AI News Articles
Artificial Intelligence (AI) is emerging technology with great promise and potential for abuse. Below are key excerpts of revealing news articles on AI technology from reliable news media sources. If any link fails to function, a paywall blocks full access, or the article is no longer available, try these digital tools.
Palantir (PLTR)’s Maven artificial intelligence system will become an official program of record, Deputy Secretary of Defense Steve Feinberg said in a letter to Pentagon leaders, a move that locks in long-term use of Palantir’s weapons-targeting technology across the U.S. military. Maven is a command-and-control software platform that analyzes battlefield data and identifies targets. It is already the primary AI operating system for the U.S. military, which has carried out thousands of targeted strikes against Iran over the last three weeks. Designating Maven as a program of record will streamline its adoption across all arms of the military. The memo ordered oversight of Maven be moved from the National Geospatial Intelligence Agency to the Pentagon’s Chief Digital Artificial Intelligence Office within 30 days. Future contracting with Palantir will be handled by the Army, the letter said. Feinberg’s order is a significant win for Palantir, which has landed a growing stream of contracts with the U.S. government, including a deal announced last summer with the U.S. Army worth up to $10 billion. Those awards have helped double the company’s stock price in the past year, lifting its market value to nearly $360 billion. Maven can rapidly analyze huge amounts of data from satellites, drones, radars, sensors and intelligence reports, and use AI to automatically identify potential threats or targets.
Note: For more along these lines, read our concise summaries of news articles on AI and military corruption.
The police department in Heber City, Utah, was forced to explain why a police report software declared that an officer had somehow shapeshifted into a frog. As Salt Lake City-based Fox 13 reports, the flawed tool seems to have picked up on some unrelated background chatter to devise its fantastical fairy tale ending. “The body cam software and the AI report writing software picked up on the movie that was playing in the background, which happened to be ‘The Princess and the Frog,'” police sergeant Rick Keel told the broadcaster, referring to Disney’s 2009 musical comedy. “That’s when we learned the importance of correcting these AI-generated reports.” The department had begun testing an AI-powered software called Draft One to automatically generate police reports from body camera footage. The goal was to reduce the amount of paperwork — but considering that immense mistakes are falling through the cracks, results clearly vary. Draft One was first announced by police tech company Axon — the same firm behind the Taser, a popular electroshock weapon — last year. The software makes use of OpenAI’s GPT large language models to generate entire police reports from body camera audio. Experts quickly warned that hallucinations could fall through the cracks in these important documents. Critics also argue that the tool could be used to introduce deniability and make officers less accountable in case mistakes were to fall through the cracks.
Note: For more along these lines, read our concise summaries of news articles on AI and police corruption.
In July, US group Delta Air Lines revealed that approximately 3 percent of its domestic fare pricing is determined using artificial intelligence (AI) – although it has not elaborated on how this happens. The company said it aims to increase this figure to 20 percent by the end of this year. According to former Federal Trade Commission Chair Lina Khan ... some companies are able to use your personal data to predict what they know as your “pain point” – the maximum amount you’re willing to spend. In January, the US’s Federal Trade Commission (FTC), which regulates fair competition, reported on a surveillance pricing study it carried out in July 2024. It found that companies can collect data directly through account registrations, email sign-ups and online purchases in order to do this. Additionally, web pixels installed by intermediaries track digital signals including your IP address, device type, browser information, language preferences and “granular” website interactions such as mouse movements, scrolling patterns and video viewing behaviour. This is known as “surveillance pricing”. The FTC Surveillance Pricing report lists several ways in which consumers can protect their data. These include using private browsers to do your online shopping, opting out of consumer tracking where possible, clearing the cookies in your history or using virtual private networks (VPNs) to shield your data from being collected.
Note: For more along these lines, read our concise summaries of news articles on Big Tech and the disappearance of privacy.
AI could mean fewer body bags on the battlefield — but that's exactly what terrifies the godfather of AI. Geoffrey Hinton, the computer scientist known as the "godfather of AI," said the rise of killer robots won't make wars safer. It will make conflicts easier to start by lowering the human and political cost of fighting. Hinton said ... that "lethal autonomous weapons, that is weapons that decide by themselves who to kill or maim, are a big advantage if a rich country wants to invade a poor country." "The thing that stops rich countries invading poor countries is their citizens coming back in body bags," he said. "If you have lethal autonomous weapons, instead of dead people coming back, you'll get dead robots coming back." That shift could embolden governments to start wars — and enrich defense contractors in the process, he said. Hinton also said AI is already reshaping the battlefield. "It's fairly clear it's already transformed warfare," he said, pointing to Ukraine as an example. "A $500 drone can now destroy a multimillion-dollar tank." Traditional hardware is beginning to look outdated, he added. "Fighter jets with people in them are a silly idea now," Hinton said. "If you can have AI in them, AIs can withstand much bigger accelerations — and you don't have to worry so much about loss of life." One Ukrainian soldier who works with drones and uncrewed systems [said] in a February report that "what we're doing in Ukraine will define warfare for the next decade."
Note: As law expert Dr. Salah Sharief put it, "The detached nature of drone warfare has anonymized and dehumanized the enemy, greatly diminishing the necessary psychological barriers of killing." For more, read our concise summaries of news articles on AI and warfare technology.
“Ice is just around the corner,” my friend said, looking up from his phone. A day earlier, I had met with foreign correspondents at the United Nations to explain the AI surveillance architecture that Immigration and Customs Enforcement (Ice) is using across the United States. The law enforcement agency uses targeting technologies which one of my past employers, Palantir Technologies, has both pioneered and proliferated. Technology like Palantir’s plays a major role in world events, from wars in Iran, Gaza and Ukraine to the detainment of immigrants and dissident students in the United States. Known as intelligence, surveillance, target acquisition and reconnaissance (Istar) systems, these tools, built by several companies, allow users to track, detain and, in the context of war, kill people at scale with the help of AI. They deliver targets to operators by combining immense amounts of publicly and privately sourced data to detect patterns, and are particularly helpful in projects of mass surveillance, forced migration and urban warfare. Also known as “AI kill chains”, they pull us all into a web of invisible tracking mechanisms that we are just beginning to comprehend, yet are starting to experience viscerally in the US as Ice wields these systems near our homes, churches, parks and schools. The dragnets powered by Istar technology trap more than migrants and combatants ... in their wake. They appear to violate first and fourth amendment rights.
Note: Read how Palantir helped the NSA and its allies spy on the entire planet. Learn more about emerging warfare technology in our comprehensive Military-Intelligence Corruption Information Center. For more, read our concise summaries of news articles on AI and Big Tech.
Health practitioners are becoming increasingly uneasy about the medical community making widespread use of error-prone generative AI tools. In their May 2024 research paper introducing a healthcare AI model, dubbed Med-Gemini, Google researchers showed off the AI analyzing brain scans from the radiology lab for various conditions. It identified an "old left basilar ganglia infarct," referring to a purported part of the brain — "basilar ganglia" — that simply doesn't exist in the human body. Board-certified neurologist Bryan Moore flagged the issue ... highlighting that Google fixed its blog post about the AI — but failed to revise the research paper itself. The AI likely conflated the basal ganglia, an area of the brain that's associated with motor movements and habit formation, and the basilar artery, a major blood vessel at the base of the brainstem. Google blamed the incident on a simple misspelling of "basal ganglia." It's an embarrassing reveal that underlines persistent and impactful shortcomings of the tech. In Google's search results, this can lead to headaches for users during their research and fact-checking efforts. But in a hospital setting, those kinds of slip-ups could have devastating consequences. While Google's faux pas more than likely didn't result in any danger to human patients, it sets a worrying precedent, experts argue. In a medical context, AI hallucinations could easily lead to confusion and potentially even put lives at risk.
Note: For more along these lines, read our concise summaries of news articles on AI and corruption in science.
U.S. Customs and Border Protection, flush with billions in new funding, is seeking “advanced AI” technologies to surveil urban residential areas, increasingly sophisticated autonomous systems, and even the ability to see through walls. A CBP presentation for an “Industry Day” summit with private sector vendors ... lays out a detailed wish list of tech CBP hopes to purchase. State-of-the-art, AI-augmented surveillance technologies will be central to the Trump administration’s anti-immigrant campaign, which will extend deep into the interior of the North American continent. [A] reference to AI-aided urban surveillance appears on a page dedicated to the operational needs of Border Patrol’s “Coastal AOR,” or area of responsibility, encompassing the entire southeast of the United States. “In the best of times, oversight of technology and data at DHS is weak and has allowed profiling, but in recent months the administration has intentionally further undermined DHS accountability,” explained [Spencer Reynolds, a former attorney with the Department of Homeland Security]. “Artificial intelligence development is opaque, even more so when it relies on private contractors that are unaccountable to the public — like those Border Patrol wants to hire. Injecting AI into an environment full of biased data and black-box intelligence systems will likely only increase risk and further embolden the agency’s increasingly aggressive behavior.”
Note: For more along these lines, read our concise summaries of news articles on AI and immigration enforcement corruption.
Negative or fear-framed coverage of AI in mainstream media tends to outnumber positive framings. The emphasis on the negative in artificial intelligence risks overshadowing what could go right — both in the future as this technology continues to develop and right now. AlphaFold, which was developed by the Google-owned AI company DeepMind, is an AI model that predicts the 3D structures of proteins based solely on their amino acid sequences. That’s important because scientists need to predict the shape of protein to better understand how it might function and how it might be used in products like drugs. By speeding up a basic part of biomedical research, AlphaFold has already managed to meaningfully accelerate drug development in everything from Huntington’s disease to antibiotic resistance. A timely warning about a natural disaster can mean the difference between life and death. That is why Google Flood Hub is so important. An open-access, AI-driven river-flood early warning system, Flood Hub provides seven-day flood forecasts for 700 million people in 100 countries. It works by marrying a global hydrology model that can forecast river levels even in basins that lack physical flood gauges with an inundation model that converts those predicted levels into high-resolution flood maps. This allows villagers to see exactly what roads or fields might end up underwater. Flood Hub ... is one of the clearest examples of how AI can be used for good.
Note: Explore more positive stories like this on technology for good.
Before signing its lucrative and controversial Project Nimbus deal with Israel, Google knew it couldn’t control what the nation and its military would do with the powerful cloud-computing technology, a confidential internal report obtained by The Intercept reveals. The report makes explicit the extent to which the tech giant understood the risk of providing state-of-the-art cloud and machine learning tools to a nation long accused of systemic human rights violations. Not only would Google be unable to fully monitor or prevent Israel from using its software to harm Palestinians, but the report also notes that the contract could obligate Google to stonewall criminal investigations by other nations into Israel’s use of its technology. And it would require close collaboration with the Israeli security establishment — including joint drills and intelligence sharing — that was unprecedented in Google’s deals with other nations. The rarely discussed question of legal culpability has grown in significance as Israel enters the third year of what has widely been acknowledged as a genocide in Gaza — with shareholders pressing the company to conduct due diligence on whether its technology contributes to human rights abuses. Google doesn’t furnish weapons to the military, but it provides computing services that allow the military to function — its ultimate function being, of course, the lethal use of those weapons. Under international law, only countries, not corporations, have binding human rights obligations.
Note: For more along these lines, read our concise summaries of news articles on AI and government corruption.
The US military may soon have an army of faceless suicide bombers at their disposal, as an American defense contractor has revealed their newest war-fighting drone. AeroVironment unveiled the Red Dragon in a video on their YouTube page, the first in a new line of 'one-way attack drones.' This new suicide drone can reach speeds up to 100 mph and can travel nearly 250 miles. The new drone takes just 10 minutes to set up and launch and weighs just 45 pounds. Once the small tripod the Red Dragon takes off from is set up, AeroVironment said soldiers would be able to launch up to five per minute. Since the suicide robot can choose its own target in the air, the US military may soon be taking life-and-death decisions out of the hands of humans. Once airborne, its AVACORE software architecture functions as the drone's brain, managing all its systems and enabling quick customization. Red Dragon's SPOTR-Edge perception system acts like smart eyes, using AI to find and identify targets independently. Simply put, the US military will soon have swarms of bombs with brains that don't land until they've chosen a target and crash into it. Despite Red Dragon's ability to choose a target with 'limited operator involvement,' the Department of Defense (DoD) has said it's against the military's policy to allow such a thing to happen. The DoD updated its own directives to mandate that 'autonomous and semi-autonomous weapon systems' always have the built-in ability to allow humans to control the device.
Note: Drones create more terrorists than they kill. For more, read our concise summaries of news articles on warfare technology and Big Tech.
In recent years, Israeli security officials have boasted of a “ChatGPT-like” arsenal used to monitor social media users for supporting or inciting terrorism. It was released in full force after Hamas’s bloody attack on October 7. Right-wing activists and politicians instructed police forces to arrest hundreds of Palestinians ... for social media-related offenses. Many had engaged in relatively low-level political speech, like posting verses from the Quran on WhatsApp. Hundreds of students with various legal statuses have been threatened with deportation on similar grounds in the U.S. this year. Recent high-profile cases have targeted those associated with student-led dissent against the Israeli military’s policies in Gaza. In some instances, the State Department has relied on informants, blacklists, and technology as simple as a screenshot. But the U.S. is in the process of activating a suite of algorithmic surveillance tools Israeli authorities have also used to monitor and criminalize online speech. In March, Secretary of State Marco Rubio announced the State Department was launching an AI-powered “Catch and Revoke” initiative to accelerate the cancellation of student visas. Algorithms would collect data from social media profiles, news outlets, and doxing sites to enforce the January 20 executive order targeting foreign nationals who threaten to “overthrow or replace the culture on which our constitutional Republic stands.”
Note: For more along these lines, read our concise summaries of news articles on AI and the erosion of civil liberties.
Have you heard of the idiom "You Can’t Lick a Badger Twice?" We haven't, either, because it doesn't exist — but Google's AI seemingly has. As netizens discovered this week that adding the word "meaning" to nonexistent folksy sayings is causing the AI to cook up invented explanations for them. "The idiom 'you can't lick a badger twice' means you can't trick or deceive someone a second time after they've been tricked once," Google's AI Overviews feature happily suggests. "It's a warning that if someone has already been deceived, they are unlikely to fall for the same trick again." There are countless other examples. We found, for instance, that Google's AI also claimed that the made-up expression "the bicycle eats first" is a "humorous idiom" and a "playful way of saying that one should prioritize their nutrition, particularly carbohydrates, to support their cycling efforts." The bizarre replies are the perfect distillation of one of AI's biggest flaws: rampant hallucinations. Large language model-based AIs have a long and troubled history of rattling off made-up facts and even gaslighting users into thinking they were wrong all along. And despite AI companies' extensive attempts to squash the bug, their models continue to hallucinate. Google's AI Overviews feature, which the company rolled out in May of last year, still has a strong tendency to hallucinate facts as well, making it far more of an irritating nuisance than a helpful research assistant for users.
Note: For more along these lines, read our concise summaries of news articles on AI and Big Tech.
In 2003 [Alexander Karp] – together with Peter Thiel and three others – founded a secretive tech company called Palantir. And some of the initial funding came from the investment arm of – wait for it – the CIA! The lesson that Karp and his co-author draw [in their book The Technological Republic: Hard Power, Soft Belief and the Future of the West] is that “a more intimate collaboration between the state and the technology sector, and a closer alignment of vision between the two, will be required if the United States and its allies are to maintain an advantage that will constrain our adversaries over the longer term. The preconditions for a durable peace often come only from a credible threat of war.” Or, to put it more dramatically, maybe the arrival of AI makes this our “Oppenheimer moment”. For those of us who have for decades been critical of tech companies, and who thought that the future for liberal democracy required that they be brought under democratic control, it’s an unsettling moment. If the AI technology that giant corporations largely own and control becomes an essential part of the national security apparatus, what happens to our concerns about fairness, diversity, equity and justice as these technologies are also deployed in “civilian” life? For some campaigners and critics, the reconceptualisation of AI as essential technology for national security will seem like an unmitigated disaster – Big Brother on steroids, with resistance being futile, if not criminal.
Note: Learn more about emerging warfare technology in our comprehensive Military-Intelligence Corruption Information Center. For more, read our concise summaries of news articles on AI and intelligence agency corruption.
Instagram has released a long-promised “reset” button to U.S. users that clears the algorithms it uses to recommend you photos and videos. TikTok offers a reset button, too. And with a little bit more effort, you can also force YouTube to start fresh with how it recommends what videos to play next. It means you now have the power to say goodbye to endless recycled dance moves, polarizing Trump posts, extreme fitness challenges, dramatic pet voice-overs, fruit-cutting tutorials, face-altering filters or whatever other else has taken over your feed like a zombie. I know some people love what their apps show them. But the reality is, none of us are really in charge of our social media experience anymore. Instead of just friends, family and the people you choose to follow, nowadays your feed or For You Page is filled with recommended content you never asked for, selected by artificial-intelligence algorithms. Their goal is to keep you hooked, often by showing you things you find outrageous or titillating — not joyful or calming. And we know from Meta whistleblower Frances Haugen and others that outrage algorithms can take a particular toll on young people. That’s one reason they’re offering a reset now: because they’re under pressure to give teens and families more control. So how does the algorithm go awry? It tries to get to know you by tracking every little thing you do. They’re even analyzing your “dwell time,” when you unconsciously scroll more slowly.
Note: Read about the developer who got permanently banned from Meta for developing a tool called “Unfollow Everything” that lets users, well, unfollow everything and restart their feeds fresh. For more along these lines, read our concise summaries of news articles on Big Tech and media manipulation.
Technology companies are having some early success selling artificial intelligence tools to police departments. Axon, widely recognized for its Taser devices and body cameras, was among the first companies to introduce AI specifically for the most common police task: report writing. Its tool, Draft One, generates police narratives directly from Axon’s bodycam audio. Currently, the AI is being piloted by 75 officers across several police departments. “The hours saved comes out to about 45 hours per police officer per month,” said Sergeant Robert Younger of the Fort Collins Police Department, an early adopter of the tool. Cassandra Burke Robertson, director of the Center for Professional Ethics at Case Western Reserve University School of Law, has reservations about AI in police reporting, especially when it comes to accuracy. “Generative AI programs are essentially predictive text tools. They can generate plausible text quickly, but the most plausible explanation is often not the correct explanation, especially in criminal investigations,” she said. In the courtroom, AI-generated police reports could introduce additional complications, especially when they rely solely on video footage rather than officer dictation. New Jersey-based lawyer Adam Rosenblum said “hallucinations” — instances when AI generates inaccurate or false information — that could distort context are another issue. Courts might need new standards ... before allowing the reports into evidence.
Note: For more along these lines, read our concise summaries of news articles on AI and police corruption.
On the sidelines of the International Institute for Strategic Studies’ annual Shangri-La Dialogue in June, US Indo-Pacific Command chief Navy Admiral Samuel Paparo colorfully described the US military’s contingency plan for a Chinese invasion of Taiwan as flooding the narrow Taiwan Strait between the two countries with swarms of thousands upon thousands of drones, by land, sea, and air, to delay a Chinese attack enough for the US and its allies to muster additional military assets. “I want to turn the Taiwan Strait into an unmanned hellscape using a number of classified capabilities,” Paparo said, “so that I can make their lives utterly miserable for a month, which buys me the time for the rest of everything.” China has a lot of drones and can make a lot more drones quickly, creating a likely advantage during a protracted conflict. This stands in contrast to American and Taiwanese forces, who do not have large inventories of drones. The Pentagon’s “hellscape” plan proposes that the US military make up for this growing gap by producing and deploying what amounts to a massive screen of autonomous drone swarms designed to confound enemy aircraft, provide guidance and targeting to allied missiles, knock out surface warships and landing craft, and generally create enough chaos to blunt (if not fully halt) a Chinese push across the Taiwan Strait. Planning a “hellscape" of hundreds of thousands of drones is one thing, but actually making it a reality is another.
Note: Learn more about warfare technology in our comprehensive Military-Intelligence Corruption Information Center. For more along these lines, see concise summaries of deeply revealing news articles on military corruption from reliable major media sources.
On July 16, the S&P 500 index, one of the most widely cited benchmarks in American capitalism, reached its highest-ever market value: $47 trillion. 1.4 percent of those companies were worth more than $16 trillion, the greatest concentration of capital in the smallest number of companies in the history of the U.S. stock market. The names are familiar: Microsoft, Apple, Amazon, Nvidia, Meta, Alphabet, and Tesla. All of them, too, have made giant bets on artificial intelligence. For all their similarities, these trillion-dollar-plus companies have been grouped together under a single banner: the Magnificent Seven. In the past month, though, these giants of the U.S. economy have been faltering. A recent rout led to a collapse of $2.6 trillion in their market value. Earlier this year, Goldman Sachs issued a deeply skeptical report on the industry, calling it too expensive, too clunky, and just simply not as useful as it has been chalked up to be. “There’s not a single thing that this is being used for that’s cost-effective at this point,” Jim Covello, an influential Goldman analyst, said on a company podcast. AI is not going away, and it will surely become more sophisticated. This explains why, even with the tempering of the AI-investment thesis, these companies are still absolutely massive. When you talk with Silicon Valley CEOs, they love to roll their eyes at their East Coast skeptics. Banks, especially, are too cautious, too concerned with short-term goals, too myopic to imagine another world.
Note: For more along these lines, see concise summaries of deeply revealing news articles on AI and corporate corruption from reliable major media sources.
Emotion artificial intelligence uses biological signals such as vocal tone, facial expressions and data from wearable devices as well as text and how people use their computers, promising to detect and predict how someone is feeling. Over 50% of large employers in the U.S. use emotion AI aiming to infer employees’ internal states, a practice that grew during the COVID-19 pandemic. For example, call centers monitor what their operators say and their tone of voice. We wondered what workers think about these technologies. My collaborators Shanley Corvite, Kat Roemmich, Tillie Ilana Rosenberg and I conducted a survey. 51% of participants expressed concerns about privacy, 36% noted the potential for incorrect inferences employers would accept at face value, and 33% expressed concern that emotion AI-generated inferences could be used to make unjust employment decisions. Despite emotion AI’s claimed goals to infer and improve workers’ well-being in the workplace, its use can lead to the opposite effect: well-being diminished due to a loss of privacy. On concerns that emotional surveillance could jeopardize their job, a participant with a diagnosed mental health condition said: “They could decide that I am no longer a good fit at work and fire me. Decide I’m not capable enough and not give a raise, or think I’m not working enough.” Participants ... said they were afraid of the dynamic they would have with employers if emotion AI were integrated into their workplace.
Note: The above article was written by Nazanin Andalibi at the University of Michigan. For more along these lines, see concise summaries of deeply revealing news articles on corporate corruption and the disappearance of privacy from reliable major media sources.
The $118bn bipartisan immigration bill that the US Senate introduced on Sunday is already facing steep opposition. The 370-page measure, which also would provide additional aid to Israel and Ukraine, has drawn the ire of both Democrats and Republicans over its proposed asylum and border laws. But privacy, immigration and digital liberties experts are also concerned over another aspect of the bill: more than $400m in funding for additional border surveillance and data-gathering tools. The lion’s share of that funding will go to two main tools: $170m for additional autonomous surveillance towers and $204m for “expenses related to the analysis of DNA samples”, which includes those collected from migrants detained by border patrol. The bill describes autonomous surveillance towers as ones that “utilize sensors, onboard computing, and artificial intelligence to identify items of interest that would otherwise be manually identified by personnel”. The rest of the funding for border surveillance ... includes $47.5m for mobile video surveillance systems and drones and $25m for “familial DNA testing”. The bill also includes $25m in funding for “subterranean detection capabilities” and $10m to acquire data from unmanned surface vehicles or autonomous boats. As of early January, CBP had deployed 396 surveillance towers along the US-Mexico border, according to the Electronic Frontier Foundation (EFF).
Note: Read more about the secret history of facial recognition technology and undeniable evidence indicating these tools do much more harm than good. For more along these lines, see concise summaries of deeply revealing news articles on government corruption and the disappearance of privacy from reliable major media sources.
Looking Glass Factory, a company based in the Greenpoint neighborhood of Brooklyn, New York, revealed its latest consumer device: a slim, holographic picture frame that turns photos taken on iPhones into 3D displays. Looking Glass received $2.54 million of “technology development” funding from In-Q-Tel, the venture capital arm of the CIA, from April 2020 to March 2021 and a $50,000 Small Business Innovation Research award from the U.S. Air Force in November 2021 to “revolutionize 3D/virtual reality visualization.” Across the various branches of the military and intelligence community, contract records show a rush to jump on holographic display technology, augmented reality, and virtual reality display systems as the latest trend. Critics argue that the technology isn’t quite ready for prime time, and that the urgency to adopt it reflects the Pentagon’s penchant for high-priced, high-tech contracts based on the latest fad in warfighting. Military interest in holographic imaging, in particular, has grown rapidly in recent years. Military planners in China and the U.S. have touted holographic technology to project images “to incite fear in soldiers on a battlefield.” Other uses involve the creation of three-dimensional maps of villages of specific buildings and to analyze blast forensics. Palmer Luckey, who founded the technology startup Anduril Industries ... has received secretive Air Force contracts to develop next-generation artificial intelligence capabilities under the so-called Project Maven initiative.
Note: For more along these lines, see concise summaries of deeply revealing news articles on intelligence agency corruption from reliable major media sources.
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