• #22 David vs. Goliath: Open Source Takes on Generative AI Giants - DODS

  • Oct 6 2024
  • Length: 40 mins
  • Podcast

#22 David vs. Goliath: Open Source Takes on Generative AI Giants - DODS

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  • Summary

  • 𝐖𝐞𝐥𝐜𝐨𝐦𝐞 𝐛𝐚𝐜𝐤 𝐭𝐨 𝐭𝐡𝐞 𝐄𝐩𝐢𝐬𝐨𝐝𝐞 21! 🎙 Have you ever wondered how much control you truly have over your Gen. AI models? What about the protection of your data? 🤔 E𝐩𝐢𝐬𝐨𝐝𝐞 #22 𝐨𝐟 “𝐃𝐢𝐚𝐫𝐢𝐞𝐬 𝐨𝐟 𝐚 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭” explores a David vs. Goliath like story: Open source taking on Generative AI Giants. ? Why should you care about models you can run 𝐥𝐨𝐜𝐚𝐥𝐥𝐲 or in your own 𝐩𝐫𝐢𝐯𝐚𝐭𝐞 𝐜𝐥𝐨𝐮𝐝 ? What if you could avoid paying a surplus on each token processed ? And how valuable is the global 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲 constantly improving and innovating these models? IWe also cover relevant 𝐨𝐩𝐞𝐧-𝐬𝐨𝐮𝐫𝐜𝐞 𝐝𝐚𝐭𝐚𝐬𝐞𝐭𝐬 and models for 𝐭𝐞𝐱𝐭-𝐭𝐨-𝐭𝐞𝐱𝐭 and 𝐭𝐞𝐱𝐭-𝐭𝐨-𝐢𝐦𝐚𝐠𝐞 generation. If you're ready to extend your horizon beyond the standard Gen AI providers, this episode is for you! 🪽 Follow Jasmin on LinkedIn: https://www.linkedin.com/in/jasmin-weimueller-bsc2018/ 🪽 Follow Kate on LinkedIn: https://www.linkedin.com/in/kate-nazarova-data-science/ 🪽 Subscribe to our official DODS page: https://www.linkedin.com/company/diaries-of-data-scientist/ Follow us on Medium👇 🖇 Jasmin’s Medium page: https://medium.com/@JasminWhy 🖇 Kate’s Medium page: https://medium.com/@Kate_in_DS Join us on other platforms: 🎧 Spotify: https://open.spotify.com/show/1DAelRe22W8vBHK7rTU361?si=4e4f3d7bc67546cc 🎧 Apple: https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://podcasts.apple.com/us/podcast/diaries-of-a-data-scientist/id1710961657&ved=2ahUKEwjhm8PdhMWIAxV6qZUCHYZsCDwQFnoECBsQAQ&usg=AOvVaw1deaPC2MF6aWM69-SKSRoH 🎧 Amazon: https://amzn.asia/d/7J3UkTE 🎧 Podimo: https://podimo.com/de/shows/diaries-of-a-data-scientist 🎧 Podscribe: https://app.podscribe.ai/series/2353052 Useful links & Resources: State of Open Source AI :https://github.blog/news-insights/research/the-state-of-open-source-and-ai/ LLaMA https://about.fb.com/news/2024/07/open-source-ai-is-the-path-forward/ **LAION-5B: https://huggingface.co/datasets/danielz01/laion-5b** **The Pile: https://huggingface.co/datasets/EleutherAI/pile** **C4: https://huggingface.co/datasets/legacy-datasets/c4** GPT-Neo / GPT-J: https://huggingface.co/docs/transformers/en/model_doc/gpt_neo; https://huggingface.co/docs/transformers/en/model_doc/gptj **Mixtral 8x7B: https://huggingface.co/mistralai/Mixtral-8x7B-v0.1** **BLOOM: https://bigscience.huggingface.co/blog/bloom** **T5: https://huggingface.co/docs/transformers/en/model_doc/t5** **LLaMA: https://ai.meta.com/blog/llama-3-2-connect-2024-vision-edge-mobile-devices/** Stable Diffusion: https://huggingface.co/models?other=stable-diffusion **DALL-E Mini: https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-Mini-Explained--Vmlldzo4NjIxODA; https://github.com/borisdayma/dalle-mini** **FLUX.1: https://www.bentoml.com/blog/a-guide-to-open-source-image-generation-models**
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