Deep Learning and AI Software Solutions

Whether pre-installed or downloaded from the cloud, deep learning frameworks are key to executing deep learning – however many of the associated data science tasks can be time consuming and impede progress. For example prior to deep learning, any data must be verified, resized and labelled – it may also be required to transfer the data between programs to do this. Recognising this, Scan has teamed up with a number of partners to offer software packages that automate many of these processes, or deliver visual insight into what the data you have means. Adding software like these into your ecosystem not only reduces time to results, but minimises reliance on expensive data scientist resource. Furthermore, we also have GPU virtualisation software to maximise the utilisation of your GPU hardware and ensure optimal performance.


Current powerful AI systems often feature multiple GPU acceleration cards and deliver enormous performance and workload throughput capabilities, but usually only for a single user per physical system. Virtualisation allows you to pool these resources in order to gain greater control and visibility. At each stage of the deep learning process, data scientists have specific needs for their compute resources.

The Run:AI software platform decouples data science workloads from the underlying hardware - regardless of what GPU hardware you have. By pooling resources and applying an advanced scheduling mechanism to data science workflows, Run:AI greatly increases the ability to fully utilise all available resources, essentially creating unlimited compute. Data scientists can increase the number of experiments they run, speed time to results, and ultimately meet the business goals of their AI initiatives.

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The OmniSci platform is designed to overcome the scalability and performance limitations of legacy analytics tools faced with the scale, velocity and location attributes of today’s big datasets. Those tools are collapsing, becoming too slow and too hardware-intensive to be effective in big data analytics. OmniSci is a breakthrough technology, designed to leverage the massively parallel processing of GPUs alongside traditional CPU compute, for extraordinary performance at scale.

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H2Oai’s Driverless AI platform, is now fully integrated on the NVIDIA DGX systems, and is available as part of your proof-of-concept with Scan. It allows business users, analysts and data scientists use an incredibly fast, intuitive, integrated computing platform. Customers can apply Automatic Feature Engineering and quickly develop hundreds of machine learning models to help your business mitigate risks and maximise revenue potential.

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Kinetica and NVIDIA together deliver unmatched performance, predictable scalability across multiple high-density nodes, and seamless integration with industry-standard connectors to data sources and applications.

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Planet AI

Planet AI is a team of scientists and engineers with deep roots in Artificial Intelligence, Machine Learning and Cognitive Computing undertaking its own ambitious research projects towards Deep Universal Sequence Understanding.

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Robovision offers a fast track in AI to get added value from your data. Some years ago, this intelligence had to be created by humans writing rules to segment through the data.

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SQream DB uses advanced, patented algorithms to give you fast access to your data. The GPU plays an important role in helping realize this. By offloading computationally-intensive operations to the GPU, SQream DB makes ingestion and analysis of data up to 100x faster, compared to industry-leading solutions.

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