Machine Learning: Growth Engine for Your Organization

As organizations evolve, the implementation of deep learning models and machine learning infrastructure becomes crucial for scalability. Our platform's modular design supports a range of adoption patterns, from R&D to production, accommodating hosted, private cloud, and on-prem scenarios. This flexibility ensures that our machine learning as a service (MLaaS) evolves with your company's needs, reflecting the usage patterns observed in recent years:

Experiment with Machine Learning: Harness the power of local GPUs for machine learning, starting with a single developer or a small team.

Prove Results from Machine Learning: Unlock the predictive intelligence of neural networks, making artificial intelligence an organizational priority.

Grow Your AI and Machine Learning Team: As expertise deepens, expand your machine learning tools and services with a mature team.

Invest in Machine Learning Infrastructure: Upgrade to advanced orchestration platforms and GPU processing, integrating technologies like the RTX 2080 Ti for multi-GPU capabilities. GPUs have been widely used for Deep Learning and Deep Learning, as they deliver significant performance improvements over CPUs. The bottom line is that GPUs will almost always be chosen for training and often be used for inference. The decision will come down to whether your prediction engine serving endpoint) is running at scale or not. A single modern GPU, for instance, can process over 3,000 images/second compared to less than 500 images/second on a CPU. This may sound like a no-brainer but this speedup is only relevant if your request volume exceeds what a CPU can process. On the other hand, when training the model, you will always want to process the maximum amount of data in the shortest amount of time possible.

Enable High-Value Predictions & Intelligent Actions with Machine Learning

Technology-driven manufacturers inundated with data from IoT sensors require intelligent machine learning algorithms to optimize operations and expedite business outcomes. Machine learning consulting is vital for tackling the challenges of predictive analytics, asset health monitoring, and customer analytics integration into your business operations. Our consultants excel in guiding companies through the data journey, from unravelling complex data points to deploying company-wide machine learning solutions. We craft an analytics implementation roadmap and development strategy tailored to your business.

Developing Machine Learning Models for Data-Driven ML Solutions

Utilizing machine data effectively to predict outcomes and behaviors is pivotal for manufacturers to lead in today's era of digital transformation. The rapid development of supervised machine learning models is essential for actionable business insights. Our expertise ranges from deploying machine learning models for wind power forecasting to automating asset failure detection and pinpointing construction faults. Platforms like Azure Machine Learning and Amazon SageMaker facilitate quick development of machine learning applications. Our team, skilled in python machine learning libraries and other open-source technologies like Apache Spark, Jupyter Notebook, and Kubernetes, leads the charge in intelligent solution development.

Machine Learning Consulting & Custom Solution Development

Unveiling patterns from big data requires robust machine learning tools. Data scientists and engineers are crucial in creating strong machine learning models that analyze structured and unstructured data for actionable insights. Our team excels in using a variety of machine learning cheat sheets and tools to address these needs. Our data science consulting approach—comprehending business data, exploratory data analysis, model building, data optimization, and deployment—equips industry leaders to swiftly navigate complex data challenges. With proficiency in R, MATLAB, data modeling, algorithms, and machine learning, our teams are your partners in innovation.

Putting Machine Learning, Data Science, and AI to Work

Custom AI and machine learning solutions are key to minimizing system downtime and predicting outages. Understanding your business intricacies is imperative to fuel innovation and optimize operations. Whether it's leveraging reinforcement learning, tackling anomaly detection, engaging in NLP machine learning, or exploring computer vision, our teams provide solutions for your unique challenges. We also specialize in integrating business intelligence solutions securely with your current business environment, ensuring a seamless blend of machine learning tools and existing systems.

Harnessing GPUs for Optimal Performance

GPUs have revolutionized machine learning GPU for machine learning, delivering notable performance enhancements over CPUs in both deep learning and model training. The supremacy of GPUs, like the multi-GPU setup of RTX 2080 Ti, is clear, with the ability to process significantly more data points per second. Whether it's playing chess with an AI system, driving a car through an active learning machine learning scenario, or analyzing real-world labeled data, the speed and efficiency of GPUs are unparalleled. The choice between GPU and CPU will hinge on your specific needs, especially when scaling prediction engines to meet the demand for rapid, intelligent processing of vast data sets.