Artificial Intelligence

ukraine-has-become-the-world’s-testing-ground-for-military-robots

Ukraine has become the world’s testing ground for military robots

The war in Ukraine has become the largest testing ground for artificial intelligence-powered autonomous and uncrewed vehicles in history. While the use of military robots is nothing new — World War II saw the birth of remote-controlled war machines and the US has deployed fully-autonomous assault drones as recently as 2020 — what we’re seeing in Ukraine is the proliferation of a new class of combat vehicle. 

This article discusses the “killer robot” technology being used by both sides in Russia’s war in Ukraine. Our main takeaway is that the “killer” part of “killer robots” doesn’t apply here. Read on to find out why. 

Uncrewed versus autonomous

This war represents the first usage of the modern class of uncrewed vehicles and automated weapons platforms in a protracted invasion involving forces with relatively similar tech. While Russia’s military appears, on paper, to be superior to Ukraine’s, the two sides have fielded forces with similar capabilities. Compared to forces Russia faced during its involvement in the Syrian civil war or, for example, those faced by the US during the Iraq and Afghanistan engagements, what’s happening on the ground in Ukraine right now demonstrates a more paralleled engagement theater. 

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It’s important, however, to mention that this is not a war being fought by machines. It’s unlikely that autonomous or uncrewed weapons and vehicles will have much impact in the war, simply because they’re untested and, currently, unreliable. 

Uncrewed vehicles and autonomous vehicles aren’t necessarily the same thing. While almost all autonomous vehicles — those which can operate without human intervention — are uncrewed, many uncrewed vehicles can only be operated remotely by humans. Perhaps most importantly, many of these vehicles have never been tested in combat. This means that they’re more likely to be used in “support” roles than as autonomous combat vehicles, even if that’s what they were designed to do. 

But, before we get into the how’s and why’s behind the usage of military robots in modern warfare, we need to explain what kind of vehicles are currently in use. There are no “killer robots” in warfare. That’s a catch-all term used to describe military vehicles both autonomous and uncrewed.

These include uncrewed aerial vehicles (UAVs), uncrewed ground vehicles (UGVs), and uncrewed surface vehicles (USVs, another term for uncrewed maritime or water-based vehicles).

So, the first question we have to answer is: why not just turn the robots into killers and let them fight the war for us? You might be surprised to learn that the answer has very little to do with regulations or rules regarding the use of “killer robots.” 

To put it simply: militaries have better things to do with their robots than just sending fire downrange. That doesn’t mean they won’t be tested that way, there’s already evidence that’s happened

A British “Harrier” USV, credit: Wikicommons

However, we’ve seen all that before. The use of “killer robots” in warfare is old hat now. The US deployed drones in Iraq and Afghanistan and, as we reported here at TNW, it even sent a Predator drone to autonomously assassinate an Iranian general.

What’s different in this war is the proliferation of UAVs and UGVs in combat support roles. We’ve seen drones and autonomous land vehicles in war before, but never at this scale. Both forces are using uncrewed vehicles to perform tasks that, traditionally, either couldn’t be done or require extra humanpower. It does also bear mentioning that they’re using gear that’s relatively untested, which explains why we’re not seeing either country deploying these units enmasse.

A developmental crucible

Developing wartime technology is a tricky gambit. Despite the best assurances of the manufacturers, there’s simply no way to know what could possibly go wrong until a given tech sees actual field use.

In the Vietnam war, we saw a prime example of this paradigm in the debut of the M-16 rifle. It was supposed to replace the trusty old M-14. But, as the first soldiers to use the new weapon tragically found out, it wasn’t suitable for use in the jungle environment without modifications to its design and special training for the soldiers who’d use it. A lot of soldiers died as a result.

A US Marine cleaning their M16 during the US-Vietnam War, credit: Wikicommons

That’s one of the many reasons why a number of nations who’ve so far refused any direct involvement in the war are eager to send cutting-edge robots and weapons to the Ukrainian government in hopes of testing out their tech’s capabilities without risking their own soldiers’ skin. 

TNW spoke with Alex Stronell, a Land Platforms Analyst and UGV lead at Janes, the defense intelligence provider. They explained that one of the more interesting things to note about the use of UGVs, in particular, in the war in Ukraine, is the absence of certain designs we might have otherwise expected.

“For example, an awful lot of attention has been paid inside and outside of Russia to the Uran-9 … It certainly looks like a menacing vehicle, and it has been touted as the world’s most advanced combat UGV,” Stronell told us, before adding “however, I have not seen any evidence that the Russians have used the Uran-9 in Ukraine, and this could be because it still requires further development.”

Uran-9 armed combat robot UGV Unmanned Ground Vehicle Rosboronexport Russia Russian Defense Industry – YouTube

On the other side, Stronell previously wrote that Ukrainian forces will soon wield the world’s largest complement of THeMIS UGVs (see the video below). That’s exceptional when you consider that the nation’s arsenal is mostly lend-leased from other countries. 

Milrem, the company that makes the THeMIS UGV, recently announced that the German Ministry of Defence ordered 14 of its vehicles to be sent to the Ukrainian forces for immediate use. According to Stronell, these vehicles will not be armed. They’re equipped for casualty evacuation, and for finding and removing landmines and similar devices. 

Milrem Robotics’ THeMIS UGVs used in a live-fire manned-unmanned teaming exercise – YouTube

But it’s also safe to say that the troops on the ground will find other uses for them. As anyone who’s ever deployed to a combat zone can tell you, space is at a premium and there’s no point in bringing more than you can carry.

The THeMIS, however, is outfitted with Milrem’s “Intelligence Function Kit,” which includes the “follow me” ability. This means that it would make for an excellent battle mule to haul ammo and other gear. And there’s certainly nothing stopping anyone from rekitting the THeMIS with combat modules or simply strapping a homemade autonomous weapon system to the top of it.

D.I.Y. Scrap Metal Auto-Turret (RaspberryPi Auto-Tracking Airsoft Sentry?!) – YouTube

On-the-job training

As much as the world fears the dawning of the age of killer robots in warfare, the current technology just simply isn’t there yet. Stronell waved off the idea that a dozen or so UGVs could, for example, be outfitted as killer guard robots that could be deployed in the defense of strategic points. Instead, he described a hybrid human/machine paradigm referred to as “manned-unmanned teaming, or M-UMT,” where-in, as described above, unmounted infantry address the battlefield with machine support. 

In the time since the M-16 was mass-adopted during an ongoing conflict, the world’s militaries have refined the methodology they use to deploy new technologies. Currently, the war in Ukraine is teaching us that autonomous vehicles are useful in support roles.

The simple fact of the matter is that we’re already exceptionally good at killing each other when it comes to war. And it’s still cheaper to train a human to do everything a soldier needs to do than it is to build massive weapons platforms for every bullet we want to send downrange. The actual military need for “killer robots” is likely much lower than the average civilian might expect. 

However, AI’s gifts when it comes to finding needles in haystacks, for example, make it the perfect recon unit, but soldiers have to do a lot more than just identify the enemy and pull a trigger.

However, that’s something that will surely change as AI technology matures. Which is why, Stronell told us, other European countries are either currently in the process of adopting autonomous weaponry or already have. 

In the Netherlands, for example, the Royal Army has engaged in training ops in Lithuania to test their own complement of THeMIS units in what they’re referring to as a “pseudo-operational” theater. Due to the closeness of the war in Ukraine and its ongoing nature, nearby nations are able to run analogous military training operations based on up-to-the-minute intel of the ongoing conflict. In essence, the rest of Europe’s watching what Ukraine and Russia do with their robots and simulating the war at home. 

Soldiers in the Netherlands Royal Army in front of a Netherlands Royal Air Force AH-64 Apache helicopter, credit: Wikicommons

This represents an intel bonanza for the related technologies and there’s no telling how much this period of warfare will advance things. We could see innumerable breakthroughs in both military and civilian artificial intelligence technology as the lessons learned from this war begin to filter out. 

To illustrate this point, it bears mention that Russia’s put out a one million ruble bounty (about €15,000) to anyone who captures a Milrem THeMIS unit from the battlefield in Ukraine. These types of bounties aren’t exactly unusual during war times, but the fact that this particular one was so publicized is a testament to how desperate Russia is to get its hands on the technology. 

An eye toward the future

It’s clear that not only is the war in Ukraine not a place where we’ll see “killer robots” deployed enmasse to overwhelm their fragile, human, enemy soldier counterparts, but that such a scenario is highly unlikely in any form of modern warfare.

However, when it comes to augmenting our current forces with UGVs or replacing crewed aerial and surface recon vehicles with robots, military leaders are excited about AI’s potential usefulness. And what we’re seeing right now in the war in Ukraine is the most likely path forward for the technology. 

That’s not to say that the world shouldn’t be worried about killer robots or their development and proliferation through wartime usage. We absolutely should be worried, because Russia’s war in Ukraine has almost certainly lowered the world’s inhibitions surrounding the development of autonomous weapons. 

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Psst, automating these 3 parts of your business is the best thing you can do right now

Content provided by IBM and TNW

Thanks to the convergence of several trends and changes across different markets and industries, automation is becoming a critical factor in the success of businesses and products. Advances in artificial intelligence, in parallel with the accelerating digitization of all aspects of business, are creating plenty of opportunities to automate operations, reduce waste, and increase efficiency.

From managing your Information Technology (IT) bill to finding bottlenecks in your business processes and taking control of your own network operations, here are three areas where companies can gain from applying automation.

1. IT automation

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Practically every large organization has IT. Even small companies that don’t have in-house IT staff may pay for another company to do it for them. The growing demand for IT can put extra strain on professionals who must deal with the ever-expanding and changing landscape of application and compute platforms.

“I’ve never met an IT person or CIO who said they have so much time and budget that they can do everything the business asks and more. There’s always a shortage of ability to drive projects through IT,” says Bill Lobig, Vice President of IBM Automation Product Management.

The talent shortage is highlighting the need to provide automation tools to IT staff so they can manage application uptime and keep IT operations stable.

Fortunately, advances in artificial intelligence are helping companies move toward smart automation by gathering and processing all sorts of structured and unstructured data.

“We’re seeing companies have more confidence in applying AI to a broader set of data, including log files and metrics and information that are spinning off of the systems that are running in your business (databases, app servers, Kubernetes, VMs),” Lobig says.

Previously, IT experts may have optimized their infrastructure through informed judgments and overprovisioning their resources. Now, they can take the guesswork out of their decisions by using AI to analyze the data of the IT infrastructure, find patterns, estimate usage, and optimize their resources.

For example, J.B. Hunt, a logistics and transportation company, uses IBM Turbonomic software to automate the scaling of its cloud and on-premise resources. For their on-premises environment, J.B. Hunt is automating all non-disruptive actions 24×7 and scaling non-production actions during a nightly maintenance window.

“Workloads scale and spike—it’s not static. No matter how much performance testing and capacity you put into sizing an application deployment, it’s a guess, albeit an educated one. You don’t really know how your customers’ workloads are going to vary across different times,” Lobig says.

In their public cloud environment, the J.B. Hunt team has been using a combination of recommendations and automated actions to manage their resources. Over the course of 12 months, Turbonomic executed nearly 2,000 resizing actions which—assuming manual intervention requires 20 minutes per action—freed up over 650 hours of the team’s time to focus on strategic initiatives.

2. Business processes

Business processes are another area that can gain from advances in AI and automation. The previous wave of automation in business processes was mostly driven by robotic process automation (RPA). While RPA has had a tremendous effect on productivity, like other solutions, it has limits too.

RPA only addresses tasks that you think need automation. It can automate a poorly designed process but can’t optimize it. It also can’t handle tasks that can’t be defined through deterministic rules. This is where “process and task mining” enter the picture. According to Lobig:

RPA executes scripts to automate what you tell it to do. It’s very deterministic and rigid in what it can do, automating highly repeatable tasks. Process and task mining find inefficiencies you can’t see.

Process and task mining can answer questions such as, is your business really running the way you think it is? Is everyone completing processes in the same way? What should you optimize first? It helps you get past the low-hanging fruit and find the hidden inefficiencies of your business that can also be addressed with automation.

3. Networking

In the past, networking was a specialized hardware-based discipline largely controlled by big telecommunications companies. Today, the networking ecosystem is more complex as enterprises now require ubiquitous application distribution in a hybrid multi-cloud environment, from customer prem, to edge, to private and public clouds.

The challenge is deploying and connecting all application endpoints at scale. Networks must be agile and dynamic to maintain application performance, availability, security and user experience. Today’s networks, however, face unprecedented challenges that can render them unresponsive and unadaptable to change. Enterprise and service providers can address those needs, delivering custom enterprise network value with self-service enterprise control.

Organizations can now own and manage their networking functions and end-to-end connectivity without being experts in switches, routers, radio-access networks, and other hardware.

“Networking has become just another part of the application supply chain (like databases, VMs, and containers) that companies are already running. Why not have your network be part of your full IT landscape so that you can apply AI to optimize it?” Lobig says.

For example, consider a large multinational bank that provides its customers access to their accounts overseas through ATM machines. The company previously outsourced network connectivity to a big telco. When the telco faced an outage in one country where the bank provided service, the customers could not access their funds. Although the bank didn’t have control over the networking service, it was fined for the outage.

Now, thanks to software-defined wide area network (SD-WAN) and automation and orchestration tools such as IBM’s AIOps solutions and IBM SevOne Network Performance Management, the bank can assume control of its own software-defined network, instead of shifting such an important responsibility to another company. New application-centric network connectivity can enhance those capabilities. This can drive enhanced security, intelligent observability, and service assurance, while providing a common way to manage networks across the diversity of infrastructure, tools, and security constructs.

Another area of networking that will provide new opportunities for automation is 5G.

“A lot of people think about 5G as a faster networking technology. But 5G is going to transform and disrupt B2B use cases. It can really bring edge computing to the forefront,” Lobig says.

There’s an opportunity for organizations to leverage software-defined networking and 5G to unlock new business models where high-bandwidth, low latency, and local connectivity is crucial.

An example is DISH Wireless, a company that’s working with IBM to automate the first greenfield cloud-native 5G network in the US. DISH Wireless is using IBM’s network orchestration software and services to bring 5G network orchestration to its business and operations platforms. One application they’re working on is enabling logistics companies to track package locations down to the centimeter, thanks to edge connectivity, RFID tags, and network management software.

“We’re helping them do this with our telco and network computing automation, edge computing automation, and enabling them to set up state-of-the-art orchestration for their customers. These unexpected industries can use 5G to really transform how business gets done across different areas,” Lobig says.

Where is the industry headed?

Automation is quickly evolving and we’re bound to see many new applications in the coming months and years. For companies that are at the beginning of their automation journey, Lobig has a few tips.

In the business automation space, look at process and task mining. Do you really know where the time is being spent in your enterprise? Do you know how work is getting done? If you use this technology, you’ll be able to identify the patterns and sequence of events that go into good outcomes and those that go into bad outcomes. Armed with these insights, you can redesign and automate the processes that have the biggest impact upon your business.

Lobig also believes that IT automation will be a bigger theme in 2023 as the world faces an energy crisis and electricity costs potentially become an escalating problem. IT automation can help organizations to use the capacity they need, which may translate into savings.

IT automation can also be important in tackling the climate change crisis.

“These days, you can tell whether your organization’s data center or workload is running on a renewable energy source,” Lobig says. “With that data, IT automation has the potential to automatically move workloads from cloud to on-prem and back and across hyper-scalers to optimize for costs and efficiencies.”

As for the future, Lobig believes that low-code/no-code application platforms will play an important role in automation by enabling more employees to build the automations that can enhance productivity.

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What you need to know about AIOps


Content provided by IBM and TNW As our lives become more digitized, the IT infrastructure supporting the applications and services we use have become increasingly complex. There are a variety of options to run services in the cloud, on-premise, serverless, and hybrid, which makes it possible to accommodate different kinds of applications, environments, and audiences. However, managing such complex IT architectures is becoming increasingly difficult. There are too many moving parts, which makes it difficult to optimize IT, predict and prevent outages, and respond to incidents after they happen. Fortunately, AIOps — the use of AI in IT operations —…

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5 AI Chatbot Mobile Apps That Aim to Put a Therapist in Your Pocket

internal/modules/cjs/loader.js: 905 throw err; ^ Error: Cannot find module ‘puppeteer’ Require stack: – /home/760439.cloudwaysapps.com/jxzdkzvxkw/public_html/wp-content/plugins/rss-feed-post-generator-echo/res/puppeteer/puppeteer.js at Function.Module._resolveFilename (internal/modules/cjs/loader.js: 902: 15) at Function.Module._load (internal/modules/cjs/loader.js: 746: 27) at Module.require (internal/modules/cjs/loader.js: 974: 19) at require (internal/modules/cjs/helpers.js: 101: 18) at Object. (/home/760439.cloudwaysapps.com/jxzdkzvxkw/public_html/wp-content/plugins/rss-feed-post-generator-echo/res/puppeteer/puppeteer.js:2: 19) at Module._compile (internal/modules/cjs/loader.js: 1085: 14) at Object.Module._extensions..js (internal/modules/cjs/loader.js: 1114: 10) at Module.load (internal/modules/cjs/loader.js: 950: 32) at Function.Module._load (internal/modules/cjs/loader.js: 790: 12) at Function.executeUserEntryPoint [as runMain] (internal/modules/run_main.js: 75: 12) code: ‘MODULE_NOT_FOUND’, requireStack: [ ‘/home/760439.cloudwaysapps.com/jxzdkzvxkw/public_html/wp-content/plugins/rss-feed-post-generator-echo/res/puppeteer/puppeteer.js’ ]

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deepfakes-explained:-the-ai-that’s-making-fake-videos-too-convincing

Deepfakes Explained: The AI That’s Making Fake Videos Too Convincing

internal/modules/cjs/loader.js: 905 throw err; ^ Error: Cannot find module ‘puppeteer’ Require stack: – /home/760439.cloudwaysapps.com/jxzdkzvxkw/public_html/wp-content/plugins/rss-feed-post-generator-echo/res/puppeteer/puppeteer.js at Function.Module._resolveFilename (internal/modules/cjs/loader.js: 902: 15) at Function.Module._load (internal/modules/cjs/loader.js: 746: 27) at Module.require (internal/modules/cjs/loader.js: 974: 19) at require (internal/modules/cjs/helpers.js: 101: 18) at Object. (/home/760439.cloudwaysapps.com/jxzdkzvxkw/public_html/wp-content/plugins/rss-feed-post-generator-echo/res/puppeteer/puppeteer.js:2: 19) at Module._compile (internal/modules/cjs/loader.js: 1085: 14) at Object.Module._extensions..js (internal/modules/cjs/loader.js: 1114: 10) at Module.load (internal/modules/cjs/loader.js: 950: 32) at Function.Module._load (internal/modules/cjs/loader.js: 790: 12) at Function.executeUserEntryPoint [as runMain] (internal/modules/run_main.js: 75: 12) code: ‘MODULE_NOT_FOUND’, requireStack: [ ‘/home/760439.cloudwaysapps.com/jxzdkzvxkw/public_html/wp-content/plugins/rss-feed-post-generator-echo/res/puppeteer/puppeteer.js’ ]

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London-based Flawless AI’s ‘True Sync’ tech is a revolutionary approach to film dubbing


When British director Scott Mann’s latest film, Fall, was on the precipice of receiving an “R” rating from the MPAA over the number of “F” bombs dropped over its one hour and 47-minute run time, he did what any reasonable person would: he used artificial intelligence to digitally alter the actor’s performances in order to change the swear words into more palatable terms. A stroke of fricking genius, if you ask us. For those who are curious: about 35 “F” words stood between a PG-13 rating and an R rating. Mann’s dilemma, then, became trying to figure out how to…

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