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Once the fodder of science fiction, mind-reading artificial intelligence (AI) is no longer far-fetched its already here. And researchers like Virginia Techs very ownRead Montaguehave spent decades building it.

What started as a backwater movement in the 80s is now a revolution with untold potential, said Montague, the Virginia Tech Carilion Vernon Mountcastle Research Professor and director of theCenter for Human Neuroscience Researchat theFralin Biomedical Research Institute at VTC.

Montague is among the worlds top neuroscientists who have long deployed machine learning tools to decode and predict complex human behaviors and neural signaling that support them.

Now he's lifting the lid on what hes learned over 30 years as a frontrunner in computational psychiatry neuroscience. He will explore the history of machine learning in neuroscience and his research in his talk,Machine Learning and Human Thought, at 5:30 p.m. Sept. 28 at the research institute.

Montague's research has spanned the neural basis of risky decision-making,confirmation bias,risk-reward analysis,mentalstates during the simulated commission of a crime,impulsiveness, andpolitical ideologies.

His group was the first toobserve nanoscalevariations in brain chemicals in awake humans in agroundbreaking 2011 study. Montague later discovered howdopamine and serotoninjointly underpin sensory processing and human perception in 2016, 2018, and 2020.

With collaborator and fellow Fralin Biomedical Research Institute professorStephen LaConte, Montague established one of the world's first labs applyingoptically pumped magnetometry, a breakthrough brain imaging technique, to parse the intricacies of social interaction.

He was invited by his former mentor and colleagueMichael Friedlander, executive director of the Fralin Biomedical Research Institute and Virginia Techs vice president for health sciences and technology, to present the institutes 116thMaury Strauss Distinguished Public Lecture, debuting the2023-34 series.

Dr. Montagues contributions to neuroscience have enriched our understanding of the brain and paved the way for a new era of scientific exploration, Friedlander said. I cant think of a better thought leader to share prescient insights about the impact of machine learning on brain research until now and what the future might hold. Its an honor to share one of our own highly regarded scientists with our community.

Today, Montagues peers and students revere his vanguard intersectional approaches to studying the brain. Over the years, hes collaborated with economists, physicists, neurosurgeons, lawyers, and psychologists to explore novel scientific questions.

Unlike many neuroscientists who started as biologists, psychologists, or chemists, Montague was a mathematician at Auburn University before completing a doctoral degree in physiology and biophysics at the University of Alabama at Birmingham in Friedlanders lab.

I was a senior in college when I read apaperby Geoffrey Hinton the father of AI and Terry Sejnowski, describing the very first learning algorithms for Boltzmann machines. That study galvanized my interest in neural networks, and from that point, I was set on working in Terrys lab, Montague said.

And thats what he did. But it took a while to get there.

Montague completed a theoretical neurobiology fellowship sponsored by Nobel Laureate Gerald Edelman at Rockefeller Universitys Neurosciences Institute and later joined joined Sejnowskis Howard Hughes Medical Institutes Computational Neurobiology Lab at the Salk Institute.

In collaboration with Peter Dayan, director of the Max Planck Institute for Biological Cybernetics in Germany, Montague proposed a reinforcement learning model of the meaning of dopamine signaling in the brain a model that is now seen as a signature breakthrough for computational models that yield new insights into brain function.

Even back then, Dr. Montague was pushing boundaries. He was among the first to apply machine-learning models to interpret vast amounts of fMRI data. He was among the first to measure neurochemical levels in awake humans using machine-learning enhanced cyclic voltammetry. And hes now among the first to encode brains magnetic waves with unprecedented resolution, opening up new ways to visualize brain activity. The sheer scope of his research is remarkable, Friedlander said.

Montague has published about 140 scientific papers in high-impact journals, accumulating over 42,000 citations. Recently, his research operation has been awarded a new $3 million award for computational neurochemistry work in conscious humans, and the group currently maintains four active National Institutes of Health grants in addition to two projects recently funded by the Red Gates Foundation as part of alandmark $50 million giftto the institute earlier this month.

Before joining Virginia Tech in 2010, Montague was the Brown Foundation Professor of Neuroscience and Psychiatry at Baylor College of Medicine, where he founded and directed the Human Neuroimaging Lab.

In addition to his primary appointment at the Fralin Biomedical Research Institute, Montague is a professor with theCollege of Sciences physics department andVirginia Tech Carilion School of Medicines psychiatry and behavioral medicine department.

Last year, Montague presented aNobel Mini-symposium lecturehosted by the Nobel Assembly in Stockholm and focused on his early modeling work of the dopamine system. In 2018, he gave theDorcas Cummings Memorial Lectureat Cold Springs Harbor Laboratory, and in 2012, he delivered aTEDGlobaltalk in Edinburgh.

He is an honorary professor with the Wellcome Centre for Human Neuroimaging at University College London and was a Wellcome Trust Principal Research Fellow from 2011-18. He formerly was a member of the MacArthur Foundation Research Network on Law and Neuroscience and the Institute for Advanced Study in Princeton. He received the Walter Gilbert Award from Auburn University and the William R. and Irene D. Miller Lectureship from Cold Spring Harbor Laboratory in 2011 and was awarded the Michael E. DeBakey Excellence in Research Award in 1997 and 2005.

Beyond his technological innovations, Montague has opened a critical window into human behavior in health and disease with his key role in developing the temporal difference prediction reward hypothesis, Friedlander said. This concept has now been directly tested in the living brain, is foundational to modern neuroscience, and provides deep insights into previously unrecognized behavior. In addition to providing insights into human brain health, this hypothesis has been validated by Montague and his team in providing a deeper understanding from an evolutionary biology perspective into behaviors such as how honey bees process and share essential information about nectar sources with their conspecifics.

The institutes free public lecture series is made possible by Maury Strauss, a longtime Roanoke businessman and benefactor who recognizes the importance of bringing leading biomedical research scientists to the community.

The public is welcome to attend the lecture, preceded by a 5 p.m. reception in the Fralin Biomedical Research Institute at2 Riverside Circle in Roanoke. Montagues talk will be streamed live viaZoom and archived on the instituteswebsite.

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Pioneer of 'mind-reading' AI to open Maury Strauss Distinguished ... - Virginia Tech

Many U.S. observers are waiting in dread for China to attempt a military takeover of Taiwan sometime before 2027, but beneath the threshold of armed conflict, China is already attacking vital Taiwanese information streams, both physically and virtually, while the island develops new tools and techniques to resist.

In April, a Chinese fishing vessel, followed by a cargo ship, dragged their anchors east of Taiwans Matsu islands, severing the two communications cables that link the islands with Taiwan itself, an act of either sabotage or clumsiness that has occurred at least 27 times in just the last five years. Taiwan has said that it suspects the severings were intentional. And of course attacks on commercial and public telecommunications channels are now a common occurrence between adversarial nations, as when Russia attacked the U.S.-based satellite communications company Viasat an hour before Moscow launched its renewed war on Ukraine.

The Taiwanese government took the interruption as an opportunity to help citizens develop workarounds to continuous Chinese-caused, er, service interruptions.

We took that as a chance to not just teach people about, you know, microwave, and also satellite [communications] backup and things like that; we also saw a lot of civil society start learning about how to set up emergency communications when the bandwidth is limited. Audrey Tang, Taiwans minister of digital affairs, told audiences during the Special Competitive Studies Project Summit in Washington, D.C. on Thursday.

But various Chinese-backed actors also regularly target the Taiwanese population with coordinated messaging and influence campaigns. A 2019 report from cybersecurity company Record Future found that the Chinese government employs as many as half a million people to sway opinions on social media at home and around the world.

As Taiwan approaches a pivotal presidential election in January, Tang said that both the government and a wide network of volunteers are preparing for China to increase efforts to manipulate Taiwanese civilians. Taiwanese civil society has developed new organizations to combat it. A group called Cofacts allows users to forward dubious messages to a chatbot. Human editors check the messages, enter them into a database, and get back to the user with a verdict.

The number of volunteers to man the service and others like are few compared to the size of Chinas efforts, said Tang. The people who actually do foreign interference nowadays coordinated with cyber attack have a lot of resources, she said.

Enter generative AI tools such as large language models, which power some of the big breakthrough online AI tools such as ChatGPT. This year, because gen AI is just so mailable, they just fine-tuned a language module together that can clarify such disinformationadding back a context and things like that. So we're no longer outnumbered, she said. It also allows the citizen-run venture to remain as such, as opposed to run by the government, which is important for its credibility. It doesn't need dedicated hardware or resources and can be done on laptops. It is still squarely in the social sector by volunteers, which is the best place to be so that it will not be captured by any state or a capitalist apparatus.

The U.S. intelligence community is also looking at how it can use generative artificial intelligence to raise productivity, Avril Haines, the Director of National Intelligence, said during the summit.

We have a program called the Unity program that's supposed to do just that. It's actually focused on artificial intelligence and it's supposed to help us take the best practices and then scale them and fund the scaling to some extent, Haines said.

But she said the United States has much more work to do to understand both the development ecosystem for such tools that are rooted in private companies and better detect how adversaries will use generative AI to attack the United States.

Haines said One fear, she said, is that new tools like generative AI are so powerful that small nations or non-state actors will be able to use them to great effect to rival the capabilities of much larger, more predictable adversaries like China. The state actors that we typically focus on are also, yes, going to be part of what we're going to be looking at in terms of the threat. But if you've got something that's cheaply available, that's commercially available, you might also see other state actors that typically would not be engaging in these kinds of threats doing so more because it's more available to them, she said.

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Taiwan is using generative AI to fight Chinese disinfo - Defense One

A doorbell camera in Chesterfield, Virginia, recently caught a man snatching a box containing a $1,600 new iPad from the arms of a FedEx delivery driver.Barely a day goes by without a similar report. Package theft, often referred to as "porch piracy," is a big crime business.

While the price tag of any single stolen package isn't extreme a study by Security.org found that the median value of stolen merchandise was $50 in 2022 the absolute level of package theft is high and rising. In 2022, 260 million delivered packages were stolen, according to home security consultant SafeWise, up from 210 million packages the year before. All in all, it estimated that 79% of Americans were victims of porch pirates last year.

In response, some of the big logistics companies have introduced technologies and programs designed to stop the crime wave.One of the most recent examples set to soon go into wider deployment came in June from UPS, with its API for DeliveryDefense, an AI-powered approach to reducing the risk of delivery theft. The UPS tech uses historic data and machine learning algorithms to assign each location a "delivery confidence score," which is rated on a one to 1,000 scale.

"If we have a score of 1,000 to an address that means that we're highly confident that that package is going to get delivered," said Mark Robinson, president of UPS Capital. "At the other end of the scale, like 100 ... would be one of those addresses where it would be most likely to happen, some sort of loss at the delivery point," Robinson said.

Powered by artificial intelligence, UPS Capital's DeliveryDefense analyzes address characteristics and generates a 'Delivery Confidence Score' for each address. If the address produced a low score, then a package recipient can then recommend in-store collection or a UPS pick-up point.

The initial version was designed to integrate with the existing software of major retailers through the API a beta test has been run with Costco Wholesale in Colorado. The company declined to provide information related to the Costco collaboration. Costco did not return a request for comment.

DeliveryDefense, said Robinson, is "a decent way for merchants to help make better decisions about how to ship packages to their recipients."

To meet the needs of more merchants, a web-based version is being launched for small- and medium-sized businesses on Oct. 18, just in time for peak holiday shipping season.

UPS says the decision about delivery options made to mitigate potential issues and enhance the customer experience will ultimately rest with the individual merchant, who will decide whether and how to address any delivery risk, including, for example, insuring the shipment or shipping to a store location for pickup.

UPS already offers its Access Points program, which lets consumers have packages shipped to Michaels and CVS locations to ensure safe deliveries.

UPS isn't alone in fighting porch piracy.

Among logistics competitors, DHL relies on one of the oldest methods of all a "signature first" approach to deliveries in which delivery personnel are required to knock on the recipient's door or ring the doorbell to obtain a signature to deliver a package. DHL customers can opt to have shipments left at their door without a signature, and in such cases, the deliverer takes a photo of the shipment to provide proof for delivery. A FedEx rep said that the company offers its own picture proof of delivery and FedEx Delivery Manager, which lets customers customize their delivery preferences, manage delivery times and locations, redirect packages to a retail location and place holds on packages.

Amazon has several features to help ensure that packages arrive safely, such as its two- to four-hour estimated delivery window "to help customers plan their day," said an Amazon spokesperson. Amazon also offers photo-on delivery, which offers visual delivery confirmation and key-in-garage Delivery, which lets eligible Amazon Prime members receive deliveries in their garage.

Amazon has also been known for its attempts to use new technology to help prevent piracy, including its Ring doorbell cameras the gadget maker's parent company was acquired by the retail giant in 2018 for a reported $1 billion.

Camera images can be important when filing police reports, according to Courtney Klosterman, director of communications for insurer Hippo. But the technology has done little to slow porch piracy, according to some experts who have studied its usage.

"I don't personally think it really prevents a lot of porch piracy," said Ben Stickle, a professor at Middle Tennessee State University and an expert on package theft.

Recent consumer experiences, including the iPad theft example in Virginia, suggest criminals may not fear the camera. Last month, Julie Litvin, a pregnant woman in Central Islip, N.Y., watched thieves make off with more than 10 packages, so she installed a doorbell camera. She quickly got footage of a woman stealing a package from her doorway after that.She filed a police report, but said her building's management company didn't seem interested in providing much help.

Stickle cited a study he conducted in 2018 that showed that only about 5% of thieves made an effort to hide their identity from the cameras. "A lot of thieves, when they walked up and saw the camera, would simply look at it, take the package and walk away anyway," he said.

SafeWise data shows that six in 10 people said they'd had packages stolen in 2022. Rebecca Edwards, security expert for SafeWise, said this reality reinforces the view that cameras don't stop theft. "I don't think that cameras in general are a deterrent anymore," Edwards said.

The increase in packages being delivered has made them more enticing to thieves. "I think it's been on the rise since the pandemic, because we all got a lot more packages," she said. "It's a crime of opportunity, the opportunity has become so much bigger."

Edwards said that the two most-effective measures consumers can take to thwart theft are requiring a signature to leave a package and dropping the package in a secure location, like a locker.

Large lockboxes start at around $70 and for the most sophisticated can run into the thousands of dollars.

Stickle recommends a lockbox to protect your packages. "Sometimes people will call and say 'Well, could someone break in the box? Well, yeah, potentially," Stickle said. "But if they don't see the item, they're probably not going to walk up to your house to try and steal it."

There is always the option of leaning on your neighbors to watch your doorstep and occasionally sign for items. Even some local police departments are willing to hold packages.

The UPS AI comes at a time of concerns about rapid deployment of artificial intelligence, and potential bias in algorithms.

UPS says that DeliveryDefense relies on a dataset derived from two years' worth of domestic UPS data, encompassing an extensive sample of billions of delivery data points. Data fairness, a UPS spokeswoman said, was built into the model, with a focus "exclusively on delivery characteristics," rather than on any individual data. For example, in a given area, one apartment complex has a secure mailroom with a lockbox and chain of custody, while a neighboring complex lacks such safeguards, making it more prone to package loss.

But the UPS AI is not free. The API starts at $3,000 per month. For the broader universe of small businesses that are being offered the web version in October, a subscription service will be charged monthly starting at $99, with a variety of other pricing options for larger customers.

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AI is policing the package theft beat for UPS as 'porch piracy' surge continues across U.S. - CNBC

Four months after committing to invest $1 billion in advanced analytics and AI, longtime BI vendor SAS institute Inc. unveiled how it plans to make generative AI part of that investment.

SAS's May commitment to spend $1 billion on developing advanced analytics and AI capabilities marked the second time the vendor revealed such plans. The first was in 2019, and over the next few years, the vendor used the allocated funds to overhaul its Viya platform.

SAS re-architected Viya in 2020 to make it fully cloud native and added augmented intelligence capabilities such as natural language processing, computer vision and predictive analytics.

In addition, the vendor built industry-specific versions of its platform.

Those vertical editions are now the focal point of SAS' second $1 billion investment in advanced analytics and AI. They are the vehicles through which the vendor plans to incorporate generative AI.

SAS, based in Cary, N.C., unveiled its generative AI strategy on Sept. 12 during Explore, a user conference held in Las Vegas. Its generative AI capabilities are now in private preview.

While Viya is available to customers as a general-purpose analytics platform they can tailor to suit their needs, SAS also offers a variety of industry-specific versions of its tools.

Industries served by editions of SAS's platform range from agriculture to manufacturing and, among others, include banking, education, healthcare, retail and consumer goods, sports, and utilities.

In addition, there are versions of Viya tailored for topics such as fraud and security, marketing and risk management.

In May, SAS said its plan for advanced analytics and AI is to develop additional tailored versions of its tools and upgrade those that have already been built.

At the time, however, although many of its competitors had already unveiled their plans for generative AI, the vendor did not reveal an intent to incorporate generative AI as part of its new $1 billion allocation.

Instead, SAS executive vice president and CIO Jay Upchurch said the vendor was taking a cautious approach to generative AI given concerns about the accuracy and security of large language models (LLMs) trained on public data.

Now, SAS has revealed that the core of its initial approach to generative AI will be to integrate third-party LLM technology with its existing industry-specific tools.

Also part of its generative AI strategy is the use of generative adversarial networks (GANs) to create synthetic data and the application of natural language processing capabilities to digital twins.

GANs can be used to reflect real-world environments and train generative AI models while simultaneously protecting the privacy and security of an organization's real data. Natural language interactions with digital twins, meanwhile, enable more efficient scenario planning to understand what actions to take under various circumstances.

Not surprisingly given its hesitation in May to unveil plans for generative AI, SAS's initial approach to generative AI is a cautious one, according to Doug Henschen, an analyst at Constellation Research.

Rather than unveil an entire new environment for generative AI development as Domo and Qlik have or acquire generative AI specialists as Databricks and Snowflake have, SAS's initial plans are instead center on combining generative AI with existing capabilities.

"SAS is being characteristically conservative on generative AI developments, highlighting existing investments in synthetic data generation and digital twin simulations, and pointing to integrations and private-preview experimentation with third-party large language models," Henschen said.

That measured approach, however, is not unusual for SAS and may be something the vendor's customers appreciate, he continued.

"SAS has long been conservative and that seems to appeal to many of its risk-averse customers in banking, insurance, healthcare, manufacturing and other industries," Henschen said. "I've seen a lot of general-purpose generative AI capabilities introduced. ... SAS hasn't jumped on that bandwagon."

Some of the key benefits of generative AI result from its improvement of natural language processing, enabling true freeform natural interaction with data rather than requiring users to phrase queries in specific ways and otherwise not understanding the queries.

Because LLMs have vast vocabularies and can understand natural language, they have the potential to make trained data workers more efficient by reducing the amount of code they need to write and open analytics to more business users by lessening the amount of training needed to use BI platforms.

SAS's generative AI plans include improved NLP so that users can be more efficient by asking questions of their data and receiving responses in natural language, according to Bryan Harris, the vendor's chief technology officer.

But SAS also wants to apply that improved NLP and other generative AI capabilities to address distinct circumstances, which is why the vendor is taking an industry-specific approach to training language models.

"We're looking at generative AI from an industry perspective because there are more concrete use cases to apply it to," Harris said. "Customers are asking us how they can apply generative AI to their environment, and that comes to a targeted industry use case. We think it's better to focus this way because it leads to measurable output."

SAS has a longstanding partnership with Microsoft. As the vendor develops its generative AI capabilities, it is using models from Microsoft Azure OpenAI as building blocks from which it can then add domain-specific data to train the models.

In May, however, SAS wasn't yet ready to start building generative AI capabilities due to security and accuracy concerns.

Harris noted that SAS serves customers in banking, healthcare, life sciences and other highly regulated industries in which data security and accuracy are critical. Before SAS was willing to add generative AI and language model capabilities, it wanted to figure out how to ensure the security of customers' data and reduce the risk of AI models delivering incorrect query responses.

Microsoft's Azure OpenAI provides an environment where SAS can protect customers' data, according to Harris. SAS' data lineage capabilities, meanwhile, enable users to understand whether an AI response can be trusted.

"We needed to see the cloud architecture and the maturity in that to emerge such that we could have a confident conversation with a customer saying that they don't have to worry about data leakage," Harris said. "We have assurances for all that through our partnership with Microsoft and its infrastructure. Second, we needed to see accuracy. We don't have the luxury of being right only sometimes."

SAS is being characteristically conservative on generative AI developments, highlighting existing investments in synthetic data generation and digital twin simulations, and pointing to integrations and coming private-preview experimentation with third-party large language models. Doug HenschenAnalyst, Constellation Research

Beyond generative AI plans, SAS unveiled Viya Workbench and the SAS App Factory, new software-as-a-service development environments in Viya now in preview with general availability planned for early 2024.

Viya Workbench is designed to help developers quickly get started building AI and machine learning models using code. Developers can use one of three coding languages -- Python, R or SAS's own language -- to build and train their analytics models while Workbench provides a cloud-native, efficient and secure environment.

Because it's a SaaS tool, it provides developers with an environment that takes minutes to start using rather than requiring hours or days to install and deploy, according to Harris.

The SAS App Factory, meanwhile, provides prebuilt analytics and AI applications that automate the setup and integration of a cloud-native ecosystem built with the React architecture, open source programming language TypeScript and PostgreSQL database.

Using the prebuilt tools -- the first two of which are the SAS Energy Forecasting Cloud and an application developed by Cambridge University Hospitals to improve health care outcomes -- customers can customize and deploy AI-driven applications designed to address specific needs.

The significance of both new services is the potential for increased efficiency, according to Henschen.

"The coming SAS Viya Workbench and SAS App Factory SaaS services promise to accelerate the development of AI- and ML-based applications," he said.

Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.

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SAS unveils plans to add generative AI to analytics suite - TechTarget