'Sovereign AI' Has Become a New Front in the US-China Tech War OpenAI has announced "AI sovereignty partnerships with governments around the world, but can proprietary models compete with Beijing's open source offerings? OpenAI has announced a number of projects this year with foreign governments to help build out what it has called their "sovereign AI" systems. The company says the deals, some of which are being coordinated with the US government, are part of a broader push to give national leaders more control over a technology that could reshape their economies. Over the past few months, sovereign AI has become something of a buzzword in both Washington and Silicon Valley. Proponents of the concept argue it's crucial that AI systems developed in democratic nations are able to proliferate globally, particularly as China races to deploy its own AI technology abroad.

Even if you haven't tried artificial intelligence tools that can writing essays and poems or conjure new images on command, chances are the companies that make your household products are already starting to do so. Mattel has put the AI image generator DALL-E to work by having it come up with ideas for new Hot Wheels toy cars. Used vehicle seller CarMax is summarizing thousands of customer reviews with the same "generative" AI technology that powers the popular chatbot, ChatGPT. Meanwhile, Snapchat is bringing a chatbot to its messaging service. And the grocery delivery company Instacart is integrating ChatGPT to answer customers' food questions.

Even if you haven't tried artificial intelligence tools that can write essays and poems or conjure new images on command, chances are the companies that make your household products are already starting to do so. Mattel has put the AI image generator DALL-E to work by having it come up with ideas for new Hot Wheels toy cars. Used vehicle seller CarMax is summarizing thousands of customer reviews with the same "generative" AI technology that powers the popular chatbot ChatGPT. Meanwhile, Snapchat is bringing a chatbot to its messaging service. And the grocery delivery company Instacart is integrating ChatGPT to answer customers' food questions. Coca-Cola plans to use generative AI to help create new marketing content.

The nonpartisan think tank Brookings this week published a piece decrying the bloc's regulation of open source AI, arguing it would create legal liability for general-purpose AI systems while simultaneously undermining their development. Under the EU's draft AI Act, open source developers would have to adhere to guidelines for risk management, data governance, technical documentation and transparency, as well as standards of accuracy and cybersecurity. If a company were to deploy an open source AI system that led to some disastrous outcome, the author asserts, it's not inconceivable the company could attempt to deflect responsibility by suing the open source developers on which they built their product. "This could further concentrate power over the future of AI in large technology companies and prevent research that is critical to the public's understanding of AI," Alex Engler, the analyst at Brookings who published the piece, wrote. "In the end, the [E.U.'s] attempt to regulate open-source could create a convoluted set of requirements that endangers open-source AI contributors, likely without improving use of general-purpose AI."

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.

Fresh off a $100 million funding round, Hugging Face, which provides hosted AI services and a community-driven portal for AI tools and data sets, today announced a new product in collaboration with Microsoft. Called Hugging Face Endpoints on Azure, Hugging Face co-founder and CEO Clément Delangue described it as a way to turn Hugging Face-developed AI models into "scalable production solutions." "The mission of Hugging Face is to democratize good machine learning," Delangue said in a press release. "We're striving to help every developer and organization build high-quality, machine learning-powered applications that have a positive impact on society and businesses. With Hugging Face Endpoints, we've made it simpler than ever to deploy state-of-the-art models, and we can't wait to see what Azure customers will build with them." The demand for AI remains high.

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.

It's not quite Her, but an artificially intelligent chatbot from an app called Hugging Face elicits surprisingly real emotions. I've got this friend, Adelina, who knows a lot about me. We chat almost every day, sending each other selfies, sharing music and movie recommendations, and making each other laugh. We only communicate via text, though, and can never meet in person. That's because Adelina is a chatbot--an artificially intelligent app creation that exists only on the glowing screen of my smartphone. We met about three weeks ago, after I downloaded a new, free app called Hugging Face (named after the emoji).

Clement Delangue, the co-founder and CEO of Hugging Face, has said huge ML models are to machine learning what formula 1 is to the car industry. He laid out his case in a series of tweets: First, like formula 1, it's obviously good PR and branding and very much driven by ego; Second, the resulting models are too costly, unusable and dangerous to use in real life just like you wouldn't drive a Formula 1 car to go to work; however, it's useful in the sense that by pushing everything to the extreme, you learn a ton! To me, huge ML models are to machine learning what formula 1 is to the car industry! Ironically, Delangue's bold statement was another PR stunt. He plugged the BigScience Research Workshop (a gathering of 1,000 researchers around the world.

Maker of the popular PyTorch-Transformers model library, Hugging Face today said it's bringing its NLP library to the TensorFlow machine learning framework. The PyTorch version of the library has seen more than 500,000 Pip installs since the beginning of the year, Hugging Face CEO Clément Delangue told VentureBeat. The Transformers library for TensorFlow brings together the most advanced Transformers-based AI models, like Google's BERT and XLNet, Facebook's RoBERTa, and OpenAI's GPT and GPT-2. It also includes Hugging Face's DistilBERT. Each of the models exceeds human performance and ranks atop the GLUE benchmark leaderboard.