Clement Delangue, co-founder and CEO of New York-based Hugging Face, turned a casual invitation to meet with open-source AI stakeholders during a trip to San Francisco into what is being called the “Woodstock of AI.” In a matter of days, the event ballooned to more than 5,000 people hosted at the Exploratorium on March 31. “We just crossed 1,500 registrations for the Open-Source AI Meetup!” Delangue messaged the RSVP list days before the event. “What started with a tweet might lead to the biggest AI meetup in history.” The 8-year-old company is also making headlines for its new HuggingGPT system. Continue reading Hugging Face Rallies Open-Source AI Community at Meetup

Google has released a research paper on a new text-to-image generator called Imagen, which combines the power of large transformer language models for text with the capabilities of diffusion models in high-fidelity image generation. “Our key discovery is that generic large language models (e.g. T5), pretrained on text-only corpora, are surprisingly effective at encoding text for image synthesis,” the company said. Simultaneously, Google is introducing DrawBench, a benchmark for text-to-image models it says was used to compare Imagen with other recent technologies including VQGAN+CLIP, latent diffusion models, and OpenAI’s DALL-E 2. Continue reading Google’s Imagen AI Model Makes Advances in Text-to-Image