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.

The company’s open-source premise is a reaction to “concerns about the potential monopolization and commodification of closed LLMs by OpenAI and other companies, such as Google and Microsoft,” VentureBeat writes, explaining that by contrast, “open LLMs are trained on general web data and serve as a substrate for downstream applications to build upon.”

Addressing the crowd at the Exploratorium, Delangue said Hugging Face’s mission is making state-of-the-art AI widely accessible while increasing transparency. Calling the event “a celebration of the power of open science and open source,” Delangue credited open-source libraries, languages and frameworks like PyTorch, TensorFlow, Keras and Hugging Face transformers and diffusers along with academic papers for latent diffusion and Google’s BERT with greatly accelerating AI development.

“All of you in the room have contributed to over 100,000 open models” on the Hugging Face platform, Delangue said.

In recent weeks, a contentious debate has unfolded over whether new large language AI models should remain proprietary and corporate or instead be managed as open-source technologies.

“On one side, researchers argue transparency reduces risks and commercial pressures to deploy AI before it’s ready; on the other, companies say secrecy is needed to profit from and control their technology,” writes VentureBeat, noting “there is still no consensus on whether open science or commercialized AI will yield more trustworthy systems.”

Forbes explores how Hugging Face leveraged ChatGPT as a way to control other AI apps using natural language, resulting in what the company calls HuggingGPT.

In a scholarly paper, the group describes how “up to now, our HuggingGPT has integrated hundreds of models on HuggingFace around ChatGPT, covering 24 tasks such as text classification, object detection, semantic segmentation, image generation, question answering, text-to-speech, and text-to-video. Experimental results demonstrate the capabilities of HuggingGPT in processing multimodal information and complicated AI tasks.”

In assessing whether this paradigm is the path to artificial general intelligence (AGI), Forbes considers all that can go right, or wrong, in pursuit “of federated AI involving AI apps that collectively work together and as led by one anointed AI.”

AI ethics and legal issues are working their way to the forefront of such discussions. Last month the White House Office of Science and Technology Policy published a Blueprint for an AI Bill of Rights.

Related:
Hugging Face and AWS Expand Cloud Partnership, SiliconANGLE, 2/21/23
Generative AI Startup Hugging Face Picks AWS to Host Future Large Language Models, Voicebot, 2/21/23