Finally, a killer app for multi-modal foundation models! 🀄️🤖 https://t.co/t9w9PSjyDl
— hardmaru (@hardmaru) 10 juin 2023
Finally, a killer app for multi-modal foundation models!
By
–
Finally, a killer app for multi-modal foundation models! 🀄️🤖 https://t.co/t9w9PSjyDl
— hardmaru (@hardmaru) 10 juin 2023
Finally, a killer app for multi-modal foundation models!

By
–
Note that due to concerns in relation to responsible AI, we are not releasing Imagen Editor to the public.

By
–
Guidance enables you to control modern language models more effectively and efficiently than traditional prompting or chaining. Guidance programs allow you to interleave generation, prompting, and logical control into a single continuous flow https://
bit.ly/3J5lJCY
By
–
AI chips are a new type of microprocessor designed to improve the performance of AI applications. These are to be widely used in smart homes, self-driving cars, robotics & other technologies. Discover seven interesting AI chips for Generative AI here: https://
rb.gy/6ywvo
By
–
this is really taken out of context! the question was about competing with us with $10 million, which i really do think is not going to work. but i still said try! however, i think it’s the wrong question.
By
–
New YouTube short! It is possible to generate music using #AI with just a text and it’s amazing!! Less than 48 hours ago, @MetaAI released a new paper with the code to make #MusicGEN work. I explain it to you.

By
–
The Generative #AI Race Has a Dirty Secret https://
bit.ly/3JWWiEU via @WIRED #ClimateChange #CarbonEmissions
By
–
yes, but we're working on an adapter on top of LLama too. Something we hope will be decently benched vs chatgpt.
By
–
Also don't forget llama exists and weights are available all over the internet. It's illogical to build an LLM from scratch if your goal is build a Chatgpt competitor. Qlora exists to reduce compute costs. Cost argument is weak unless there's some need to reinvent the universe.

By
–
How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources Wang et al.: https://
arxiv.org/abs/2306.04751 #ArtificialIntelligence #DeepLearning #MachineLearning