Google’s supremacy in the AI landscape is under scrutiny. A senior engineer at the tech giant has expressed concerns about Google’s position in the AI race, warning that the company might be lagging behind due to the rapid advancements in open-source AI technologies. This comes amidst increasing competition from other AI leaders like OpenAI, Microsoft, and now the emergent open source community.
Luke Sernau, a respected engineer within Google, voiced these apprehensions in an internal message later made public by semianalysis.com. The crux of his argument centers on Google’s intense focus on its rivalry with OpenAI, which, in his view, is distracting the company from recognizing the real competition: the open source community.
Sernau warns, "While we've been squabbling, a third faction has been quietly eating our lunch. I’m talking, of course, about open source."
He further elaborates that the open source community is outpacing both Google and OpenAI in solving major open problems and making significant leaps in AI development.
Sernau highlights a few examples of open source communities’ prowess, pointing to their ability to run foundation models on devices as compact as a Pixel 6 and fine-tune personalized AI on a standard laptop in just an evening. He emphasizes that these open-source models are not only cheaper and faster but also easily adaptable, making them more appealing to clients than Google’s larger, more complex models.
It’s worth noting the recent success of OpenAI’s chatbot, ChatGPT, which Microsoft immediately integrated into its Bing search engine and across its product lineup. This move, in combination with Google’s introduction of Bard, a rival to ChatGPT, has further amplified the competition within the AI space. However, according to Sernau, the real threat doesn’t lie with OpenAI or Microsoft, but with the open source community.
In response to Sernau’s concerns, a Google spokesperson said, “We’re energized by the activity in this space and the new opportunities it creates,” emphasizing the company’s culture of information sharing, debate, and discussion.
However, Sernau remains critical of the company’s strategy, arguing that Google can’t afford to ignore the commercial implications of the open-source advancements. “People will not pay for a restricted model when free, unrestricted alternatives are comparable in quality,” he wrote. He suggests that Google’s best hope lies in learning from and collaborating with what others are doing outside of Google, focusing on rapid iterations rather than bulky models.
Sernau’s analysis underscores the dynamic nature of the AI landscape and the importance of adaptability in this rapidly evolving field. It’s a clear call to action for Google, and indeed for all companies in the AI race, to acknowledge and adapt to the changing dynamics of the industry. To learn more about the current state of AI and the potential of open-source models, check out this resource.
