Kneron, a San Diego-based semiconductor startup, has secured $49 million in funding from investors including Foxconn and Alltek to accelerate the commercialization of artificial intelligence (AI) chips. The additional funding brings Kneron’s total Series B financing to $97 million.
The funds will be used to accelerate the deployment of advanced AI, with a particular focus on nano GPT solutions for the automotive industry. Kneron aims to address the growing demand for AI and overcome the challenges associated with running powerful GPT models out of cloud data centers, such as high latency, high data transfer costs, and concerns around user privacy and security protection.
Kneron offers end-to-end integrated hardware and software solutions that enable on-device edge AI inferencing. In 2021, the company launched the first edge AI chip supporting transformer neural networks, which serve as the foundation for all GPT models. These hyper-efficient AI chips aim to make AI technology more secure, accessible, and energy-efficient.
The strategic funding from Foxconn and Alltek comes as the value of semiconductor companies continues to surge in 2023, driven by the increasing demand for AI. Chip-maker Nvidia, for example, has seen its shares nearly triple this year, with a market capitalization of over $1 trillion.
Albert Liu, the founder, and CEO of Kneron, expressed excitement about the completion of the Series B funding round and highlighted the company’s commitment to advancing AI technology. By creating hyper-efficient AI chips, Kneron aims to address industry bottlenecks and provide solutions that enhance user experiences while ensuring privacy, security, and energy efficiency.
This funding injection from industry giants like Foxconn and Alltek will enable Kneron to expedite the commercialization of AI chips, particularly in the automotive sector. The advancements made by Kneron aim to revolutionize the deployment of AI, making it more accessible and efficient across various industries.
For the latest updates on Kneron’s progress and their contributions to the field of AI chip commercialization, stay tuned.
