cheap

I thought that in 2026 I could buy a cheap cell phone without worrying about anything. big mistake

by

I have spent half my life being especially critical when analyzing phones and, on the only occasion that I have decided to stop being so, I have hit a wall. We are in 2026, a year in which one might think that at this point in the game practically any phone newly launched on the market must work well. Mistake, big mistake. So I want to tell you how the component crisis in the technology sector and, to be honest, a certain apathy on the part of manufacturers, continues to make choosing an affordable mobile phone complex in 2026. Either we look closely at what we buy, or it may turn out to be a failure. The objectives. A mobile to send and receive WhatsAppsliterally. I wanted a phone whose main use was to manage communication with clients in one of my projects and, taking advantage of the fact that I had a new purchase, use it as GPS when I ride a motorcycle. The demands were minimal, there were practically no requirements other than that the cell phone worked decently. The expectation was not high either: I know that a low-end mobile phone does not work like a high-end one, not even like a mid-range one. I was just looking for something functional and simple. The search. I started the search, with phones over 100 euros. For that price it was practically impossible to access basic phones like the LITTLE M7which at least has a Snapdragon 685 (a processor, mind you, from 2023), so I had to continue lowering the bar. I ended up finding a 199 euro phone on sale for 89 euros on Aliexpress. One with 8 GB of RAM, 256 GB of internal memory… and a Helium G100 Ultra. the drama. The Helio G100 Ultra is an entry-level processor launched in 2024, relatively modern, and should have enough capacity to run basic applications. That’s what I thought. It’s been a while since I’ve tried an entry-level model. I thought that in 2026 things would be a little better, and I couldn’t be more wrong Almost two seconds to open the camera, lag in the launcher with the mobile newly configured, constant freezes and a performance that, after having tried other cheap mobile phones of a similar price (without offer), was simply unacceptable. And no, I’m not going to tell you the model so as not to draw blood, but it is one of the most popular mobile phones in Spain. Blind. One of the supposed advantages that it has brought us the semiconductor race is all about performance. For some time now, in certain ranges, my recommendations when asked which mobile phone to buy for The same does not happen with the entry ranges. Processors like Helium G99Helio G100, and even some Snapdragon 600 series (or Gen 6) are still barely moving basic apps. And the worrying thing is not how the phone performs right out of the box (which already performs poorly), it is how it will perform in a few years with some hardware degradation, system and app updates. big horse. At this point in the game there is something that is very clear to me, something that I have always defended: the processor It is much more important than we can think as average users. It is the heart of our mobile: The Gross Performance Manager The person in charge of the modem who will make us have better or worse coverage The element behind photo quality and camera performance The one that allows the final audio quality to be better or worse The one that helps to manage energy consumption more or less efficiently And here, even though the chip race continues at its pace, the high-end processors from a few years ago are noticeably superior to the entry-level ones. So between that high end of 2024 full of chicha and that newly released entry range… I’m clear about what I should have done. Image | Xataka In Xataka | Best mobile phones in quality price. Which one to buy based on use and nine recommended models

the explanation points to a cheap Iranian drone

by

If we stage a AH-64 Apache of about 25 million dollars and, on the other side, an Iranian drone Shahid of about $35,000, the answer seems written before starting. One is an attack helicopter designed to operate in hostile scenarios; the other, a low-cost ammunition associated with long-range attacks. But the current war is leaving less and less room for these inherited intuitions. What we have seen near Oman points just in that direction. The incident. According to the United States Central Commandthe AH-64 Apache went down on June 8 near the coast of Oman while patrolling regional waters. Its two crew members were rescued by US forces in about two hours and are stable, although the cause was still under investigation in the official communication. The trickiest part comes next: The New York Timesciting US officials, attribute the crash to the impact of an Iranian Shahed one-way attack drone. The great unknown. This distinction is important because not even the version that points to the Shahed completely closes the sequence. Military investigators were trying to determine whether the Iranian drone hit the Apache deliberately or if it all happened as a reckless accident in congested airspace off the Omani coast. In other words: the result is already extraordinary, but the intention remains under examination. Why is it surprising?. Shahed’s basic models are not typically intended to pursue moving targets such as a helicopter. Mark Canciansenior advisor at the Center for Strategic and International Studies cited by the aforementioned newspaper, explained that these versions depend on GPS guidance and pre-programmed coordinates to attack stationary targets at long distances. If the impact is confirmed in these terms, we would not be facing a routine case, but rather an episode that forces us to look closely at the trajectory of the drone, the environment and the possible existence of modified variants. A more present threat. Loitering munitions and drones are changing the way we operate in the air, also for platforms that were born in another technological era. The US Army reflects this in its own exercises: last year it presented the AH-64E Apachev as an adaptable solution to the UAS threat after a live fire demonstration. That context helps to understand why the incident near Oman is not just a striking anecdote, but part of a much broader concern. In detail. In exercises carried out by the US Armythe AH-64E appears using electro-optical, infrared and radar sensors, in addition to missiles, guided rockets and the 30 mm cannon to confront drones. The other plane is the survival of the aircraft itself: BAE describes the AN/AAR-57 as a warning system for US and allied fixed and rotary wing aircraft against infrared missiles and hostile fire, compatible with chaff, flares, radio frequency decoys and DIRCM/ATIRCM systems. But there is no invulnerability. This list of capabilities should not be confused with an absolute guarantee against any scenario. It is one thing to detect, track and destroy drones in controlled exercises, and another to operate in a real environment where there may be unexpected trajectories or just seconds to react. The US Army itself left a relevant nuance in March 2026: Many pilots had not conducted air-to-air combat with the Apache, so they were still developing tactics, techniques and procedures for that mission profile. The equation has changed. The episode does not demonstrate that a cheap drone can always prevail over a much more sophisticated platform, nor that the Apache is vulnerable by definition. What it does leave behind is an idea that is difficult for any modern military to ignore: a low-cost threat can disrupt an operation, elevate risk, and expose even highly advanced systems if conditions align. That is one of the lessons that is pushing armies to adapt: ​​the price of a weapon is no longer enough to anticipate its impact. Images | Richard Kim/2nd Combat Aviation Brigade In Xataka | Silently, Russia has deployed a sophisticated network of satellites with one mission: to leave all of Europe without GPS

DeepSeek is good, pretty and very cheap. And above all, the weapon to create a Chinese hardware industry independent of Nvidia

by

The arrival of DeepSeek-V4-Pro It hasn’t caused that much of a stir. like the one caused by DeepSeek R1 a year and a half ago, but we may be facing an even more important model. If that version revealed to the world that China was advancing spectacularly in this race, this other one is beginning to allow us to glimpse something else more interesting. What most people see is a very decent model and above all “low priced”. Which hide the company It’s another more important thing: achieve independence from Nvidia and US hardware. what has happened. Last Friday, those responsible for DeepSeek announced something surprising: their promotional offer with a 75% price cut to use their DeepSeek-V4-Pro model will be maintained permanently. That makes this model offer very decent features (but not exceptional) for a really low price: 1M entry tokens 1M tokens output DeepSeek-V4-Pro 0.435 0.87 GPT-5.5 5 30 Opus 4.7 5 25 Gemini 3.5 Flash 1.5 9 Good, pretty and very cheap. It is true that the performance of DeepSeek-V4-Pro is inferior to that of rival models from OpenAI, Anthropic or Google. Artificial Analysis tests indicate that the DeepSeek model is at a very good level, but it is also much cheaper than its competitors. This is especially relevant for agentic tasks that consume many tokens and that with this model become accessible and very affordable. According to Artificial Analysis, DeepSeek is close to the performance of the best models in the industry, and although it is slower in its responses, it is also much cheaper than the frontier models from OpenAI, Anthropic or Google. A different strategy. How is this company going to make money? It does not have subscription plans like its local competition (GLM, Kimi) or the western one (ChatGPT Plus, Claude Pro). It also does not have voice or image models. It does not have an AI agent for programming that competes with Claude Code. It publishes the open weights of its models and shares its technical innovations with the industry (and with its competitors). For those who closely follow the company and these decisions, the strategy is clear. DeepSeek’s goal is not to win the AI ​​model race. Their goal is to build a Chinese AI hardware industry that doesn’t depend on Nvidia or TSMC… and get paid their share in that process. Hardware independence. China has a structural problem in this AI race: sanctions and vetoes imposed by the US make you unable to access the most advanced chips nor to ASML UVE photolithography. And since China cannot currently compete in terms of computing power, what its companies are doing is ensuring that their AI models need less computing power to achieve similar results. Efficient architectures. The Mixture of Experts (MoE) and Multi-head Latent Attention (MLA) architectures are two key weapons in this strategy. The first already existed but was adapted by DeepSeek for their model: with it only part of the total parameters of the model are activated to answer the query without losing precision. What MLA does is compress the attention information (the so-called KV Cache) with which the model maintains the context of a conversation, reducing it by 90%. Both techniques allow us to reduce the need to use high-speed HBM memories, something that is also striking in order to reveal DeepSeek’s probable strategy. The importance of KV Cache. As the GDP analyst explains in Xthat use of MLA allows that for one million tokens, DeepSeek-V4-Pro only needs 5.48 GB of HBM memory. Competitors like Zhipo AI, which develops GLM 5, need 60 GB for the same, while Alibaba’s Qwen 3 needs 89 GB. This advantage allows DeepSeek to offer much lower prices to obtain performances similar to those of its competition, but it also means that DeepSeek models can run on Chinese memory chips that cannot compete in speed with HBM modules. Goodbye HBM, hello NAND and SSD. These innovations open the door to the use of NAND memories and even SSD drives to process this data, and there YMTC enters the scenea Chinese Flash memory manufacturer that is slowly becoming a global giant. Also CXMTwhich manufactures DRAM memoriesbecomes an alternative here and the reason is equally interesting: DeepSeek introduced a memory search module in LLMs called Engram which is also intended to avoid excessive dependence on HBM memories. How to bypass the CUDA monopoly. Nvidia continues to have a fundamental element in CUDA to maintain its market dominance, but here DeepSeek too has proposed an alternative. Is called Tile Kernels and these are software cores created with TileLang (a variant of Python for this field) that allow governing advanced AI chips (GPUs). Huawei as an invisible ally. Those responsible for Huawei recently indicated that its new Ascend AI supernodes fully support DeepSeek v4 models. Precisely this provides another fundamental advantage to the company, which thus avoids (at least in part) total dependence on the use of Nvidia chips and prepares to further strengthen Huawei’s relevance in a market in which until recently Jensen Huang’s company was queen and mistress. Open models to attract the hardware industry. US companies continue to maintain their closed and proprietary models, but DeepSeek is one of the many Chinese startups that publish them with open weights. With this, what she and the others intend to do is not only attract AI developers and users, but also create a hardware ecosystem that adopts these architectures. DeepSeek invites its rivals to use techniques such as MoE or MLA precisely so that all these advances become a de facto standard and hardware manufacturers also adopt them and integrate them in an optimized way into their designs. A round of 10,000 million to advance. The company is also preparing a financing round in which they intend to raise 10,000 million dollars and with which they would achieve a valuation of between 45,000 and 50,000 million dollars. Still far from the mammoth valuations of OpenAI or Anthropic (already close to a billion dollars) but certainly … Read more

There is a battle to have the AI ​​model that programs best. And a good, pretty and very cheap rival has appeared in it: Cursor

by

Cursor has introduced Composer 2.5a generative AI model specifically intended for one thing: programming well. How good? Well, according to this startup, it does it as well as the best models of the moment, Claude Opus 4.7 and GPT 5.5, but it also does it for a lower cost. The challenge is striking not only because of what it means for Cursor, but because of how they have created that model: it turns out that it is based on a Chinese AI model. AI models specialized in one thing. While OpenAI and Anthropic try to develop general-purpose models—they do a lot of things really well— Cursor you have decided to focus on a specific task. The AI ​​startup has created an AI model specialized in programming, and has done so by arguing that a billion parameters are not necessary to compete with the best. Devoting yourself to a single thing allows you to not only gain efficiency, but also costs. This is not a decathlete, but a specialist in the 200 m event, so to speak. As good as GPT-5.5 or Claude Opus 4.7? That’s what they say in Cursor, because according to their tests with several specific programming benchmarks, the performance is on par with those two models that today are the great references both in programming and in other areas. And much cheaper. These results are also especially interesting when we add the cost factor. The average cost per task in the CursorBench 3.1 benchmark showed that Composer 2.5 managed to solve almost 65% of all tests for a cost of just $0.3. Opus 4.7 max and GPT-5.5 xhigh managed to reach that 65%, but at much higher costs: just over 4 dollars in the case of GPT, and 11 dollars in the case of Opus. The difference is abysmal. He API access price demonstrates the differences: 0.5 dollars per million input tokens 2.5 dollars per million output tokens, when Claude Opus 4.7 is 5/25 and that of GPT-5.5 is 5/30 respectively. Textual feedback. Unlike models that only learn from the final result, Composer 2.5 has been trained with a reinforcement learning technique (Reinforcement Learning) that allows us to offer clues about what is happening if errors are being made. This allows the model to recalibrate and act as a transparent teacher. One that also corrects word by word as it solves the exercise, not just when seeing the final result. 85% of the training budget has been dedicated exclusively to reinforcement learning, calibrating the model not for chat, but to execute code refactorings or fix bugs in real time. A model “born” in China. Those responsible for Cursor themselves have explained that Composer 2.5—like its predecessor, Composer 2launched at the end of March—is a model derived from Kimi K2.5, the AI ​​model of the Chinese startup Moonshot. Although that is the basis, already in Composer 2 the training and post-training tasks manage to improve the behavior in a very notable way in programming benchmarks and also in others such as Terminal Bench that evaluate the agentic behavior of these models. Cursor gets older. This startup became famous for creating a programming AI agent that was a pioneer in that fever we live for vibecoding. The user experience is no longer that of programming, as in traditional IDEs (Integrated Development Environments), but rather that of directing the machine to program it for you. Composer 2.5 doesn’t just program: it understands the structure and relationships between files, and turns Cursor into a much more competitive AI company, because it no longer depends on being able to work with Anthropic or OpenAI models, for example. Having both the AI ​​agent and the model processing everything makes it a much more competitive solution. Elon Musk has Cursor in his sights. Cursor’s good performance has led to growing interest in buying this company even before it becomes too big. Elon Musk knows this well and Grok, xAI’s model, is not so popular in the programming field. In April we learned that SpaceX had reached an agreement that gives you the option to buy Cursor for 60,000 million dollars. It would be a promising deal for both, because Composer 2.5 has already used Colossus’ infrastructure to train, and xAI could thus try to gain market share in the juicy enterprise sector. In Xataka | Elon Musk knows that TSMC is overwhelmed: Terafab is his idea to completely change the global chip industry

This is the Basque project that wants to convert waves into cheap electricity

by

On May 12, a 42-meter steel buoy was towed from the Bilbao estuary to the open sea off Armintza. It is not the first time he has made that trip. It already did it in 2016, endured three winters with waves of up to 14 meters, generated electricity and returned to port with something equally valuable: data. Now it comes back improved. The Basque firm IDOM has released the Marmok A-5 again in the Cantabrian Sea, and this time he knows exactly what he has to prove. It’s not just another test. The promise of wave energy is not small. As he explains to the magazine Renewable Energies IDOM wave engineer, Patxi Etxaniz: “The amount of resources available worldwide is brutal; if we are able to obtain that energy in an economically profitable way, we have solved the global energy problem.” The problem, until now, has always been the same: extract it without ruining yourself in the attempt. The race to achieve this is fought by just a dozen or fifteen actors around the world: the Swedish CorPower, several Scottish engineering companies, companies from France, Wales, Finland and Italy, and Asian actors from Korea, China and Japan who, in the words of Etxaniz, “do not publish anything, they are very discreet.” IDOM is already in that group. The Cantabrian piston. The Marmok is, in essence, a buoy with a cylinder of water inside. As detailed Europe Wavewhen a wave arrives, that column of water rises and falls like a piston, compressing and expanding the air in an upper chamber. In this way, this air flow moves a turbine that generates electricity and, finally, an underwater cable takes it to land. The technology is called OWC – oscillating water column – and the new Marmok has improved it on three fronts, according to BiMEP: new turbine with controllable blades, intelligent control system with onboard batteries, and radically simplified anchoring. This latest change was born directly from one of the most costly and dangerous problems of the first campaign. As Etxaniz explained: “The anchorage we had worked well, but we needed a lot of divers, and they are expensive, and their work is dangerous: underwater, with ropes with a lot of tension, one of them whips you and you can have a serious problem.” Problem detected, problem solved. In this new campaign, in addition, the Marmok will connect to the grid for the first time through the HarshLab platform, a floating laboratory integrated into the BiMEP infrastructure, which will allow both to evacuate the energy generated and to monitor the behavior of the system in real time. Twelve years of work. The Marmok did not appear overnight. Its first models were tested at the El Pardo Hydrodynamic Experience Center in 2012. From there they went to the Tecnalia laboratories, then to the BiMEP offshore facilities in Mutriku, and finally to the open sea in October 2016, where it became the first wave energy converter connected to the electrical grid in Spain and one of the first in the world. Behind that journey was the team from the Basque company Oceantec. IDOM saw the potential, hired them en bloc and integrated them into its structure. More than a decade of work, financing from the Basque Energy Agency and support from the European innovation program EuropeWave later, what began as a laboratory prototype is today, according to BiMEPa device ready to advance towards pre-commercial phases. As Borja de Miguel, project manager at IDOM, summarizes: in statements collected by Europe Wave: “Achieving secure installation and grid connection at BiMEP is a key step in bringing wave energy closer to commercial reality.” What’s coming Over the next few months, the team will verify the performance of the new systems and progressively increase operations. The data collected by this campaign will serve two purposes: demonstrate results to EuropeWave and decide what the next phase of development will look like. The objective is not academic. It means lowering costs until a Cantabrian wave can compete, in price, with any other energy source. There is no date for that yet. “It will depend on the investment,” says Etxaniz. But the window exists, the group of applicants is small, and Basque engineering has been learning to read the sea for more than ten years. The Marmok already knows how to survive three stormy winters. Now you have to learn how to do it cheaply. Image | EuropeWave Xataka | For years, wave energy was the ugly duckling of renewables. AI and data centers have taken a turn

BYD promised them very happy by putting very advanced ADAS in very cheap cars. Until the RAM crisis came

by

In recent years, BYD had turned its brand new advanced driving system into one of the biggest arguments to confront Tesla. And having this type of technology in affordable cars can be attractive to the consumer, but it has a cost that other companies can hardly absorb. BYD thought so, but the RAM crisis It has stopped him, and the context is now much more complicated. Prices go up. BYD just announced in China a 21% increase in the price of the ‘DiPilot 300’ option (basically its “God’s Eye” in its version with LiDAR), which goes from 9,900 to 12,000 yuan (about 1,560 euros). The company justifies the measure by the “significant increase in global storage hardware costs.” In other words, DRAM memory and storage have become so expensive that they can no longer absorb the cost without passing it on to the customer. Until now, no major manufacturer had so explicitly linked a price increase to the memory market, according to collect South China Morning Post. In detail. The ADAS Modern ones (and especially those that integrate LiDAR like those from BYD) are very demanding on memory. They need high-performance chips to process LiDAR point clouds in real time, run driving models, and store route data. The problem is that this same type of memory is being absorbed en masse by artificial intelligence data centers, which account for most of the global production of DRAM and NAND. The prices of these chips have entered what analysts call a “supercycle,” with increases that according to TrendForce are around 55-60% in conventional DRAM this year, but that in premium automotive segments (which also use DDR5) have reached up to 300% in free market price. A problem of scale. BYD’s colossal deployment makes the problem especially bulging in its case. The company has installed your “God’s Eye” system in more than 2.85 million vehicles as of March 2026, generating approximately 180 million kilometers of driving data per day, according to own data of the signature. At that scale, every extra cent in memory multiplies into millions. On the other hand, BYD closed the first quarter of 2026 with its worst net profit in three years: 4.08 billion yuan, a drop of 55% compared to the same period of the previous year, according to figures published by the company. In this context, maintaining prices without making a move has become unsustainable for the company. They are not alone. Chery, Xiaomi and the Huawei Aito brand prices have also increased on models with similar advanced driving systems in recent months. William Li, founder and CEO of Nio, counted in January that the biggest cost pressure of the year would not come from raw materials, but from memory. What changes for the buyer. The founding promise of “God’s Eye” was that autonomous driving would no longer be an expensive privilege. As we counted almost a year agothe experience of the system on the highway (even in the most economical model, the Dolphin Surf/Seagull, which sells for around 9,000 euros in China at the exchange rate) was genuinely impressive. Lane keeping was impeccable, autonomous lane changes were well executed and traffic management rivaled other premium range systems. BYD even planned to distribute it as standard in all its models, regardless of the price. Although that narrative is not dead, it is beginning to have nuances. At the moment, the version with LiDAR (the most capable) is already a payment option that has just become 21% more expensive. And now what. From Counterpoint Research they point that the blow will be uneven: low-end models simply will not carry this technology, and high-end ones have less price-sensitive buyers. The greatest impact falls on the mid-segment, where BYD’s value proposition was most disruptive. As the markets are, we will have to wait to find out what direction the company finally takes. Cover image | BYD In Xataka | Cuba is experiencing a brutal energy crisis, so a Cuban has used ingenuity to fuel his car: charcoal

If you were waiting for Xiaomi to launch cheap cars, its CEO encourages you to continue waiting seated

by

Xiaomi has been in the automobile market for a couple of years (although it is still we are waiting for your arrival in Europe), and in contrast to what the brand offers in other areas such as smartphones, the company wants to position itself rather high in the price table of its cars. Lei Jun, CEO of Xiaomi, confirmed during a live broadcast on April 17 that the brand has no intention of launching electric vehicles below 100,000 yuan (about 12,500 euros) in the coming years. Here, as expected from the figures, he talks about the Chinese market. Communication. Lei Jun made these statements during a live autonomy test in which he drove a new generation SU7 Pro from Beijing to Shanghai (1,265 kilometers) with a single stop to charge. On the way, he took the opportunity to chat with the chat, a calculated communication strategy that has been noticed. Luckily, during the talk, we were able to find very interesting statements from the head of the brand himself and get an idea of ​​his roadmap. No to the cheap car. According to counted Jun during the broadcast, today’s competitive electric cars increasingly depend on intelligent driving systems, and that type of technology has a high cost that does not fit with a sales price below that barrier of 100,000 yuan in China. According to collect the media CarNewsChina, Lei himself recognized that the new generation of the SU7 It accumulates more than 100 improvements compared to the previous model, with an increase in material costs of almost 20,000 yuan, but its selling price only rose by about 4,000 yuan. For Xiaomi, the equation applied to an entry-level car simply does not add up. Where Xiaomi does want to be. The updated SU7 starts at 219,900 yuan (around 27,500 euros), and the brand’s direction points even higher, as the firm is ready to launch its SU7 Ultra which already competes in the high-performance segment, and in the not too distant future models such as the YU7 GT or a premium variant of the SU7 will also appear, according to they count from ChinaEVHome. We will have to see prices when the firm lands in Europe with its SU7, but everything indicates that Xiaomi wants to consolidate itself within the field of the mid/high range of automobiles. The Chinese car is not synonymous with cheap. Xiaomi is not the only one that avoids the price war in the entry segment. He Xiaopeng, president of XPeng, declared during the presentation of MONA M03 that his company also has no plans to go below that 100,000 yuan threshold. Among the reasons it gave were too tight margins, unsustainable investment in smart technology and real risk of a destructive price spiral. What the numbers say. Sales data in China reinforce this reading. And it is that according to figures collected by CarNewsChina, entry-level electric cars, such as the Wuling Hongguang Mini EV or the BYD Seagull (Dolphin Surf here in Spain), registered year-on-year falls of almost 58% in the first months of 2026, partly due to the end of tax exemptions on purchases. The sedan and utility vehicle segment as a whole also fell almost 20% year-on-year in March. The volume is there, but the profitability is not. Promises. All in all, Lei Jun left a door ajar in the long term. Their goal is for Xiaomi to be among the five largest car manufacturers in the world. Reaching that scale would, sooner or later, require greater price coverage. But for this scenario to come true, there still seems to be time. Cover image | Xiaomi In Xataka | Journey to the center of the Chinese motor (part 2): I have seen the future of cars in Beijing and yes, it is electric (and very cool)

Fed up with paying almost 8 euros for a Guinness, someone thought of setting up an index to find cheap beer

by

How delicious is that little beer that you drink right after leaving work or after a paddle tennis game and how angry it is when you find out that they have raised the price. Matt Cortland He paid €7.80 for a pint of Guinness in Dublin in March 2026 and didn’t like it one bit (the price, not the beer). So instead of criticizing the waiter or posting a review on Google complaining like some people do, he adopted another strategy that was slightly more laborious but much more effective (judging by its results): a very complete price index where he would know where to drink the best and at what price. Because revenge, like beer, is served cold. The project. Is called Guinndex and is independent of the very famous Irish beer brand. You go to the website, enter a pub, a city, a county or a postcode in the box and it returns pubs and the cost of a pint, as well as useful information such as its location or its score. Or you zoom in on the map to see with a traffic light map which taverns look cheaper than others. A good way to save if you travel to Ireland and fancy a pint of Guinness. In fact, it has very diverse rankings ranging from how long it takes to earn a pint (depending on salary) to pubs named after animals or the best pub names (praise be the “Hairy Lemon”). Today it has almost 6,500 registered pubs in the 32 counties of the country and almost 1,300 prices verified and rising thanks to anonymous contributions from users. The price index for Dublin. Guinndex Why is it important. Because the Irish Central Statistics Office stopped tracking the price of a pint since 2011, leaving a data gap of more than a decade in a country where Guinness is much more than a beer. And although Guinness is almost a religion in Ireland, it is the same everywhere: no one knows for sure if they are overcharging you compared to the standard price or how much extra. The Guinndex fills that gap with real, verified data, not estimates. Furthermore, it does so publicly and for free, so that it allows obtaining an objective reference so that consumers have information and can put pressure on prices. It’s the market, friend. On the other hand, and leaving aside the anecdote of finding where to drink cheaper, what it shows is relevant: that the cost of carrying out a complex idea has plummeted and streamlined so much that a single dev is capable of setting up a project of this magnitude in just 48 hours when before it took weeks of work, a certain budget and a team. Context. Matt Cortland likes AI, data and Guinness, as he himself admits on the project website. He is an American engineer based in London with strong ties to Ireland: his partner is irishlived and trained there with the George Mitchell scholarship and course the Creative Digital Media master’s degree from TU Dublin. He is not just a tourist they are trying to scam. The project came at a critical time: Diageo, the company that owns Guinness, had applied several price rises in a row and some pubs had taken the opportunity to inflate margins. If you’re not careful, you can pay up to €11 for a pint, although the average price in Dublin is €6.94 and €6.06 nationwide. How has he done it. With an AI agent named Rachel who looked human, understood Irish humor, and had a Northern Irish accent (after several tests, she concluded that this worked best), as its author tells. The task was simple and quick: call, ask the price of a pint of Guinness, say thank you and hang up. Few people discovered that it was a chatbot and there were all kinds of responses, even waiters who offered to buy him a round. During the St. Patrick’s weekend he called 3,000 pubs, answered more than 2,000 calls and more than a thousand pubs provided a price: he already had the Guinndex base. The technical stack was jack, knight and king: the Google Maps API, ElevenLabs for the voice and agent logic, Twilio for making the phone calls, and Claude for extracting Guinness prices from the transcripts. Cortland explains What cost him the most was time, since he only invested about 200 euros. The consequences. The most immediate impact is behavioral: Cortland account that the owner of a pub lowered the price of his Guinness by 0.40 euros and then updated the information in the Guinndex himself. When there is price transparency and it is available to everyone, it is capable of changing behaviors. However, the biggest consequence is the technological moment in which we live: three APIs, 200 euros and a weekend are enough to build a project from scratch, with real utility and that is already changing prices. The bottleneck is no longer money or infrastructure: it is knowing what problem is worth solving. In Xataka | Spain can tell itself as many times as it wants that it hates Cruzcampo. The figures say a very different thing In Xataka | We humans like beer. The big question is whether we like it enough to have invented agriculture Cover | Guinndex and Christopher Zapf

China has shown that the good and cheap electric car exists. So Citröen has had to get its act together

by

China is doing very well with the cheap electric car. And if not, tell them BYD Dolphin Surfa 100% electric vehicle that the company finances at just over 3% for 125 euros per month. Without financing it costs 19,990 euros which, after aid, can become 11,780 euros. Saving exceptions like Dacia Springwhich compete in a much lower league, Western manufacturers have no choice but to respond. And Citröen has been the first to do so. 11,700 euros. Citroen has been lowering the price of its ë-C3 for more than a yeara car that was launched on the market for more than 20,000 euros and that, since its launch, has been reduced by almost half. Now, after aid, the Citröen C3 costs 11,700 euros, with an eight-year warranty. What it offers. With a price practically identical to the Dolphin Surf, an almost identical autonomy (220 km under the WLTP cycle), and a technology relatively similar to that of the Chinese alternative, we are finally talking about a price at which the company can be competitive. What China offers. Both vehicles, in their most economical version, have LFP batteries. The main difference is in the charging system: 65 kW for the BYD and 30 kW for the Citröen. The key, however, is not in the specs: it is that BYD has been offering a competitive price since its arrival in Spain, which has catapulted it into the top 3 of the best-selling electric cars in the country. Beyond Tesla. There is no electric car that sells more than the Model 3 in Spain. This is to be expected, given the reliability, range and price of the vehicle. Just below Tesla, we have the BYD Dolphin Surf, which has sold more than 1,332 units so far this year (compared to 2,489 for the Model 3 and 2,023 for the Model Y). Taking into account that they play in completely different leagues, the BYD case is a resounding success. A purely urban car that sells practically twice as much as its direct rivals. The electric C3 has 634 units sold, placing it in the top 9. The ranking points to something very clear: the price is the main purchasing factor for the Spanish electric companyand Western manufacturers will have to tighten their grip if they want to compete with China. In Xataka | The electric cars with the most autonomy that can be bought in 2026

The depressing future of cheap mobile phones, in two graphs that are a death sentence for the low-end

by

Quick, make a wish. The motive behind these lines is more difficult to see today than a four-leaf clover: the Realme C71 (which we tested less than a year ago) came on the market with 8GB of RAM, 256GB of storage and a RRP of 149 euros. A species in extinction, something impossible in 2026. We are facing a paradigm shift in the mobile industry. In recent years we have seen how manufacturers benefited from an excess supply of memories that made it possible to build combinations of RAM and storage at ridiculous prices. That era is over: a recent report from Counterpoint Research confirms that the cost of components is suffering its greatest pressure in a decade and the outlook is bleak: either brands sacrifice their profits or pass the cost on to the consumer. Or both and an extra: the entry range is disappearing in every sense. What has happened to the price of NAND and DRAM. The price increase in the first quarter of 2026 has been abysmal and without close precedents: RAM memory (DRAM) has suffered a quarterly increase of more than 50%. NAND Flash has seen an even more aggressive rise, exceeding 90% compared to the previous quarter As a picture says a thousand words, the graph prepared by Counterpoint Research: Source: Counterpoint Research Price Tracker Why is it important. This phenomenon is not a simple fluctuation or a temporary shortage, it is a structural change that puts the economic viability of many manufacturers in check. DRAM (speed and multitasking) and NAND (storage capacity) are essential in the user experience. Until now, scaling these memories was cheap, but not anymore. In the entry range, the cost of memory already represents almost half of the manufacturing “ticket”, sometimes exceeding the cost of the processor or the screen itself. With current profit margins, absorbing this impact is impossible: either the price is raised, or it is sold at a loss. The market has already revised downwards global shipment forecasts for 2026: Counterpoint estimates a drop of 2.1%, while IDC is more pessimistic and projects a decline of 12.9%, which would exceed the 12% contraction recorded in 2022. Context. The culprit has its own name: generative artificial intelligence. More specifically, the explosion of artificial intelligence infrastructure. The data centers that power AI models are demanding memory on a large scale, thus becoming direct competition with mobile manufacturers for the production of Samsung, SK Hynix and Micron. Capacity is finite and AI takes priority for reasons of profitability. If we also take into account that the latest generation processors manufactured in 2nm they have become more expensivewe have the perfect storm. Retail. The increase in the price of memory does not affect all mobile phones equally. This is how the weight of memory is distributed in the total cost of the device: The entry range ($200 or less) is the most affected. With a typical configuration of 6 GB + 128 GB, memories already represent 43% of the total cost of the device. An increase of 30 dollars per unit is estimated. In the mid-range (400-600 dollars) the combination goes from 25 to 36%, which can mean 60 to 80 dollars per unit. In the premium range (over 800 dollars), the increase is more diffuse and they are also exposed to double pressure, that of the most expensive memories and that of the processors, which translates into increases of between 100 and 150 dollars that we will begin to see reflected in the launches of the second half of the year. How will the user notice it?. Counterpoint has estimated these price increases between $30 and $150 depending on the range, but the cushioning is not always going to be so obvious and direct. In the entry range, where the margins are so small, another way out is to cut the catalog to a minimum. We will see manufacturers “killing” the base model to force the jump to the next price step, much smaller catalogs and, above all, technical stagnation. The old 128GB will return as standard and, in the worst case, we will see steps backwards with the use of slower and older memories (LPDDR4X) to try to save the furniture in the mid-range. In Xataka | Best mobile phones in quality price. Which one to buy based on use and seven recommended models In Xataka | Having an AI on my phone that works without an Internet connection is more useful than I thought: this way you can start it Cover | Xataka, Pepu Ricca

Log In

Forgot password?

Forgot password?

Enter your account data and we will send you a link to reset your password.

Your password reset link appears to be invalid or expired.

Log in

Privacy Policy

Add to Collection

No Collections

Here you'll find all collections you've created before.