It’s revision season. If you’re a student preparing for upcoming exams, you might be tempted to put aside sport or other physical activity for a while in order to dedicate more time to learning.

But exercise is extremely important for academic success. Make time to be active. It may well help you revise better.

Doing some physical activity improves our ability to think and process information. My research with colleagues has shown this to be true for both primary school and secondary school pupils.

In fact, when we consider the different types of cognition, such as perception, memory and attention, the domain where physical activity has the greatest benefit is executive function. This is our ability to carry out complex, higher-level thinking. It’s the domain that is linked to academic performance.

Research has found that the beneficial effects of physical activity on cognition last for around 45 minutes. This means it is important to have regular activity breaks to maximise the boost exercise gives to revision.

You could try scheduling your revision in hour-long blocks: 45 minutes of work followed by 10-15 minutes of physical activity. This could be walking, running, body weight exercises such as squats, or even some stretching.

Perhaps most importantly, though, find an activity that you like. You’ll then be more likely to incorporate it into your revision routine. So this could be a ten-minute walk after an hour of revision, a quick five-minute break for some squats or press-ups every half hour – or a morning swim or lunchtime run.

If you can, try to go outside for these breaks. My colleagues and I have recently carried out research showing that outdoor physical activity is more beneficial than indoor physical activity for cognition.

This was true for attention, memory and executive function, which we assessed using a battery of computerised tests. So, get up, take a break, get outside, get active and boost your revision.

You can also use the boost that exercise gives you on exam days. Perhaps take a pre-exam walk – it might help calm any nerves, too.

There are many possible reasons why physical activity can boost your revision. For example, it can increase blood flow to the brain and cause the release of chemicals called neurotransmitters – the tiny signalling molecules which help our brains work more effectively.

It’s vital that schools keep in mind how important physical activity is during exam season, too. One challenge here is that, in many schools, the sports hall also becomes the exam hall. This is understandable given space requirements.

Rather than limiting opportunities for PE, though, it could seen as an opportunity to take school physical activity outside, and for teachers to find innovative ways to help their students get the extra cognition boost that comes from being outdoors.

It’s key that schools, parents and students themselves don’t stop prioritising keeping active, even when there’s so much revision to cram in. Of course, there is always a balance to be found, but physical activity boosts our cognition, revision and learning. Why would we not want to make the most of this?

I often use the term “unleashing the power of physical activity”. I encourage you to do just this during revision and exam season. Whether you (or your child, your class, or any young people you know) are revising for GCSEs, A levels, university exams or any other tests, the same applies – stay smart, and stay active.

Simon Cooper has received funding from the Waterloo Foundation, Rosetrees Trust, Stoneygate Trust, Education Endowment Foundation and Sport England.

Birds sing the most around an hour before dawn, when the air is at its stillest. Theoretically, this enables sounds to travel further, making song up to 20 times more effective than if sung at midday.

With International Dawn Chorus day approaching, it’s time to take a moment to soak in the spring birdsong and notice the individual harmonies blending together.

International Dawn Chorus Day brings casual bird appreciators, ornithological experts and dedicated twitchers together in a celebration of birdsong. In our series, experts give their insights on nature’s chorus.

The dawn chorus is beautiful anywhere, but your local birdsong may sound rather different to nearby areas. Even in the same neighbourhood, birds of the same species don’t always sound exactly alike. I was recently teaching undergraduates about bird song, and they recorded blue tits singing around campus. The students found plenty of differences between individual birds. Some blue tits sang their classic song, which sounds a bit like they are saying “he-llo, I’m a little blue tit”. Some sang a more elaborate “he-llo, I’m a little blue tit, blue tit”, and some only bothered with “he-llo”.

Alongside individual differences, birds have regional differences in song. For example, the birdsong that sounds a bit like “my toe bleeds Be-tty”, commonly sung by the woodpigeon is, in some parts of the UK, “my toe bleeds Ju-li-a”, with an extra syllable to the final section of the song. These sorts of regional dialects have been reported in several British bird species including blackbirds and great tits.

However, one of the most interesting accents comes from farmland bird the yellowhammer, who typically sings birdsong that sounds like “a little bit of bread and no cheese please”. In the UK, the yellowhammer largely has two distinct dialects, differing in the final “cheese please” part of the song. In the east of England, “cheese” has a lower pitch than “please”, and this is reversed in south and west England.

Read more: Why do birds sing?

The yellowhammer was introduced to New Zealand from the UK in the 1860s and 70s. But, unlike the UK, the New Zealand yellowhammers have around seven dialects, despite originating from the south of England. These five extra dialects have also been detected in birds across Europe, indicating that the New Zealand birds still sing the 19th century British dialects that have since disappeared in the UK. This is likely due to the large decline in the number of yellowhammers in the UK which caused some populations to go extinct. An ongoing project allows you to view a map of yellowhammer dialects or help with citizen science research on their song.

Most birds only sing one dialect, learned from parents or neighbours, resulting in a geographical mosaic of regional accents. Dialects often overlap but can dominate certain areas, essentially producing geordie, brummie, cockney and scouse birds.

Although some bird species have an innate ability to sing the song of their species (the cuckoo, for example), species with more elaborate song must learn to sing. Young birds inherit a template which they add to from listening to songs around them.

For example, chaffinches that have been hand-reared in isolation produce simple songs, whereas wild chaffinches learn complexities from their parents or immediate neighbours in their first weeks of life. Finer details of their song are acquired the following breeding season when they come into contact with neighbouring territory owners. Interestingly, corn buntings, a farmland bird, sing the same song as their nearest neighbour rather than their parents, seeming to learn most after dispersing from their nest.

Birds are also adapting to humans. In urban areas, wildlife is subjected to human-made noise such as cars and machinery. Consequently, urban birds now sing at a higher pitch than rural birds as higher-pitched songs carry better over low-pitch urban noise. And it’s not just the pitch of the song that has been altered.

Great tits sing shorter and faster songs in cities compared to forests, and blackbirds sing louder in urban areas. However, even when cities are quiet, like in the early hours, urban birds maintain these song features, which suggests that sounds echo off large buildings and don’t travel as far in urban areas.

Birds are singing earlier in response to traffic noise, with city blackbirds starting their dawn chorus up to five hours earlier than rural birds. The effect of artificial light also leads to an earlier start of dawn singing, with song thrushes starting ten minutes earlier, and robins and great tits 20 minutes earlier than in areas without street lighting. And, artificial light causes blackbirds to sing around an hour earlier than those exposed to natural light.

Scientists still have much to learn about the differences in birdsong within a species. When you hear birdsong, it’s easy to assume that it’s a male. And it is more usually males that sing. Females choose males with the best song so that his high quality genes will be inherited by her offspring. But female birds have been massively under-represented in archives and scientific studies. A 2016 analysis found that for 3,500 out of 4,814 species we don’t even have enough data to know whether or not the females of the species sing. As researchers take a closer look at female birdsong, we may learn of even more differences.

Next time you listen to a bird singing, see if you can hear the nuances in the dialect, or spot the difference between urban and rural birds.

Louise Gentle works for Nottingham Trent University.

Each May, nature lovers get out of bed early to experience the seasonal wonder of birds singing, as the sun rises above the horizon to take part in International Dawn Chorus Day.

In Europe you may hear blackbirds, chiffchaffs and nightingales. In the US, cardinals, chickadees and blue jays. In East Africa, morning thrush, hornbills and wood doves. Each with their own song.

There is no single dawn chorus, but the harmonies of hundreds of bird voices at first light change from place to place in a huge wave that surfs around the world as the planet rotates.

A dawn chorus is part of a wider soundscape – the interaction between biological sounds from birds and other animals (biophony), natural physical sounds such as wind or water (geophony) and human‑generated sounds like traffic (anthrophony). The dawn chorus is often the most prominent component of the soundscape at sunrise, but it never exists in isolation.

Scientists believe that birds structure their early morning singing in a way that prevents overlap and masking of each other’s vocalisations. They use different pitches and timings to partition and share the acoustic space. Birds in open landscapes such as grasslands use shorter, scratchier sounding song phrases, while birds in woodlands use longer whistling notes – each evolved to allow the best transmission of their song in their own habitat. So birdsong is filtered by trees, grasses, across water and through urban areas, to create a soundscape phenomenon that differs very clearly from region to region.

In the Caledonian pinewoods of northern Scotland, the first morning sounds are often geophonic: wind moving through tall pine canopies. Typically before first light, male western capercaillies gather together to vie for females. The males fan out their tail feathers, puff out their chests and produce a series of clicks, pops and wheezing notes. These are short‑range sounds, shaped by the open understorey and the resonant qualities of the forest.

Fieldwork in these woods has shown how these vocalisations are tied to group mating activity (known as lekking) and can be used to assess the populations of this rare and declining species. These sounds indicate a specialised habitat that has remained untouched for a long time? and without much human disturbance, where the secretive birds can go about their lives, while contributing to the distinctive acoustic character of the pinewoods.

Move to a lowland heath in southern England though, and the differences are immediate. The geophony shifts to the dry hiss of wind across heather and scattered gorse. The dawn biophony is dominated by an assemblage of species that are rare across Europe. The nightjar might have been producing its continuous churring since well before first light. Woodlarks add clear, falling song phrases, while Dartford warblers deliver rapid, scratchy calls from gorse clumps. Research on heathland species has shown how these calls are useful indicators of local habitat quality and structure.

In urban areas, birds have to compete with the noises made by people and their machines. Cars, motorbikes, trains. Sirens and alarms. Nightclubs and pubs. The urban architecture often makes this worse, with reflective hard surfaces bouncing these noises around the streets, instead of absorbing them as natural spaces would.

Birds have to adjust their behaviour around this. Some advance or delay the timing of their singing; others increase volume or shift pitch to higher frequencies. Large‑scale studies indicate that spring soundscapes across Europe and the US are becoming quieter and less varied, due to changes and declines in bird communities, linked to climate change and habitat loss.

Because many people hear birds more often than they see them, changes in soundscape complexity can be one of the earliest signs that local biodiversity is under pressure. Long‑term listeners of bird song – whether through formal monitoring or casual early‑morning walks – may be detecting real ecological change.

Listen up

Understanding soundscapes can help make sense of these changes. A chorus lacking high‑frequency elements may indicate the loss of particular warblers; reduced low‑frequency components may point to declines in larger bird species.

Changes in the geophony, such as increased wind noise in fragmented woodland, can alter how well birds communicate. And increasing man-made noise can mask quieter species entirely, leading to an impression of silence even where birds are still present.

In the UK, pinewoods and heaths both depend upon active vegetation management for conservation and long‑term habitat stability. Maintaining these landscapes means maintaining the conditions that support their characteristic sounds.

Paying attention to how different places sound at first light can be a reminder that biodiversity is something we can hear as well as see. You can even compare it with the sounds that accompany sunrise from other places. Arts cooperative SoundCamp’s Reveil project offers a 24‑hour broadcast that relays sunrise sounds from microphones around the world, allowing us to track the soundscape as the Earth rotates through one full day each spring.

A dawn chorus is more than an aesthetic experience: it is a summary of local ecology, habitat condition and the pressures shaping both.

Carlos Abrahams is director of Naturesound Ltd, an ecoacoustics consultancy. He is a Fellow of the Chartered Institute of Ecology and Environmental Management.

A table tennis robot has outperformed elite players in recent evaluations. The robot, called Ace, marks a significant step toward artificial intelligence (AI) systems that can operate in fast, uncertain, real-world environments.

In the tests, the autonomous robot won three out of five matches against elite players – competitive athletes with over ten years’ experience and an average of 20 hours weekly training. The robot, developed by Sony AI, lost both matches against players in professional Japanese leagues, but did win a game against one of them. The system is described in detail in a recent paper published in Nature.

AI has spent decades mastering games. It has repeatedly outperformed the best humans in everything from complex video games like StarCraft II to chess – where modern programs now far exceed human ratings.

Landmark systems such as Deep Blue and AlphaGo have confirmed that, given clear rules and enough data, AI can achieve superhuman performance. But these victories all shared one key feature: they happened in controlled, digital environments.

At first glance, table tennis might seem like an unusual benchmark for artificial intelligence. In reality, it is one of the most demanding imaginable. The ball can travel faster than 20 metres per second, giving players less than half a second to react.

On top of that, spin introduces enormous complexity. A ball rotating at extreme speeds can curve mid-air and rebound unpredictably off the table. For humans, interpreting spin is largely intuitive. For robots, it has been a longstanding obstacle.

Earlier table tennis robotic systems such as Forpheus, developed by Japanese company Omron, addressed this by simplifying the game – using controlled ball launchers, limiting movement, or ignoring spin altogether. More recent iterations have aimed for interaction, but still operate under constrained conditions.

Ace does none of this. It plays with standard equipment, on a regulation table, against human opponents who are free to use the full range of shots.

How Ace works

Ace’s performance relies on three key innovations: how it sees the world, how it decides what to do, and how it carries out those actions. First, let’s deal with how Ace sees the world. Traditional cameras struggle with fast motion, often producing a blur or missing critical details.

Ace instead uses three “event-based” vision sensors, which detect changes in light rather than capturing full images at fixed intervals. These are complemented by nine high-speed cameras that track the environment, including the opponent and their racket.

Together, these systems enable high-speed gaze control (the technology that enables a robot to direct its sensors to focus on specific things) and allow the robot to follow the ball with exceptional real-time precision.

By tracking markings on the ball, where professional players can generate spin approaching 9,000 revolutions per minute (rpm), the system can estimate spin in real time, something that has long challenged robotic systems.

The second important innovation is how Ace decides what to do. Knowing where the ball is going is only half the problem; the robot must also respond instantly. Ace uses deep reinforcement learning, trained in simulation over millions of virtual rallies, including self-play.

It continuously generates movement commands for its multi-jointed robotic arm, recalculating trajectories every few tens of milliseconds while avoiding collisions with the table or itself.

The third innovation is how Ace carries out its actions. To match the speed of human elite players, the robot is built around a high-performance arm combining two prismatic (sliding) and six revolute (rotational) joints. This enables rapid sideways motion and precise striking. There is both a table tennis racket and a mechanism for ball handling, allowing one-armed serves.

Crucially, the system is engineered for high-speed interaction: lightweight structures and optimised actuation (the mechanisms in a robot that convert energy into mechanical force) allow Ace to return balls at speeds approaching 20 metres per second. This enables sustained, competitive rallies with skilled human players.

What makes this particularly notable is the transition from simulation to reality. Many AI systems perform well in virtual environments but fail when exposed to real-world noise and uncertainty. Ace demonstrates that this “sim-to-real” gap can be meaningfully reduced.

One moment during a rally with an elite player illustrates the way that Ace has leapt over this gap. When a predicted ball trajectory suddenly changed after clipping the net, Ace reacted almost instantly, returning the shot and winning the point. What makes Ace particularly significant is therefore not just its performance, but its ability to operate reliably under real-world uncertainty.

Why this matters beyond sport

A robot returning high-speed topspin shots may be entertaining, but the implications go far beyond table tennis. In manufacturing, for example, robots are typically confined to highly structured tasks.

The real challenge is adaptability, handling irregular objects, responding to variation. This is particularly relevant for next-generation robots operating in unstructured environments.

To function effectively in homes, hospitals or construction sites, robots must be able to predict, adapt and respond to constantly changing conditions. The same predictive and control capabilities that allow Ace to respond to unpredictable shots could enable more flexible, responsive automation.

There are also implications for human–robot interaction. Most industrial robots are kept behind safety barriers because they cannot react quickly or reliably enough to unexpected human behaviour. Ace operates at the edge of human reaction time, suggesting a future where robots can safely collaborate with people in shared spaces.

More broadly, this work represents a shift in what AI is expected to do. The next frontier is not just intelligence in abstract problem-solving, but intelligence embedded in the physical world. The gap between simulations and reality needs filling, and this is a big step forward.

Read more: Amazon’s new robot has a sense of touch, but it’s not here to replace humans

What humans still do better

Professional players were still able to exploit Ace’s limitations – particularly in reach, speed, and the ability to handle extreme or highly deceptive shots. This highlights that intelligence is not just about prediction and control, but also about physical embodiment. Humans combine perception, movement and strategy in ways that remain difficult to replicate.

Interestingly, systems like Ace may end up enhancing human performance rather than replacing it. As one former Olympic player observed after facing the robot, seeing it return seemingly impossible shots suggests humans might be capable of more than previously thought.

Kartikeya Walia receives funding from Innovate UK, UKRI. He does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.