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Four Corners - Season Episode 21 -Click to Kill: The AI War Machine englishsub fullmovie⚡️🍿 Secret Engagement
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00:00This program contains graphic images of victims of war.
00:20February 27th, 2026.
00:24Donald Trump's war room.
00:26At 3.38 Eastern time, the president orders a strike on Iran.
00:32As dawn crept up across the Central Command AOR, the sky surged to light.
00:39More than 100 aircraft launched from land, sea, fighters, tankers, airborne early warning, electronic attack, bombers from the states and
00:50unmanned platforms forming a single synchronized wave.
00:56The attackers send back positions, images and radio signals.
01:05Which are instantly processed and analyzed by artificial intelligence.
01:13Within hours, Iran's supreme leader, Ayatollah Aliyah Khamenei, is killed by an Israeli strike.
01:23The United States and its partners have launched Operation Epic Fury, one of the largest, most complex, most overwhelming military
01:34offensives the world has ever seen.
01:37Nobody's seen anything like it.
01:40There's never been a military like we possess and, frankly, there's nobody even close, but we are now using that
01:48military for good.
01:51The strike against Khamenei was successful because the Israelis knew exactly where to find him.
01:57In the preceding months, artificial intelligence had also been deployed to analyze vast troves of satellite, signals and human intelligence.
02:07The strikes against Iran and, before that, Venezuela, are just the latest and most vivid demonstration of how we're in
02:15the midst of a once-in-a-generation transformation of the technology of war.
02:21It is an inflection point. It's going to change our processes. It's going to change the way we fight our
02:25operating systems.
02:26So you're watching all that play out. And whoever figures it out first will have an advantage. This is about
02:33winning, right? Winning. We can't forget our job is to win.
02:39The transformation has been building for decades as computers became more powerful, giving rise to AI and more compact, allowing
02:49for swarms of lethal drones.
02:54This is a film about the development of these new war machines and how they're already being used by Israel,
03:02Ukraine and by the United States.
03:06Will this new technology make war more precise? Reducing collateral damage and even preventing conflict altogether by deterrence?
03:16Or might it simply make wars cheaper, more frequent and ever more brutal?
03:23When you rely on AI, you need less people to ground you. And people can tell themselves a beautiful story
03:30on the most precise war ever.
03:33And they don't have to speak to anyone that will efface them with the fact that they're just killing families
03:38and with no actual solution in the near future.
03:59Bavaria, southern Germany.
04:047,000 US and NATO troops are preparing to act in case Russia invades a NATO country.
04:14They're racing to learn how to use this new technology on the battlefield.
04:201, 2, 9, 9, 0.
04:221, 2, 9, 9, 0.
04:231, 2, 9, 0, 2, 9, 0.
04:31This is the headquarters of an army formation of about a thousand soldiers.
04:38Sir, there is no change to combat power, location or arraignment of our forces.
04:44There it is.
04:44All right, cool. Let's have a lock-tight plan to get all our replacements and our vehicles out to the
04:50front.
04:50So, three...
04:51Ten miles away, more NATO troops acting as an advancing enemy.
04:58The big picture of what we're doing here is we're exercising our brigades and our battalion's ability to do a
05:04combined arms fight against an enemy that has near or peer threats against us.
05:10We're starting to see the indicators and warnings that the enemy is about to try to breach, break through our
05:16lines using assault, maneuver, fires.
05:28You are experiencing gas non-persistent for four-hour duration.
05:33If you look at any of the exercises, any of the experimentation that we're doing, clearly it's leading to make
05:39sure that we have the right capability, in particular along the eastern flank.
05:49This is the command center for NATO and the U.S. Army.
05:53Any land war against Russia will be orchestrated from here.
05:58The commanding general is Chris Donoghue.
06:01He led much of the technological innovation in the U.S. Army and is now in charge of all U
06:07.S. soldiers in Europe.
06:09It's our job to make sure that Europe and everyone that's part of Europe remains safe, remains secure, and that
06:17we live up to what NATO expects us all to do.
06:21Donoghue was an early adopter of the idea that wars can be won or lost not only because of the
06:27strength of the armies, but also because of how much information can be gathered and analyzed.
06:33If you can truly harness the right data, have the right processes, you can really come up with a distinct
06:40advantage.
06:40And what is that advantage?
06:42You have to outthink, out decide, out act, and then do that multiple times.
06:51What's innovative is that this command center has access to all information from the battlefield through a single network of
06:58computers, called MAVEN, that supports all U.S. and NATO operations.
07:04These screens deliver the picture through MAVEN smart systems, which takes in multiple different streams of data that operators are
07:13looking at and analyzing and giving me the recommendations or their understanding of what they've seen on the battlefield.
07:21I think the first thing with MAVEN smart systems is it gives us the ability to take classified of all
07:28type, unclassified, and then commercial data, and you can aggregate it all together to help you make all the decisions
07:36that you have to in warfare.
07:40Underpinning MAVEN is artificial intelligence.
07:44MAVEN smart systems is a battle command system tool.
07:48We're starting now to use a lot of different machine learning or computer vision models to help, especially with imagery
07:55or videos.
07:56For example, you can have a computer vision model that's looking specifically for tanks.
08:03To do that, you have to take thousands of images of tanks and you train the model to look for
08:08those.
08:09So what you do is you take a picture of a tank and you draw a box around the tank
08:14and you tell the computer, this is a tank.
08:16And you do that a thousand times.
08:19Now, when you feed an image to that model, it's going to tell you, yes, this is a tank or
08:25no, it's not.
08:26Once the computer has flagged an image where it suspects it's detected a tank, for instance, we don't just action
08:34that immediately, right?
08:35That's when we would take it to our human analysts and say, hey, can you confirm or deny that this
08:39was properly classified?
08:41What the AI is doing, it's not replacing the human, but it's enabling them to do their job faster so
08:46we can process more and more data and identify targets quicker and solve problems faster.
08:57AI is helping glean what's important, what's useful, what's not useful, so I can say friendly or foe or target
09:06or not.
09:07The enemy has the same capability, so I have to be quicker, I have to be faster, otherwise I'm at
09:13risk for becoming that target.
09:20The revolution in how wars are ford has come about not only with the processing of data, but also with
09:27small unmanned vehicles, drones.
09:36So this drone, you send up, this is your eyes in the sky, to detect everybody around you, early warning,
09:42to see what's going on on the battlefield.
09:46And in addition, FPV, first-person view drones, can carry bombs.
09:52The FPV drones, that's your strike drone, that's what's going to take everything out.
09:57Okay, I think they're about to launch.
10:05Two BMPs, like 200 meters for a month. You can hear them driving.
10:09The battlefield makes me move quicker and understand quicker and make decisions quicker.
10:17I hit the rear BMP. Add one to the scoreboard.
10:22The enemy is currently moving about a click every two minutes. Over.
10:28I just spotted a vehicle in the wood line.
10:31What's the grid?
10:32Zero one.
10:32What you see is now a completely digitally data-driven unit that had all these new forms of mass, drones,
10:41unmanned systems,
10:42in there to make them as able to find the enemy, hide from the enemy, see the enemy, and kill
10:48the enemy.
10:49Artillery.
10:50Artillery.
10:50Artillery.
10:57This year, Sergeant Cole has noticed that the Ukrainians are also putting AI into drones, so they can fly themselves
11:04to targets.
11:07It's just absolutely insane, what they're doing.
11:10The targeting software, it'll detect, like, that's a person, that's a truck.
11:14The hard part is to program it to actually fly on its own and then hit something.
11:19You know, that comes in with, like, morals and ethics, like, do we want something to decide on its own
11:26to kill something?
11:28I mean, what's your view of that?
11:30I mean, if it flies completely autonomously and kills stuff, I don't necessarily agree with it.
11:42Completely autonomous drones flying around, killing people, that's just insanity.
11:47That's stuff out of nightmares.
11:51All right, I've got to come land.
11:53All right, I've got to go ahead.
11:54It's anyone's guess how these technologies play out in future wars.
11:59But clues already exist in Israel and Ukraine, where the technology is already in use.
12:12The trajectory of this new war machine begins in about 2016, when the technology of war was limited mostly to
12:21hardware, like aircraft carriers.
12:24Artillery and tanks.
12:28But already there were experiments in data processing, especially in Israel, a nation that promoted itself as a tech superpower.
12:40Today, our biggest export is technology, Israeli technology, which powers the world's computers, cell phones, cars, and so much more.
12:51The future belongs to those who innovate, and this is why the future belongs to countries like Israel.
13:01Nearly 50 years after Israel's occupation of the West Bank and Gaza, some Palestinians, hemmed in by the newly built
13:10separation wall, turned to lone wolf attacks.
13:15A few years later, they were fighting against terror attacks.
13:16A few years ago, at the central bus station in Jerusalem, one terrorist carried out an attack against a security
13:21guard that was stabbed.
13:23I've been trapped outside the entrance. At the moment, the area is still closed off. We've confirmed it was a
13:27terrorist attack.
13:29These attacks were different to the previous waves,
13:33as they weren't organised by a militia organisation.
13:37Instead, single Palestinians skirted round the security controls.
13:45You just had lone individuals, usually very young.
13:48These people usually just took a knife or even a screwdriver
13:51to attack soldiers in checkpoints
13:53or just suddenly batten people on the street
13:57or driving cars into people.
14:01The challenge was to try to figure out
14:03who's the random person that will wake up today,
14:06pick up a knife and stab someone.
14:11These witnesses are intelligence analysts
14:14who were called up to work for the Israeli army.
14:18They don't want to reveal their identities
14:20and their voices have been digitally altered.
14:23Their job was to monitor security threats in the West Bank.
14:29I was recruited to the army in the late 2010s.
14:33In the theoretical framework that I worked under,
14:37every Palestinian is a suspect.
14:41When I joined the army,
14:43it was in the midst of a technological transformation
14:47of trying to adopt new technologies.
14:52Israel had a special advantage in tracking the threat.
14:56It controlled Palestinian communications.
15:01Israel has basically unlimited data
15:04because all stellar data of the West Bank
15:08goes through Israeli technological centres.
15:13The whole network is basically in Israel's hands.
15:17All phone calls that are being made
15:20through the regular network in the West Bank in Gaza,
15:23they would all go to a big data base, sort of archive.
15:33These lone wolf attacks,
15:35they naturally encourage the army to think in terms of big data.
15:40The traditional approach of just, you know,
15:42trying to infiltrate a terrorist organisation,
15:45this wouldn't really work for people
15:47to just spontaneously decide to attack Israelis.
15:52At first, Israel tried simple word search
15:55to catch lone wolf militants before they attacked.
16:00We were really doing the first steps of, for example,
16:04working with telephone calls
16:05on how to identify a relevant telephone call
16:08according to keywords.
16:12They kind of figured out that many people
16:15who'd go on these lone wolf things
16:16send text message, basically.
16:19Beforehand, some kind of declaration of intent.
16:24Certain words, whenever they are reported in the system,
16:28these words would trigger some sort of alarm.
16:33But soon they experimented with data patterns
16:36that would predict who might merely be tempted to become a radical.
16:41You want to create a usable data set of possible terrorists.
16:46So the general method to do it is specify as many attributes as we can.
16:53So age, gender, and try to find patterns in the data
17:00that can be used to squeeze it.
17:03Thousands of individual Palestinians were categorised by dozens of attributes,
17:09and every attribute was given a value.
17:12A computer then calculated how likely each person was to turn violent.
17:18The initial algorithms created grades as to predictability to be terrorists for 1 to 10.
17:30You're a 7.8 terrorist, and here's the group of potential terrorists.
17:35Now let's surveil them on a daily basis to see which of them is actually planning to do terror.
17:46At some point, these attacks are reduced significantly.
17:52It was pretty efficient.
17:55I remember that I was almost shocked to see how efficient it was.
17:59They did feeling quite emboldened by this.
18:03But in the last year, in the last year,
18:06we managed to increase from 400 potential attacks.
18:11It's a military activity.
18:13It's a military activity that is based on the biggest intelligence,
18:17the biggest challenges of the world.
18:18There's a lot built there.
18:23Although Israel's military leadership was convinced
18:26that the decline in attacks was due to prediction technology,
18:31human rights groups reckoned the waves of violence had always ebbed and flowed.
18:37And they accused Israel of an egregious invasion
18:41of the privacy of millions of Palestinians.
18:47To me, it was very clear that this total control
18:50is precisely what enables the political process to be frozen.
18:56Clearly, if we have that total control,
18:58then there's no motivation to change anything.
19:02We really thought that technology has solved most of our problems.
19:07While Israel concentrated more of its intelligence resources on technology,
19:12they neglected the role of human sources,
19:15particularly in the Gaza Strip.
19:19This had been an essential part of Israeli intelligence in the past.
19:25And it would prove to be a catastrophic error
19:28in the lead-up to the Hamas attack of October 7th, 2023.
19:43The next chapter in the story of warfare technology began when Russian tanks rolled into Ukraine in February 2022.
20:14The odds were stacked against Ukraine, who had 250,000 soldiers,
20:20but stood against an army of about a minute.
20:25The challenge that Zelensky had in fighting back was working out which Russian targets to hit.
20:34From the command centre in Germany,
20:37NATO offered assistance in the form of MAVEN smart systems,
20:42though the US military won't talk about what help was given.
20:47But the technology behind MAVEN smart systems was created by a controversial company called Palantir.
20:56Their CEO was and is a maverick skier called Alex Karp.
21:01Welcome to our...
21:03Here he is, speaking to investors in the early months of the Ukraine war.
21:08Palantir, for example, we are a company to thrive in good times and we thrive in bad times.
21:18We are going to continue supplying the world's most important products
21:21to the most interesting, creative and effectual people in the world.
21:25Palantir's products are on the absolute front line and you see them in the news every day.
21:30Palantir's early investor was the CIA
21:33and they have contracts with global national security organisations, including US immigration.
21:39Their next customer was to be Zelensky.
21:42The invitation came from the Ukrainians.
21:45So Alex Karp, our chief executive and founder, and I travelled to Kyiv May, June of 2022.
21:57We turned up at the appointed place to meet Zelensky.
22:02I think Zelensky understood that the biggest challenge the Ukrainians faced was one of mass and numbers.
22:08They were outnumbered by the Russians and also outgunned.
22:14They had more armaments, more industrial capacity than Ukrainians did.
22:18And so the only way of correcting that imbalance was with technology.
22:25And Zelensky explained that he wanted us to come and help the Ukrainian war effort
22:28and that he believed that Ukraine was going to be the research and development laboratory for conflict over the coming
22:36years.
22:38So, of course, Alex said yes, and then it fell to me and others on the Palantir team to turn
22:45that into a reality.
22:47We provided them with a software platform called Foundry and at its core, it's a data integration platform.
22:55So that's to say it enables our customers to bring together data, information from really any source of any type,
23:03any format, any scale,
23:05bring that data together, clean it, harmonize it and make it useful.
23:10In military technology terms, in a war like the one that Ukraine faced, there were many, many more targets,
23:17many, many more things to shoot at than they had things to shoot with.
23:21So the big challenge was not precision, it was prioritization.
23:26So you can identify a barn in a field in Ukraine, but you're not going to be able to tell
23:32from the satellite image
23:33that that barn might be the command and control center for an important part of Russian forces.
23:39And for that, you might need to layer on another kind of data, for example, radio frequencies, signals intelligence.
23:46So if you combine satellite imagery and signals intelligence, you can tell where something is and what it is.
23:53And that allows you to then, with the precision munitions that exist today, destroy it with pinpoint accuracy.
24:04In November 2022, nine months after the war began, ChatGPT burst onto the scene, showcasing the power of a new
24:13technology, large language models.
24:17Palantir and the Ukrainians were quick to harness the underlying technical breakthrough.
24:22There might be thousands or even tens of thousands of different data sources that need to be monitored at any
24:28given time on a battlefield.
24:30And analysts traditionally would have had to review each of those data sources individually and manually.
24:38Large language models, as we all know, can synthesize information very quickly and can draw out important inferences, links or
24:48key points, depending on what you're looking for.
24:51And I think that did play a critical role in those early phases of the war.
24:55Isn't there something difficult about running a company that's speeding up the process of killing people?
25:01Deeply morally complex, and it's something that we wrestle with every day.
25:06But ultimately, I think ensuring that our armed forces have the most effective technology is actually the best way of
25:13preserving peace and therefore saving lives.
25:21But AI wasn't the only technology to take a huge leap forward in Ukraine.
25:28Also fast-tracked was the development of unmanned vehicles.
25:32Two Ukrainian soldiers describe how drones have transformed the battlefield.
25:46They may have started as tools of surveillance, but soon became deadly weapons.
25:54One of the major mediums.
26:00Well, it's already the FPS-1 drone, but with skid.
26:04It works like a bomber.
26:08With a wheelbarrow.
26:09There is the turning camera.
26:11And skid.
26:13Well, skid.
26:14He has a power diagram and skid.
26:16Well, skid about like such weapons.
26:22By 2022, it has been time to deliver the war.
26:24Each side had more than a million drones.
27:01With a range of up to 30 kilometers, they transformed the front line.
27:36Ukraine demonstrated that the fundamental character of war has changed, with drones killing hundreds of thousands of soldiers.
27:49Because now in the middle of every 3-5 minutes, on the front line, there is a minimum one drone.
28:01It's a feeling when they are constantly waiting for you.
28:05It's a moral pressure, because you understand, that when you go and what you don't have to do,
28:10then early or early you'll find you.
28:17It will be gone.
28:22These new technologies of AI and drones had allowed a smaller army to hold ground,
28:29albeit in a brutal and intractable fight.
28:33But soon these technologies would be used in Gaza, with devastating consequences.
28:51The next development in the new war machine began when hundreds of Hamas operatives breached Israel's high-tech border at
29:00dawn on October 7th, 2023.
29:05Social media quickly revealed the brutality of the attack.
29:29I was in my apartment, and to resume, just me and one of my fat mates.
29:36And I got up in the morning from other sirens.
29:45Like almost every Israeli, I have family closer to the border with Gaza.
29:50And that these moments, there were actual fear for their lives.
29:53I didn't know what's going on with them.
29:59For me, and I guess for many other people, it was more like from the collected level of, you know,
30:04if people like me that were attacked, it could have been me.
30:14In a matter of hours, 1,200 were killed.
30:24251 hostages were taken to Gaza.
30:30The Israeli military and political response was immediate.
30:37The Israeli military, we were in war.
30:43We are in war.
30:43Not in law or in laws, we have battles.
30:48And in war.
30:48I was able to carry out a wide range of attacks
30:51and to save the war in peace and peace
30:54that the enemy didn't know.
31:01The three intelligence analysts,
31:03who were witness to the tech development around lone wolves,
31:07now returned to duty.
31:10Once you arrive over there to the unit,
31:12I mean, of course, you sit in front of a computer,
31:14it's not as if you're able to stop the attack from there,
31:16but you can't feel like, okay, okay, I do my part.
31:21The whole atmosphere was, like, pretty insane,
31:24and I don't know, no one really knew what they were doing, I suppose.
31:29Like, originally, they kind of thought they could, like,
31:31wipe out from us in the...
31:32because it's true, like, the space of, like, a few days,
31:35and then we just have, like, the easy win, supposedly,
31:38and I get on with our lives.
31:40In the first few days of the war,
31:43the biggest tasks were creating what's called
31:46targets.
31:48The creation of targets was a challenge
31:50because the Israeli government said
31:52it followed international law,
31:55in which a strike would be prohibited
31:57when the expected incidental loss of civilian life
32:00is excessive in relation to the direct military advantage.
32:07There were complaints that there aren't enough targets
32:09in the Gaza Strip, even before the war.
32:12People high-up were very content with the amount of targets
32:14that were being produced.
32:16They set up this thing called the...
32:18the tariff factory.
32:21Then they were like, OK, we just need to make tariffs.
32:24Just finding locations and finding people, basically,
32:28to assassinate.
32:42The Israeli Air Force posted multiple videos of their strikes,
32:47and the numbers of their targets, on their telegram channel.
32:51There was an urge for extreme measures.
32:55So the general belief was that human work will not do
33:00to create the number of targets required.
33:03So the convenient solution was to use non-human ways of creating targets,
33:09which is namely AI.
33:16Computers created lists of locations and people that were passed to target rooms.
33:23There, other soldiers checked the targets were correct,
33:27assessed the collateral damage.
33:29And it's reported that sometimes they had less than a minute to make this decision.
33:35At early on, it was very clear that anything that has any connection with Hamas,
33:41and that includes also people who are not part of the military wing,
33:44but also part of the political wings.
33:46Anyone who has a connection to Hamas is a legitimate target.
34:17How did the Israeli army generate?
34:20So many targets.
34:23In the preceding years, the Israelis had built targeting systems
34:27that had been derived from the software used to prevent lone wolf attacks.
34:36At some point, we were using an AI algorithm
34:39that gets a data set of people who are approved Hamas members
34:43and looks for people with similar attributes
34:47in general data sets of the entire Palestinian population.
34:51There were a number of different systems.
34:54One ascribed a threat probability to any individual between one and a hundred.
34:59Anyone over a threshold, say 90, could be targeted.
35:14If your requirement is to kill in numbers,
35:17you want to kill an impressive number of people.
35:21AI can give you theoretically an endless number
35:26as long as you're willing to give up on the precision.
35:31Within three weeks, Israel announced it had attacked 11,000 targets.
35:38And the Gaza Health Ministry, controlled by Hamas,
35:42had reported 8,800 dead and 22,000 injured.
35:49It was perfectly clear that we want this space of targeting
35:54with this level of collateral damage.
36:00Allahu Akbar!
36:04But in the end, what drove the high number of casualties
36:08was not technology, but political and military choices.
36:12In the previous rounds of violence,
36:15the number of civilian casualties deemed acceptable
36:18by the Israeli military had been much lower.
36:22A different decision was made for Gaza in 2023.
36:29They have this decision at the source of the war
36:32that you can bomb any commerce operative anywhere he is
36:35and take funny people along with him.
36:38Basically assassinating people in the homes
36:41just means that you know that people have killed
36:44wives, children.
36:50Ition Bechiki took the licence to kill a significant number
36:55of civilian casualties along with a target.
36:59Basically, you're right, yeah, he's there, boom.
37:04These intelligence analysts accuse Israel
37:07of allowing collateral damage of 20 civilians
37:10for any approved target.
37:12But they go further.
37:15There are actual numbers in Israeli military doctrine
37:19for each level of collateral damage which is allowed.
37:24I think they raised the base level
37:26and then for especially important targets,
37:28it could be even higher.
37:30It could be even higher.
37:40On the 2nd of December, 2023,
37:43the Israelis appeared to reinforce the claim.
37:46They launched more than 400 strikes
37:50and one on a housing block in Gaza City
37:54where they said they'd eliminated a Hamas commander
37:57who'd helped plan the October 7th massacre.
38:20I remember there was this operation
38:23where other innocent people were killed.
38:25I listened to the call beforehand of the guy saying,
38:28you know, I'm in my family home
38:30and my whole family are here
38:31and I'm worried that we will get bombed
38:33and I finally would die.
38:36And then I'm just sitting there,
38:38it's like 4 in the morning waiting for
38:39like the fucking planes to bomb.
38:43This kind of bureaucratic apparatus takes
38:47like the personal responsibility of people
38:50and you don't see the face of people
38:52of you like killing, you know.
38:54But the weird thing is that
38:55I did hear these people's voices,
38:57you know, and I was like,
39:00it's horrible to say this, but you know,
39:02I heard them crying when the relatives were killed.
39:09I think a lot of what technology gives us
39:12is that it blurs the reality for us
39:16to be able to not be completely responsible
39:19for what's going on.
39:23The decision was just to bomb and bomb and bomb.
39:26If you want this space of bombings
39:28and still make them look legal,
39:31let's call it that,
39:33then you need at least this tool
39:35that does the combination of data
39:39to reach the legal threshold
39:42for what is a legitimate target.
39:43It's hard to pile up.
39:46In this sense,
39:47this scale of technology is more of an excuse.
39:52All three intelligence analysts
39:55are no longer on duty in the Israeli army.
40:00By January 2026,
40:02an Israeli official briefed newspapers
40:05that they agreed there had been more than 70,000 deaths
40:08in strikes in the two years of the war.
40:13in the U.S.
40:14Organisations including Amnesty International,
40:16Bet Salem and parts of the U.N.
40:18now accuse Israel of committing war crimes
40:20by, amongst other things,
40:22the disproportionate attacks on civilians
40:24in densely populated areas.
40:28The Israel Defence Force says the IDF
40:31does not use an AI system that identifies terrorist operatives
40:35or tries to predict whether a person is a terrorist.
40:38Information systems are merely tools for analysts
40:41in the target identification process.
40:44The IDF operates in accordance with international law.
40:48Each strike undergoes an individualised case-by-case assessment
40:51evaluating anticipated military advantage
40:54against expected incidental civilian harm.
40:58Proportionality decisions are made based
41:00on the information available at the time of decision
41:02and not in hindsight.
41:04The IDF has also said
41:06that the 70,000 deaths figure
41:08does not reflect official IDF data.
41:14Whatever the lessons of the tactics in Gaza and Ukraine,
41:18the race for warfare technology shows no sign of slowing down.
41:22Thank you!
41:23In January 2026,
41:25the U.S. Secretary of War, Pete Hegseth,
41:28was fully committed.
41:30Simply put, the United States must win
41:32the strategic competition
41:34for 21st century technological supremacy.
41:38We must ensure that America's military AI dominance,
41:42so that no adversary can exploit that same technology
41:45to hold our national security interests
41:48or our citizens at risk.
41:51America first in every domain.
41:55In short, we will win this race
41:57by becoming an AI first war-fighting force across all domains.
42:02The rest of the world is following suit.
42:06Western governments have entered into hefty military contracts
42:09with American-based technology companies
42:12like Palantir, Google, Microsoft and Amazon.
42:15Making them ever more dependent
42:17on a few corporations
42:18for the next generation of military technology.
42:22I think it's incredibly important
42:24if we want to maintain our way of life,
42:26if we want to remain advanced first world economies,
42:30if we want to keep our value system,
42:33that we in the West, broadly defined,
42:35have the dominant militaries.
42:37We have to maintain that technological advantage.
42:39And if we are in an arms race,
42:41that means we have to win it.
42:45As drones replace missiles and computers replace men,
42:49it seems that wars have not become cleaner,
42:51more surgical and quicker.
42:53If anything,
42:54the costs in money and political capital
42:56of entering wars has declined.
42:59And they're likely to become more frequent.
43:03So now is the moment for citizens and their governments
43:06to decide whether,
43:07just like for nuclear and biological weapons,
43:10we need international agreements
43:12to control the new warfare.
43:15I got to see, like,
43:17the advantages that AI gives
43:19a furious before the rest of the public,
43:22and there's zero good value given by that.
43:26It only creates more dust.
43:29It only gives opportunity for deadly wars.
43:32To be fair, I really think it's a mistake.
43:35It just creates more dust and more wars.
43:44Any war means that they reduce the growth of technology,
43:51change the growth of innovation and innovation.
43:56You know,
43:59First to use these innovations, this is the highest level.
44:04Ready to work!
44:37First to use these innovations, this is the highest level.
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