$NVIDIA (NVDA.US)$With its advanced AI chip and powerful software platform CUDA, it has become a leader in the AI field, attracting more than 4 million developers around the world and driving its market capitalization to over $2.4 trillion. Its chips have become including startups,$Microsoft (MSFT.US)$Core infrastructure for many developers such as OpenAI, and Google.

However, the tech giants$Qualcomm (QCOM.US)$,$Alphabet-C (GOOG.US)$und$Intel (INTC.US)$They are teaming up to challenge Nvidia's dominance. They plan to break Nvidia's software monopoly to weaken its market influence. Vinesh Sukumar, Qualcomm's head of AI and machine learning, said:

“We're guiding developers on how to migrate from the Nvidia platform to other platforms.”

Tech giants “join forces”

Nvidia not only relies on its hardware, but also on its 20 years' accumulated software code to become a leader in the AI field, attracting more than 4 million developers around the world to use its CUDA software platform.

CUDA, as a parallel computing platform and application programming interface (API), allows software developers to use Nvidia's GPUs for high-performance computing, enabling Nvidia's GPUs to play a key role in artificial intelligence, scientific computing, and graphics processing.

However, a coalition of tech giants, including Qualcomm, Google, and Intel, is challenging Nvidia's dominance. They plan to target critical software for Nvidia chips by attacking key software for Nvidia chips and work to provide developers with alternative solutions, reduce their dependency on Nvidia, and drive the migration of applications to other platforms.

Furthermore, according to reports, the UXL Foundation, an alliance of technology companies, plans to use Intel's OneAPI technology to develop a set of software and tools to support various AI accelerator chips.

The project aims to enable cross-platform operation of code, enabling developers to write code once and then run it on different hardware platforms without customizing the code for each hardware. This lowers the technical threshold for developers facing different hardware platforms, thereby simplifying the development process, improving efficiency, and accelerating the innovation and application of AI technology.

Google is a founding member of the UXL Foundation. Recently, Bill Hugo, head of Google's high-performance computing department and chief technology officer, said that the UXL Foundation is committed to building an open ecosystem under the machine learning framework and providing more hardware options to help developers run AI applications efficiently. The foundation is planning to finalize technical specifications in the first half of this year, and strive to improve technical details by the end of the year to achieve a stable and reliable technical solution.

Additionally, the UXL Foundation is expanding its range of partners, including$Amazon (AMZN.US)$Cloud computing companies and chip manufacturers such as Microsoft Azure to attract external technical contributions and enrich the technical framework. Currently, a cross-platform AI software tool suite based on Intel OneAPI technology has been put into use, marking an important step in the development of UXL technology.

As time progresses, UXL also plans to support Nvidia's hardware and code, demonstrating the importance it attaches to compatibility with existing mainstream technology. Facing efforts to challenge Nvidia's dominance within the industry, Nvidia executive Ian Buck said, “The world is accelerating. New ideas to accelerate computing will advance the development of AI and computing capabilities, and the entire ecosystem will benefit from it.”

The “encirclement” of over 100 startups

According to PitchBook data, to weaken Nvidia's dominance in AI software, venture capitalists and corporate capital have invested more than $4 billion in 93 different projects, of which the UXL Foundation's plan is just one of many efforts.

In 2023 alone, startups dedicated to challenging Nvidia's leadership received more than $2 billion in investment, compared to only $580 million a year ago, and the market's interest in shaking Nvidia's position through potential weaknesses in software has grown dramatically.

However, startups face a huge challenge, where Nvidia's CUDA software is entrenched in the AI field. Nvidia's CUDA is a fully functional software that has received not only continued investment from Nvidia, but also extensive support and contributions from the developer community.

Jay Goldberg, CEO of D2D Advisory, stated:

“CUDA software is important not only because of its functionality, but also because people have been using CUDA for 15 years and have built a lot of code around it. That's what really matters.”

CUDA is already deeply rooted in many artificial intelligence and high-performance computing projects, and changing the status quo requires overcoming enormous inertia and dependency. For startups that want to succeed in Nvidia's shadow, they need to not only provide competitive technology, but also overcome users' deep dependence on existing technology.

As more capital and resources pour into this field, the industry waits to see if these startups can pose a substantial challenge to Nvidia in the AI software market.

Editor/Somer