Introducing lightweight, industry-specific AI models for individual licence, SAS hopes to equip organisations with readily deployable AI technology to productionise real-world use cases with unparalleled efficiency.

Chandana Gopal, research director, Future of Intelligence, IDC, said: “SAS is evolving its portfolio to meet wider user needs and capture market share with innovative new offerings,

“An area that is ripe for SAS is productising models built on SAS’ core assets, talent and IP from its wealth of experience working with customers to solve industry problems.”

In today’s market, the consumption of models is primarily focused on large language models (LLMs) for generative AI. In reality, LLMs are a very small part of the modelling needs of real-world production deployments of AI and decision making for businesses. With the new offering, SAS is moving beyond LLMs and delivering industry-proven deterministic AI models for industries that span use cases such as fraud detection, supply chain optimization, entity management, document conversation and health care payment integrity and more.

Unlike traditional AI implementations that can be cumbersome and time-consuming, SAS’ industry-specific models are engineered for quick integration, enabling organisations to operationalise trustworthy AI technology and accelerate the realisation of tangible benefits and trusted results.

Expanding market footprint

Organisations are facing pressure to compete effectively and are looking to AI to gain an edge. At the same time, staffing data science teams has never been more challenging due to AI skills shortages. Consequently, businesses are demanding agility in using AI to solve problems and require flexible AI solutions to quickly drive business outcomes. SAS’ easy-to-use, yet powerful models tuned for the enterprise enable organisations to benefit from a half-century of SAS’ leadership across industries.

Delivering industry models as packaged offerings is one outcome of SAS’ commitment of $1 billion to AIpowered industry solutions. As outlined in the May 2023 announcement, the investment in AI builds on SAS’ decades-long focus on providing packaged solutions to address industry challenges in banking, government, health care and more.

Udo Sglavo, VP for AI and Analytics, SAS, said: “Models are the perfect complement to our existing solutions and SAS Viya platform offerings and cater to diverse business needs across various audiences, ensuring that innovation reaches every corner of our ecosystem. 

“By tailoring our approach to understanding specific industry needs, our frameworks empower businesses to flourish in their distinctive Environments.”

Bringing AI to the masses

SAS is democratising AI by offering out-of-the-box, lightweight AI models – making AI accessible regardless of skill set – starting with an AI assistant for warehouse space optimisation. Leveraging technology like large language models, these assistants cater to nontechnical users, translating interactions into optimised workflows seamlessly and aiding in faster planning decisions.

Sgvalo said: “SAS Models provide organisations with flexible, timely and accessible AI that aligns with industry challenges.

“Whether you’re embarking on your AI journey or seeking to accelerate the expansion of AI across your enterprise, SAS offers unparalleled depth and breadth in addressing your business’s unique needs.”

The first SAS Models are expected to be generally available later this year.

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Space is an unforgiving environment and equipment failures can be catastrophic. Gloves are particularly prone to wear and tear as they’re used for just about everything, including repairing equipment and installing new equipment.

Currently, astronauts will send back images of their gloves to Earth to be manually examined by NASA analysts.

“This process gets the job done with the ISS’s low orbit distance of about 250 miles from Earth, but things will be different when NASA once again sends people to the moon, and then to Mars – 140 million miles away from Earth,” explains Tom Keane, Corporate Vice President of Mission Engineering at Microsoft, in a blog post.

Harnessing the power of HPE’s Spaceborne Computer-2, the teams from the three companies are developing an AI system that can quickly detect even small signs of wear and tear on astronauts’ gloves that could end up compromising their safety.

Astronauts’ gloves are built to be robust and have five layers. The outer layer features a rubber coating for grip and acts as the first defense. Next up is the Vectran® layer, a cut-resistant material. The final three layers maintain pressure and protect against the extreme temperatures of space.

However, space does its best to do all it can to get through these defenses and problems can occur when the Vectran® layer is reached. Aside from the usual day-to-day wear that happens even from using gloves here on Earth, astronauts’ gloves have to deal with a variety of additional hazards.

Micrometeorites, for example, create numerous sharp edges on handrails and other components. On arrival to locations like the moon and Mars, the lack of natural erosion means rock particles are more like broken glass than sand.

To create the glove analyser, the project’s team first started with images of new, undamaged gloves and those which featured wear and tear from spacewalk and terrestrial training. NASA engineers went through the images and tagged specific types of wear through Azure Cognitive Services’ Custom Vision.

A cloud-based AI system was trained using the data and the results were comparable to NASA’s own actual damage reports. The tool generates a probability score of damage to areas of each glove.

In space, images would be taken of astronauts’ gloves while they remove their equipment in the airlock. These images would then be analysed locally using HPE’s Spaceborne Computer-2 for signs of damage and, if any is detected, a message will be sent to Earth with areas highlighted for additional human review by NASA engineers.

“What we demonstrated is that we can perform AI and edge processing on the ISS and analyse gloves in real-time,” said Ryan Campbell, senior software engineer at Microsoft Azure Space. 

“Because we’re literally next to the astronaut when we’re processing, we can run our tests faster than the images can be sent to the ground.”

The project serves as a great example of the power of AI combined with edge computing, in areas with as limited connectivity as space.

Going forward, the project could extend to detecting early damage to other areas like docking hatches before they become a serious problem. Microsoft even envisions that a device like HoloLens 2 or a successor could be used to enable astronauts to visually scan for damage in real-time.

“Bringing cloud computing power to the ultimate edge through projects like this allows us to think about and prepare for what we can safely do next – as we expect longer-range human spaceflights in the future and as we collectively begin pushing that edge further out,” concludes Jennifer Ott, Data and AI Specialist at Microsoft. 

(Photo by NASA on Unsplash)

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