Neurocat was voted one of the 247 most promising German AI startups by the initiative for applied artificial intelligence. We are pleased to be part of the AI Startup Landscape 2020 and working hard to shape the future of AI quality.
The Startup Landscape and a detailed report can be found here: AI Startup Landscape 2020
Stay tuned and keep coding.
Neurocat won 1st place in Software and Compute Category at the 2022 edition of the Tech.AD EUROPE AWARD. The Tech.AD Europe Award exclusively honours extraordinary projects in the automotive industry and celebrates exceptional solutions & innovations. “The winners...
Our CEO Florens Greßner featured in IHK Berlin magazine’s February 2022 edition talking about his inspiration for #neurocat, love for abstract #mathematics and advice for #young #entrepreneurs 📰 Check out the magazine below (#35, only in German) 👇🏻...
neurocat had the pleasure to be invited to talk at the AI Guild’s #datalift series, where our CEO Florens Greßner talks about his inspiration behind neurocat and our work towards enabling trust in AI systems. Check out the video below:...
Neurocat was awarded with the VisionAward 2021 at MedienTage Munich. VisionAwards have been given to young and established companies and entrepreneurs who set new trends with a new business idea. The jury for the award consisted of interdisciplinary experts and...
dSPACE, an internationally leading provider of simulation and validation solutions for the development of networked, self-driving, and electric vehicles, has acquired interests in neurocat. Support from a renowned industry leader will give us the necessary support in...
We are proud to present our joint work with the University of Göttingen. Formal verification of neural networks is a challenging topic! In the past, verification methods were mainly focused on Lp-norms for measuring imperceptibility. Using Lp-norms for measuring the...
Neurocat has been accepted into the NVIDIA AI Inception program! Being recognized by one of the giants in AI space showcases the potential of our software offering aidkit and neurocat's work in the domain of AI robustness, explainability and functionality. Want to try...
Proud to present the research paper contributed by colleagues at neurocat GmbH & Volkswagen AG. Risk Assessment for ML models is of paramount importance to understand the failure modes and improve the models before deployment. Our paper defines the standardized...
Making AI models robust against adversarial attacks, unboxing the black-box models to make their decision-making process more explainable, and also working with standardization agencies to bring quality in AI to the forefront. It's all in a day's work for us. Read the...
State-of-the-art neural networks are vulnerable to adversarial examples. This major problem for the safe deployment of ML models arises when minor input modifications push a data point across the decision boundary of the model. The existence of adversarial examples is...
