Stepfunction Podcast
Seymour and Jeff discuss the recently announced updates from OpenAI, especially regarding image generation in GPT-4 and DALL-E 3. Our ranking of image generation AI's from best to worst: (1) Midjourney, (2) Google Search Generative Experience (SGE), and finally (3) DALL-E. Jeff closes by talking about the recent LLM workshop he conducted for junior high and middle school students. Links: * OpenAI announces new voice chat and image features [https://www.theverge.com/2023/9/25/23886699/chatgpt-pictures-voice-commands-ai-chatbot-openai] for ChatGPT. * DALL-E 3 update [https://techcrunch.com/2023/09/20/openai-unveils-dall-e-3-allows-artists-to-opt-out-of-training/]. * Google Converse [https://www.gadgetsnow.com/featured/how-googles-converse-generative-ai-is-different-from-google-search/articleshow/103252562.cms] aka Google SGE [https://blog.google/products/search/generative-ai-search/] is still better than DALL-E. * Midjourney [https://zapier.com/blog/how-to-use-midjourney/] is still the best. * Regarding earlier deep learning methods of translating sketches into finished drawings, Jeff was thinking of NVIDIA's GauGAN, based on SPatially-Adaptive DEnormalization (SPADE). * 2019 blog post [https://blogs.nvidia.com/blog/2019/03/18/gaugan-photorealistic-landscapes-nvidia-research/] by NVIDIA. * Associated paper at arXiv [https://arxiv.org/abs/1903.07291] and code at GitHub [https://github.com/NVlabs/SPADE]. * From Jeff's workshop: * Definitions for the G,P, and T in "ChatGPT" * Generative (as in generative AI--see this entire podcast 😉). * Pre-trained [https://stats.stackexchange.com/questions/193082/what-is-pre-training-a-neural-network]. * Transformer [https://en.wikipedia.org/wiki/Transformer_(machine_learning_model)]. * Meta/FB's Llama2 [https://ai.meta.com/llama/] (7 Billion parameters). * Fine-Tuning–one of part of many methods to optimize a base model. See charts in this NVIDIA article [https://developer.nvidia.com/blog/selecting-large-language-model-customization-techniques/]. * Low-Rank Adaptation: * Conceptual article about LoRA [https://huggingface.co/docs/peft/conceptual_guides/lora] at HuggingFace. * Original LoRA 2021 paper [https://arxiv.org/abs/2106.09685]. * May 2023 QLoRA paper [https://arxiv.org/abs/2305.14314]. * August 2023 LoRA-FA paper [https://arxiv.org/abs/2308.03303]. * Short Wikipedia description of LoRA [https://Wiki%20article%20--%20https//en.wikipedia.org/wiki/Fine-tuning_(deep_learning)#Low-rank_adaption]. * 2019 programmer joke [https://www.reddit.com/r/ProgrammerHumor/comments/bgrlu4/stackoverflow_in_a_nutshell/] about using Google and StackOverflow [https://en.wikipedia.org/wiki/Stack_Overflow]. Send questions/comments to stepfunctionpod@gmail.com and find us on the web at www.stepfunction.org
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