What-if
Delangue: AI Would Be Decades Behind Without Five Years of Open Source
“If you know, remove the open source from that equation, if they wouldn't have been as much open source at As there's been in the five past five years, we would be like decades away from, you know, where, where we are now.”
Insight
Open-source AI prevents bias better than closed labs, argues Delangue
“Building in the open with open source is actually
more part of the solution than part of the problem, because obviously control of power as you democratize it much more and biases you actually include in the process.
People who are impacted by these biases,…”
Opinion
GitHub probably sold to Microsoft too early, argues Delangue
“So when you talk about, you know, money in GitHub for me, like the, if there was a mistake, it's probably to have sold it too, too early to Microsoft.”
Prediction Not checkable as stated
ML-native companies like Runway are poised to challenge tech incumbents
“And when you look at the capabilities of some of these companies, when they're like translated into product building I mean, runway, you've all seen like the videos of runway. I think that's amazing. And I think they're going to be able to really challenge, ch…”
Prediction Not checkable as stated
Delangue: Open-source and proprietary AI will both permanently coexist
“The truth is that there's always going to be both, right? I think if you see most, most technologies, you know, if you look at search, you always have the elastic search, the Algolia, or like, if you look at databases, you have that MongoDB and the proverter a…”
Insight
Developer platforms like Hugging Face become gateways for compute and infrastructure
“When you get so much usage, so much network effects, and you actually like for a lot of these projects, you are like the starting point. Of projects like the same way. I think probably companies are starting on GitHub to see the open source projects before sta…”
Disclosure
Delangue: Hugging Face dedicates 30% to 40% of effort to exploration
“What we've always done and I think we'll always do with hugging face is to make sure that, you know, Whenever, always kind of like make sure to spend at least like 30 or 40% of the company's efforts on explorating new things and kind of like finding the long-t…”
Disclosure
Hugging Face never hired dedicated PR or community managers, per Delangue
“And then something that we did that I think worked really, really well for us is that we never hired any
Kind of like community manager, any kind of like communication PR kind of team members because we wanted it to be part of every single team members work.”
Disclosure
Every Hugging Face employee has access to its official Twitter account
“Everyone, everyone in the team has access to the Twitter account and are tweeting from the Twitter account.”
Insight
Machine learning models move from research to production in days
“What we're seeing in, in machine learning is that it's actually making its way into production after, you know, a year, a few months, a few weeks sometimes a few days now. So this is, in my opinion, this is amazing. And that's what's driving Most of the speeds…”
Insight
Delangue: Specialized AI models are cheaper, faster, and usually more accurate
“When you look at why are companies using so many models on Hugging Face, you usually realize that you know, a more specialized model is more efficient. It's cheaper to run. It's usually faster to run. And most of the time actually more accurate for the specifi…”
Assertion Not checkable as stated
Hugging Face has 15,000 company users and 3,000 paying customers
“Right now we have like 15,000 companies using, using the platform and we have 3000 companies paying us, right?”
Assertion Supported
Delangue: Hugging Face Spaces reached 50,000 ML demos in ~18 months
“We just crossed 50,000 of machine learning demos in the past year, year and a half on that.”
Assertion Partly supported
Delangue: Hugging Face crossed 250,000 models from nearly 15,000 companies
“On Hugging Face we just crossed 250,000 models, right? A quarter of a million models uploaded by almost 15,000 companies now.”
Assertion Supported
Delangue: NLP, vision, and audio are the top three Hugging Face tasks
“The three main tasks right now are NLP, so text, right?
From like information extraction, text generation, text classification.
the second one is text to image and computer vision, right?
So object detection, text to image, text image generation.
the third o…”
Assertion Supported
Uber calculates ETAs using a time series transformer model, says Delangue
“The ETA from Uber, when you get your Uber is like a transformer time series”
Assertion Not checkable as stated
Delangue: Hugging Face sees rising adoption of opt-in training datasets
“We're starting to see on Hugging Face more and more opt-in data sets, meaning like data sets that have been trained only on data that the creators of the data have consented to having a model trained on.”
Assertion Supported
BigScience is the largest ML collaboration to date, says Delangue
“Big science was like the largest collaboration in, in machine learning to date with like a thousand researchers from 200 organizations, kind of like coming together in order to build and train a large language model completely in the open.”
Disclosure
Hugging Face is building an open-source library for RLHF, says Delangue
“We're leading the development of an open source library that is helping companies integrate that into their models and into their workflows.”
Assertion Supported
Delangue: Bloomberg and Meta are Hugging Face customers
“When we're talking about Bloomberg, for example, using us or Meta using us both being kind of like customers.”
Assertion Not checkable as stated
Delangue: Hugging Face's early AI companion saw billions of messages exchanged
“And we did that for almost, almost three years got some level of traction billions of messages exchanged between, between users and the chatbots.”
