5 ways OpenAI’s ChatGPT plugins could change the AI game | The AI Beat
What are the implications of ChatGPT plugins, OpenAI’s latest chess move? Here are five key possibilities.Read More
What are the implications of ChatGPT plugins, OpenAI’s latest chess move? Here are five key possibilities.Read More
Information taken from the GitHub page: https://github.com/Stability-AI/stablediffusion/blob/main/doc/UNCLIP.MD HuggingFace checkpoints and diffusers integration: https://huggingface.co/stabilityai/stable-diffusion-2-1-unclip Public web-demo: https://clipdrop.co/stable-diffusion-reimagine unCLIP is the approach behind OpenAI’s DALL·E 2, trained to invert CLIP image embeddings. We finetuned SD 2.1 to accept a CLIP ViT-L/14 image embedding in addition to the text encodings. This means that the model can be used …
With technology ever-advancing, edge AI is within reach. How to build, validate and push new edge AI software into production.Read More
The field of public health has transformed medicine, yet failed the most vulnerable. This trajectory can be avoided.
I wrote this paper two years ago: https://arxiv.org/abs/2106.09685 Super happy that people find it useful for diffusion models. I had text in mind when I wrote the paper, so there are probably things we can tweak to make LoRA more suited for image generation. I want to better understand how exactly LoRA is used in …
Read more “I’m the creator of LoRA. How can I make it better?”
Skills mapping allows for more complex and personalized work journeys, ultimately allowing organizations to thrive.Read More
New tools like Adventure Game Studio are responsible for a thriving indie scene for the genre.
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Cookies had a good run. The third-party data trackers beloved by marketers have been a part of the consumer web experience since the launch of Netscape in 1994. But, in an effort to position themselves as guardians of consumer privacy—and to comply with increasing regulations—tech giants Apple, Mozilla, and Google have rendered cookies virtually obsolete. …
Read more “Embrace a Cookieless Future With Generative AI and First-Party Data”
Self-training (ST), or pseudo-labeling has sparked significant interest in the automatic speech recognition (ASR) community recently because of its success in harnessing unlabeled data. Unlike prior semi-supervised learning approaches that relied on iteratively regenerating pseudo-labels (PLs) from a trained model and using them to train a new model, recent state-of-the-art methods perform ‘continuous training’ where …