2012.09841</a> Andrej's attempted re-implementation of VQVAE and GumbelSoftmax: <a href="https://github.com/karpathy/deep-vector-quantization/blob/main/model.py" rel="nofollow" target="_blank">https://github.com/karpathy/deep-vector-quantization/blob/main/model.py</a> You can see a video version of this episode on YouTube: <a href="https://www.youtube.com/watch?v=gMc90bqHMSM" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=gMc90bqHMSM</a> We reached out to all speakers and obtained their written consent to appear in this recording.

Episode #2: DALL-E and friends in image generation

Long-form technical deep dives with Andrej Karpathy and Justin Johnson

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