Home » Hugging Face hosts ‘Woodstock of AI,’ emerges as main voice for open-source AI growth

Hugging Face hosts ‘Woodstock of AI,’ emerges as main voice for open-source AI growth

by Oscar Tetalia
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Hugging Face, the fast-growing New York-based startup that has turn out to be a central hub for open-source code and fashions, cemented its standing as a number one voice within the AI group on Friday, drawing greater than 5,000 individuals to an area meetup celebrating open-source expertise on the Exploratorium in downtown San Francisco.

The gathering was serendipitously born three weeks in the past, when Hugging Face’s charismatic cofounder and CEO, Clement Delangue, tweeted that he was planning to be in San Francisco and wished to satisfy with others all in favour of open-source AI growth. 

Within days, curiosity within the casual meetup snowballed. Registrations ballooned into the 1000’s. In the ultimate week earlier than the occasion, Delangue booked the Exploratorium museum, one of many few venues nonetheless obtainable that might assist 1000’s of individuals.

He turned the casual meetup into an enormous showcase and networking alternative for these fascinated by synthetic intelligence, from real-world researchers and programmers to buyers, entrepreneurs and the merely curious.


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“We simply crossed 1,500 registrations for the Open-Source AI Meetup!” Delangue mentioned in a textual content blast to the RSVP record just some days earlier than the occasion. “What began with a tweet may result in the most important AI meetup in historical past.”

Hugging Face CEO Clem Delangue messages attendees that his occasion is perhaps “the most important AI meetup in historical past.”

The occasion was set towards the backdrop of a rising debate over giant language fashions (LLMs) and their functions. Critics have expressed considerations concerning the potential monopolization and commodification of closed LLMs by OpenAI and different corporations, resembling Google and Microsoft.

In distinction, open LLMs are educated on basic internet information and function a substrate for downstream functions to construct upon. The open-source group views LLMs as a public good or a standard useful resource, slightly than a personal services or products.

Open-source AI has a breakout second

Attendees started streaming into the Exploratorium round 6 pm on Friday and didn’t cease coming for hours. They fashioned a hanging mix of ages, races and backgrounds, together with retirees, mother and father, engineers and huge teams of 20-somethings wearing a variety of apparel — from ball robes to saggy denims — a broad mixture of excessive style and streetwear. The ambiance was stuffed with vitality and the group buzzing with pleasure, much like a music pageant.

In temporary remarks, Delangue addressed the attendees and mentioned the turnout testified to the rising mainstream curiosity and pleasure round open-source AI growth. He mentioned Hugging Face’s mission was to make state-of-the-art AI accessible to as broad an viewers as doable and, within the course of, enhance transparency throughout the ecosystem.

“We anticipated perhaps just a few, 100 individuals to point out up,” Delangue mentioned in an tackle to attendees. “We have 5,000 individuals tonight. That’s wonderful. People are calling it the ‘Woodstock of AI.’”

“I feel this occasion is a celebration of the facility of open science and open supply,” mentioned Delangue. “I feel it’s actually essential for us to recollect in AI that we’re the place we’re due to open science and open supply.”

“If this wasn’t for the ‘Attention Is All You Need’ paper, for ‘The Birth’ paper, and for the ‘Latent Diffusion’ paper, we is perhaps 20, 30, 40 or 50 years away from the place we’re at the moment by way of capabilities and prospects for AI,” he mentioned. “If it wasn’t for open-source libraries or languages, if it wasn’t for frameworks like PyTorch, TensorFlow, Keras, Hugging Face, transformers and diffusers, we wouldn’t be the place we’re at the moment.”

“Open science and open supply [are ways] to construct a extra inclusive future, with much less focus of energy within the fingers of some, extra contribution from underrepresented populations to battle biases, and general a a lot safer future with the involvement of civil society, of nonprofits, of regulators to carry all of the optimistic influence that we are able to have with AI and machine studying,” Delangue added. “And that’s what we’ve seen on Hugging Face: the influence of open science open supply. All of you within the room have contributed to over 100,000 open fashions on the platform.”

The battle between open and closed LLMs

In latest weeks, a high-stakes debate has been unfolding over whether or not new giant AI fashions ought to stay proprietary and commercialized or as a substitute be launched as open-source applied sciences.

On one aspect, researchers argue transparency reduces dangers and business pressures to deploy AI earlier than it’s prepared; on the opposite, corporations say secrecy is required to revenue from and management their expertise. The difficulty has come to a head in latest weeks as LLMs start to lift alarms, however there’s nonetheless no consensus on whether or not open science or commercialized AI will yield extra reliable programs.

On Wednesday, three days previous to the open-source AI occasion, a extremely contentious open letter calling for a six-month pause on large-scale AI growth made the rounds within the AI group. The letter was signed by high-profile names resembling Elon Musk, Steve Wozniak, Yoshua Bengio, Gary Marcus and a number of other thousand different AI consultants, researchers and trade leaders.

“I feel OpenAI has completed unimaginable work advancing the state-of-the-art. I feel first they’re advancing giant language fashions via GPT-2 and GPT-3 — after which the instructGPT or ChatGPT-style mannequin that follows directions. So, I feel that’s no less than two main breakthroughs that OpenAI has been chargeable for,” Andrew Ng, probably the most influential voices in machine studying over the previous decade, mentioned in an interview with VentureBeat.

“At the identical time, I really feel like I’m additionally enthusiastic about all of the open-language fashions which might be being launched,” he added. “But I feel it’s very cheap if, for various causes, totally different corporations select to have totally different insurance policies. I’m excited concerning the very open fashions and grateful for all of the researchers publishing open fashions, however I’m additionally grateful for all of the work that OpenAI has completed to push this out.”

The path to moral AI probably relies on balancing scientific openness and company secrecy. But that steadiness clearly stays elusive, and the way forward for AI hangs within the steadiness. How tech corporations and researchers collaborate — or don’t — will decide whether or not AI elevates or endangers our lives. The stakes are immense, however so, too, are the challenges of navigating this debate.

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