Skip to content
Github Business

Github Business

Business Printing

Primary Menu
  • Github Business
  • Advertise Here
  • Contact Us
  • Privacy Policy
  • Sitemap
  • Home
  • Hugging Face Wants To Be Launchpad For A Machine Learning Revolution
  • Github Business

Hugging Face Wants To Be Launchpad For A Machine Learning Revolution

By Milton Clarendon 1 week ago

Table of Contents

  • Newly valued at $2 billion, the AI 50 debutant originated as a chatbot for teenagers. Now, it has aspirations—and $100 million in fresh dry powder—to be the GitHub of machine learning.
      • MORE FROM AI 50 2022

Newly valued at $2 billion, the AI 50 debutant originated as a chatbot for teenagers. Now, it has aspirations—and $100 million in fresh dry powder—to be the GitHub of machine learning.


When Hugging Face first announced itself to the world five years ago, it came in the form of an iPhone chatbot app for bored teenagers. It shared selfies of its computer-generated face, cracked jokes and gossiped about its crush on Siri. It hardly made any money.

The viral moment came in 2018—not among teens, but developers. The founders of Hugging Face had begun to share bits of the app’s underlying code online for free. Almost immediately, researchers from some of the biggest tech names in the business, including Google and Microsoft, began using it for AI applications. Today, the chatbot has long since disappeared from the App Store, but Hugging Face has become the central depot for ready-to-use machine-learning models, the starting point from which more than 10,000 organizations have created AI-powered tools for their businesses.

Related Posts:

  • GitHub Universe 2018 zeros in on the future of software development

Hugging Face announced Monday, in conjunction with its debut appearance on Forbes’ AI 50 list, that it raised a $100 million round of venture financing, valuing the company at $2 billion. Top-tier venture capital firms Coatue and Sequoia won slots as new backers in the hotly contested Series C, joining A.Capital Ventures, Addition Capital and lead investor Lux Capital as major stakeholders in the Brooklyn-based startup.

“Machine learning is becoming the new way to build technology, replacing software,” says Clément Delangue, cofounder and CEO of Hugging Face, which is named after the emoji that looks like a smiling face with jazz hands. “The old school of building technology was writing a million lines of code. Machine learning is starting to do that, but much better and much faster.”

Hugging Face CEO Clément Delangue: “A year or two ago, machine learning was still considered almost as a bet. Now it’s becoming—for the best-in-class companies—the default way of building technology.”

Hugging Face

Speaking from his home in Miami, where he moved during the pandemic (weather, not web3, he explains), Delangue, 33, says he believes that what GitHub is for software, Hugging Face has become for machine learning. That’s a confident comparison, considering the widespread popularity of GitHub, which is used by more than 70 million developers to share and collaborate on code and was last recorded making $300 million in revenue at the time of its $7.5 billion sale to Microsoft in 2018. Hugging Face, by contrast, generated less than $10 million last year, according to three people familiar with its finances. Delangue declines to comment on the number, but he and investors think that machine learning is already becoming the single most important technology of the 2020s, and that Hugging Face can eventually make billions in revenue with its own army of AI-minded developers.

“The companies you would assume are competitors on first blush—whether it’s Google or Amazon or Facebook—almost all of them are proponents,” says Lux Capital’s Brandon Reeves, who first invested in Hugging Face in 2019. “It really feels like this Switzerland-like piece of real estate in the ecosystem.”

“I don’t really see a world where machine learning becomes the default way to build technology and where Hugging Face is the No. 1 platform for this, and we don’t manage to generate several billion dollars in revenue.”

Hugging Face CEO Clément Delangue

Growing up in La Bassée, a small town of 6,000 in the north of France, Delangue recalls an idle childhood until he got his first computer at age 12. By 17, he’d become one of the top French merchants on eBay, selling ATVs and dirt bikes he imported from China and stockpiled in his father’s garden equipment shop. That prowess impressed eBay, which offered him an internship once he began college at ESCP Business School in Paris. Representing the company at an e-commerce trade show, Delangue was accosted by another attendee who trashed eBay’s recent acquisition of a barcode-scanning app—barcodes, the man said, would soon be obsolete because of advances in AI.

The man turned out to be a cofounder of Moodstocks, a startup making image-recognition software using machine learning. “With a very small team, they were managing to do stuff on par with what Google was doing with 100 times more people,” he says (years later, the company was acquired by Google). Impressed by the nimbleness of startups, Delangue never looked back. He declined eBay’s offer to extend his internship so that he could spend his free time at Moodstocks. After graduating in 2012, he turned down a job from Google to run his own startup. Delangue’s idea for a collaborative note-taking app didn’t go far, but in the tight-knit European startup scene he met Julien Chaumond, a fellow entrepreneur building a collaborative ebook reader. The pair riffed on their mutual interest in open technology and talked about starting a company together.

That time came in 2016, after both their companies had ground to a halt. A third cofounder was recruited in Thomas Wolf, a college friend of Chaumond’s who had gone on to receive a Ph.D. in physics and written research papers on machine learning. For the business idea, they settled on “open-domain conversational AI”—in other words, a chatbot that could understand any kind of conversation topic—because they felt it was the most difficult problem in technology they had the expertise to tackle at the time, Delangue says. “There’s this dream we all have to speak with an AI about everything, like you see in sci-fi.”

Hugging Face began as a personalized, Tamagotchi-like friend powered by a form of AI known as natural language processing (NLP). To train the chatbot’s natural language capabilities, the team also built an underlying library to house various machine-learning models—for example, one to detect the emotions behind a text message and another to be able to generate a coherent response—and the many datasets for understanding different kinds of conversational topics, like sports or classroom gossip. Harking back to the founders’ values for open collaboration, they released free pieces of the library as an open-source project on GitHub. The company participated in a bot-specific accelerator program run by the New York-based startup studio Betaworks and raised seed funding from venture capitalists as well as NBA star Kevin Durant. But two years in, their chatbot hadn’t made much money and was losing its hold on the attention spans of its young users.

Around the same time, researchers at Google and OpenAI announced the development of “transformers,” a new type of NLP model that demolished the reading comprehension abilities of both humans and the best AI incumbent at the time. By 2019, Google was powering its search results using this model. Hugging Face’s open-source library appeared at the perfect time for organizations that wanted to harness these NLP breakthroughs but didn’t have the same machinery as Google to build them from scratch. It became a near-instant hit as the machine-learning community converged around it as the central base for deploying transformer models. “We released things without thinking too much about it and the community blew up, as a surprise even to us,” Delangue says.

Reeves, the Lux investor, first met Delangue at a coffee shop in downtown San Francisco on a Friday near the end of 2019. Scared to miss out on a chance to invest, he offered a term sheet the following Monday at an $80 million valuation. “For 90% of the companies I’ve invested in, I’ve known them for many weeks or months or years,” he says. “I don’t think any have come over a weekend.” Since Delangue accepted Lux’s check, usage has continued to skyrocket. The developer community has built more than 100,000 machine learning models on Hugging Face, enabling others in turn to use those pretrained models for their own AI projects instead of having to build models from scratch. On GitHub, Hugging Face has accumulated “stars”—a vanity metric measuring the popularity of an open-source project—at a faster pace than the projects behind Confluent (annual revenue of $388 million), Databricks (more than $800 million) and MongoDB ($874 million).

From Hugging Face’s inception in 2016, the cofounders have worked from different countries: CEO Delangue in the U.S., chief technology officer Julien Chaumond in France and chief scientist Thomas Wolf in the Netherlands.

Hugging Face

Although funding rounds for companies with similar stature were plentiful in 2021, the growth-stage venture capital market has since slowed to a near halt. Hugging Face’s latest financing then indicates a more rarified vote of investor confidence, but some in the data startup ecosystem have privately expressed curiosity about how Delangue can grow Hugging Face’s revenue enough to validate its hefty valuation. Delangue thinks that if enough free users get hooked on Hugging Face, the money will follow in time from some of the companies that employ the users. “Given how valuable machine learning is and how mainstream it’s becoming, usage is deferred revenue,” Delangue says. “I don’t really see a world where machine learning becomes the default way to build technology and where Hugging Face is the No. 1 platform for this, and we don’t manage to generate several billion dollars in revenue.”

Hugging Face only started to offer paid features last year and counts more than 1,000 companies as customers, according to Delangue, including Intel and his former stomping ground eBay. Pharmaceutical giants Pfizer and Roche pay for enterprise-grade security features, while Bloomberg is paying to run machine learning for its real-time terminal through Hugging Face instead of having to build out its own infrastructure. Microsoft is not a customer, but prominently uses Hugging Face as the basis to train its Bing search engine to better understand natural language queries.

“They prioritized adoption over monetization, which I think was correct,” says Sequoia partner Pat Grady, one of the new investors. “They saw that transformer-based models working their way outside of NLP and saw a chance to be the GitHub not just for NLP, but for every domain of machine learning.” Indeed, over the course of the last year, Hugging Face has started to become a hub for machine learning models for a variety of uses, such as computer vision to train image recognition in self-driving cars and recommender systems to help pharmaceutical companies predict the effectiveness of new drug therapies.

If his assumptions of machine learning supremacy are wrong, Delangue says Hugging Face is close to breakeven and has all $40 million from its previous fundraise still in the bank to reorient. “One of my personal learnings as an entrepreneur is to not think too much strategically with a big business plan of ten years, but more to experiment and follow the validation of the community and what they’re telling you,” he says. If the vision pans out, Reeves thinks the prize could be a $50 billion or $100 billion market capitalization on the stock market. It’s no wonder that Delangue says he’s turned down multiple “meaningful acquisition offers” and won’t sell his business, like GitHub did to Microsoft.

“We want to be the first company to go public with an emoji, rather than a three-letter ticker,” he says with an emoji-like smile. “We have to start doing some lobbying to the Nasdaq to make sure it can happen.”

MORE FROM AI 50 2022

MORE FROM FORBESAI 50 2022: North America’s Top AI Companies Shaping The FutureBy Helen A. S. Popkin
MORE FROM FORBESThe $2 Billion Emoji: Hugging Face Wants To Be Launchpad For A Machine Learning RevolutionBy Kenrick Cai
MORE FROM FORBESAI Upstart Waabi Adding Self-Driving Veterans In Race To Commercialize Robot TrucksBy Alan Ohnsman
MORE FROM FORBESMashgin Hits $1.5 Billion Valuation With AI-Powered Self-Checkout SystemBy Rashi Shrivastava

Tags: American Express Business Cards, At&T Business Login, Att Business Customer Service, Att Business Internet, Bad Business Codes, Bank Of America Small Business, Buffalo Business First, Business Administration Jobs, Business Administration Salary, Business Analyst Jobs, Business Card Dimensions, Business Casual Female, Business Casual For Women, Business Casual Women Outfits, Business Ideas 2021, Business Letter Example, Business License California, Business Name Search, Business Process Reengineering, Business Proposal Template, Buy A Business, Card For Business, Chase For Business, Chase Ink Business Card, Columbia Business School, Costco Business Center San Jose, Emirates Business Class, Facebook Business Account, Fictitious Business Name, Florida Business Entity Search, Ga Sos Business Search, Georgia Business Search, Google Business Email, Houston Business Journal, Illinois Business Search, Instagram Business Account, Is Lularoe Still In Business, London Business School, Master Of Business Administration, Men'S Business Casual, Pittsburgh Business Times, Qualified Business Income Deduction, Sacramento Business Journal, Secured Business Credit Card, Standard Business Card Size, T Mobile Business, Texas Business Search, Tië³´o The Business, Top Business Schools In Us, Types Of Business

Continue Reading

Previous Searchable.ai launches Collections to empower teams of all kinds with advanced, seamless knowledge sharing
Next Decentralization is helping to shape the course of scientific research and business

Recent Posts

  • Fireblocks unveils Web3 Engine to support DeFi and NFT apps
  • IMF’s Georgieva says finance leaders must prepare for more inflation shocks
  • 6 Free Advertising Ideas for Your Small Business
  • How to choose and maximize the benefits at your new job
  • Bruce Billson says regulation falling “disproportionately” on small business

Archives

  • May 2022
  • April 2022
  • March 2022
  • October 2021
  • August 2021
  • July 2021
  • June 2021
  • May 2021
  • April 2021
  • March 2021
  • February 2021
  • January 2021
  • December 2020
  • November 2020
  • November 2018
  • January 2017

Categories

  • Business & Finance News
  • Business Finance & Support
  • Financial Function
  • Github Business
  • Iphone Business
  • Largest Business

visit now

Computer Science Degree
Intellifluence Trusted Blogger

backlinks

linkspanel

textlinks

bestwindshieldwipers2019.xyz © All rights reserved. | Magazine 7 by AF themes.
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept”, you consent to the use of ALL the cookies.
Cookie settingsACCEPT
Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Non-necessary
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.
SAVE & ACCEPT