AI: US companies building on Chinese open source LLM AI models. RTZ #923

...an accelerating trend amidst continued US-China 'AI Space Race'

I’ve discussed for a while now how China is leading the US in open source LLM AIs this AI Tech Wave. Having taken the mantle just last year since DeepSeek’s breakthroughs. There’s increasing adoption of Chinese open source LLM AI models by US startups and enterprise customers. Led by Alibaba’s Qwen AI models amongst many others.

NBC outlines the latest details in “More of Silicon Valley is building on free Chinese AI”:

“NBC News spoke to over 15 AI startup founders, machine-learning engineers, industry experts and investors, who said that while models from American companies continue to set the pace of progress at the frontier of AI capabilities, many Chinese systems are cheaper to access, more customizable and have become sufficiently capable for many uses over the past year.”

“The growing embrace could pose a problem for the U.S. AI industry. Investors have staked tens of billions on OpenAI and Anthropic, wagering that leading American artificial intelligence companies will dominate the world’s AI market. But the increasing use of free Chinese models by American companies raises questions about how exceptional those models actually are — and whether America’s pursuit of closed models might be misguided altogether.”

“AI startups are seeing record valuations, but many are building on a foundation of cheap, free-to-download Chinese AI models.”

NBC goes onto to introduce Reflection AI, a US open source LLM AI startup, with the founder having built some of Google’s best AI models. It counts as Nvidia as an investor:

“Surveying the state of America’s artificial intelligence landscape earlier this year, Misha Laskin was concerned.”

“Laskin, a theoretical physicist and machine learning engineer who helped create some of Google’s most powerful AI models, saw a growing embrace among American AI companies of free, customizable and increasingly powerful “open” AI models.”

It was a bit of a rapid surprise, in terms of US adoption of these Chinese new-comers:

“But most of these models were being made in China, and these systems were quickly gaining ground on their U.S. competitors.”

““These models were not that far behind the frontier. In fact, they were surprisingly close to the frontier. The ones that are coming now,” Laskin said, pausing slightly, “well they’re palpably close to the frontier.”

“Laskin founded a startup called Reflection AI, recently valued at $8 billion, to provide an open-source American alternative to these increasingly capable Chinese models that have gained traction in Silicon Valley.”

“You’re starting to see glimpses of open-model companies actually driving the frontier of intelligence in China, and overall, the frontier of intelligence,” Laskin said.”

“Over the past year, a growing share of America’s hottest AI startups have turned to open Chinese AI models that increasingly rival, and sometimes replace, expensive U.S. systems as the foundation for American AI products.”

These Chinese open source models can be run on US AI data center clouds, many from neoclouds and the established cloud vendors like Amazon AWS, Google Cloud, and of course Microsoft Axure. So, not necessarily Trojan horses:

“Michael Fine, head machine learning at Exa, an AI-focused search company valued at $700 million and supported by Silicon Valley mainstays like Lightspeed Venture Partners and Nvidia, said running Chinese models on Exa’s own hardware has proved to be significantly faster and less expensive than using bigger models, like OpenAI’s GPT-5 or Google’s Gemini, in many cases.”

This assures none of the uses of the chinese open source models ever run through China:

“What often happens is we’ll get a feature working with a closed model and realize it’s too expensive or too slow, and we ask, ‘What levers do we have to make this faster and cheaper?’”

“That usually means replacing the closed model with the equivalent open model and then running it on our own infrastructure,” Fine said.”

The most popular Chinese models are already popular amongst US users, with Alibaba of late leading the pack:

“Chinese models, like DeepSeek’s R1 and Alibaba’s Qwen, are free to use and considered “open-source” or “open-weight” because anyone can download, copy, modify and operate them. They differ from leading American systems like Anthropic’s Claude or OpenAI’s most popular GPT models, which are “closed,” or proprietary, and accessed through data centers and pipelines controlled by the big tech giants.”

“For years, American closed-source models from OpenAI and Anthropic vastly outperformed both American and Chinese open alternatives. Even well-resourced in-house efforts to use open-source models struggled: Bloomberg tried to create an internal tool, BloombergGPT, using open-source models trained on its expansive collection of financial news and documents, only to see it trail OpenAI’s closed models on financial knowledge.”

“Yet in the past year, Chinese companies like DeepSeek and Alibaba have made huge technological advancements. Their open-source products now closely approach or even match the performance of leading closed American models in many domains, according to metrics tracked by Artificial Analysis, an independent AI benchmarking company.”

“The gap is really shrinking,” Lin Qiao, CEO of Fireworks AI and co-creator of PyTorch, the dominant framework for training AI models, said of the capability differences between American closed-source and Chinese open-source models.”

Expect this trend to continue, especially as Meta which for a long time had the most popular open source LLM AI models with its Llama products, is now focused on Meta Superintelligence models running on its rapidly ramping AI data centers.

It’s unclear where these new models will land on the open-closed spectrum. Even as Meta and its peers also compete for AI Research Talent worldwide. And as Nvidia’s Jensen Huang reminds us often, China supplies half the world’s supply on that important input.

So even while the geopolitical ‘AI Space Race’ continues between the US and China, AI customers here are increasingly employing open source options from there to use at scale over here. A trend to watch in the next phase of this AI Tech Wave. Stay tuned.

(NOTE: The discussions here are for information purposes only, and not meant as investment advice at any time. Thanks for joining us here)