The First Rule of Fight Club and Irregular Warfare Should be the Same

David Maxwell

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“You have your way. I have my way. As for the right way, the correct way, and the only way, it does not exist.”

- Friedrich Nietzsche

Scholars, practitioners, and policymakers continue to contemplate the definition of irregular warfare (IW) and what it means for U.S. national security and defense strategy. Many electrons are flowing through cyberspace with debates and arguments about what constitutes irregular warfare, why it is or is not important, who should conduct it (e.g., specific forces or all forces) and how it should be taught in professional military education.

Recently a mentor and expert on China and Special Operations pointed some of us to a 2021 Modern Warfare Institute article, “China’s Irregular Approach to War: The Myth of a Purely Conventional Future Fight,” with this excerpt about China and irregular warfare.

Algorithmic Warfare: Machine Learning, AI Needed For JADC2 Secure Comms

Meredith Roaten

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The Pentagon-wide effort to connect sensors to shooters to gain decision dominance should prioritize secure communications, industry executives said.

The Air Force is looking at new technologies to support its contribution to the joint all-domain command and control, or JADC2, campaign, including systems that use machine learning and artificial intelligence to speed up comms. A secure communications demonstration this fall spurred the buildup of networking capability needed for the effort, officials said.

The Air Force Research Laboratory partnered with Raytheon and Starlink for a demonstration of the robust information provisioning layer program, or RIPL, Brian Holmes, program manager of AFRL advanced planning and autonomous command and control systems branch, announced in a December press release.

In September, using internet protocol encryptors, Starlink engineers demonstrated a secure link between a test facility in Oneida, New York, and the main research lab several miles away in Rome, New York.

“It’s software to try and connect and establish communications networking across different legacy links in a way that supports all those links and gets the data from the suppliers to the people that need it,” Jason Redi, president of Raytheon BBN, told reporters at a Raytheon event in November.

There are many different links that are created for unique purposes that are not able to talk to one another, he said. Operators don’t have time to look for where the data they need is, especially if certain links are taken out by adversaries.

Groundbreaking patents and scientific discoveries are happening less and less often. Here’s why.

Dan Vergano

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So much for “The Jetsons.” Flying cars, floating cities and robot servants never happened. A decadeslong slowdown in “disruptive” discoveries, detailed in a new report looking at scientific studies and issued patents, might be one explanation.

For more than a decade, scientists and economists have worried that groundbreaking inventions have become fewer and farther between. Where the early 20th century delivered novel innovations that ranged from airplanes to atomic bombs, more recent years have instead seen an “innovation slowdown” in the rate of invention, even in the face of ever-growing investments in research.

“A lot of the funders behind science and technology have been arguing or proposing that we need more disruptive science and technology to deal with climate change and other societal grand challenges [as] just kind of a way to address these very important problems,” said University of Minnesota innovation researcher Michael Park, an author of the new analysis in the journal Nature. Even though the raw number of papers and patents have exploded in the last half-century, said Park, “the percentage of disruptive work is declining across all major fields.”

The slowdown — seen across 45 million papers and 3.9 million U.S. patents stretching from 1945 to 2010 — may point to even bigger problems in the economy and cultural scene, say some observers. About half the economic gains in productivity come from innovations in science and technology, for example, but productivity growth has slowed in advanced economies. In the last 15 years, it has increased at just half the rate it did in the 15 years before then. Striking declines in “disruptive” works, ones that “break with the past in ways that push science and technology in new directions” in fields from physics to medicine, might just be a symptom of this bigger slowdown.

What generative AI like ChatGPT gets right — and wrong

Benjamin Powers

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ChatGPT, the chatbot created by OpenAI, has taken the terminally online crowd by storm. People have used it to write sonnets, essays and even computer code — usually followed by some statement akin to “Wow, this is incredible.”

It’s the latest, buzziest example of generative artificial intelligence, the same type of model that allows online platforms like Midjourney and DALL-E 2 to make images from prompts. Already, advocates and detractors alike are heralding the leaps in large language models like ChatGPT and others as forces that will fundamentally change how we live and work, from how kids do homework to who writes computer code.

But the reality is more complicated. Generative AI models are very good at very specific tasks — but they are not one-size-fits-all tools. For example, ChatGPT can create lovely sonnets about tectonic plates, but it struggles to write an up-to-date explanation of what plate tectonics is. It also has trouble generating accurate code or understanding context around current events given that GPT-3, the large language model it was trained on, stopped gathering data in 2021, and it can be biased. Moreover, while numerous startups say they’re working on “generative AI,” experts and venture capitalists say that in some cases that’s just marketing, as small firms hop on the latest buzzword bandwagon.

Where generative AI can shine is more general tasks that may not end up the way you thought — writing form emails, drafting a philosophical essay or creating cover art for an album. Sometimes, how convincing it can be is a detriment. One recent paper found that AI-written abstracts of fake scientific papers managed to fool real scientists, who couldn’t tell they were written by AI.

“It might look like an overnight success for specific models, but the truth is this space and generative AI has been brewing, and folks and companies like Runway, we have been working on this for years,” said Cristóbal Valenzuela, CEO and co-founder of Runway, a company that works in content creation and editing using AI and was launched in 2018. “I think what has changed now as models have gotten better and people’s understanding of how those products and those models can be used and leveraged is becoming more mainstream.”

What is generative AI?

The Hunt for the Dark Web’s Biggest Kingpin, Part 6: Endgame

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ON A TYPICAL day, the Private House Buddhamonthon development on the western edge of Bangkok offers a quiet respite from the traffic jams and diesel fumes of the city's central neighborhoods. The cul-de-sac where Alexandre Cazes lived in that semi-suburban enclave was dotted with yellow trumpetbush blossoms. The only sounds were of palm fronds and banana trees rustling in the breeze and the chatter of tropical birds. But on the morning of July 5, that street would have seemed unusually busy to anyone paying attention.

At one end, a gardener was trimming the foliage, and an electrician was busy with a nearby wiring box. Inside the house at the street's dead end, a model home and sales office for Private House's real estate development firm, a man and woman were getting a tour of the property and inquiring about moving into the neighborhood. Their driver sat waiting in a car outside. Another car with two women in it was slowly pulling into the cul-de-sac, looking lost after taking an apparent wrong turn.

In fact, every one of the characters in this bustling scene was an undercover agent. Thailand’s DEA equivalent, the Narcotics Suppression Bureau, had assembled an entire theatrical production's worth of actors around the unwitting target, busily performing their roles and waiting for a signal for Operation Bayonet's takedown to finally begin.

The only non-Thai player in this pantomime was the DEA's Wilfredo Guzman. He stood inside the real estate spec house at the end of the cul-de-sac wearing a Red Hot Chili Peppers T-shirt and jeans, posing as a wealthy foreign buyer with a Thai wife. Guzman's primary job that morning was to distract the polite real estate agent, straining the limits of his Thai vocabulary to bombard her with questions about the layout of the spec house, the number of bedrooms, the size of the garage, and every other domestic detail he could think of. All of this was designed to allow the agent playing his wife to venture to an upstairs window and get eyes on Cazes' house and driveway next door, in anticipation of the action set to unfold there.

Outsmarting Agile Adversaries in the Electromagnetic Spectrum

Padmaja Vedula

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Research QuestionsHow are adversary capabilities in the EMS evolving?

How fast does electronic warfare–related software reprogramming need to be to keep pace with threats?

What obstacles exist within the current intel-to-reprogramming process?

What advanced technologies are needed to achieve necessary improvements?

The U.S. Air Force's electronic warfare integrated reprogramming (EWIR) enterprise examines intelligence on adversary threats that emit in the electromagnetic spectrum (EMS) (in particular, radars and jammers) and configures electronic warfare software and hardware to enable aircraft or other resources to react to and/or respond to adverse changes in the EMS environment. With the growing advancements in U.S. adversaries' electronic warfare assets that enable complex and diverse EMS capabilities, identifying, tracking, and responding to these threats requires much faster updates than the existing EWIR enterprise was designed for. The research team conducted four interrelated technology case studies that together comprise the fundamental elements necessary for creating a near-real-time, autonomous, inflight software reprogramming capability and, more specifically, artificial intelligence–enabled cognitive electronic warfare capabilities—the use of machine learning algorithms that enable platforms to learn, reprogram, adapt, and effectively counter threats in flight. The research team also highlighted important continuing roles for the existing EWIR enterprise even as the U.S. Air Force moves toward a cognitive future.

Key Findings

Right Hands, Right Place: Why We Must Push Military Technology Experimentation to the Edge

SCHUYLER MOORE

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In the summer of 1943, the American submarine USS Tinosa came upon the Tonan Maru, a Japanese oil tanker supporting the imperial fleet. The American submarine spent an entire day and 15 torpedoes trying to sink the Maru, which escaped with light damage after all but one of the U.S. weapons failed to explode on target. Sadly, this episode was hardly unique: more than 70 percent of the sub fleet’s Mark XIV torpedoes malfunctioned during the first two years of World War II.

It turned out that the Mark XIV had only been tested in shallow, calm water, at targets that were closer than was realistic, and from barges that did not accurately simulate the effect of firing from submarines. Most importantly, few submariners were part of the testing. When the torpedoes were fired in the deep, choppy water of the Pacific, they neither ran correctly nor consistently detonated.

The enduring lesson? Mature technologies must be put in the hands of the user as quickly as possible to debug, iterate, and improve their capabilities. The commercial sector intuitively knows this. Apple would never release an iPhone without extensive tests and user feedback. (And when it doesn’t, it accidentally releases a phone that doesn’t work for left-handed users; “Antennagate,” anyone?)

Real-world testing is even more important for military equipment. Apple may replicate how and where someone might use an iPhone with some precision, but you will have a harder time precisely replicating how a soldier, sailor, airman, or guardian would use technology in the field, where performance is affected by temperature, geography, weather, and available facilities. A quadcopter might have a perfect record from a company’s launch pad in the U.S. but struggle to take off in the windy mountains of Germany. A fast boat might run well off the coast of Rhode Island, but only half as long in the hot, salty, choppy waters of the Arabian Gulf.

India Is Critical to Deterring a Chinese Invasion of Taiwan

Satoru Nagao

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The Quadrilateral Security Dialogue, also known as the “Quad,” is a security framework that includes Australia, India, Japan and the US It was launched by former Prime Minister Shinzo Abe before his assassination, and it has become a core part of the strategy to counter China. Among the four members, India is considered to be the most out-of-step, especially when it comes to military matters. Nonetheless, India would play a crucial role in one of the most serious security challenges the Quad could face: a Chinese invasion of Taiwan.

Reluctant partner

Even if China invades Taiwan and the US, Japan and Australia must fight to defend it, India is unlikely to join. India has two aircraft carriers, for example, but it is unlikely to dispatch them to defend Taiwan. So far, the carriers have visited Sri Lanka and Maldives on friendship visits, but New Delhi has not dispatched them to countries further abroad.

Indian Navy destroyers have made port calls in Japan more often, and Indian submarines are deployed in the South China Sea. However, while India participated the November 2022 “Malabar” joint exercises with the US, Japan, and Australia, it did not join them and the UK in the “Keen Sword” exercises that simulated a Taiwan crisis. Both joint exercises happened near Japan at nearly the same time. India’s restraint indicates that one should not expect it to join a war to defend Taiwan.

Despite this, India will be vital in defending Taiwan for three reasons.

1. Strategic balancing