AEye is the brainchild of industry veterans in the world of computer vision. Developments in AI and more specifically in deep learning, were making headlines regularly in academic circles. These events provided a glimpse into how this technology would revolutionize computer science in general and more specifically bring about a paradigm shift in computer vision.
The team identified three key realities:
AI was a fundamentally different software product paradigm. The abundant ecosystem of tools, infrastructure and platforms available for traditional S/W products wouldn’t suffice any longer. To support the scale-up and roll-out of deep learning-based solutions by product teams, new tools would need to be created.
AI was a learning-based paradigm, but all the work on AI was essentially creating “learned” [static] solutions as opposed to learning [dynamic] solutions. The learning always ceased when products were deployed, although AI has the potential – in fact one of its key strengths – to continue learning post-deployment.
Real-time computer vision solutions require processing / decision -making to happen at the edge. AI, and more specifically deep learning, is a very computationally heavy technology. The problem then becomes: How to produce results with limited resources in real-time? The only architectural solution that is device and H/W platform agnostic is one that delivers a uniquely tailored solution to each edge device and its uniquely specific environment. As such, the S/W solution to the problem carries the highest ROI and widest use-case applicability.
With these realizations, to embark on a journey to address these challenges and opportunities with a vision of enabling every organization to leverage the full power of deep learning to build solutions for a better world.
From the get-go, the founders understood that any best of breed platform requires a combination of deep domain-expertise as well as superb software engineering in relevant areas. So the partners set up to build a 360-degree team in terms of the talent surrounding the problem statement. They brought in key talent in deep learning, high performance computing, backend, DevOps, embedded development and product management.
AEye believes machine learning is the life-saving technology that will transform healthcare. This technology challenges the traditional, reactive approach to healthcare. In fact, it’s the exact opposite: predictive, proactive, and preventative—life-saving qualities that make it a critically essential capability in every health system.
Media houses rely on advance analytics using various parameters from the customer data like demographics, current trends, market scenarios etc. and incorporate our AI-based content improvements with dynamic ad insertions into their offerings to enhance the contextualization customer experience.
We help commercial aerospace manufacturers, defense integrator’s and space technology companies harness this digital revolution to improve operational performance and deliver new growth opportunities. The potential of digital transformation is exciting and largely untapped. Now is the time to fly beyond the realms of possibility.
The safety of passengers, pedestrians, and drivers has always been the number one concern for the transportation industry. Taking advantage of AEye models does far more than decrease the number of human errors; transportation analytics assists in minimizing effects of driving hazards in crowded urban areas, while monitoring safety regulation compliance of vehicles.
AEye-powered education equips students with fundamental IT skills. With more inventions, there will be a wider range of courses available online and with the help of AI, students will be learning from wherever they are. Technology brings drastic transitions by facilitating the learning of any course from anywhere across the globe and at any time.
AEye facilitates to conquer many internal challenges that have been around in the industry from expertise shortage to complexity in decision making, issues related to integration, and overloaded information. Making use of AI in manufacturing plants enables businesses to completely transform their proceedings.
Our customer centric approach in business strengthens us to go an extra mile and deliver solutions that are especially engineered as per requirements. With the leadership involvement towards customer satisfaction is an integral part of our stronger commitment to our customers.