Gauss Labs

230 Homer Ave
Palo Alto,  CA  94301

United States
  • Booth: B2466

Gauss Labs is an industrial AI startup based in Palo Alto.

Gauss Labs provides AI-based metrology solutions called Panoptes VM and Panoptes IM. 

  • Panoptes VM (Virtual Metrology) predicts process outcomes for all wafers (100% sampling) using sensor data. This allows manufacturers to control their processes better and faster. 
  • Panoptes IM (Image Metrology) provides Univeral Denoiser, Augmented Metrology and Anomaly Detector functions that enable manufacturers to acquire clean images faster and extract more information from the image.

 Press Releases

  • https://news.skhynix.com/gauss-labss-ai-based-virtual-metrology-solution/

    • Gauss Labs, an industrial AI startup SK hynix invested in, delivers an AI-based virtual metrology solution called “Panoptes VM” for high-volume manufacturing
    • By predicting wafer process outcomes based on sensor data, Panoptes VM reduces process variability by 21.5% on average and ultimately improves the yield as well
    • Panoptes VM has been utilized in SK hynix’s thin film deposition process since December 2022 and is expected to expand into other processes in the future

    Looking to improve operational efficiency and yield in its semiconductor manufacturing process, SK hynix has turned to an artificial intelligence (AI) solution. Gauss Labs, an industrial AI startup SK hynix invested in, launched an AI-based virtual metrology (VM) solution software product called Panoptes VM in November 2022. Right after in December 2022, SK hynix began using Panoptes VM in its mass production fabs.

    Panoptes VM predicts manufacturing process outcomes using sensor data. The product is named after Panoptes in Greek mythology, the all-seeing giant with 100 eyes. Accordingly, Panoptes VM is designed to monitor everything that happens during the manufacturing process.

    Panoptes VM was first applied to thin film vapor deposition1, a crucial process that coats a thin film on a wafer. The thickness and refractive index of the thin film are key process outcomes that are directly related to the quality of a semiconductor chip. However, measuring these process outcomes for such a thin film would take a great deal of time and resources, so it is infeasible to make measurements for all wafers.

    SK hynix now relies on Panoptes VM to resolve this problem. Combining prediction values generated by Panoptes VM with APC2, SK hynix reduced process variability3 by 21.5% on average, which also led to improvement in yield. SK hynix and Gauss Labs are considering plans to expand this technology to various processes beyond thin film vapor deposition.

    1Thin Film Vapor Deposition: A process that coats the top of a wafer by forming a thin film — a very fine layer of material on a substrate surface, e.g., insulated semiconductor, glass, and ceramic — via a physical or chemical reaction such as vacuum deposition or sputtering.

    2APC (Advanced Process Control): A solution that finds optimal process conditions for equipment during a manufacturing process.

    3Process Variability: The amount of fluctuation in the quality of manufactured products in respective processes. As the probability of defects falls when the fluctuation decreases, the process variability should be managed within a certain level.

    Analyzing the real sensor data with AI technology, prediction models by Panoptes VM achieve a high level of accuracy comparable to physical metrology equipment. Consequently, virtual metrology allows manufacturers to monitor essentially all wafers and opens up endless possibilities through predicted values.

    Mike Kim, CEO of Gauss Labs, said: “Gauss Labs is solving the most challenging problems in manufacturing by using state-of-the-art AI technology and creating real impact and values in practice. With Panoptes VM at the forefront, we will continue to develop products that will lead innovation in manufacturing.”

    Regarding the adoption of Panoptes VM, Young-sik Kim, EVP of Manufacturing/Technology at SK hynix, said: “SK hynix is making concerted efforts with Gauss Labs to realize smart factories with a next level of intelligence. We will continue to maintain our technological edge by incorporating AI technology into all stages of semiconductor manufacturing. The arrival of Panoptes VM is just the beginning.”

  • https://semiengineering.com/using-ai-to-improve-metrology-tooling/

    Virtual metrology is carefully being added into semiconductor manufacturing, where it is showing positive results, but the chip industry is proceeding cautiously.

    The first use of this technology has been for augmenting existing fab processes, such as advanced process control (APC). Controlling processes and managing yield generally do not require GPU processing and advanced algorithms, so this is more of a test than a stamp of approval. As with any AI/ML technology, virtual metrology is subject to a certain level of industry overexuberance that will take time to justify across a wider set of use cases.

    Nevertheless, initial implementations are showing some benefits. Among the examples:

    • SK hynix recently deployed virtual metrology from Gauss Labs in multiple fabs, providing 22% reduction in process variation over multiple deposition tools;
    • Siemens EDA and GlobalFoundries are fine-tuning process and design interactions for new layouts. [1,2];
    • NXP has qualified deep learning by Lynceus to monitor trench etch depth and profile, a key parameter for automotive chips;
    • Synopsys is tying its process monitors to design, and
    • Metrology, inspection, and yield management tools are starting to incorporate data analytics in various forms.

    Still, the practical implementation of virtual metrology (VM) in semiconductor manufacturing is challenging on multiple fronts, starting with the data, which often is scattered among different companies, or different groups within the same company.


  • Panoptes VM (Virtual Metrology)
    Panoptes VM predicts key features of a process outcome based on equipment sensor data for real-time process monitoring and control....

  • Panoptes VM is the industry’s first successful virtual metrology solution that predicts process outcomes reliably and robustly for real-time process monitoring and control. It tracks the temporal changes in sensor and measurement data by updating and optimizing the model continuously. Panoptes VM navigates massive data from hundreds of sensors and other metadata, and selects most relevant features for best prediction performance. By aggregating measurement data from multiple machines and tools for the same process, Panoptes VM overcomes the scarcity of the measurement data while providing precise and individualized models for the multiple machines and tools. Although all these core features are fully automatized without any manual operation, process engineers can incorporate their domain knowledge on process data and physics into main steps of predictive modeling.
  • Panoptes IM (Image Metrology)
    Panoptes IM is an integrated image metrology solution that overcomes the limits of conventional measurement tools through state-of-the-art computer vision technology....

  • To overcome the limit on metrology resources, Panoptes IM enhances higher-throughput, lower-quality images by advanced denoising techniques. This enables faster acquisition without any loss in the image quality. In addition to automatically measuring all conventional measurands in a given image, Panoptes IM also detects anomalies within the image and identifies their causes, which serves as another indicator for yield changes. In order to handle diverse metrology recipes, Panoptes IM provides a unified set of recipes, or methods and procedures for measuring features in images. These recipes are created, tested, deployed, and managed in an engineering platform, which is integrated seamlessly with existing manufacturing systems.

Send Email

Type your information and click "Send Email" to send an email to this exhibitor. To return to the previous screen without saving, click "Reset".