humans

It is literally the largest and heaviest machine ever built by humans and it does one thing: extract coal.

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In North Rhine-Westphalia, western Germany, the largest machine that man has put on earth operates. Forget about huge ships, aircraft carrier either oil platforms: It’s an excavator. It is called Bagger 293, and its very existence is the moving memory of what industrial engineering is capable of when it is demanded without limits. What is it, exactly? The Bagger 293, also known as the MAN TAKRAF RB293, is a bucket wheel excavator (those that have a giant toothed disc at one end) designed for open pit mining. It was built by the German company TAKRAF, a subsidiary of the MAN group, between 1990 and 1995 in Leipzig. His goal from day one was only one: extract lignitethe so-called brown coal, in the Hambach mine, one of the largest mining operations in Europe. Today it remains operational, owned by RWE Power AG, Germany’s second largest energy producer. Numbers. It is 96 meters high, equivalent to a building of more than 30 floorsand 225 meters long, which is more than two football fields placed in a row. It weighs 14,200 tons. The Guinness Book of Records officially recognizes it as the largest and heaviest land vehicle in the world. Shares title with its predecessor, the Bagger 288although the 293 surpasses it in size and capacity. It also cannot be transported. And moving it about 120 kilometers requires more than three weeks of continuous work, with progress of just 5 or 6 kilometers a day. How it works istea monster. The heart of the machine is a 21.3 meter diameter rotating wheel armed with 18 buckets, large steel buckets, each capable of loading up to 15 cubic meters of material per cycle. That wheel spins non-stop, tearing off layers of earth and rock to reveal the veins of lignite, which are then transported by giant belts to the electricity generation plants. Under normal conditions, the Bagger 293 can move up to 240,000 tons of material in a single day. Furthermore, it is estimated that what it does in one day is equivalent to the manual work of about 40,000 miners. All this with only five operators on board, controlling the system from a central cockpit. electric appetite. To start such a structure, a direct external energy source of 16.56 megawatts is needed (about more than 22,500 HP if we do the conversion). This would be approximately equivalent to the electricity needed to supply a city of about 20,000 inhabitants. On the other hand, it should be noted that the Bagger 293 does not have its own conventional engine, it is permanently connected to the industrial electrical network. Its 12 steel tracks, each 3.8 meters wide, distribute the immense weight over the ground in a controlled manner so that the ground does not give way under it. Leaf where you work. The excavator works in the Hambach mine, the largest open-pit mine in Germany, with an approved area of ​​up to 8,500 hectares and a depth that reaches 500 meters below ground level. According to Bloombergthe mine produces around 40 million tonnes of lignite per year, enough to power around 8 million homes. But the mine is not without controversy. Brown coal is the most polluting fossil fuel per unit of energy produced, and the exploitation of Hambach 90% of the historic Hambach Forest has been wiped outan ecosystem more than 12,000 years old. As of 2012, environmental activists They occupied the remaining trees for years in a protest that ended up becoming a symbol of the climate debate in Germany. In 2018, tens of thousands of people demonstrated against the mine’s expansion. Greta Thunberg herself visited the place in 2019stating that he found it “devastating” to see places like the Hambach mine. In January 2020, the German government agreed to preserve the remaining forest, and in August of that same year Germany committed to its definitive exit from coal by 2038. According to Global Energy Monitormining at the Hambach mine will cease in 2029, and the plan is to transform the territory into a reclaimed landscape that will include a large artificial lake. Images | Andreas Lippold (Wikimedia Commons), Stefan Fussan (Wikimedia Commons), Steve Rowell In Xataka | The key hidden infrastructure for AI is not data centers: it is undersea cables and the Middle East leads the way

Science had always believed that only humans understand geometry. Until we noticed the crows again

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The perception of geometric regularity in shapes, a variant of elementary geometry, has long been considered an ability that only human beings had. And it is no wonder, since from quite early stages of development and across multiple cultures, our species has demonstrated a natural understanding of spatial rules. But this has changed in a species similar to crows. A radical change. Although this innate quality of humans was quite well established, science has now shown that the crows too They have geometric understanding. A cognitive milestone that rethinks what we thought we knew about animal intelligence and the evolution of pure mathematics. A myth. The scientific bases showed a notable gap between human abilities and those of the rest of the animal kingdom with regard to euclidean geometry. Previous research had already seen that primates lacked the ability to recognize geometric regularity in tests of visual perception of shapes, something fundamental, since they may be the first that come to mind when thinking about this property. And this was crucial to determining that humans have an innate ability to process geometric regularity, since the recurring inability to species like baboons After intensive training he laid these foundations. However, the researchers decided to explore these abilities in birds known for their impressive cognitive and arithmetic skills. Touch screens. To test birds’ spatial intuition, scientists from the University of Tübingen They designed an experiment based on the detection of visual anomalies. In this case, two 10- and 11-year-old male crows were trained using touch screens located inside conditioning chambers. Here the birds could observe an array that displayed six simultaneous shapes on the screen and the task was to detect an “intruder”, that is, to peck at the shape that differed in its visual parameters with respect to the other five base stimuli. The tests. For the final test, five reference quadrilaterals were used, ordered by their level of regularity: the square, the isosceles trapezoid, the rhombus, the right hinge, and a completely irregular shape. From here on, the “intrusive” figures were artificially generated moving the lower right vertex of the original figure at a fixed distance equivalent to 75% of the average distance between the vertices. Results. The most impressive thing seen was the immediacy of understanding the problem, as the crows were able to apply the concept of detecting the intruder immediately upon being exposed to the new sets of quadrilaterals. Both subjects dramatically exceeded the 16.7% chance level during their first trials, demonstrating that they understood the task without hesitating or mindlessly pecking. Furthermore, during the first 60 trials, the first crow achieved 48.3% success and the second crow 56.7%. The most impressive thing. The most revealing data from these tests was precisely that the birds showed significantly better performance with shapes that presented properties of pure Euclidean geometry, such as right angles, parallel lines or symmetry. It is crucial here to highlight that this performance advantage did not require extensive prior training, but rather the regularity effect was present from the very beginning of the testing phase. Because? Faced with the logical question of why crows achieved what other primates failed, the authors of the study recognize certain important methodological differences compared to classic experiments with baboons. In this case, they point out that the crows were subjected to a strict progress criterion during training, needing to maintain 75% correctness over five consecutive sessions. In contrast, baboons only needed to reach a criterion of 80% correct responses only once, without the need for consecutive sessions. And although this difference may make a direct and exact comparison between the species difficult, the main finding is incontestable: crows recognize geometric regularity. Images | Tyler Quiring In Xataka | Punch, the monkey clinging to a stuffed animal and a victim of bullying, has achieved the impossible: uniting the Internet under the same cause

International law was written with humans who decide in mind. AI just broke that chain and no one knows who answers now

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Pete Hegseth’s threat to Dario Amodei has a subtext that goes far beyond the $200 million contract that the Pentagon can cancel: If the US military deploys AI-controlled autonomous weapons without the safeguards that Anthropic requiresyou will have removed the only firewall that has historically prevented an illegal order from being executed. Why is it importantand. The entire legal and ethical system of the US military rests on a principle that seems obvious but has important consequences: a soldier can and should disobey a manifestly illegal order. It is the mechanism that, in theory, prevents war crimes. A drone AI-controlled autonomous vehicle does not have that mechanism. You can’t refuse. You can’t hesitate. He cannot be tried in a court-martial. Between the lines. Amodei speaks of “autonomous weapons that fire without human intervention” to point out a legal vacuum. If an AI makes the decision to kill, who is responsible criminally? The programmer? The general who activated the system? The president who signed the order? International humanitarian law (including the Geneva Conventions) was written with human beings making decisions in mind. And now AI dissolves that chain of responsibility. The backdrop. The mass surveillance argument is also a bitter pill to swallow. The Fourth Amendment of the US Constitution protects citizens from warrantless searches and interventions. It works, among other reasons, because the State has never had the physical capacity to process everything that happens in public spaces. And in the same way, with AI that operational limit disappears: we move to millions of conversations recorded in real time, transcribed, classified and connected in just seconds. What was previously impossible due to lack of human resources becomes routine with a LLM. Constitutional protection until now has depended, in part, on the inefficiency of the State, its limitations. Yes, but. The Pentagon has an argument that cannot be ruled out: other democracies are also developing these capabilities, and China or Russia are not going to wait for the United States to resolve their ethical dilemmas. The practical question is whether having those unrestricted capabilities makes you safer or simply more dangerous to your own citizens. The big question. OpenAI and Google have accepted the Pentagon’s conditions“all legal uses” without specific exceptions, and xAI has just been cleared to operate on classified systems. Anthropic has been left alone in its position. And what is at stake now is not whether Claude survives as a military supplier or not, it is whether the AI ​​industry is going to set some limit on what it sells to the State, or whether that debate will be settled directly by Congress, the courts or, in the worst case, the first serious incident that no one could have foreseen. It seems like a matter of time. In Xataka | AI is already a battlefield: Anthropic has just accused DeepSeek and other Chinese companies of “distilling” Claude Featured image | Xataka

AI consumes obscene amounts of energy. Sam Altman compares it to the cost of “training” humans

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OpenAI CEO Sam Altman participated in an event organized by The Indian Express. During the interview made some striking statements, but the greatest of all of them was the one he dedicated to talking about what it costs to train an AI model. In fact, he complained about how many of ChatGPT’s energy consumption discussions they are unfair. Training humans also consumes a lot. The interviewer asked Altman about ChatGPT’s energy consumption and Sam Altman took a few seconds to answer the question, and then made a peculiar comparison (my bold): One of the things that is always unfair in this comparison is that it talks about how much energy it takes to train an AI model compared to what it costs a human to perform an inference query. But it also takes a lot of energy to train a human. It takes about 20 years of life and all the food you eat during that time before you become intelligent. And not only that, it took the widespread evolution of the hundred billion people who have lived and learned not to be eaten by predators and to understand science and so on to create you. The fair comparison is if you ask ChatGPT, how much energy does it take once their model is trained to answer that question compared to a human? And AI has probably already caught up in terms of energy efficiency if we measure it that way. A previous Epoch AI study corroborates that energy consumption during inference (when we actually use ChatGPT, for example) is low. Source: Epoch AI. Training is one thing, inference another.. The answer may be controversial, but to a certain extent it is logical: learning, both in the case of humans and AI, takes time and consumes many resources, but that cost is one thing and the cost of inference, of “applying that training”, is another. Once we have learned, it is not too difficult to answer things. This is what Altman is trying to point out here, who recognizes that AI does indeed consume a lot of energy in training, but that it has then become very efficient in the inference phase, when we actually use ChatGPT. The problem is that although Altman has already spoken that in inference consumption is minimal, does not provide evidence of this. The water problem is no longer a problem. He also spoke about the controversial water consumption that was theoretically carried out in large AI data centers. Although he acknowledged that this was a problem when “we used to use evaporative cooling in data centers.” Now, however, “we don’t do that,” he recalled, and made it clear that those accusations that “ChatGPT uses 17 gallons per query, or whatever” is totally false, “totally crazy, it has no connection with reality.” But again, there is still no official data from AI companies in this section. How much does AI really consume? The truth is that at this point we still do not have really clear data on how much the AI ​​consumes both in the training phase and in the inference phase. There are those who have investigated energy and water consumption and have made a mistake. wildly exaggerating the databut for example in the US, where a large number of data centers are concentrated, there is no legislation that forces transparency with those figures. Increasingly more efficient models and data centers. One of the most interesting studies was the one made by Epoch AI in February 2025, and at that time it was also concluded that AI did not actually consume as much as it was said to consume. In fact, it consumed relatively little and the models have only improved in efficiency. Chips and cooling systems have also improved, and although data centers have certainly require enormous amounts of energywe continue blindly in this section. In Xataka | Spain has a plan to capture more data centers than anyone else: “shield” them from energy costs

We believed that imagination was exclusive to humans. Kanzi, the bonobo who drinks “invisible coffee”, has just proven the opposite

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For decades, cognitive science has drawn a firm red line between us and the rest of the animals that is the imagination. Although animals can use tools and even solve complex problems, the ability to disconnect from immediate reality and imagine a scenario that does not exist was considered something exclusive to humans. Until Kanzi arrived. Kanzi. A bonobo that is world famous for its mastery of lexigrams to communicate and that has now starred a published study this week in the magazine Science that could rewrite the books of evolution. And it is no wonder, since Kanzi not only knows how to order food, but also knows how to pretend to eat it when it’s not there yet, and being completely aware of what it does. The tea party. The study published earlier this month presents the strongest evidence to date for the representation of pretend objects in a great ape. And for a human Pretend you are drinking coffee by imagining you have a cup in your hand It is something very simple to do. But until now in apes it was something unthinkable. But to prove us wrong about our exclusive quality, the studio designed an experiment where they sat Kanzi down and interacted with empty objects. Specifically, they pretended to pour juice from an empty bottle into a juice or eat “grapes” that did not really exist. But the best thing is that it was not a simple imitation, but Kanzi followed the game with astonishing precision as if he really imagined it. The juice trick. The objective here was to rule out that Kanzi was simply copying movements without understanding the basic concept, and to do this the team designed three tests. The first of them began with the researcher pretending pouring juice into one of several empty glasses. Kanzi was then asked to interact with them by picking one up. In this case, in 68% of the 50 tests, Kanzi chose the glass that “contained” the imaginary juice, ignoring the other identical but “empty” glasses. Fact versus fiction. This is where the crucial point of the investigation is, since if Kanzi were confused, he would treat real and imaginary juice the same. This was not the case, since when given a choice, Kanzi preferred the real object in 78% of the cases. Something that may seem insignificant, but that shows that it maintains two simultaneous mental representations: the physical reality of the empty glass, and the fake reality where we play that the glass has juice. The same thing happened when imaginary grapes were used instead of juice, where Kanzi maintained a 69% success rate in identifying the location of the pretend food. Decoupling reality. The technical term being discussed here is decoupled secondary representation, which is the brain’s ability to hold an image of the world that contradicts direct sensory information. That is, what is being seen or heard. Until now, it was debated whether this ability emerged with modern human language, but Kanzi’s results suggest that this “spark” of imagination was already present in the common ancestor we share with bonobos and chimpanzees. between 6 and 9 million years ago. This is something that also changes our understanding of childhood play, since when a two-year-old takes a banana and pretends it is a telephone, he is exercising a cognitive muscle that evolution has been refining long before telephones or cultivated bananas existed. Exception or rule. It must be taken into account that these experiments have not been done with just any bonobo, but rather an “enculturated” ape since it has spent its life surrounded by humans and trained in the use of lexigramsmaking it have extraordinary capabilities. This gives rise to some critics, such as comparative psychologist Daniel Povinelli, who usually argue that these results could be the result of intensive training that “humanizes” the ape’s mind, rather than a natural capacity in the wild. Although it is something that the investigation tries to counteract with rigorous controls to ensure that Kanzi was not responding to human clues. Images | Will Rust In Xataka | Humans are evolving live on the Tibetan plateau. And understanding what happens there will be essential in space

In medieval Europe, not only humans ended up on the gallows. Other criminals were also executed: the “murderer” pigs

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For centuries, medieval Europe It was a place where justice was dispensed not only in the courts, but in the squares, in full view of everyone, with public rituals designed to repair order when someone broke it in an intolerable way. At that time, the fear of the unforeseeable did not come only from armies, plagues or famines, but also from what moved through the streets and corrals. In the France Medieval times, for example, the public ritual of punishment (carriage amidst mockery, solemn sentence and execution before the community) did not always have a human as the protagonist: sometimes, the condemned was a pig. The image, which today seems like an oddity from a black chronicle or a folkloric exaggeration, was real enough to leave repeated documentary traces: animals led as prisoners, hung upside down until they died and treated, in practice, as perpetrators responsible for a crime that had broken the social balance. The pig as a real threat The frequency of these cases is better understood by remembering that the medieval world lived attached to animals and their risks. Pigs, in particular, were useful because they ate everything and could feed on scraps, but that same omnivorous condition made them dangerous if they roamed free near small children. The records collect numerous episodes in which pigs killed and even devoured children, a violence that today clashes with the modern image of the docile and slow animal, but which was then associated with specimens closest to the wild boar: fast, strong and capable of imposing themselves physically in seconds. Medieval archives collect cases like the one from 1379when a group of pigs in Saint-Marcel-lès-Jussey killed the son of a swineherd, or the from 1386 in FalaiseNormandy, where a sow destroyed a child who ended up dying. Also that of 1457 in Savigny, Burgundywhen little Jehan Martin was killed by a sow and, especially disturbingly, his six piglets were found nearby, stained with blood. They were not vague rumors, but stories that were fixed with names and placesand that fueled the need for a public response that was not limited to a simple private loss. In France, these events often led to in judicial proceedings formalities in which the animal was imprisoned, transferred and executed as if it were a common criminal. Sources talk about expenses registered normally (cart, prison, executioner even brought from Paris) and an administrative routine that suggests that, for the people of that time, it was not an absurd spectacle, but a legitimate mechanism of justice. The strangeness, therefore, was not that there was violence, but rather that the violence was channeled through a trial with the appearance of ordinary procedure. When money is not enough A practical explanation of these processes was that medieval justice tended to seek reconciliation between partiesand many disputes could be resolved with compensation or agreements. But when a child death came into the picture, that logic was broken: the damage was too serious and the money could be insufficient to close the social wound. In that context, the court intervened to “take control” of the conflict, separate it from private revenge and offer an institutional solution that would distribute the emotional and political burden of the outcome. Trials also functioned as a form of organize the story: It was not just about punishing the animal, but about clarifying human responsibilities. If a pig was known for being dangerouswhy was he allowed to loiter near children? Was there negligence on the part of the owner? a chain of negligence? There was even a suggestion of the possibility of darkest questions: if the child was “unwanted”, if he or she was deliberately left in a risky situation or if the accident hid an intention. The court, by intervening, not only imposed a penalty, it produced an official explanation that the community could accept. Sometimes, the local machinery was not the last word and the matter escalated towards higher authorities. In the case of 1379, some of the accused pigs belonged to an abbey, and from there a petition was sent to Duke Philip “the Bold” requesting clemency. They defended that their animals had not participated and that they were “well-behaved pigs.” The duke heeded the request and issued a pardon for the animals of the abbey, showing that these processes, strange as they may seem, were inserted in real networks of power, influences and political decisions. Far from being simple superstition or peasant rage, these executions could serve to assert authority. The right to erect a gallows and execute criminals it was a privilegeand taking a case to the end allowed a local lord to exhibit the ability to punish and control order. There are episodes that reinforce that reading: a pig murderer from the 15th century it remained imprisoned five years before being executed, and formal letters were sent for permission to build a gallows. When the duke finally agreed, the triumph was not only symbolic: in addition to showing power, the lord stopped carrying the practical cost of keeping the animal imprisoned and feeding it. Plus: another key is the medieval vision of reality as a logical system created by godwith animals destined to serve humans. For a pig to devour a child was an unbearable investment of that order, a rupture of hierarchies that demanded public reparation. In that mental framework, the trial and execution were not theater: they were a way of “putting back together” what had been broken, of affirming that the world still had rules and that chaos, even when it came from an animal, could be put back into place by a solemn act of justice. Image | Ernest Figueras, Zoe Clarke In Xataka | The Middle Ages were not as dark as they told us In Xataka | 900 years ago, Europe had its own Manhattan: the impressive skyscrapers of more than 100 meters of Bologna

We humans like beer. The big question is whether we like it enough to have invented agriculture

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The big question is not whether it was the chicken or the egg first, but rather what our ancestors began to make first: bread or beer? Does about 12,000 years We humans promote one of the most important chapters in our history in the Middle East, the Neolithic Revolution. From being nomads who lived by hunting and gathering, we became sedentary creatures who cultivated the fields. The change was so momentous that anthropologists have long wondered what caused it. It would be reasonable to think that the search for something as simple as bread, but there are those who believe that the answer is another: beer. What if the great catalyst that led us to plow and harvest the fields was not the search for bread but our ancestral hobby to raise your elbow? Cereals, what do I want you for? Scientists have spent the last few decades unraveling the mysteries from our most remote past, but there is one (fundamental) one that they have not yet agreed on: What the hell led humanity to change hunting and gathering for a sedentary life based on agriculture and livestock? What was the catalyst for the Neolithic Revolution, one of the most momentous periods of all time? Since since humans have been human, they need to eat, the answer seems simple: if those men and women settled to plant wheat and barley, it had to be to make bread, right? That is, they began to spend hours and hours tending their fields to obtain grain with which to nourish themselves. In the 50s however a question began to creep into the anthropological debate: What if what really interested them in grain was not bread or porridge but beer? But… And why is that? The debate is not new. It has been on the table for some time and is heated from time to time with new discoveries, such as the one announced in 2018 by a group of Stanford researchers who found “the oldest record of alcohol”, clues that tell us about the manufacture of beer ago 13,000 years. The last one to raise the discussion was Michael Marshall, a scientific journalist and columnist for New Scientist. In December he published a wide chronicle in which he reviews the latest findings on the subject and (most importantly) exposes how much it is costing anthropologists to reach a conclusion. The benefits of beer. To understand the discussion, we must first clarify a key point: neither the bread nor the beer of the Stone Age were like the bread and beer that we know today. The latter in fact has little or nothing to do with the refreshing amber liquid that they serve us in bars. It was more like a puree, a “sweet, slightly fermented porridge,” clarify Professor Jiajing Wang, from Dartmouth College in New Hampshire. “They germinated the grains, cooked them and then used wild yeast.” The result was a nutritious, caloric, protein-rich concoction that could even be safer than drinking water from rivers and wells. After all, it was the result of fermentation. Added to that was its alcohol content, a “social lubricant” that we still use in the 21st century to relax and socialize. Archaeologist Brin Hayden highlights, for example, its use in events that helped structure communities. There is research which suggest that (at least some communities) used it in rituals and for veneration of the deceased. Much more than suspicions. If the debate has been on the table since the 1950s, it is basically because it has been nourished by archaeological findings. Researchers have found traces that tell us about beer brewing at least 5,000 years ago in southern egypt and northern china or how he does 10,000 years Shangshan culture They brewed rice beer. One of the most important revelations in recent years, however, was the one achieved in a cave in Israel in 2018 by a team led by Professor Li Liu, from Stanford University. There they found evidence of beer brewing before the first cereals cultivated in the Middle East. The finding is related to the Natufiansa town dedicated to gathering and hunting, although they also tended to stay for long periods in the same place. “The oldest”. After analyzing residues located in 13,000-year-old mortars located in a cave in Raqefet, a Natufian cemetery near Haifa, Liu and his colleagues discovered remains of beer. Quite a milestone, like she herself stands out: “It is the oldest record of alcohol made by man.” “This discovery indicates that alcohol production was not necessarily a result of agricultural surplus production, but was developed for ritual and spiritual purposes, at least to some extent, before agriculture.” Issue settled? At all. To understand the complexity of the subject, it helps to review the discovery announced in 2018. At least at that time, the oldest known remains of bread, extracted from a Natufian site located east of Jordan, had between 11,600 and 14,600 years old. The traces of beer discovered by Liu’s team move in a similar range: a priori, they could be dated between 11,700 and 13,700 years ago. One of the keys to the problem, explains Marshall in your articleis that basically the making of bread and beer leaves very similar traces, basically starch residues. “We still don’t have conclusive evidence to answer that question,” Liu recognizes on the question of whether we turned to beer or bread first. The reality is more complex: because we don’t know, we don’t even know if some of those foods were the great catalyst that led our ancestors to change their lifestyle. “I wouldn’t be surprised if both were the motivations.” At the end of the day, the ‘beer first, bread first’ debate does not seek definitive conclusions so much as vindicating the weight of both foods. Both beer and bread, bread and beer, played a decisive role in diets and rituals. Images | Gary Todd (Flickr), Enhin Akyurt (Unsplash) and Gerrie van der Walt (Unsplash) In Xataka | The Wari … Read more

In 1969, humans set foot on the Moon for the first time. He did it thanks to a computer less powerful than your cell phone

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The arrival to the Moon It was one of the scientific and technological milestones most notable of the 20th century and something that remained in those who lived and in those who did not thanks to the images and audios. Something that happened more than 40 years ago, when there were still many technological revolutions to come, such as personal computers or mobile phones. What technologies made it possible for humans to reach the Moon? Something that is already fascinating in itself, but it is even more so if you know the details of the computers, cameras and other devices that were used in the mission, taking into account their characteristics. What technology made it possible for three human beings they reached the moonWould they walk around and tell us in the meantime? We travel in time and space to review. like matryoshkas The Apollo 11 mission was the eleventh of a NASA program that had a total of 22 missions (19 of them being successful), in the 1960s until 1972. Until mission 7 the launches were unmanned and mission 8 was the first to orbit the Moon, but for all of them a Saturn rocket launcher was used. The one for Apollo 11 was the Saturn V, a rocket 110.64 meters high and weighing 2,700 tons with a tank full of fuel (the largest NASA has ever built). Depending on the stage (there were three, S-IC, S-II and S-IVB) the number of engines varied and so did the fuel, which were mixtures of oxygen, kerosene or liquid hydrogen. But the Saturn V was not the one that reached the Moon, but rather the one that went out into space and directed the modules towards it. These modules were the command and service (CM) and the lunar (LEM); The CM contained the engine of the propulsion system that was responsible for entering and leaving lunar orbit and had space for three astronauts, and the LEM was the first ship designed to be able to fly in a vacuum, without aerodynamic capacity. (POT) The LEM separated from the CM as it entered the orbit of the Moon and descended to its surface. It was designed to land only on the Moon since the legs were so weak that they would not support the weight of the LEM in Earth’s gravity (9.8 m/s² versus 1.6 m/s² on the Moon). There was room here for only two astronauts. The speeds that were reached (increasing upon entering the gravitational field of the Moon) were 3,700 kilometers per hour and up to 9,000 km/h due to lunar gravity. And here comes a question: how is it possible to brake at those speeds? To enter lunar orbit, hypergolic braking was used (using hydrazine, dimethylhydrazine and nitrogen tetroxide, hypergolic compounds – which explode without a heat source) and engine shutdown. The computers of the Apollo 11 mission To review the computing involved in the Apollo 11 mission, we must take into account the emission and reception, that is, what was on the ground and what the aircraft carried. And it is also worth remembering that at the time a computer was far from being something domestic or common, or from fitting on a desk. On Earth, in the Goddard Space Flight Center and the Manned Spacecraft Center in Houston, worked with the IBM System/360 75 mainfream, which (along with the 44, 91, 95 and 195) was implemented with hardwired logic instead of microcode like all other IBM S/360 models. For the curious techieshere a configuration diagram and explanation of the team. In the ships, however, the Apollo Guiding Computer (AGC), manufactured by Raytheon and designed by the MIT Instrumentation Laboratory. This team stood out for being one of the first to use integrated circuits. There was one in the LEM and another in the CM. The specifications of these teams are surprising not because the numbers are smaller compared to the current ones, but because even making the effort to place our minds in the 1960s, it is impressive to see that teams like this managed to carry out something as complex as a round trip to the Moon. The AGC had storage of 36,864 14-bit words and RAM of 2,048 words. (POT) Comparing it with later equipment, more or less between the two AGCs they have approximately the same memory as what a Commodore-64 (from 1982) had, but it was about eight times less powerful than an IBM XT (from 1981, which was 4.77 MHz compared to 0.043 MHz for the AGC). In fact, a computer with half a GB of RAM has 100,000 times more memory than AGC. But computers do not live on hardware alone, and software here has considerable weight. 300 people participated in its creation over seven years, at an approximate cost of 46 million dollars (at the time). Among them was Allan Klumpp, a mechanical engineer at MIT whose proposal for landing on the Moon reflects all calculations as well as diagrams and drawings of the situation on the dashboard. The program was called LUMINARY and was written in MAC programming language (MIT Algebraic Compiler), but no terminal or compilation programs, this was done with some punched cards which were prepared with a kind of typewriter (and if a hole was made wrong, a new one had to be made). On the occasion of the 40th anniversary of the famous achievement, it was transcribed the code of both modules (transcribing it), where we read that Klumpp said that this was never exempt from bugs. What is notable here is the multitaskgiven that the fact that the software allowed it was already an achievement and that it was not easy for him to carry it out. In fact, there was some alarm due to the high demand on the computers as at the time of the moon landing, which resulted in a slow response and not with all the calculations, so there was one minute of the eleven that lasted the … Read more

20 years after Dolly we still haven’t cloned humans, but stopping aging is feasible: Crossover 1×32

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In the summer of 1996, a Scottish laboratory made a breakthrough that would forever alter our understanding of genetics and ignite intense debates about the ethics and the possibilities of cloning. That day Dolly was bornthe first mammal cloned from an adult somatic cell. This milestone, achieved by researchers at the Roslin Institute, opened a new era in genetic engineering and shattered the belief that only embryonic cells possess the potential for the complete development of a new individual. Since then there has been debate about the possibility of cloning human beings, but we have not done it and it does not seem that we will ever do it. Serezade, molecular biologist, researcher and scientific communicator, talks to us about that and many other things this week. But we also discussed with her another fascinating topic: how the latest advances seem to be achieving something long sought after: slow aging. There is a lot of fabric to cut here, and for example the environment, culture and habits shape our DNA. But there are also risks, ethics and genetic privacy intertwined. And all this raises a key question: does it make sense to be immortal? On YouTube | Crossover In Xataka | The promise of 120 years is dismantled: biology sets a life ceiling that is quite difficult to break

take down a Russian ghost fleet without the need for humans

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Europe has been dealing with the call for years “ghost fleet” Russian, a network of aging tankerspoorly insured and with opaque owners who have evaded sanctions, turned off transponders, manipulated routes and put European waters at risk with incidents, leaks and dangerous maneuvers. These ships have operated at border of legality to keep afloat energy income from the Kremlin, forcing Brussels to strengthen maritime controls and several coastal states to investigate suspicious incidents near critical infrastructure. The birth of an offensive. The night of November 28 marked a turning point silent but decisive in the war that has pitted Ukraine and Russia for almost three years. A few dozen km from the Turkish coast, far from the usual range of Ukrainian systems and in the heart of Moscow’s logistical rearguard, two Sea Baby naval drones (unmanned, guided by AI and armed with explosive charges weighing more than a ton) rushed at full speed against two oil tankers of the Russian “ghost fleet”the network of aging and opaquely owned ships that Moscow uses to circumvent Western sanctions. The hits against the Kairos and Virat not only showed a technological leap in the range and precision of Ukrainian naval drones, but also sent a strategic message to all actors in the global energy trade: any ship supporting Russian exports can become a military target, and kyiv is no longer limited by the geographic space of the northern Black Sea to impose that cost. The meticulous execution of the attacks (aiming propulsion and rudders to disable, not sink) reveals the extent to which Ukraine is trying to balance military effectiveness with the political risk before international partners, aware that it is hitting an economically sensitive terrain for Türkiye, Kazakhstan and several Western companies with energy interests. How the ghost fleet works. The so-called ghost fleet is one of the pillars that Russia has built since 2022 to maintain its income stream tankers, recruiting hundreds of tankers with decades of service, dubious insurers and convenience records, many of them under African flags like that of the Gambia. The Kairos and the Virat, pointed out by sanctions bodies from the United States, the United Kingdom, the EU, Switzerland and Canada, are perfect examples of this network: very old ships, with questionable maintenance, designed to operate in the legal shadows that allow real owners and routes to be hidden. Its function is key because oil continues to be the Kremlin’s financial key: only in October, Russia entered 13.1 billion dollars for sales of crude oil and derivatives, although the figure already shows a significant decrease compared to the previous year. Damaging these ships (and above all, showing that no part of the Black Sea is safe) turns each transit into a calculated risk. The ultimate goal it is erosive: increase insurance costs, slow down logistics, increase the risk perceived by intermediary companies and force them to reconsider their collaboration with Moscow. He sinking of the M/T Mersin off Senegal, although it is not proven that it was the work of Ukraine, it illustrates the growing deterioration of a fleet that operates with minimum standards. The transformation of the Sea Baby. The Sea Baby have established themselves as the spearhead of an unprecedented Ukrainian naval revolution. Their early versions acted as medium-range explosive platforms; but the updated prototype, shown by the SBU in October, has multiplied its capabilities: 1,500 kilometers of autonomy, high speeds, autonomous navigation supported by AI and up to 2,000 kilograms of payload. Now they can operate anywhere in the Black Sea, from Odessa to the Bosphorus, from Crimea to global oil routes. This expansion underlines an evolution with two simultaneous layers: Ukraine is destroying the historical Russian hegemony in the Black Sea, and it is doing no traditional boatswithout sailors and without risking lives, relying on a naval concept that Moscow has not managed to replicate with the same efficiency. The combination of drones, Western satellite reconnaissance, electronic intelligence and autonomous platforms makes the Russian navy look increasingly corneredforced to disperse fleets, reinforce escorts and operate with a caution that reduces their freedom of action. Geopolitical leap and message to third parties. That the blows occurred a few km from the Turkish coast is not a technical whim: it means that Ukraine has crossed a symbolic and geopolitical threshold. For the first time, it has attacked Russian naval infrastructure in areas where global trade, NATO and maritime law converge. The images verified by BBC show drones hitting ships that were assisted by the Turkish coast guard, in an extremely sensitive environment for Ankara. Türkiye reacted with a very low profilelimiting itself to putting out fires and rescuing crews, aware that openly protesting would go against its difficult balance between Russia, NATO and its own regional agenda. But the message is there: Ukraine is no longer limited to destroying Russian ships within the space that Moscow considered comfortable control; Now it can harass energy trade even when plying international routes. This reconfigures the calculations of insurers, shipping companies and states involved: even Kazakhstan protested after the Caspian Pipeline Consortium terminal was affected, underlining that the Ukrainian campaign is touching multinational interests. Hitting ships, but also infrastructure. One day after the attack on the oil tankers, the Sea Babies attacked the CPC marine terminal in Novorossiyskforcing it to stop operations. Is the third time In just a few months, Ukraine hits this crucial enclave. The emerging equation it’s clear: disabling ships is just one part; degrade the infrastructure that allows oil exports, another even more destructive for Moscow. Ukraine is applying a dual strategy that suffocates the Russian oil system at both ends: the ships that transport the crude oil and the points where they are loaded. The result is a predicted fall of 35% in Russian oil revenues in November and a fiscal impact that already force unpopular measures how to increase VAT or suspend payments to veterans, a sign that the Kremlin’s “war economy” is beginning to feel the accumulated pressure. A … Read more

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