AI & Machine Learning
Artificial Neural Networks
Machine learning is predicated on the assumption that, over time, computing systems can form logical connections based on past experiences that better enable them to solve complex problems to which they have not previously been exposed.
Enter: artificial neural networks, or ANNs. Similar to the biological neural networks formed in “living” brains, ANNs are capable of iterating their own decision-making constructs in order to more effectively perform tasks in the absence of specific instruction or human intervention. Applications range from image processing and speech recognition to medical diagnostics and driverless cars.
krtkl brings the benefits of ANNs to widely deployed systems through the use of high-performance, software-reconfigurable embedded hardware and machine learning intellectual property cores.
Language
Processing
Pattern
Matching
Distributed
Computation
Image
Recognition
Genetic
Algorithms
Non-Linear
Systems
Deep Learning
Collection and storage of information is merely the first stage of generating actionable insights into large data sets. The ultimate value of such information lies in its analysis and interpretation, resulting in the establishment of previously unforeseen patterns and correlations.
In practice, deep learning leverages neural networks to parse and process volumes of data that would be impractical or unreasonable for humans to address. This technique has been used in areas including medical and genetic research, drug discovery, natural language processing, and even customer service and business intelligence.
By providing powerful “edge” data parsing and processing, krtkl enables lightweight, hardware-accelerated, scalable deep learning capabilities for a wide variety of products and applications.
Prediction and Adaptation
The vast majority of failures, accidents, and malfunctions are easily avoidable or mitigated. Unfortunately, many impending calamities are either hidden from plain view or buried under a mountain of information beyond the capacity of human comprehension.
By incorporating predictive analytics into systems and processes, data can be acted upon before real-world issues result in irreversible damage or loss. From turbines to robotics, common cause failures resulting from excessive wear, heat generation, misalignment, and more can be constantly monitored, recorded, and processed in “near real-time,” thereby protecting equipment, facilities, infrastructure, and people.
krtkl’s experience with mission-critical systems means special attention is afforded to monitoring vital components and subsystems to ensure your investments are protected.
