Today in News History
On July 3, several notable moments in the history of News stand out. In 1917, João Saldanha, Brazilian footballer, manager, and journalist (died 1990) was born. In 1944, World War II: The Minsk Offensive clears German troops from the city. In 1985, Frank J. Selke, Canadian ice hockey player and manager (born 1893) passed away. In 1990, Lucas Mendes, Brazilian footballer was born. In 1990, Bobby Hopkinson, English footballer was born. In 1992, Crystal Dunn, American soccer player was born. In 2004, Andriyan Nikolayev, Russian general, pilot, and astronaut (born 1929) passed away. In 2006, Joseph Goguen, American computer scientist, developed the OBJ programming language (born 1941) passed away. In 2012, Sergio Pininfarina, Italian engineer and politician (born 1926) passed away. In 2014, Ira Ruskin, American politician (born 1943) passed away. Together, these milestones provide historical context for today's news news and ongoing narratives.
The secret AI that could help explain this wild World Cup

This year’s FIFA World Cup has been unusually volatile. The expanded 48-team format has produced a string of surprise results—including Cape Verde, ranked 67th and playing in its first World Cup, holding cofavorite Spain to a scoreless draw in Atlanta before coming from behind to draw 2-2 with Uruguay. The 32-team knockout round has continued that pattern. Paraguay eliminated four-time champion Germany on penalties after a controversial video assistant referee (VAR) call wiped out a German extra-time goal for a foul in the box. One potential factor at play here: the way tournament data is now being distributed. Lenovo, the PC and computing infrastructure maker, built an artificial intelligence tool that gives all 48 teams access to FIFA’s tournament data. The system, called Football AI Pro, is a knowledge assistant that orchestrates multiple AI agents across more than 2,000 football-specific metrics and petabytes of tracking, performance, and historical data. Every team began the tournament with the same data foundation, from vastly experienced Spain to debutant Curaçao. That raises a larger question for this World Cup: What happens when advanced football intelligence moves from elite back rooms into the hands of every team at the tournament? AI on the sideline The software is also available on teams’ mobile phones, giving players and coaching staffs direct access. According to a source close to FIFA, teams and players appear to be using it extensively after matches to review individual and team performance and compare results with previous games. Lenovo’s role extends beyond scouting reports. Building on a partnership FIFA announced in October 2024, the company developed an AI-powered 3D model of all 1,248 players competing this summer. Those avatars support offside reviews and give fans a clearer view of close calls from multiple angles. Behind the scenes, Lenovo ThinkSystem servers at FIFA’s International Broadcast Center in Dallas process and distribute live match content to more than 1,000 screens across FIFA venues, cutting streaming latency, Lenovo claims, from roughly 40 seconds to under 5. One of those 3D avatars recently drew attention in Miami, during Portugal’s group stage match against Colombia. Colombia briefly appeared to have scored a stoppage-time winner when center back Davinson Sánchez headed in a corner. A video review ruled his toe offside by a very small margin. Ken Wong, global president of Lenovo’s Solutions Services Group, leads the team behind these technologies. He says one of Lenovo’s goals is to use technology to improve how the game is played, officiated, and presented. “For us, it’s about how we can put together our technology, make a promise to the game, and prove it,” he tells Fast Company. “We are super well known for our hardware portfolio, from pocket to the edge to the cloud. Where we have been doing a lot of work is helping our customers, including FIFA, understand how different Lenovo is today, and our capabilities beyond our PC endpoint devices.” Teams appear to be approaching matches differently, particularly against traditional powerhouses. Wong does not argue that equal access to Football AI Pro produces equal results. He says FIFA has valued the platform because it makes the tournament’s proprietary data available to every team. “Before, only the powerful teams could have a highly talented analytics team and the computing power to match. However, our job is not to teach them how to use Football AI Pro. Some teams use and will use Football AI Pro better than others,” he says. “We are just making sure we unleash the full power of technology, democratize AI and FIFA’s proprietary assets, to make the game more interesting and more fair.” Lenovo’s CTO, Tolga Kurtoglu, made a similar point when Football AI Pro launched at this year’s Consumer Electronics Show in Las Vegas. The company had already deployed early versions of several technologies at the FIFA Club World Cup in summer 2025, using that tournament as a test before the larger event this summer. That allowed Lenovo to learn, iterate, and improve before deploying the systems at World Cup scale, including an Intelligent Command Center that uses real-time AI summaries to help manage tournament operations across three countries. Kurtoglu said the deeper use of AI and data could affect tactics, decision-making, and tournament planning. “The more data you have, the more analytics and AI you can apply, and eventually that will change tactics, analysis and even commentary,” he said. The referee-cam AI that almost didn’t work One of the tournament’s most visible technologies is Referee View, the AI-stabilized, head-mounted camera footage that shows viewers what officials see during key moments. Wong said building this year’s AI-stabilized video version required solving three practical engineering problems. The camera had to be light enough for a referee to wear for more than 90 minutes. The battery had to last through water breaks and any additional time required beyond the regulation 90 minutes. The footage also had to reach broadcasters with very low latency. Lenovo’s first approach did not work. “When we first did it, we just put everything into a single large language model. And we found the result was not super promising, because the latency wasn’t as good as we expected, and the power we consumed was a lot,” Wong said. So the team rebuilt the pipeline around Lenovo’s internal architecture, called xIQ. “Indeed, the whole AI video-stabilizing task can be divided into four different subtasks,” Wong explained. “So we divided it into four subtasks and asked four smaller AI models to do the four tasks, then we integrate everything together. The latency is a lot shorter and power consumption a lot better.” The experience reflects a broader lesson in applied AI. Larger models are not always the best fit for real-time systems that must operate under strict power and latency constraints. “We applied the same technology before for our own supply chain—we use video analytics in our quality control for manufacturing systems,” Wong said. “We’re not football experts.” Lenovo also embedded engineers with FIFA’s staff for 18 months before kickoff. The digital body behind every offside call Every player was digitally scanned before the tournament began. Lenovo says the process takes about a second per athlete and produces the 3D model now feeding VAR and offside systems, including the call that ended Colombia’s celebration against Portugal. But athletes change over a monthlong tournament. They can lose weight, alter their stride after an injury, or carry fatigue differently in the third week from the way they did at the start. I asked Wong whether calls this precise are being measured against bodies that may have changed since the original scan. “The scan is only done once, and minute changes might not affect the outcome by a material amount,” he said. “Minute changes won’t have a substantial impact because we are constantly working on the accuracy improvement we can produce. A lot of the video footage will be affected by lighting, weather and the speed of the player. Those are the main parameters in our modeling.” The system’s origins are outside football. Wong said Lenovo first developed related technology for robotics. “The technology, when it first came for ourselves, was for our robotic solutions,” Wong said. “We need IP to create a digital space, a digital twin, so we can orchestrate a robot working in 3D space the same way it exists in physical space. The same platform is now being applied to these 3D avatars to provide more accurate input for the referee’s judgment.” The human whistle and machine evidence AI-stabilized referee footage and 3D player models now help inform decisions on goals, fouls, and offsides. That raises a practical question about Lenovo’s role in football’s evidence system. Wong said the company’s role is limited to providing technology. “There’s been a very clear divide of roles and responsibilities,” he said. “Lenovo is a technology provider, and FIFA runs the greatest football tournaments on the planet. Our job is to explore all the technology options to help FIFA achieve whatever it intends to.” Wong said the referee still has the final authority. “He now has a lot of additional information and data assistance to help him make the right call. But he makes the final judgment.” That distinction is important, even if it is becoming more complicated in practice. A referee supported by centimeter-level 3D modeling is working with a different evidence base than one judging an offside line by eye. The rulebook still credits the human official with the decision, but the decision now depends on a technical system that shapes what the official sees. Lenovo’s World Cup technology is designed to reduce the analytics gap between football’s richest federations and the rest of the field. It does not make every team equally capable, and it does not determine match results on its own. It does, however, give every team access to a level of data and computing power that was once much harder to obtain. In a tournament already shaped by a larger field and narrower margins, that shift may be one reason the gap between favorites and underdogs feels smaller than usual.
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This article was published by Fast Company, a source frequently categorized with a lean left bias based in United States of America. Our narrative intelligence engine continuously monitors coverage from this outlet to track framing, bias, and rhetorical patterns. Our initial algorithmic scan of this specific piece did not flag high-confidence rhetorical techniques, suggesting a generally straightforward reporting style or neutral framing. By understanding the editorial perspective of Fast Company, readers can better contextualize the information presented and compare it across our broader media matrix to find the real narrative.
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