Unified Communications Manager Cloud for Government (UCM) – Formerly Hosted Collaboration Solution for Government (HCS-G)

Iron Bow’s UCM (formerly HCS-G), powered by Cisco, is a FedRAMP Authorized cloud-based collaboration service built to help you improve communication capabilities, empower your mobile workforce, meet cloud-first mandates and maintain stringent security standards. Check out this video and see how we can help your agency overcome key IT and business challenges.

See what VDI can do for your agency.

The case for Virtual Desktop Infrastructure (VDI) has never been stronger. Agencies are looking for better approaches to securing and managing end-user devices. Check out this infographic and see what’s driving the interest in VDI solutions—and what concerns are slowing agencies down.

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Welcome to Iron Bow's TechSource, a blog about the issues facing the government and industry today and the technologies being adopted to help overcome them.

Mythbusters: What AI Is and What It Isn’t

Jim Smid, CTO, Iron Bow Technologies


Artificial Intelligence. Two words we have heard before, but what does it mean? Govexec President Constance Sayers and Iron Bow’s CTO, Jim Smid, sit down to discuss what AI is and what it isn’t in this Machine Momentum podcast.

What is Artificial Intelligence?

Artificial Intelligence is used interchangeably with words like machine learning (ML), big data and data science and while these terms overlap, they have their differences. Jim Smid defines AI as “getting your computer to behave like a human and do actions on the user’s behalf.” A good example of AI is self driving cars. Oftentimes, we are presented with an abundance of data sets, or “big data,” in which we can teach our computer to file, analyze and perform; this is artificial intelligence.

Another term, data science, is an umbrella term that includes AI. Think of data science as an overarching term used that encompasses various disciplines including big data, artificial intelligence, statistics, visualizations and pattern recognition. Data science uses scientific methods and algorithms to extract knowledge and insights from large amounts of data. Used most interchangeable with AI, though, is machine learning, a subset of artificial intelligence utilized for very specific tasks. ML is essentially how machines can be taught to perform a particular task by framing the rules with data. In the example with a self driving car, machine learning would help with the process of braking. With new tires or varying road conditions, the car behaves differently even after many trials, so the process of machine learning is to take all this data, analyze it and improve the outcome a little more every time this process is repeated.

How federal agencies are using AI and Machine Learning?

Within federal agencies, artificial intelligence is applicable in so many ways, especially in the Department of Defense. AI can be very helpful in the field to make sure technology and communications work the way they should. Logistically, AI can be used to make sure the people, equipment and food are available and delivered at the right time and place. In civilian spaces, AI-related technologies like predicted maintenance are also being applied. Are their Jeeps, helicopters and planes running as they should? Will they continue to run? Technology that can answer questions like these can be a game changer for government agencies and allow for effective and innovative advancements.

What is the most significant barrier that government executives are facing when it comes to AI adoption?

Some government executives struggle with where to start because of the amount of data, security concerns and disparate systems. Jim Smid states that agencies tend to have an excess amount of tools that aren’t compatible and don’t communicate with each other but are still creating data. Here is where AI can be applied and can help with this communication; AI will thread together the systems, organize the data and give analysts the results of what that data means. This saves time and resources because AI can perform these repetitive, iterative processes in a fraction of the time it would take a person allowing the agency to focus on more crucial tasks to keep the organization running. When considering implementing an AI or ML tool, security is always a top concern for agencies, as well. Relying on a single person to analyze, prioritize and validate every piece of data that comes through increases the probability of missing a potential malicious attack so allowing your AI tool to do that for you ensures a higher level of security for the organization as whole. Smid suggests the best approach is to start small with one process and scale up to larger projects to help build trust in the AI processes and results and encourage a solid security posture.

For the full interview with Jim Smid, click here. To learn more about how Iron Bow is using artificial intelligence to help organizations like yours, click here. Read next week as Jim Smid sits down with Iron Bow’s Director of Cyber Security, Rob Chee, to discuss the relationship between AI and government security.


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