Revolutionizing Operations: Data-Centric Plans, AI And Tech Concerns Revealed

Amid a landscape of rapid technological evolution, the U.S. Army stands on the cusp of a profound data-driven transformation.

Speaking Thursday at AFCEA's TechNet Augusta 2023, held in Augusta, Georgia, August 14-17, military leaders discussed the service's ascendancy of information plan in a shift that hasn't been witnessed in nearly four decades.

"It's the first time in almost four decades that I've seen the Army aligned behind the network and communications and cyber, that I've ever seen since I've been in, and you have to be excited about that," said Maj. Gen. Jeth Rey, director of the U.S. Army's Network Cross-Functional Team.

The expert panel discussed how data sharing, processing and security initiatives reach the majority of those in uniform across roles and functions in the Army.

"This is probably the first time you're now getting the operational folks and the actual operators into the conversation on what is the relevant data," said Brig. Gen. Joseph Papenfus, USAR, chief of staff at the Defense Information Systems Agency.

Panelists stressed the security built around information that allows it to flow while seeking to feed the edge, where connectivity may be a limitation.

They also addressed competition from adversaries and how critical it is to stay ahead in every possible domain, including hardware.

"Some of those foreign militaries that we might compete with in a kinetic environment are the same militaries that we will compete with for IT parts going forward," said Maj. Gen. Robert Edmonson, commanding general of the U.S. Army Communications-Electronics Command.

The panel directly addressed businessmen in the audience.

"As we acquire capability, what we're asking industry to ensure is that you may have [suppliers] that are out there doing a circuit board for you. We really need to ensure that there's quality control behind those circuit boards that are being built out there," Rey said.

Among the many issues behind quality control lies the traceability of hardware and software to prevent malicious actors from exploiting vulnerabilities.

"If there is an issue along the supply chain, we can defend not only what we have but to understand where defense goes in depth across the supply chain," said David M. Markowitz, chief data and analytics officer, U.S. Army.

Markowitz stressed that both hardware and software had to be protected as the United States operates with allies and partners.

"Our allies are being asked as our same industrial base, so understanding where those choke points are throughout both the United States and our international partners is critical so that we understand dependencies," Markowitz added.

The panel also addressed generative artificial intelligence and large language models.

"At the Department of Defense level, there's a project, Project Lima, that's going to look at thirty plus use cases and large language models and really identify where they fit because some are going to fit well, some are not," Markowitz said.

The expert offered his preliminary opinion.

"I personally believe that one of the best use cases is software development," Markowitz told the audience.

The panel "Synchronizing Critical Roles to Enable a Data-Centric Army" was moderated by Lt. Gen. Edward Cardon, USA (Ret.), founding partner and co-CEO of Touchstone Futures.

Col. Eric Van Den Bosch, USA, commander, 7th Signal Command, also participated in the panel.

Cloud Data Systems And Edge AI Make A Major Impact On Today's Data Science

Gartner outlines the top trends in machine learning and data science, including the impact of generative AI. Learn more about the top trends with our article.

Image: kras99/Adobe Stock

Gartner outlines the top trends in machine learning and data science, including the impact of generative AI.

Investors will pour more than $10 billion into AI startups that use foundation models, tech consultancy Gartner found in its August report on top trends in data science and machine learning. In particular, business leaders across the globe are interested in edge and data-centric generative AI, plus using generative AI responsibly.

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Cloud-native solutions take over from self-contained software

By 2024, 50% of new system deployments in the cloud will reside entirely within a cloud data ecosystem as opposed to manually integrated point solutions, Gartner predicted. Organizations should look out for converged data and analytics platforms that can solve problems over a wide swath of distributed data. That means businesses will continue to see more cloud-native solutions as opposed to self-contained software or blended deployments.

SEE: Explore the best data science tools for any use case (TechRepublic)

Edge and AI will move analysis toward IoT endpoints

"As machine learning adoption continues to grow rapidly across industries, DSML [data science and machine learning] is evolving from just focusing on predictive models toward a more democratized, dynamic and data-centric discipline," said Peter Krensky, director analyst at Gartner, at the Gartner Data & Analytics Summit on August 1, as quoted in a press release. "This is now also fueled by the fervor around generative AI. While potential risks are emerging, so too are the many new capabilities and use cases for data scientists and their organizations."

Businesses are keeping an eye on how AI training and inferencing can help transition data analytics to edge environments near IoT endpoints.

More than 55% of all data analysis by deep neural networks (which generative AI is based on) will occur at the point on the edge where the data is captured by 2025, Gartner said. That's a large jump from the 10% that occurred in 2021, and speaks to the massive increase in AI adoption since the beginning of 2023.

Cloud and edge computing saw a $84 billion equity investment in 2022, McKinsey found in its 2023 tech trends report.

Data-centric AI can include training on synthetic data

Data-centric AI performs tasks such as AI-specific data management, synthetic data and data labeling to solve problems in accessibility, volume, privacy, security, complexity and scope.

Generative AI can also be used to create synthetic data with which to train other applications. Use cases such as simulating real conditions, predicting future scenarios and removing some risk from AI will boost the amount of synthetic data in industry to 60% by 2024, Gartner predicts. That's up from just 1% in 2021, likely driven again by the commercialization of generative AI in late 2022 and early 2023.

Responsible AI follows the trend toward regulation

Responsible AI is a philosophy that takes into account business and societal value, risk, trust, transparency and accountability, in regards to generative AI. Gartner pointed out that "The concentration of pretrained AI models among 1% of AI vendors by 2025 will make responsible AI a societal concern" – meaning that a problem in one model could rapidly spread across a massive number of clients. Concerns include generative AI introducing factual mistakes into content — accidentally because of hallucinations or on purpose as part of a planned misinformation campaign. People are also concerned about AI introducing bias into content or plagiarizing copyrighted work.

More must-read AI coverage

Some organizations, including Salesforce, support recent conversations about government regulation on generative AI.

"Salesforce supports tailored, risk-based AI regulation that differentiates contexts and uses of the technology and ensures the protection of individuals, builds trust, and encourages innovation," Salesforce's executive vice president of government affairs, Eric Loeb wrote in a blog post in July.

AI investment continues to rise

Overall, Gartner found that more than $10 billion will have been invested in AI startups that rely on foundation models by 2026. More organizations will implement AI solutions, and more industries will take AI technologies and AI-based businesses into account.

In a pool of 2,500 executive leaders in May, Gartner found that 45% said the hype around ChatGPT spurred them to put more money into generative AI. Most (70%) of those organizations are still exploring their options, while 19% have a pilot program or have put use of generative AI into production.

Labelbox Joins Cloud Security Alliance

Bringing its expertise in data-centric security practices focused on the development of AI applications, Labelbox is helping lead a safer and more secure Cloud Computing Environment.

SAN FRANCISCO, Aug. 24, 2023 /PRNewswire/ -- Labelbox has announced today that it has joined the Cloud Security Alliance (CSA), the world's leading organization dedicated to defining and raising awareness of best practices to help ensure a secure cloud computing environment.

Labelbox is leading a safer and more secure cloud computing environment with data-centric security focused on AI apps.

Labelbox is the leading data-centric AI platform that empowers organizations to build intelligent applications. With a strong commitment to security, Labelbox continuously reviews and updates its security posture to align with global standards, ensuring the utmost protection for an enterprise's valuable data and IP. By becoming a member of the Cloud Security Alliance, Labelbox brings its expertise in data-centric security practices related to AI, contributing to a safer and more secure cloud computing environment.

"Joining the Cloud Security Alliance empowers Labelbox to fortify its security posture and foster a collaborative ecosystem for advancing our best-in-class SaaS solutions to our hundreds of enterprise customers. As Labelbox is becoming the foundational capability for companies to build AI/ML applications, we strive to enhance the entire industry's security standards and continue to protect users and their core AI initiatives," said Manu Sharma, Labelbox CEO and cofounder.

"Now more than ever, organizations need to make cybersecurity an everyday priority. Enterprises of all sizes need to understand the unrelenting risk, and they need to have a plan to protect their data continuously. We're excited to have Labelbox join the Cloud Security Alliance and to work together on developing standards that allow for the proper scoping of cloud environments through education, training, and collaboration to effectively protect data and improve security," said Jim Reavis, CEO and co-founder, Cloud Security Alliance. 

About the Cloud Security Alliance

The Cloud Security Alliance (CSA) is the world's leading organization dedicated to defining and raising awareness of best practices to help ensure a secure cloud computing environment. CSA harnesses the subject matter expertise of industry practitioners, associations, governments, and its corporate and individual members to offer cloud security-specific research, education, certification, events and products. CSA's activities, knowledge and extensive network benefit the entire community impacted by cloud — from providers and customers, to governments, entrepreneurs and the assurance industry — and provide a forum through which diverse parties can work together to create and maintain a trusted cloud ecosystem. For further information, visit us at www.Cloudsecurityalliance.Org, and follow us on Twitter @cloudsa.

About Labelbox

Labelbox is the leading data-centric AI platform for building intelligent applications. Data and ML teams use Labelbox to explore and visualize their data, organize datasets for AI processing and labeling, and measure the effectiveness of data within their AI models. The platform is used by Fortune 500 enterprises including Walmart, Procter & Gamble, Genentech, and Adobe, as well as hundreds of leading AI teams. Labelbox is backed by leading venture capital firms, including Andreessen Horowitz, B Capital Group, Databricks Ventures, Gradient (Google's AI venture firm), Kleiner Perkins, SoftBank and more.

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SOURCE Labelbox

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