SAS Institute launches its first generative AI assistants, plus tools to help businesses build their own

Data Analytics Company SAS Institute Inc. said today that he was improving his SAS Viya artificial intelligence platform with the introduction of new industry-specific generative AI assistants, a new synthetic data generator called SAS Data Maker, and a new development platform called SAS Viya Workbench.

The company got its start SAS Viya last year, explaining that it is a kind of AI integration platform that allows organizations to integrate the most powerful large language models, such as OpenAI’s GPT-4 and Gemini Pro 1.5 from Google LLC, into their existing business processes. In doing so, companies can orchestrate these LLMs to create personalized AI models and agents, fine-tuned to accomplish specific business tasks, with explainable results and enhanced privacy and security, ensuring compliance.

Starting today, SAS Viya is enriched with a new Viya Copilot offering aimed at developers, data scientists and professional users. Available in preview by invitation only, it’s like a personal assistant designed to help users speed up various business tasks. It does this by using a comprehensive toolset encompassing code generation, data cleaning, data mining and knowledge gap analysis, the company said.

Andy Thurai, vice president and principal analyst at Constellation Research Inc., told SiliconANGLE that Viya Copilot is a useful offering that can help users with multiple tasks and is likely to be particularly useful in analyzing knowledge gaps and data management tasks. “This could be useful in reducing the need for manual tasks that data scientists spend a lot of their time on,” he said.

SAS Viya also enhances the company’s flagship marketing platform, SAS Customer Intelligence 360, building on its existing generative AI capabilities that facilitate tasks such as marketing planning and customer journey design. With today’s update, marketers can now use generative AI to create recommended audiences based on natural language prompts, suggest email subject lines, and extract insights from audience data.

Improving AI development

The company is also targeting AI developers by launching a new SAS Data Creator platform that aims to kill two birds with one stone by eliminating privacy concerns and data scarcity challenges. Also available in private preview, SAS Data Maker can generate “high-quality synthetic tabular data” for AI training, meaning customers do not need to compromise their existing, highly sensitive data. At the same time, it will be useful in situations where companies lack sufficient data to train AI models capable of achieving their performance requirements.

Thurai was less enthusiastic about SAS Data Maker, saying the problem is that it can only create synthetic data in tabular form. “The problem is that AI needs a lot of unstructured data, which is harder to generate, so it may not be of much use to many organizations today,” he said. -he declares.

In the meantime, Established SAS Viya is a new platform dedicated to AI development within SAS Viya, providing an on-demand, self-service computing environment for important tasks such as data preparation, exploratory data analysis and creating analytical AI models.

With SAS Viya Workbench, developers have the benefit of being able to work in the programming language of their choice, the company said. The platform will launch in the second quarter on Amazon Web Services Inc.’s AWS Marketplace, with support for SAS and Python programming languages, and will add support for R before the end of the year.

Users can access two development environment options in SAS Viya Workbench, including Visual Studio Code and Jupyter Notebooks. With these, they take advantage of the company’s powerful analytical tools, native Python application programming interfaces, and customizable compute resources to accelerate the development of high-performance AI models, the company said.

Jared Peterson, senior vice president of engineering at SAS, said the business case for Viya Workbench is compelling because customers are under pressure to deliver rapid results at lower cost. So it makes sense to use prebuilt, scalable frameworks that allow users to focus on creating, innovating, iterating and testing, he said.

“The many challenges developers face aren’t just minor inconveniences: they’re obstacles to answering questions and getting work done,” Peterson added. “Viya Workbench provides maximum flexibility and results by allowing developers to use the language and IDE of their choice, scale computing power up or down to meet project needs, and, in turn, ultimately increase their productivity and efficiency. »

Wiktor Markiewicz, an analyst at International Data Corp., said most users and business leaders don’t understand AI technology and have no idea how to apply it in a meaningful way. “Having an already reliable data and AI platform removes the guesswork and starts the generative AI journey,” he said of SAS’s new platform.

Packaged AI models

Not all companies have the time or inclination to develop their own AI models. Instead, they’re looking for ready-to-use solutions that they can simply plug into their business systems and get started right away. SAS said it recognizes this demand and that is why it presents the first of a complete catalog of lightweight products, industry-specific AI modelsaimed at customers in financial services, healthcare, government institutions, manufacturing and more.

The packaged AI models are built using proprietary LLMs and designed to meet the needs of non-technical users, SAS said, with the aim of optimizing workflows and improving decision-making. To get the ball rolling, SAS announced its first packaged model, a AI Assistant for Warehouse Space Optimization who can evaluate customer warehouse layouts and suggest better ways to organize things, to maximize capacity or improve efficiency.

According to Thurai, packaged AI models are an interesting concept, and it is notable that more and more vendors are moving in this direction in addition to SAS. “Last week, Google Cloud announced its own concept of specialized models that can operate at the edge and other lightweight locations,” the analyst said. “Although there is an argument that specialized and lightweight models may underperform unless model cascading or other forms of augmentation are included. Additionally, to be useful, they need to be heavily trained on industry-specific data, although SAS probably takes care of that.

The analyst also highlighted SAS’s Trustworthy AI Lifecycle Workflow Framework as an intriguing development, saying it has been mapped to SAS’s AI Risk Management Framework. National Institute of Standards and Technologies. “These types of model maps and AI governance advisory services can help companies improve AI governance, but again, SAS is not the only game in town, with startups smaller ones like Guardrails AI with much broader offerings in this area,” Thurai said.

Thurai said SAS’s AI initiatives are noteworthy and should be of interest to the company’s customers. “But the AI ​​market is evolving rapidly and many other vendors have already announced more advanced and revolutionary features,” he said.

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