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	<title>SAS Blogs</title>
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	<link>https://blogs.sas.com/content/</link>
	<description>Connecting you to people, products &#38; ideas from SAS</description>
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		<title>Why tax agencies are embracing hybrid AI and generative AI</title>
		<link>https://blogs.sas.com/content/sascom/2026/05/12/tax-agency-generative-ai-hybrid/</link>
		
		<dc:creator><![CDATA[Teya Dyan]]></dc:creator>
		<pubDate>Tue, 12 May 2026 09:00:52 +0000</pubDate>
				<category><![CDATA[Innovation]]></category>
		<category><![CDATA[AI governance]]></category>
		<category><![CDATA[financial crime]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[hybrid AI]]></category>
		<category><![CDATA[tax compliance]]></category>
		<category><![CDATA[tax fraud]]></category>
		<guid isPermaLink="false">http://2.78333</guid>

					<description><![CDATA[<p>Tax return registrations and filings continue to rise and fraud schemes are becoming more automated and sophisticated. At the same time, public expectations for fast, digital service are higher than ever. The intensity is real and the data tells a sobering story. In the United States alone, the Internal Revenue [...]</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/sascom/2026/05/12/tax-agency-generative-ai-hybrid/">Why tax agencies are embracing hybrid AI and generative AI</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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		<title>Compute multivariate normal orthant probabilities</title>
		<link>https://blogs.sas.com/content/iml/2026/05/11/mvn-orthant-probability.html</link>
		
		<dc:creator><![CDATA[Rick Wicklin]]></dc:creator>
		<pubDate>Mon, 11 May 2026 09:24:15 +0000</pubDate>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Numerical Analysis]]></category>
		<category><![CDATA[Simulation]]></category>
		<category><![CDATA[Statistical Programming]]></category>
		<guid isPermaLink="false">http://22.58590</guid>

					<description><![CDATA[<p>In general, it is very difficult to compute a probability for a multivariate continuous distribution. For all continuous distributions, the probability requires solving a complicated multiple integral. For example, the probability for a bivariate normal distribution requires integrating the bivariate normal density over a two-dimensional (2-D) area. The probability for [...]</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/iml/2026/05/11/mvn-orthant-probability.html">Compute multivariate normal orthant probabilities</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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		<title>Designing for society: NC State students reimagine the role of AI</title>
		<link>https://blogs.sas.com/content/sascom/2026/05/08/designing-for-society-nc-state-students-reimagine-the-role-of-ai/</link>
		
		<dc:creator><![CDATA[Caroline Kinlaw]]></dc:creator>
		<pubDate>Fri, 08 May 2026 08:00:18 +0000</pubDate>
				<category><![CDATA[Innovation]]></category>
		<category><![CDATA[agentic AI]]></category>
		<category><![CDATA[AI agents]]></category>
		<category><![CDATA[NC State]]></category>
		<category><![CDATA[students]]></category>
		<guid isPermaLink="false">http://2.78300</guid>

					<description><![CDATA[<p>For the past 13 years, NC State College of Design students have been tasked with exploring how technology and design can help tackle society’s biggest challenges. This year, students were asked to reconsider the role design plays in society. Rather than developing a traditional B2B interface, they explored how design, [...]</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/sascom/2026/05/08/designing-for-society-nc-state-students-reimagine-the-role-of-ai/">Designing for society: NC State students reimagine the role of AI</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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		<title>Fraud at scale: Trends the public sector cannot ignore</title>
		<link>https://blogs.sas.com/content/sascom/2026/05/07/fraud-public-sector-trends/</link>
		
		<dc:creator><![CDATA[Liz Goldberg]]></dc:creator>
		<pubDate>Thu, 07 May 2026 08:00:57 +0000</pubDate>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[AI fraud]]></category>
		<category><![CDATA[financial crime]]></category>
		<category><![CDATA[fragmentation]]></category>
		<category><![CDATA[fraud waste and abuse]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[public sector trends]]></category>
		<guid isPermaLink="false">http://2.78276</guid>

					<description><![CDATA[<p>Fraud targeting public sector programs has entered a new phase. Sophisticated fraudsters, armed with AI, are depleting public sector budgets and damaging trust in government – and that’s a reality governments must face. What was once largely opportunistic and fragmented has become organized, industrialized and increasingly cross-border. Fraudsters no longer [...]</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/sascom/2026/05/07/fraud-public-sector-trends/">Fraud at scale: Trends the public sector cannot ignore</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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		<title>From predicting risk to changing behavior: Rethinking medication adherence with agentic AI</title>
		<link>https://blogs.sas.com/content/sascom/2026/05/06/from-predicting-risk-to-changing-behavior-rethinking-medication-adherence-with-agentic-ai/</link>
		
		<dc:creator><![CDATA[Heather Hallett]]></dc:creator>
		<pubDate>Wed, 06 May 2026 10:00:22 +0000</pubDate>
				<category><![CDATA[Innovation]]></category>
		<category><![CDATA[agentic AI]]></category>
		<category><![CDATA[AI agents]]></category>
		<category><![CDATA[medication adherence]]></category>
		<category><![CDATA[model cards]]></category>
		<category><![CDATA[sas intelligent decisioning]]></category>
		<category><![CDATA[Trustworthy AI]]></category>
		<guid isPermaLink="false">http://2.78186</guid>

					<description><![CDATA[<p>Medication non‑adherence remains one of health care’s most persistent and expensive challenges. Across chronic conditions, only about half of patients take medications as prescribed, even when effective treatments are available. The consequences are significant: disease progression, avoidable hospitalizations, increased mortality, and hundreds of billions of dollars in preventable health care [...]</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/sascom/2026/05/06/from-predicting-risk-to-changing-behavior-rethinking-medication-adherence-with-agentic-ai/">From predicting risk to changing behavior: Rethinking medication adherence with agentic AI</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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		<item>
		<title>Working with Microsoft 365 Sensitivity Labels from SAS programs</title>
		<link>https://blogs.sas.com/content/sasdummy/2026/05/05/sensitivity-labels-sas/</link>
		
		<dc:creator><![CDATA[Chris Hemedinger]]></dc:creator>
		<pubDate>Tue, 05 May 2026 15:07:54 +0000</pubDate>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Microsoft 365]]></category>
		<category><![CDATA[OneDrive]]></category>
		<category><![CDATA[SAS Programming]]></category>
		<category><![CDATA[SharePoint]]></category>
		<guid isPermaLink="false">http://23.8259</guid>

					<description><![CDATA[<p>How to detect and respect Sensitivity Labels when working with SAS and Microsoft 365 content.</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/sasdummy/2026/05/05/sensitivity-labels-sas/">Working with Microsoft 365 Sensitivity Labels from SAS programs</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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		<title>Your AI agent found the issue. Now what?</title>
		<link>https://blogs.sas.com/content/sascom/2026/05/05/your-ai-agent-found-the-issue-now-what/</link>
		
		<dc:creator><![CDATA[Caslee Sims]]></dc:creator>
		<pubDate>Tue, 05 May 2026 12:00:36 +0000</pubDate>
				<category><![CDATA[Innovation]]></category>
		<category><![CDATA[agentic AI]]></category>
		<category><![CDATA[AI agents]]></category>
		<category><![CDATA[event stream processing]]></category>
		<category><![CDATA[large language models]]></category>
		<category><![CDATA[model context protocol]]></category>
		<category><![CDATA[SAS events]]></category>
		<category><![CDATA[SAS Innovate]]></category>
		<guid isPermaLink="false">http://2.78228</guid>

					<description><![CDATA[<p>If you’ve been experimenting with tools inside ChatGPT or Claude, you’ve probably seen how quickly an AI agent can surface useful information. It can pull data, summarize what’s happening and point you in the right direction. That part works. Where things still break down is what happens next. You find [...]</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/sascom/2026/05/05/your-ai-agent-found-the-issue-now-what/">Your AI agent found the issue. Now what?</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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		<title>How to develop accurate demand forecasts in a volatile market</title>
		<link>https://blogs.sas.com/content/sascom/2026/05/04/how-to-develop-accurate-demand-forecasts-in-a-volatile-market/</link>
		
		<dc:creator><![CDATA[Alison Bolen]]></dc:creator>
		<pubDate>Mon, 04 May 2026 15:42:38 +0000</pubDate>
				<category><![CDATA[Innovation]]></category>
		<category><![CDATA[Speed and Agility]]></category>
		<category><![CDATA[amirax]]></category>
		<category><![CDATA[customer story]]></category>
		<category><![CDATA[demand forecasting]]></category>
		<category><![CDATA[forecasting]]></category>
		<category><![CDATA[SAS Innovate]]></category>
		<category><![CDATA[SAS Viya]]></category>
		<guid isPermaLink="false">http://2.78231</guid>

					<description><![CDATA[<p>Pandemics. Wars. Energy crises. Unprecedented circumstances can make it hard to build accurate forecasts, especially when forecasts are based on historical data alone, explains Josh Ackerman, a Data Scientist Manager at DOW. “It’s hard to make strategic decisions when you can’t predict the future from the past,” says Ackerman. Leaders [...]</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/sascom/2026/05/04/how-to-develop-accurate-demand-forecasts-in-a-volatile-market/">How to develop accurate demand forecasts in a volatile market</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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		<title>On standardizing multivariate normal probabilities</title>
		<link>https://blogs.sas.com/content/iml/2026/05/04/standardize-mvn-probabilities.html</link>
		
		<dc:creator><![CDATA[Rick Wicklin]]></dc:creator>
		<pubDate>Mon, 04 May 2026 09:24:47 +0000</pubDate>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Statistical Programming]]></category>
		<guid isPermaLink="false">http://22.58605</guid>

					<description><![CDATA[<p>A course in elementary statistics always introduces the "Z-score." A Z-score is the result of standardizing a normally distributed random variable. By subtracting the distribution's mean and dividing by its standard deviation, you transform a general normal random variable into a standardized variable that has zero mean and unit standard [...]</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/iml/2026/05/04/standardize-mvn-probabilities.html">On standardizing multivariate normal probabilities</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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		<title>Less spiraling, more possibility: Mel Robbins at SAS Innovate 2026</title>
		<link>https://blogs.sas.com/content/sascom/2026/05/01/less-spiraling-more-possibility-mel-robbins-at-sas-innovate-2026/</link>
		
		<dc:creator><![CDATA[Becky Graebe]]></dc:creator>
		<pubDate>Fri, 01 May 2026 09:00:06 +0000</pubDate>
				<category><![CDATA[Curiosity]]></category>
		<category><![CDATA[behavior change]]></category>
		<category><![CDATA[change]]></category>
		<category><![CDATA[curiosity]]></category>
		<category><![CDATA[Mel Robbins]]></category>
		<category><![CDATA[SAS executives]]></category>
		<category><![CDATA[SAS Innovate]]></category>
		<guid isPermaLink="false">http://2.78117</guid>

					<description><![CDATA[<p>At SAS Innovate 2026, best-selling author and podcaster Mel Robbins joined CMO Jenn Chase on the main stage for a candid, energizing conversation about change – why it’s so hard, why it feels relentless right now and how we can show up more effectively as leaders, teammates and humans. From [...]</p>
<p>The post <a rel="nofollow" href="https://blogs.sas.com/content/sascom/2026/05/01/less-spiraling-more-possibility-mel-robbins-at-sas-innovate-2026/">Less spiraling, more possibility: Mel Robbins at SAS Innovate 2026</a> appeared first on <a rel="nofollow" href="https://blogs.sas.com/content">SAS Blogs</a>.</p>
]]></description>
		
		
		
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