La primera tarde de octubre que sales a correr te das cuenta de dos cosas. Ya no hace el calor de agosto, y las zapatillas viejas del armario no estaban pensadas para esto. A partir de ahí empieza la búsqueda de calzado, y muchas veces pasa por la gama de entrada de Adidas.
Las Runfalcon 6 de mujer son justo eso: unas zapatillas pensadas para rodar por asfalto cada pocos días, sin complicarte la vida. Ahora están rebajadas y no llegan a los 36 euros. Para empezar yo no gastaría más, porque los dos primeros meses no necesitas una zapatilla de competición. Necesitas una que amortigüe, que no apriete y que te deje pensar en la respiración y no en los pies.
Cloudfoam para rodar tranquila, no para batir marcas
Cloudfoam es la espuma de amortiguación que llevan estas zapatillas, pensada para el día a día y para tiradas de hasta unos 10 kilómetros. Y eso es lo que pide quien empieza: salir a ritmo de charla, 5 kilómetros por el parque, y volver a casa sin la sensación de haber corrido sobre una tabla.
Si en primavera te apuntas a una media maratón o empiezas con series, ahí sí pedirán relevo por algo con más respuesta. Hasta entonces, son de sobra.
Una horma de las de toda la vida
La horma es clásica, sin formas raras ni suelas exageradas. El pie entra y no hay semanas de adaptación. El empeine es textil y sintético, así que respira mejor que una deportiva de piel cuando el otoño todavía regala tardes templadas. La plantilla también es de tela.
Abajo lleva una suela de goma que agarra bien en asfalto y en la tierra compactada de los caminos del parque. El color de esta versión es negro con detalles en blanco y gris carbón (que no se ensucia a la primera charca). Van con medias tallas de la 36 a la 45 y un tercio, así que cuesta poco dar con la tuya. Y no es casualidad que estén entre las más vendidas de Amazon en zapatillas de asfalto para mujer.
Cómo sacarles partido las primeras semanas
Unas zapatillas de entrada rinden más cuando se usan con cabeza. Si estás empezando, este esquema funciona:
Tres salidas por semana, con un día de descanso entre medias.
Alterna correr y caminar hasta que aguantes media hora seguida sin ahogarte.
Resérvalas para correr: si también las llevas al trabajo, la espuma se gasta antes.
Para la cinta del gimnasio en los días de lluvia también valen. Ahí la suela de goma y la espuma blanda hacen el mismo trabajo que en la calle, sin sorpresas.
Merecen la pena si este otoño quieres pasar de caminar a correr tres días por semana: octubre deja unas cuantas semanas buenas antes de que el frío empiece a poner excusas, y con estas Runfalcon 6 la excusa del material desaparece. Lo que te ahorras frente a unas zapatillas de gama alta da para unas mallas largas y una camiseta térmica, que es lo siguiente que vas a necesitar cuando llegue diciembre y sigas saliendo.
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Ukraine has struck a major blow to Russia’s digital infrastructure. Since last Thursday, Ukrainian drones have carried out a series of attacks that destroyed three large data centers belonging to Yandex — known as “the Kremlin’s Google”— on the outskirts of Moscow. The Yandex Taxi ride-hailing app and the group’s payments service, Yandex Pay, have been temporarily taken offline. Ukrainian President Volodymyr Zelenskiy even said the bombings disabled Russian bots.
Artificial intelligence is also making its way into the world of books. EL PAÍS examined the use of AI in a sample of 119 popular books published in 2025 and 2026, analyzing titles that appeared on the bestseller lists at Amazon.es and the Spanish bookstore chain Casa del Libro, as well as the winners of a major literary prize.
They aren’t made of asphalt, have no traffic lights, and no cars drive on them. Yet, these unusual “highways” are already saving thousands of lives. In the Brazilian Amazon, conservationists have built rope bridges high up in the trees, allowing monkeys, sloths, and other jungle inhabitants to safely cross over the roads. The results are […]
As the controversy over AI safety grows, another debate is emerging. Bill Gates, the founder of Microsoft, has said that artificial intelligence should pay taxes to compensate for the jobs that will be destroyed by the deployment of this technology.
The 18th-century notion of the panopticon — a circular prison design with a guard station in the middle, allowing a single officer to enforce discipline by keeping watch over all the prisoners — has become real in the 21st century through AI-driven surveillance against workers: It’s the Amazon warehouse.
It should be no surprise that the company that harnessed technology to create a vast, $2.7 trillion empire would employ the same sophistication to enforce workplace discipline and tamp down insurgent unionization efforts. A recent disclosure of Amazon’s internal “employee relations” documents reveals just how extreme Amazon’s methods of warehouse surveillance and control have become.
Amazon employs what it calls the “Atlas” model, inputting into a computerized model a staggering amount of information on workers, their thoughts and behaviors, the workplace environment, and myriad other factors — “hundreds of data points,” according to the company. Atlas produces not just a granular measurement of ongoing worker unrest, worksite by worksite around the world, but also a prediction model for future organizing. It’s like the “precrime” police in the film Minority Report who use psychic powers to identify and apprehend would-be criminals before they act — except in this case, it’s an AI-driven tool used by the billionaire owners of one of the richest companies in history to head off rebellion among its low-wage workforce. And this is not Tom Cruise play-acting; it’s very real.
Workers anywhere who have endured anti-union campaigns can relate to stories of overbearing surveillance by management; the Atlas model, however, takes the spying to an entirely new level.
Details of the Atlas model came to light recently as a result of a legal dispute between Amazon and Unifor, the Canadian private sector union. Last year, British Columbia’s Labour Relations Board awarded union certification to Unifor at Amazon’s YVR2 warehouse outside Vancouver, finding that the company had broadly interfered in the union drive. It was the second union certification at Amazon in North America — the other being the 2022 union win at JFK8 in Staten Island, New York. But in contrast to the U.S., where Amazon has managed to stall bargaining for four and a half years because of weak labor laws, the B.C. Labour Relations Board ordered Amazon to recognize the union and negotiate. Contract bargaining commenced last December.
Not surprisingly, Amazon has dragged its feet in negotiations, prompting the union to file unfair labor practice charges with the Labour Board. Following a series of hearings earlier this year, the Labour Board found that Amazon violated provincial law. In August it ordered a remarkable step — first-contract arbitration at YVR2. That fight remains in play, but as a result of the legal proceedings, Amazon was required to turn over documents to the Labour Board and Unifor. Unifor has shared them with Truthout, and they can be viewed here.
Atlas produces not just a granular measurement of ongoing worker unrest, worksite by worksite around the world, but also a prediction model for future organizing.
In addition to the Atlas model revelation (beginning on Page 19 of the document), the material includes more than 100 pages that reveal in great detail how Amazon trains its frontline managers in union-busting. My colleague at the Center for Work and Democracy, Ben Fong, has written about this other portion of the disclosed material.
“Amazon’s own documents pull back the curtain on what workers have been telling us for years,” said Justin Gniposky, Unifor’s organizing director. “Behind the friendly PR, Amazon sees workers as property and treats their fundamental right to unionize as a threat to be managed and then eliminated.”
Amazon did not respond to Truthout’s request for comment on the Atlas model.
The documents describe the Atlas model as “a labor risk framework to clarify how Amazon evaluates emerging workforce issues, labor union targets, and internal or external labor threats.” The Atlas model ingests hundreds of data points: employee trainings completed; health and safety incidents, from simple first-aid cases to serious injuries; feedback from workers on management; worker tenure and turnover; the proximity of a warehouse to another workplace experiencing union activity; local minimum wage rates and other area economic conditions; and even the temperatures inside and outside of the warehouse.
Amazon seems especially thorough about scraping data from worker communications channels to plug into the Atlas model — the company’s internal “Voice of the Associate” (VOA) electronic bulletin board, the answers to digital questions posed daily to workers, and externally, forums including Reddit — “to understand the tenor of the discussion at the site level,” according to the documents.
“Behind the friendly PR, Amazon sees workers as property and treats their fundamental right to unionize as a threat to be managed and then eliminated.”
Atlas uses AI to identify phrases and “common keywords” to allow managers to do a “deep dive into the worker population driving the discussion.” Atlas also looks at the upvotes or other responses — positive, negative, or neutral — that the comments elicit, and the volume of those worker reactions. All of these data points go into Atlas and let managers “look around corners to identify developing themes” so they can “tailor strategic responses for addressing emerging risk.”
Amazon also tracks and documents all organizing activities that managers detect, and records them under the category of “employee relations events.” Each activity is assigned a severity score. “High severity” events include employees signing union cards, delegations of workers approaching management with demands, protests, sickouts, and work stoppages.
Atlas uses mathematical modeling to create a point system for all these data points, assigning a “labor score” to each workplace. The scale is further broken down into tiers, with the Tier 5 designation applied to facilities with high scores, where there is “no immediate perceived risk,” and Tier 1 applied to facilities where “future activity is imminent.” Amazon’s union busters focus largely on Tier 1 and 2 facilities.
Atlas produces extensive spreadsheets ranking different facilities and looking not just at raw “labor scores” but also at monthly trends. In 2024, the year the documents date from, Amazon was most concerned about union activity at 16 warehouses it had ranked as Tier 1. For instance, at LDJ5, a Staten Island sortation center across the street from JFK8, Atlas noted that leading issues of worker concern were “bathroom breaks, equipment, rest breaks, leadership/management, temperature.” The spreadsheet noted that “internal activists” — workers — were organizing, and that by looking at month-over-month trends, LDJ5 was experiencing “Risk Increase,” with the phrase placed inside a bright red box. At four of these Tier 1 facilities, the spreadsheet noted, the threat of union activity was sufficiently high to justify deploying Amazon’s “rapid response” team: union busters who travel to hotspots of organizing throughout Amazon’s global network.
Union organizing at Amazon is not just a battle over economics; it’s also a fight for basic freedom and democracy.
But the main value of Atlas seems to be predictive. For the Tier 2 worksites (“future activity is highly probable”), the spreadsheet poses these questions: “Which sites are showing the most future risk that are not Tier 1 sites yet?” and “What is the risk in each business line and which has the most risk, is it increasing or decreasing? What is driving the risk?” Tier 2 spreadsheets in the document look at the number of investigations of workers that management has handled in the last month, whether that number is trending up or down, the number of worker appeals of those investigations, and — notably — the percentage of negative worker comments on internal bulletin boards.
Voice of the Associate and other internal bulletin boards are key focal points. Charts in the document track how often workers raise particular topics, like weather, time off, breakroom amenities, management treatment, and restroom cleanliness. They also analyze the “vector” of each issue: “What are the top drivers of negative Sentiment and change MoM [month over month]?” is one question posed in the document. “What Sites are spiking MoM in negative sentiment? What themes are driving the sentiment? What anecdotes can we pull?”
Atlas is not strictly a North American tool. One chart analyzes trends for warehouses globally, documenting “employee relations events” — worker organizing — and cataloguing the number of worker comments on Voice of the Associate and the percentage of those comments that were negative. Two warehouses in the English Midlands where workers have been organizing with the GMB union — both Tier 1 sites in Atlas’ taxonomy — showed high volumes of negative VOA posts. A warehouse in Melbourne, Australia, also showed mostly negative Voice of the Associate posts, while posts were mostly not negative in some of the warehouses in Poland, Germany, and Italy.
All this is surely a tiny sliver of Atlas’s output. The former head of Amazon’s HR platforms, Bud Cashatt, boasted on LinkedIn recently about how his department created “predictive site-risk ML touching every building in Amazon’s global network.” (“ML” stands for machine learning, where programmers train AI to learn patterns and build predictions based on analyzing vast quantities of data.)
Did Jeremy Bentham, the 18th-century British philosopher who dreamed up the panopticon, anticipate Atlas? Nearly 250 years ago, he imagined his panopticon as a useful tool for prisons, “madhouses,” and also “to the business of manufactories,” the industrialized manufacturing plants then just emerging in England. Speaking of his watchman in the center of the operation — the human Atlas of his time — Bentham wrote, “The concealment of his person will be of use.”
The documents uncovered at the B.C. Labour Board shine a light on Amazon’s concealed watchman. Atlas illustrates just how far Amazon will go to try to rule the warehouse floor. And its scope also underscores just how terrified Amazon’s masters are of their own workforce rising up and claiming their due.
Bentham theorized that the panopticon would facilitate social control: He imagined that incarcerated people would behave, not knowing at any moment whether they were being watched by the guard. It was, he wrote, “A new mode of obtaining power of mind over mind.”
But what happens when prisoners — or workers — resist such attempts at social control? There’s no level of AI sophistication that can erase the reality that Amazon’s workers move millions of packages every day, and without their labor, the Amazon supply chain collapses.
Peter B. Olney, the retired organizing director of the International Longshore and Warehouse Union, calls Atlas “a promethean tool for union busting and the thwarting of any employee organizing.”
To fight back against this “existential threat” to basic worker rights and unions, Olney says, “we have to get real about deploying massive resources towards organizing the workforce and finding their serious vulnerabilities and choke points.”
Today we see emerging fights everywhere against a billionaire class intent on harnessing AI and technology to undermine basic democracy and impose authoritarianism, both in the workplace and throughout society: in revolts against the algorithmically driven content we are force-fed on the internet; protests against and sabotage of the Flock cameras on neighborhood lampposts; and resistance against the replacement of workers with bots and computers. The Atlas model places Amazon workers at the center of this global fight against the AI billionaires. And it highlights that union organizing at Amazon is not just a battle over economics; it’s also a fight for basic freedom and democracy.
Along a freshly repaved stretch of the BR-317 highway in Acre, a Brazilian state bordering Bolivia and Peru in the Western Amazon, pasture stretches out as far as the eye can see. Solitary Brazil nut trees (Bertholletia excelsa), a protected species, are the only reminder of the tropical forest that once stood there. The road is part of the Interoceanic Highway, inaugurated in 2011 as the first paved road in South America connecting the Atlantic and Pacific oceans. Built through the Brazilian and Peruvian Amazon to help increase trade to Asia as well as between neighboring countries, the highway has been associated with deforestation on both sides of the border. “Roads are the main vector for deforestation and irregular [land] occupation,” says Sonaira Souza da Silva, a professor at the Federal University of Acre’s Floresta Campus and co-author of a recent paper on road expansion in Acre. The desolate landscape that now lines the BR-317 could be replicated elsewhere in Acre, environmentalists warn, if plans go ahead to build a second road connection with Peru. This is part of a renewed push to turn the state into a corridor to the Pacific for the export of Brazilian agricultural and mineral goods, following the 2024 inauguration of Chancay, a Chinese-built mega-port just north of Peru’s capital Lima. A new report from the NGO Amazon Conservation argues that expanding road infrastructure is incompatible with Acre’s deforestation commitments and that new corridors could add between 74,700 to 133,800 hectares (around 184,600 to 330,600…This article was originally published on Mongabay
For years, Europe grew used to a contradiction that it is only now beginning to see as a risk: being one of the world’s foremost regulatory powers in the digital sphere while remaining dependent on others for much of the technology those rules were designed to govern. Over the past decade, Brussels has assembled an extensive legislative arsenal aimed at curbing the power of big tech, from the General Data Protection Regulation (GDPR) to the Digital Markets Act, the Digital Services Act and the AI Act. Yet while Europe was writing rules, the United States and China were building companies, data centers, chips, cloud platforms and artificial-intelligence models on a scale that no European firm has managed to match.
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