For the first time, a streaming service has overtaken the BBC as the place UK viewers say they turn to first. In Ofcom’s annual Media Nations report, published this week, Netflix was named first choice by 26% of viewers, just ahead of the BBC on 25% and ITV on 15%.

The measure is about instinct, not hours. Ofcom asked viewers which service they reach for first, and for decades the answer in Britain was overwhelmingly the BBC.

A single percentage point is not a rout, but it is a milestone. The corporation has anchored British viewing for generations, and being pipped by a Californian subscription service, however narrowly, marks a shift the BBC has long seen coming and long dreaded.

The wider numbers tell the same story more slowly. Around 70% of Britons watched traditional broadcasters for at least 15 minutes a week in 2025, down from 73% the year before and 78% in 2022, a gentle but unmistakable decline.

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The broadcasters are not standing still. Their own streaming apps, including iPlayer, ITVX, Channel 4 Streaming, and 5, grew 9% year on year, as viewers who left the schedule followed the same programmes onto on-demand.

Subscription streaming, meanwhile, looks close to saturated. Services such as Netflix, Disney+, and Amazon Prime Video now reach roughly 70% of British homes, a figure that has largely stopped climbing.

The plateau matters for what comes next. With most households that will pay for streaming already paying, growth now has to come from taking time off rivals rather than signing up newcomers.

The more striking mover is YouTube. Viewing of the Google-owned platform on actual television sets has doubled, to 19 minutes a day per person, up from nine minutes in 2022.

That growth is no longer confined to the young. Among Britons aged 75 and over, YouTube’s weekly reach rose to 33% in 2025 from 28% in 2022, a sign the platform has crept well beyond its digital-native base.

The generational pattern is the report’s throughline. Younger viewers have rebuilt their watching around on-demand and video platforms, and each year a little more of the older audience follows them there.

ITV, on 15%, sits some way behind both. The contest at the top is really between one public broadcaster and one global streamer, rather than a broad field of rivals.

Being first choice is not the same as being most watched, either. Traditional broadcasters still fill more total viewing hours than any single streamer, even as the habit of reaching for them first quietly erodes.

For the BBC, the report arrives at an awkward moment. The corporation is defending the licence fee and preparing for charter renewal, and a headline saying Netflix has passed it will make neither conversation easier.

The funding question sits beneath the viewing one. The licence fee is levied on the assumption that the BBC is a near-universal habit, and a ranking that now places it second hands its critics a fresh line of attack.

The competitive pressure is not only about attention. Netflix faces its own frictions in Europe, including a consumer lawsuit in the Netherlands over subscription price rises, a reminder that scale brings scrutiny.

Britain’s public broadcasters have weathered the streaming era better than many feared. Public-service programming still draws large crowds for live events and news, and the collapse once predicted for traditional UK television has looked more like slow erosion than a cliff.

Still, the direction is not in doubt. Each edition of Media Nations records the same drift, younger viewers leading and older ones following, from the schedule to the app and from broadcast to the feed.

What the report cannot say is where the line settles. Netflix’s one-point lead could widen or reverse next year, but the more durable finding is that “first choice” is now a contest the BBC has to win rather than a title it holds by default.

Physicists have been trying to measure the fundamental gravitational constant for well over two centuries. The current accepted value of big G, as it’s known, is 6.67430 × 10-11 cubic meters per kilogram per square second. It also has an uncertainty of ±0.00015 × 10^-11 m³/(kg s²). As far as constants of the universe go, that’s very uncertain.

Stephan Schlamminger recently completed a 10-year effort at the U.S. National Institute of Standards and Technology to replicate an earlier measurement of big G from the International Bureau of Weights and Measures, or BIPM (located near Paris) that’s notably higher than most measurements. He spoke with IEEE Spectrum about why it took so long to get a number—6.67387 x 10^-11 m³/(kg s²)—and why it’s notably lower than the BIPM result, to the tune of 0.0235 percent.

Why is it so difficult to measure big G?

Stephan Schlamminger: Gravity is very weak. When you were a kid, you probably played with fridge magnets, and it was a force you could feel. But if you have two coffee cups, you can try all you want—you can’t feel the force between them. It is there, but it’s so, so weak.

How did you attempt to measure big G?

NIST used a torsion balance with a fourfold geometry. This animation shows an exaggerated version of how the outer green masses gravitationally attract the inner blue masses.S. Kelley/NIST

Schlamminger: We used what’s called a torsion balance. The key idea in the torsion balance is that it decouples vertical gravity that you have from Earth from horizontal gravity, and that makes it sensitive to masses that are around the torsion balance but not the Earth below.

Ours had a fourfold geometry. It has a very thin torsion strip, then four cylinders in a “plus sign” arrangement. All of this is inside a vacuum. Outside, we have four larger cylinders that gravitationally attract the four smaller masses to them. If I move the outer masses just a tiny little bit, the plus sign will rotate, and we measure that angle that it moves. That angle is proportional to the gravitational torque.

Why try to replicate the BIPM value?

Schlamminger: We could move the field forward. The measurements have been plagued with inconsistencies, so by redoing an experiment, we hoped to shed light on the inconsistencies.

We did not find a smoking gun, so there’s no single reason why it’s different—our value versus their value. It’s still a big question mark.

What was it like spending 10 years on this?

Schlamminger: It’s a bit like herding cats. I’ve measured other fundamental constants, like Planck’s constant, and for most experiments, they have some sort of self-calibration built in. But with the gravitational constant, you have to keep track of every single mass that moves—where they are, how big they are, and weigh them.

How does your result compare to the rest?

Schlamminger: Our result is a little bit below the standard accepted literature value. I was disappointed because it doesn’t agree with the BIPM value, nor with the literature value. If there’s something wrong with the BIPM experiment, then the literature value—which includes that result—probably ought to come down a bit. But that is not for me to say. I think somebody else, independent, should figure out what the new mean value ought to be.

A Katalyst Space robot that was launched to grab on to a space telescope and raise it to a higher orbit tumbled out of control after a series of failures, NASA and the company said today.

The company is trying to stabilize the spacecraft using back-up systems, before NASA will decide if the mission can continue.

This is the first time the space agency has hired a private company to lift one of its space telescopes to a higher orbit, allowing the observatory to continue operations beyond its expected lifespan.

The Neil Gehrels Swift Observatory was launched in 2004, with the ability to swiftly point at ephemeral space events like gamma ray bursts. The spacecraft has been pulled back toward Earth and needs to be pushed back up to a higher orbit to continue doing its job.

The LINK spacecraft was launched into space on July 3 on board a Northrop Grumman Pegasus rocket. Over the past several weeks, flight controllers have worked to commission the spacecraft, activating its various systems before it heads off to rendezvous with Swift.

However, the spacecraft suffered issues controlling itself and began spinning over the weekend. According to NASA, the spinning has resulted in “sporadic communications” with the satellite, likely because its antenna flips away from the planet. Two of the three reaction wheels that control the spacecraft’s alignment have failed, and there are problems with one of the spacecraft’s thruster systems.

Flight controllers are working to recover the spacecraft using another set of thrusters on the spacecraft to slow the spin, and they said in a statement that “we have already begun this series of burns and are seeing the intended effect.” Katalyst told TechCrunch that “this remains an active mission, and we continue to move forward with plans to rendezvous with Swift.”

Katalyst’s Kieran Wilson, the principal investigator for the mission, told reporters ahead of the mission that the spacecraft had been built incredibly quickly because of the urgent need to raise Swift in the next few months.

“All this is challenging and risky,” he said at the time. “There’re a lot of spacecraft that have had far longer development cycles with far more funding behind them that have failed for mundane reasons.”

Katalyst raised a $12 million round in June to help support this mission, backed by investors Fortitude Ventures and Geodesic Capital. The company has also won funding from the U.S. military, which is interested in a dynamic vehicle that can service satellites or surveil rival spacecraft.

This story has been updated to include comment from Katalyst.

OFFBEAT

Researchers uncover patterns in how sleeping minds recombine memories, people, and places

Your brain apparently spends the night remixing reality rather than simply replaying it, according to researchers armed with AI and more than 3,700 accounts of dreams and waking life.

Researchers at Italy’s IMT School for Advanced Studies Lucca used natural language processing (NLP) to analyze more than 3,700 reports of dreams and waking experiences from 287 adults and found dreams are neither random mental noise nor faithful replays of the day’s events. Instead, the sleeping brain appears to recycle memories, emotions, familiar places, and imagined possibilities into entirely new scenarios.

Published in Communications Psychology, the study combined two weeks of dream and daily experience diaries with data on participants’ personalities, sleep quality, cognitive abilities, and psychological traits. Researchers used NLP to compare the semantic structure of the waking and dream reports.

Everyday settings such as workplaces, hospitals, and classrooms were combined with unrelated places, shifting viewpoints, or unfamiliar surroundings, while different parts of a person’s life could merge into a single scene. The findings suggest dreams do not replay reality so much as rebuild it from familiar parts.

Dream reports also varied with participants’ traits and attitudes. Those prone to mind-wandering tended to report dreams that jumped quickly from one scene to another, while those who said dreams were personally meaningful generally described more vivid and immersive experiences.

The researchers also looked at dream reports collected during the COVID-19 lockdown by a separate team at Sapienza University of Rome. Compared with more recent reports, those dreams contained more references to confinement, barriers, restrictions, and heightened emotions, reflecting the reality people were living through at the time.

“Our findings show that dreams are not just a reflection of past experiences, but a dynamic process shaped by who we are and what we live through,” said lead author Valentina Elce. “By combining large-scale data with computational methods, we were able to uncover patterns in dream content that were previously difficult to detect.”

The work also hints at a new role for AI. Rather than asking researchers to read and categorize thousands of dream reports themselves, the team used NLP to spot patterns across the entire dataset. The software’s assessments closely matched those of independent human reviewers, suggesting it could make large-scale dream studies far less laborious.

Before you ask ChatGPT why your dentist turned into your boss, the research has some obvious limitations. It relies on people remembering and accurately describing their dreams, and it doesn’t explain why we dream in the first place. However, it does suggest dreams have more structure than random neural noise – even if your brain still insists on making you sit an exam you forgot to revise for. ®