Kneron Raises $49M to Accelerate AI Deployment for Autonomous Vehicles
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Kneron, a San Diego-based semiconductor company, today announced that it has raised $49 million in a Series B extension.
The company primarily focuses on developing AI chips to power autonomous vehicles.
Kneron, a San Diego-based semiconductor company, today announced that it has raised $49 million in a Series B extension, bringing its total Series B financing to $97 million. Horizons Ventures led the full round, with participation from Taiwanese electronics manufacturing giant Foxconn, Alltek, Liteon Technology Corp, Adata and Palpilot.
The company will use the newly raised funds to focus on developing edge AI chips for self-driving vehicles. Kneron claims that in 2021, it introduced the inaugural edge AI chip designed to support transformer neural networks, the foundational technology behind all GPT models.
Albert Liu, CEO of Kneron, says that GPT models are still running out of cloud data centers, which causes issues such as high latency, high data transfer costs, and inadequacies in user privacy and security protection. The company aims to solve these industry bottlenecks with its edge AI chips, which run on the device instead of the cloud.
Kneron, established in 2015, is the brainchild of its co-founders Liu and Frank Chang. Before embarking on this venture, Liu accumulated experience in research and management roles at prominent companies such as Qualcomm and Samsung.
The company has raised a total of $190 million since its launch.
The company could potentially compete with Nvidia as the demand for high-quality AI chips outweighs supply. In contrast to graphic processing unit (GPU) chips that currently dominate the market, Kneron is developing neural processing unit (NPU) chips. The company asserts that its NPU chips are more suitable for AI computing.
Kneron recently unveiled the KL370, an automotive-grade NPU chip that is claimed to support the latest lightweight GPT LLMs. The company intends to develop these chips with a focus on enabling autonomous driving capabilities.
Leveraging transformers, a technology typically used in language processing, Kneron applies them to image-based applications. This takes advantage of transformers to enhance the handling of time-series data and the holistic analysis of image data.
Through these advancements in contextualization and processing, Kneron claims to achieve a minimum 30% boost in accuracy for image-based applications.
In addition to the latest funding, Kneron is expanding its partnership with Foxconn to speed up the deployment AI technologies for the automotive industry. The collaboration involves developing an ultra-lightweight AI chip capable of running GPT models independently without relying on cloud resources.
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