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00:02February 27th, 2026.
00:05Donald Trump's war room.
00:08At 3.38 Eastern time, the president orders a strike on Iran.
00:14As dawn crept up across the Central Command AOR,
00:18the sky surged to light.
00:21More than 100 aircraft launched from land, sea.
00:25Fighters, tankers, airborne early warning, electronic attack.
00:29Bombers from the states and unmanned platforms
00:32forming a single, synchronised wave.
00:38The attackers send back positions, images and radio signals.
00:47Which are instantly processed and analysed by artificial intelligence.
00:54Within hours, Iran's supreme leader, Ayatollah Aliyah Khamenei,
00:59is killed by an Israeli strike.
01:04The United States and its partners have launched Operation Epic Fury.
01:10One of the largest, most complex, most overwhelming military offensives
01:16the world has ever seen.
01:18Nobody's seen anything like it.
01:22There's never been a military like we possess.
01:25And frankly, there's nobody even close, but we are now using that military for good.
01:32The strike against Khamenei was successful because the Israelis knew exactly where to find him.
01:38In the preceding months, artificial intelligence had also been deployed
01:43to analyse vast troves of satellite, signals and human intelligence.
01:49The strikes against Iran, and before that Venezuela, are just the latest and most vivid demonstration
01:55of how we're in the midst of a once in a generation transformation of the technology of war.
02:02is an inflection point. It's going to change our processes.
02:05It's going to change the way we fight our operating systems.
02:08So you're watching all that play out.
02:10And whoever figures it out first, will have an advantage.
02:14This is about winning, right? Winning.
02:17We can't forget our job is to win.
02:20The transformation has been building for decades,
02:23as computers became more powerful, giving rise to AI.
02:29And more compact, allowing for swarms of lethal drones.
02:36This is a film about the development of these new war machines,
02:40and how they're already being used by Israel, Ukraine and by the United States.
02:47The most important thing is to ensure that we in the West, broadly defined,
02:52have the most powerful versions of this technology and continue to do so.
02:57Will this new technology make war more precise, reducing collateral damage,
03:04and even preventing conflict altogether by deterrence?
03:08Or might it simply make wars cheaper, more frequent, and ever more brutal?
03:15When you rely on AI, you need less people to ground you.
03:18And people can tell themselves a beautiful story on the most precise war ever.
03:25And they don't have to speak to anyone that will face them with the fact that
03:28they're just killing families and with no actual solution in the near future.
03:51Bavaria, southern Germany.
03:567,000 US and NATO troops are preparing to act in case Russia invades a NATO country.
04:06They're racing to learn how to use this new technology on the battlefield.
04:111, 2, 9, 9, 0.
04:131, 2, 9, 9, 0.
04:161, 2, 9, 9, 0.
04:23This is the headquarters of an army formation of about a thousand soldiers.
04:28You don't know where you're going to break.
04:30Sir, there's no change to combat power, location, or arraignment of our forces.
04:36There it is.
04:36All right, cool.
04:37Let's have a lock type plan to get all our replacements and our vehicles out to the front.
04:4310 miles away, more NATO troops acting as an advancing enemy.
04:50The big picture of what we're doing here is we're exercising our brigades and our battalion's ability to do a
04:56combined arms fight against an enemy that has near or peer threats against us.
05:02We're starting to see the indicators and warnings that the enemy is about to try to breach, break through our
05:07lines using assault maneuver fires.
05:20You are experiencing gas, non-persistent for four-hour duration.
05:27We have a chemical attack, so let me, hey, uh, tape, I need tape, I need tape out.
05:31If you look at any of the exercises, any of the experimentation that we're doing, clearly it's leading to make
05:37sure that we have the right capability, in particular along the eastern flank.
05:47This is the command center for NATO and the U.S. Army.
05:51Any land war against Russia will be orchestrated from here.
05:56The commanding general is Chris Donoghue.
05:59He led much of the technological innovation in the U.S. Army and is now in charge of all U
06:05.S. soldiers in Europe.
06:07It's our job to make sure that Europe and everyone that's part of Europe remains safe, remains secure, and that
06:15we live up to what NATO expects us all to do.
06:19Donoghue was an early adopter of the idea that wars can be won or lost, not only because of the
06:25strength of the armies, but also because of how much information can be gathered and analyzed.
06:31If you can truly harness the right data, have the right processes, you can really come up with a distinct
06:38advantage.
06:39And what is that advantage?
06:40You have to outthink, out decide, out act, and then do that multiple times.
06:49What's innovative is that this command center has access to all information from the battlefield through a single network of
06:56computers, called MAVEN, that supports all U.S. and NATO operations.
07:03On MSS, put something on there, keep people out of Hawk Hill.
07:09These screens deliver the picture through MAVEN Smart Systems, which takes in multiple different streams of data that operators are
07:18looking at and analyzing and giving me the recommendations or their understanding of what they've seen on the battlefield.
07:26I think the first thing with MAVEN Smart Systems is, it gives us the ability to take classified of all
07:33type, unclassified, and then commercial data, and you can aggregate it all together to help you make all the decisions
07:40that you have to in warfare.
07:45Underpinning MAVEN is artificial intelligence.
07:49MAVEN Smart Systems is a battle command system tool.
07:53We're starting now to use a lot of different machine learning or computer vision models to help, especially with imagery
08:00or videos.
08:01For example, you can have a computer vision model that's looking specifically for tanks.
08:08To do that, you have to take thousands of images of tanks, and you train the model to look for
08:13those.
08:14So what you do is you take a picture of a tank, and you draw a box around the tank,
08:19and you tell the computer, this is a tank.
08:21And you do that 1,000 times.
08:24Now, when you feed an image to that model, it's going to tell you, yes, this is a tank, or
08:30no, it's not.
08:31Once the computer has flagged an image where it suspects it's detected a tank, for instance, we don't just action
08:39that immediately, right?
08:40That's when we would take it to our human analysts and say, hey, can you confirm or deny that this
08:44was properly classified?
08:45What the AI is doing, it's not replacing the human, but it's enabling them to do their job faster, so
08:51we can process more and more data, and identify targets quicker, and solve problems faster.
08:57Five, five, nine, zero, seven.
09:00It's a BMP stationary, over.
09:02AI is helping glean what's important, what's useful, what's not useful, so I can, say, friendly or foe, or target
09:11or not.
09:12The enemy has the same capability, so I have to be quicker, I have to be faster, otherwise I'm at
09:18risk for becoming that target.
09:25AI is not used to be faster, but이, when you have to be faster, sooner or later, than a big隻,
09:25then one would be faster.
09:25The revolution in how wars are forward has come about not only with the processing of data, but also with
09:32small unmanned vehicles, drones.
09:41This drone, this is your eyes in the skies, to detect everybody around you, early warning, see what's going on,
09:48on the battlefield.
09:50And in addition, FPV, first-person view drones, can carry bombs.
09:57The FPV drones, that's your strike drone. That's what's going to take everything out.
10:02OK, I think they're about to launch.
10:10Two BMDs, like 200 meters from us. You can hear them driving.
10:14The battlefield makes me move quicker and understand quicker and make decisions quicker.
10:22I hit the rear BMP. Add one to the scoreboard.
10:27The enemy is currently moving about a click every two minutes over.
10:33I just spotted a vehicle in the wood line.
10:37What you see is now a completely digitally data-driven unit
10:42that had all these new forms of mass, drones, unmanned systems,
10:47in there to make them as able to find the enemy, hide from the enemy,
10:52see the enemy and kill the enemy.
10:54Artillery, incoming.
11:01This year, Sergeant Cole has noticed that the Ukrainians are also putting AI into drones,
11:08so they can fly themselves to targets.
11:12It's just absolutely insane what they're doing.
11:15The targeting software, it'll detect, like, that's a person, that's a truck.
11:19The hard part is to program it to actually fly on its own and then hit something.
11:24And that comes in with, like, morals and ethics, like, do we want something to decide on its own to
11:31kill something?
11:32What's your view of that?
11:35I mean...
11:39If it flies completely autonomously and kills stuff, I don't necessarily agree with it.
11:47Completely autonomous drones flying around, killing people, that's just insanity.
11:52That's stuff out of nightmares.
11:55All right, I gotta come land.
11:59It's anyone's guess how these technologies play out in future wars.
12:04But clues already exist in Israel and Ukraine, where the technology is already in use.
12:17The trajectory of this new war machine begins in about 2016,
12:23when the technology of war was limited mostly to hardware,
12:27like aircraft carriers,
12:29artillery,
12:30and tanks.
12:33But already there were experiments in data processing,
12:38especially in Israel,
12:40a nation that promoted itself as a tech superpower.
12:45Today, our biggest export is technology.
12:48Israeli technology, which powers the world's computers, cell phones, cars, and so much more.
12:56The future belongs to those who innovate.
12:59And this is why the future belongs to countries like Israel.
13:06Nearly 50 years after Israel's occupation of the West Bank and Gaza,
13:11some Palestinians, hemmed in by the newly built separation wall,
13:16turned to lone wolf attacks.
13:20A short while ago here at the central bus station in Jerusalem,
13:24one terrorist carried out an attack against a security guard that was stabbed.
13:27Just outside the entrance at the moment, the area is still closed off.
13:31We've confirmed it was a terrorist attack.
13:34These attacks were different to the previous waves,
13:38as they weren't organised by a militia organisation.
13:42Instead, single Palestinians skirted round the security controls.
13:50You just had lone individuals, usually very young.
13:53These people usually just took a knife or even a screwdriver
13:56to attack soldiers in checkpoints,
13:59or just suddenly batting people on the streets,
14:02or driving cars into people.
14:06The challenge was to try to figure out
14:08who's the random person that will wake up today,
14:11pick up a knife and stab someone.
14:12And that's what they're doing.
14:16These witnesses are intelligence analysts
14:19who were called up to work for the Israeli army.
14:23They don't want to reveal their identities,
14:25and their voices have been digitally altered.
14:29Their job was to monitor security threats in the West Bank.
14:33I was recruited to the army in the late 2010s.
14:38In the theoretical framework that I worked under,
14:42every Palestinian is a suspect.
14:46When I joined the army,
14:47it was in the midst of a technological transformation,
14:52of trying to adopt new technologies.
14:57Israel had a special advantage in tracking the threat.
15:01It controlled Palestinian communications.
15:06Israel is basically unlimited data,
15:09because all stellar data of the West Bank
15:13goes through Israeli technological centers.
15:18The whole network is basically in Israel's hands.
15:22All phone calls that are being made through the regular network
15:26in the West Bank and Gaza,
15:28they would all go to a big database,
15:32sort of archive.
15:38These lone wolf attacks,
15:40they naturally encourage the army to think in terms of big data.
15:45The traditional approach of just, you know,
15:47trying to infiltrate a terrorist organization,
15:50this wouldn't really work for people
15:52to just spontaneously decide to attack Israelis.
15:57At first, Israel tried simple word search to catch lone wolf militants,
16:02before they attacked.
16:04We were really doing the first steps of, for example,
16:08working with telephone calls on how to identify a relevant telephone call
16:13according to keywords.
16:17They kind of figured out that many people who'd go on these long wolf things
16:22send text message, basically.
16:24Beforehand, some kind of declaration of intent.
16:27They would be very good.
16:29Certain words, whenever they are reported in the system,
16:33these words would trigger some sort of alarm.
16:38But soon they experimented with data patterns
16:41that would predict who might merely be tempted to become a radical.
16:46We want to create a usable data set of possible terrorists.
16:51So the general method to do it is specify as many attributes as we can.
16:58So age, gender, and try to find patterns in the data
17:05that can be used to squeeze it.
17:07Thousands of individual Palestinians were categorised by dozens of attributes,
17:14and every attribute was given a value.
17:17A computer then calculated how likely each person was to turn violent.
17:24The initial algorithms created grades as to predictability
17:30to be terrorists for one to ten.
17:35You're a 7.8 terrorist, and here's the group of potential terrorists.
17:40Now let's surveil them on a daily basis
17:43to see which of them is actually planning to do terror.
17:51At some point, these attacks are reduced significantly.
17:57It was pretty efficient.
17:59I remember that I was almost shocked to see how efficient it was.
18:04They did feeling quite emboldened by this.
18:08But in the last year,
18:11we managed to get to the level of 400 obvious attacks.
18:16This is a military activity.
18:18A military activity that is based on the biggest intelligence
18:21and the biggest strategies.
18:23This is a lot built there.
18:28Although Israel's military leadership was convinced
18:31that the decline in attacks was due to prediction technology,
18:35human rights groups reckoned the waves of violence
18:39had always ebbed and flowed.
18:42And they accused Israel of an egregious invasion
18:46of the privacy of millions of Palestinians.
18:52To me, it was very clear that this total control
18:55is precisely what enables the political process to be frozen.
19:01Clearly, if we have that total control,
19:03then there's no motivation to change anything.
19:07We really thought that technology has solved most of our problems.
19:11While Israel concentrated more of its intelligence resources on technology,
19:17they neglected the role of human sources,
19:20particularly in the Gaza Strip.
19:24This had been an essential part of Israeli intelligence in the past.
19:30And it would prove to be a catastrophic error
19:33in the lead-up to the Hamas attack of October 7th, 2023.
19:48The next chapter in the story of warfare technology began
19:53when Russian tanks rolled into Ukraine in February 2022.
19:58Ladies and gentlemen of Ukraine,
20:01Today, in the morning, President Putin
20:03made a special military operation on Donbass.
20:07Russia made attacks on our military infrastructure
20:10and on our borderlines, borderlines.
20:28The odds were stacked against Ukraine,
20:31who had 250,000 soldiers,
20:34but stood against an army of about a million.
20:42Russia made itself harder in Russia.
20:56Russia left to the U.S.
21:01Russia leva back to the United States SCAD,推幼ğiNow
21:06for our country.
21:14The challenge that Zelenskyy had in fighting back
21:17was working out which Russian targets to hit.
21:23From the command centre in Germany, NATO offered assistance
21:28in the form of MAVEN smart systems,
21:31though the US military won't talk about what help was given.
21:36But the technology behind MAVEN smart systems
21:39was created by a controversial company called Palantir.
21:44Their CEO was and is a maverick skier called Alex Karm.
21:50Welcome to our...
21:52Here he is, speaking to investors in the early months of the Ukraine war.
21:57Palantir, for example, we are a company to thrive in good times,
22:04and we thrive in bad times.
22:06We are going to continue supplying the world's most important products
22:10to the most interesting, creative and effectual people in the world.
22:13Palantir's products are on the absolute front line,
22:16and you see them in the news every day.
22:19Palantir's early investor was the CIA,
22:21and they have contracts with global national security organisations,
22:26including US immigration.
22:27Their next customer was to be Zelensky.
22:31The invitation came from the Ukrainians.
22:34So Alex Karpal, chief executive and founder,
22:38and I travelled to Kyiv May-June of 2022.
22:44I remember we woke up very early in Sheshov,
22:48on the Polish side of the border.
22:50You know, it was dawn at 4am,
22:52and set off on a very long car journey,
22:55cross that eastern border of Poland into Ukraine,
22:59and then eight hours on the road to Kyiv.
23:06We turned up at the appointed place to meet Zelensky.
23:10You know, what was extraordinary about that meeting
23:12was frankly how lively he was.
23:14He was very funny.
23:15He was cracking jokes.
23:17And I mean, I guess I know he's a comedian,
23:19but still that was a very surprising and unexpected thing.
23:22You know, there was a couple of times he had us in stitches.
23:26I think Zelensky understood that the biggest challenge
23:29the Ukrainians faced was one of mass and numbers.
23:32They were outnumbered by the Russians and also outgunned.
23:38They had more armaments,
23:40more industrial capacity than Ukrainians did.
23:42And so the only way of correcting that imbalance
23:47was with technology.
23:48And Zelensky explained that he wanted us
23:51to come and help the Ukrainian war effort
23:52and that he believed that Ukraine was going to be
23:55the research and development laboratory
23:58for conflict over the coming years.
24:02So, of course, Alex said yes.
24:04And then it fell to me and others on the Palantir team
24:08to turn that into a reality.
24:11We provided them with a software platform called Foundry.
24:14And at its core, it's a data integration platform.
24:19So that's to say it enables our customers
24:21to bring together data, information from really any source
24:26of any type, any format, any scale,
24:29bring that data together, clean it, harmonize it,
24:33and make it useful.
24:34In military technology terms,
24:36in a war like the one that Ukraine faced,
24:39there were many, many more targets,
24:41many, many more things to shoot at
24:43than they had things to shoot with.
24:45So the big challenge was not precision.
24:47It was prioritization.
24:49And that is a data integration problem.
24:52So at the beginning of the war, for example,
24:55there was lots of satellite imagery.
24:56And satellite imagery is very good at telling you
24:59where something is.
25:00But it's often very hard to tell what the thing is
25:04or why the thing might be important.
25:08So you can identify a barn in a field in Ukraine,
25:13but you're not going to be able to tell from the satellite image
25:15that that barn might be the command and control center
25:18for an important part of Russian forces.
25:21And for that, you might need to layer on another kind of data,
25:24for example, radio frequencies, signals intelligence.
25:28So if you combine satellite imagery and signals intelligence,
25:32you can tell where something is and what it is.
25:35And that allows you to then,
25:37with the precision munitions that exist today,
25:40destroy it with pinpoint accuracy.
25:46In November 2022, nine months after the war began,
25:51ChatGPT burst onto the scene,
25:53showcasing the power of a new technology,
25:56large language models.
25:59Palantir and the Ukrainians were quick to harness
26:01the underlying technical breakthrough.
26:04So the emergence of large language models in 2022
26:07has a dramatic impact on the battlefield.
26:11If you imagine, there might be thousands
26:13or even tens of thousands of different data sources
26:16that need to be monitored at any given time on a battlefield.
26:19And analysts traditionally would have had to review
26:23each of those data sources individually
26:25and manually.
26:28Large language models, as we all know,
26:30can synthesize information very quickly
26:33and can draw out important inferences, links,
26:37or key points depending on what you're looking for.
26:40And I think that did play a critical role
26:42in those early phases of the war.
26:45Isn't there something difficult about running a company
26:48that's speeding up the process of killing people?
26:50It's deeply morally complex,
26:52and it's something that we wrestle with every day.
26:55But ultimately, I think ensuring that our armed forces
26:59have the most effective technology
27:00is actually the best way of preserving peace
27:03and therefore saving lives.
27:10But AI wasn't the only technology to take a huge leap forward in Ukraine.
27:17Also fast-tracked was the development of unmanned vehicles.
27:21Two Ukrainian soldiers describe how drones have transformed the battlefield.
27:36They may have started as tools of surveillance,
27:40but soon became deadly weapons.
27:52But soon became deadly weapons.
28:11By 2024, each side had more than a million drones.
28:16All right, that's all, veryglichenius.
28:21Go away from this drone!
28:22It's, for us, not a certainty,
28:23there's a few percent,
28:24there's probably 70 of the drone,
28:30there's a drone drone.
28:32There's a drone drone.
28:32Well, when you have a BZRK rocket engine,
28:39that costs 60,000 dollars,
28:43there's a drone drone,
28:44that costs 2000 dollars.
28:50With a range of up to 30 kilometers, they transformed the front line.
29:26Ukraine demonstrated that the fundamental character of war has changed, with drones killing hundreds of thousands of soldiers.
29:38Because now, in the middle of every 3-5 minutes, on the front line lies at least one drone.
29:50It's a feeling when they're constantly waiting for you.
29:54It's a moral pressure.
29:56Because you understand, that when you go and what you don't do,
29:59you will find you soon.
30:11These new technologies of AI and drones had allowed a smaller army to hold ground,
30:18albeit in a brutal and intractable fight.
30:22But soon these technologies would be used in Gaza, with devastating consequences.
30:43The next development in the new war machine began when hundreds of Hamas operatives
30:48breached Israel's high-tech border at dawn on October 7th, 2023.
30:57Social media quickly revealed the brutality of the attack.
31:21I was in my apartment, and it was just me and one of my fat mates.
31:27And I got up in the morning from all the sirens.
31:36Like almost every Israeli, I have family closer to the border with Gaza.
31:41And at these moments, there were actual fear for their lives.
31:44I didn't know what's going on with them.
31:50For me, and I guess for many other people, it was more like from the collected level of,
31:55you know, if people like me that were attacked, it could have been me.
32:06In a matter of hours, 1,200 Israelis were killed.
32:17251 hostages were taken to Gaza.
32:22The Israeli military and political response was immediate.
32:29222 workers, the U.S. Army, the United States were killed.
32:38222 soldiers, the U.S. Army, the U.S. Army.
32:57development around lone wolves now return to duty.
33:02Once you arrive over there to the unit,
33:04I mean, of course, you sit in front of a computer.
33:06It's not as if you're able to stop the attack from there,
33:08but you can't feel like, OK, OK, I do my part.
33:13The whole atmosphere was like pretty insane.
33:16And I don't know, no one really knew what they were doing,
33:20I suppose.
33:21Like, originally, they kind of thought
33:22they could, like, wipe out from us in the,
33:24because it's through, like, the space of, like, a few days,
33:27and then we just have, like, the easy win, supposedly,
33:30and I get on with our lives.
33:32In the first few days of the war,
33:35the biggest tasks were creating what's called targets.
33:40The creation of targets was a challenge
33:43because the Israeli government said it followed international law,
33:47in which a strike would be prohibited
33:49when the expected incidental loss of civilian life
33:52is excessive in relation to the direct military advantage.
33:59There were complaints that there aren't enough targets
34:01in the Gaza Strip, even before the war.
34:04People high up were very content with the amount of targets
34:07that were being produced.
34:08They set up this thing called the tariff factory.
34:13Then they were like, OK, we just need to make tariff.
34:15Just finding locations and finding people, basically, to assassinate.
34:33The Israeli Air Force posted multiple videos of their strikes
34:38and the numbers of their targets on their telegram channel.
34:43There was an urge for extreme measures.
34:47So the general belief was that human work will not do
34:52to create the number of targets required.
34:55So the convenient solution was to use non-human ways of creating targets,
35:01which is, namely, AI.
35:13It was already clear that we have to bomb as much as we can.
35:19No realistic amount of humans could do this job in this amount of time,
35:24then, naturally, they turned to machines.
35:28Computers created lists of locations and people
35:32that were passed to target rooms.
35:35There, other soldiers checked the targets were correct,
35:39assessed the collateral damage.
35:41And it's reported that sometimes they had less than a minute
35:45to make this decision.
35:47Early on, it was very clear that anything that has any connection with Hamas,
35:53and that includes also people who are not part of the military wing,
35:56but also part of the political wings.
35:58Anyone who has a connection with Hamas is a legitimate target.
36:08We were in Shuggah, at the 4th.
36:11At the 4th of the morning, it was about 4th,
36:14and they came back to us, and we didn't know why.
36:18We had a brother, a brother, a brother,
36:21a brother, a daughter, a daughter, and a daughter.
36:24And the two of us, and I was killed, and I was the only one.
36:30How did the Israeli army generate so many targets?
36:37In the preceding years, the Israelis had built targeting systems
36:41that had been derived from the software used to prevent lone wolf attacks.
36:50At some point, we were using an AI algorithm that gets a data set of people
36:56who are approved Hamas members,
36:58and looks for people with similar attributes
37:01in general data sets of the entire Palestinian population.
37:06There were a number of different systems.
37:08One ascribed a threat probability to any individual
37:11between one and a hundred.
37:14Anyone over a threshold of, say, 90, could be targeted.
37:28If your requirement is to kill in numbers,
37:31you want to kill an impressive number of people.
37:35AI can give you, theoretically, an endless number,
37:40as long as you're willing to give up on the precision.
37:45Within three weeks, Israel announced it had attacked 11,000 targets.
37:53And the Gaza Health Ministry, controlled by Hamas,
37:56had reported 8,800 dead and 22,000 injured.
38:03It was perfectly clear that we want this space of targeting
38:08with this level of carceral damage.
38:15Allahu Akbar!
38:18But in the end, what drove the high number of casualties
38:22was not technology, but political and military choices.
38:27In the previous rounds of violence,
38:29the number of civilian casualties deemed acceptable by the Israeli military
38:33had been much lower.
38:37A different decision was made for Gaza in 2023.
38:44They have this decision at the source of the war
38:46that you can bomb any commerce operative anywhere he is
38:49and take 20 people along with him.
38:53Basically, assassinating people in the homes
38:55just means that you know that people of the army have killed.
38:59Wives, children.
39:00Wives, children.
39:05Ition basically took the licence to kill
39:08a significant number of civilian casualties along with a target.
39:14Basically, you're right, yeah, he's there, boom.
39:18These intelligence analysts accuse Israel of allowing collateral damage
39:23of 20 civilians for any approved target, but they go further.
39:30There are actual numbers in Israeli military doctrine
39:33for each level of collateral damage which is allowed.
39:38I think they raised the base level,
39:40and then for especially important targets, it could be even higher.
39:44So, there was permission to kill 300 people at Croatia or at Bamic.
39:52Yeah.
39:54300 innocent victims for an approved target?
39:58Yes, sir!
39:58Yes, sir!
39:59Yes, sir!
40:00Yes, sir!
40:02Yes, sir!
40:04Yes, sir!
40:05Yes, sir!
40:06Yes, sir!
40:07Yes, sir!
40:08Yes, sir!
40:08On the 2nd of December, 2023,
40:10the Israelis appeared to reinforce the claim.
40:14They launched more than 400 strikes.
40:18And one on a housing block in Gaza City,
40:22where they said they'd eliminated a Hamas commander
40:25who'd helped plan the October 7th massacre.
40:28But in doing so, the strike had killed an estimated 300 neighbours.
40:54I remember there was this operation where other innocent people were killed.
40:58I listened to the call beforehand of the guy saying,
41:01yeah, I'm in my family home and my whole family are here
41:04and I'm worried that we will get bombed.
41:06And I finally would die.
41:09And then I'm just sitting there at like 4 in the morning,
41:12waiting for like the fucking planes to bomb.
41:16This kind of bureaucratical apparatus takes
41:19like the personal responsibility of people.
41:23And you don't see the face of people of you like killing, you know.
41:27But the weird thing is that I did hear these people's voices, you know.
41:31And I was like,
41:33it's horrible to say this, but, you know,
41:35I heard them crying when their relatives were killed.
41:42I think a lot of what technology gives us is that it blurs the reality
41:48for us to be able to not be completely responsible for what's going on.
41:55The decision was just to bomb and bomb and bomb.
41:59If you want this space of bombings and still make them look legal,
42:04let's call it that,
42:06then you need at least this tool that does the combination of data
42:13to reach the legal threshold for what is a legitimate target.
42:16It's hard to pile up.
42:19In this sense, this sky-lift technology is more of an excuse.
42:25All three intelligence analysts are no longer on duty in the Israeli army.
42:34By January 2026, an Israeli official briefed newspapers that they agreed
42:40there had been more than 70,000 deaths in strikes in the two years of the war.
42:48In this sense, it's a very difficult time.
42:49Organisations, including Amnesty International,
42:51Beth Selem and parts of the UN,
42:53now accuse Israel of committing war crimes by, amongst other things,
42:57the disproportionate attacks on civilians in densely populated areas.
43:01Whilst Israel's strategy was driven by human choices,
43:05the technology enabled the onslaught.
43:09The Israel Defence Force says the IDF does not use an AI system
43:14that identifies terrorist operatives
43:16or tries to predict whether a person is a terrorist.
43:19Information systems are merely tools for analysts
43:22in the target identification process.
43:25The IDF operates in accordance with international law.
43:28Each strike undergoes an individualised case-by-case assessment
43:32evaluating anticipated military advantage
43:35against expected incidental civilian harm.
43:39Proportionality decisions are made based on the information available
43:42at the time of decision and not in hindsight.
43:45The IDF has also said that the 70,000 deaths figure
43:49does not reflect official IDF data.
43:55Whatever the lessons of the tactics in Gaza and Ukraine,
43:59the Race for Warfare technology shows no sign of slowing down.
44:03In January 2026, the US Secretary of War, Pete Hegseth,
44:09was fully committed.
44:11Simply put, the United States must win the strategic competition
44:15for 21st century technological supremacy.
44:19We must ensure that America's military AI dominance,
44:23so that no adversary can exploit that same technology
44:26to hold our national security interests
44:29or our citizens at risk.
44:32America first in every domain.
44:36In short, we will win this race
44:38by becoming an AI-first warfighting force across all domains.
44:43The rest of the world is following suit.
44:47Western governments have entered into hefty military contracts
44:50with American-based technology companies like Palantir, Google,
44:55Microsoft and Amazon,
44:56making them ever more dependent
44:58on a few corporations for the next generation of military technology.
45:03I think it's incredibly important
45:05if we want to maintain our way of life,
45:07if we want to remain advanced first world economies,
45:11if we want to keep our value system,
45:13that we in the West, broadly defined,
45:16have the dominant militaries.
45:18We have to maintain that technological advantage.
45:20And if we are in an arms race,
45:22that means we have to win it.
45:26As drones replace missiles and computers replace men,
45:30it seems that wars have not become cleaner,
45:32more surgical and quicker.
45:34If anything, the costs in money and political capital
45:37of entering wars has declined.
45:40And they're likely to become more frequent.
45:44So now is the moment for citizens and their governments
45:47to decide whether,
45:49just like for nuclear and biological weapons,
45:51we need international agreements to control the new warfare.
45:56I got to see, like,
45:58the advantages that AI gives.
46:01A fear is before the rest of the public,
46:03and there's zero good value given by that.
46:07It only creates more dust.
46:10It only gives opportunity for deadly wars.
46:13To be fair, I really think it's a mistake.
46:16It just creates more dust and more wars.
46:26The whole war brings to the optimizing and innovations,
46:34as it makes it into account
46:37If anyone grows up,
46:41that civilization will restore technologies in the past.
46:44I tried to work on the發HEAPH他們 did care.
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