In a world increasingly shaped by artificial intelligence, few companies will make a mark in 2024 like the open source project Face hugging.

What started as a chatbot application has since evolved into an open source AI hub, becoming an indispensable resource for researchers, developers, and businesses alike. By 2023, after several investment rounds, Hugging Face was valued $4.5 billion.

Hugging Face is Emerge's Project of 2024 for its transformative role in AI and its dedication to democratizing machine learning. Through visionary leadership, open source tools, and a strong focus on ethics, they empower researchers and startups around the world. Thanks to a thriving online community of open source AI enthusiasts, Hugging Face has become a standard bearer for responsible, collaborative AI innovation.

What is a face hug?

Hugging Face, founded in 2016 by French entrepreneurs Clement Delange, Julian Schumondand Thomas Wolfe Headquartered in New York City, it is an open source platform for Machine learning and Natural language processing.

It consists of huge library Of more than a million Artificial intelligence modelsWith 190,000 datasets and 55,000 demo apps, Hugging Face allows developers, researchers, and data scientists to build, train, share, and deploy AI models.

"We started as a gaming company, and we discovered that we could have a much bigger impact when we started to open source some of our research code. That led to us creating our own Transformers library and seeing the impact and excitement around it in the community," said Wolf, co-founder and president. Science Executive. Decryption. “We believe open source is the key approach to democratizing machine learning.”

In essence it is transformers Library, which offers state-of-the-art pre-trained models for a wide range of tasks. Users can explore models through browser-based inference widgets, access them via an application programming interface (API), and deploy them across computing environments. Hugging Face also promotes collaboration by allowing users to share and fine tune Models through the Hub, a central repository where users can experiment with and contribute to cutting-edge AI models.

Fine-tuning in AI refers to using a pre-trained AI model — which contains weights and features learned from raw data sets to train the model — and adapting it to perform a specific task, or improve performance on a specialized data set.

“Open science and open source AI prevent black box systems, make companies more accountable, and help[solve]today’s challenges – such as mitigating biases, reducing misinformation, strengthening copyright, and rewarding all stakeholders including artists and content creators.” “In the process of creating value,” Co-Founder and CEO Delangue He said On X (formerly Twitter).

Democracy of artificial intelligence

It is common in the decentralized and open source community to “democratize AI,” or empowering individuals to use AI for social good, innovation, and solving complex problems without corporate and government control.

In an industry dominated by proprietary technologies and closed ecosystems, Hugging Face stands out in making cutting-edge tools freely available to the global AI community. DeLange reiterated Hugging Face's commitment to the cause of democratizing AI during a June 2023 congressional hearing of the Committee on Science, Space, and Technology.

“Hugging Face is a US-based community-oriented company with a mission to democratize good machine learning,” Delangue He said During the hearing. “We fulfill our mission primarily through open source and open science, through our platform to host machine learning models and datasets, and the infrastructure that supports research and resources to lower the barrier for all backgrounds to contribute to AI.”

The democratization of AI is particularly impactful in underrepresented regions and industries, where researchers and small startups often lack the resources to compete with tech giants.

“Long-standing and widening divisions in resources, especially between industry and academia, limit the ability to contribute to innovative research and applications,” DeLange told Congress. “We strongly support national AI research resources in the United States and provide resources to small companies and startups conducting public interest research.”

Cooperation over competition

Underscoring Hugging Face's collaborative spirit, the company has worked with other big names in AI, including Google, AWS, Meta, Nvidia, and Microsoft.

In January, Hugging Face collaborated with Google Cloud By combining its open models with Google's infrastructure, all with the goal of making AI more accessible. In the same month, Hugging Face presented Hallucinations LeaderboardsWhich was launched by the company to address the ongoing problem of hallucinating artificial intelligence.

“The challenge now is to have enough startups and teams ready to deploy models across different sectors,” Wolf said. “No need to wait for GPT-5; The time to build AI applications is now by learning how to use, evaluate, and adapt these models in today's world.

In May, Hugging Face expanded its partnership with Microsoft Which launches in 2022, providing developers with a broader infrastructure and tools to create more powerful versions of their Copilot AI models. Later that month, Amazon Announce New alliance with Hugging Face to make it easier for developers to run AI models using Amazon's computer chips.

Computer chip giant Nvidia It announced a collaboration with Hugging Face in July that will bring Nvidia-accelerated inference services to the open source platform, enabling developers to deploy AI models like Llama 3 with up to five times faster symbolic processing.

In October, Hugging Face was launched HuggingChatthe platform's answer to OpenAI's ChatGPT. HuggingChat allows users to choose from a variety of open source AI models for text generation capabilities. This was followed by the release of Hugging Face Genetic AI Services, or Hugswhich allows developers to deploy and train AI models offline in a dedicated environment.

At the Learning Robotics Conference in Germany in November, Hugging Face and NVIDIA announced... partnership To push open source robotics forward, by combining with the Hugging Face robotics platform lerobot Using NVIDIA's AI tools to blend simulation and real-world training — all with the goal of making robots smarter and more effective.

However, it wasn't always smooth sailing for Hugging Face. In November, the company subsequently faced backlash open A dataset containing over a million posts was created using content stolen from Rise Bluesky The social media platform before being removed the next day.

“I have removed Bluesky data from the repo.” “Although I wanted to support the development of tools for the platform, I realize that this approach violates the principles of transparency and consent in data collection,” Hugging Face Machine Learning Librarian Danielle Van Streen Written on Bluesky. "I apologize for this mistake."

The future of face hugging

Moving into 2025, Hugging Face's CEO laid out his predictions for the year ahead in the AI ​​space - including the first major public AI-related outcry, a major company's market capitalization being cut in half due to AI, and over 100,000 AI personal robots poised To work. pre order.

“We will start to see the economic growth and employment potential of AI, with 15 million AI creators in the face,” Delango chirp.

Wolf shared a similarly optimistic view on the future of open source AI and robotics moving into 2025, pointing to more energy-efficient, open-source models.

“There are many things that excite me about the future, but not limited to,” Wolff said. “Smaller models can be more energy efficient, the emergence of open source robotics and the expansion of all the tools we have discovered in artificial intelligence into the realm of science, for example, weather forecasting, materials discovery.”

Hugging Face has played a pivotal role in the evolution of AI in 2024 by driving innovation, global accessibility, and transparency while lowering barriers for startups and developers to create multiple AI solutions.