TECH

CEOs say AI saves a workday a week; employees disagree, surveys show

Artificial intelligence was touted as a technology capable of completely transforming the workplace. However, at least for now, that promise seems far from being realized for many companies.

Two recent surveys reveal a significant gap between how executives and employees perceive the benefits of AI. While CEOs see substantial productivity gains, many workers say the technology saves little time and, in some cases, actually creates new tasks—such as reviewing errors or correcting inaccurate responses.

A survey by the consultancy Section polled approximately 5,000 employees and executives at U.S. companies to answer a simple question: how many hours of work does artificial intelligence save per week?

The responses show a significant contrast.

Among CEOs, roughly one-third claim to save between four and eight hours a week thanks to AI. Another third say they gain more than eight hours a week, while the remainder report saving up to four hours.

In practice, many executives believe artificial intelligence already equates to saving a full workday each week.

Employees report a different reality...The perception among the workforce is far less optimistic.

According to the survey, two out of three workers state that AI saves no time at all or reduces their workload by less than two hours per week.

The most striking figure comes from those who see no benefit whatsoever: 40% of employees say artificial intelligence simply does not save time. Among CEOs, only 2% share this view.

This discrepancy highlights how the adoption of the technology is still perceived in vastly different ways within organizations.

AI errors still require extra work...Part of this frustration stems from the need to review content generated by AI models.

Interface designer Steve McGarvey noted that many executives automatically assume AI will be the solution to all of a company's problems. In practice, however, his experience was different.

According to him, on several occasions, large language models provided incorrect answers to questions regarding digital accessibility, necessitating a complete review of the suggestions offered.

On the other hand, McGarvey acknowledges using tools like Perplexity for research and quick inquiries, which does indeed reduce the time spent on certain activities. Even so, he maintains that these tools are far from replacing the technical expertise required for more complex tasks.

Another point raised by the research is that a large proportion of professionals use artificial intelligence solely for quick searches, much like how search engines were used in the past.

More advanced applications—such as code generation, data analysis, or process automation—appear far less frequently.

Experts point out that this limited usage may prevent users from harnessing the technology's full potential.

Another study, conducted by the software company Workday, identified a phenomenon known as the "AI tax."

Although 85% of the 1,600 employees surveyed claim to save between one and seven hours a week by using artificial intelligence, a significant portion of that time ends up being consumed by correcting incorrect answers, tweaking automatically generated text, and verifying information produced by the systems.

In practice, some of the productivity gains vanish during the review stage.

Another survey, conducted by PricewaterhouseCoopers (PwC) among 4,500 CEOs, also shows modest results.

Only 30% of executives believe that AI is already contributing to increased company revenue. When it comes to tangible financial returns, the figures are even lower: just 12% report significant benefits regarding costs or revenue, while 56% say they have seen no significant return on their investments.

These results align with findings from recent studies indicating that many generative AI pilot projects have yet to deliver the expected gains.

Nevertheless, experts believe the landscape could change in the coming years. As companies and employees learn to make better use of these tools and expand their integration into work processes, productivity is likely to increase more consistently, especially in areas such as software development, data analysis, and the automation of repetitive tasks.

mundophone

SONY

Sony RX10 V

Sony has finally decided to end a nearly decade-long wait by unveiling the new RX10 V to the world. This superzoom compact camera arrives to refresh a lineup many thought the Japanese manufacturer had abandoned, bringing long-awaited improvements.

With a completely revamped design and eye-popping video specifications, the camera promises to be a true "all-rounder" for travel photographers and content creators. The heavy emphasis on artificial intelligence is clear, bringing this compact camera's capabilities closer to those of the brand's professional mirrorless models.

However, this array of innovations comes at a cost that is, to say the least, concerning for most consumers. Priced around $2,300, Sony's new star offering positions itself as one of the most expensive 1-inch compact cameras ever to hit the market.

The RX10 V ditches the somewhat dated look of its predecessor in favor of straighter, modern lines, drawing heavy inspiration from the aesthetic of the acclaimed A7 V. The grip has been significantly enlarged to ensure superior ergonomics—essential when a lens of such generous proportions is attached to the body. Another notable detail is the removal of the built-in flash, favoring a more "pro" look.

Both the electronic viewfinder (now boasting 3.69 million dots) and the rear screen have received welcome resolution upgrades, ensuring a fantastic viewing experience. Yet, in a move that seems almost inexplicable by today's standards, the rear screen only tilts and is not fully articulated. For anyone planning to use this camera for vlogging, this comes as a real letdown.

Internally, the 20.1-megapixel stacked sensor remains unchanged from the RX10 IV, which may disappoint some fans given the price hike. The real magic happens thanks to the new processor, which enables continuous shooting at up to 30 fps with zero viewfinder blackout when using the electronic shutter—a significant leap over the previous model's 24 fps.

The autofocus system has undergone a complete overhaul, now integrating a dedicated AI chip. Whether you are a sports photographer capturing fast-paced action or a wildlife enthusiast, the camera can now detect and track the heads, eyes, and bodies of humans, animals, birds, vehicles, and even insects with surgical precision.

Where the RX10 V truly shines compared to the previous generation is in its video capabilities. The camera allows for 4K recording at 60 fps using the full sensor width without pixel binning, or ramping up to 120 fps for super slow-motion footage, albeit with a slight image crop.

24-600mm f/2.4-4.0 optical zoom lens

20.1 MP 1-inch stacked sensor

Video recording up to 4K 120p and 1080p at 240p

AI-powered autofocus with 575 points (70% coverage)

Long-lasting NP-FZ100 battery (up to 630 shots)

Native support for S-Log3 profiles and direct LUT import

Merging a 20.1MP 1" stacked sensor, expansive zoom range, intelligent autofocus, and professional video and photo tools in a single versatile body, the Sony RX10 V Digital Camera is an all-in-one powerhouse. Designed for creators who need to work quickly without switching lenses, the camera pairs a 24-600mm (35mm equivalent) Zeiss Vario-Sonnar T* lens with the AI-powered BIONZ XR processing engine. Whether capturing fast-paced action, sweeping landscapes, distant wildlife, or close-up macro shots, RX10 V delivers consistent, cinematic image quality with uncropped 4K60 video and blackout-free continuous shooting up to 30 fps. Its deep-learning AI processing unit provides advanced subject recognition and active stabilization for reliable automatic focus and framing, making it an exceptional asset for solo creators.

Its 20.1MP 1" backside-illuminated stacked CMOS sensor has an advanced BIONZ XR processor and a dedicated AI chip to provide the ideal mix of low noise, sharp detail, and exceptional speed. The stacked sensor architecture maximizes readout speed, enabling advanced exposure and color algorithms to render natural skin tones, foliage, and skies with smooth gradations. Delivering accurate exposure in a wide range of challenging environments, Sony's latest AE algorithm detects and exposes for faces hidden in deep shadow or illuminated by bright sunlight. The RX10 V offers a standard sensitivity range of ISO 100 to 12800, which you can expand down to ISO 64 for stills.

While it is undeniably a formidable and versatile tool, it is hard to ignore the price tag. The RX10 V offers incredible reach and robust video features, but you will need to carefully consider whether this package is worth the small fortune the brand is asking for it.

mundophone

 

TECH

"VARgentina": AI-generated memes alleging Infantino favored Messi go viral after Argentina's comeback win against Egypt

Argentina's comeback victory over Egypt in the World Cup Round of 16 last Tuesday (7) sparked a wave of memes and accusations against FIFA President Gianni Infantino, driven by internet users' suspicions that the South American team was receiving preferential treatment.

Fifteen minutes into the second half, Egypt threatened Argentina's goal for the second time. However, a goal by midfielder Zico was disallowed after French referee François Letexier called a foul on Argentine defender Lisandro Martínez at the start of the play. In the 22nd minute, Zico struck again, officially scoring the Egyptian team's second goal.

In the 34th minute, Argentina narrowed the deficit with a goal from defender Cristian Romero; in the 38th, they equalized through Messi—who had missed a penalty in the first half—and in the 48th, they took the lead with a header from Enzo Fernández.

The elimination fueled the "VARgentina" hashtag on social media, along with AI-generated images featuring Messi and Infantino, stemming from suspicions that FIFA was steering the tournament to benefit the player and his national team.

The FIFA chief has faced a series of controversies during his tenure... This incident adds to a list of controversies already surrounding Infantino's leadership at FIFA. Prior to the match between Argentina and Egypt, the organization's decision to lift the suspension of US forward Folarin Balogun for the Round of 16 clash against Belgium had also caused unease.

According to the BBC, UEFA described the decision as a "red line" crossed by FIFA, and former manager Jürgen Klopp stated that if Trump and Infantino had indeed resolved the matter between themselves, it "calls everything into question." Infantino himself denied any political interference, stating that the organization's disciplinary committee is independent.

Other episodes fueling mistrust regarding Infantino's leadership include:

The creation of the FIFA Peace Award, presented to Trump during the World Cup draw—an initiative criticized by the human rights NGO FairSquare for allegedly violating the organization's political neutrality rules;

The case of Somali referee Omar Artan, who was barred from entering the United States by immigration authorities;

The selection of Saudi Arabia as the host for the 2034 World Cup—a decision the Norwegian federation described as a threat to confidence in FIFA's good governance reforms;

And the creation of the Club World Cup, described by FIFPRO president Sergio Marchi as a tournament imposed "without dialogue, sensitivity, or respect."

Despite the damage to his image, Infantino's position at the helm of FIFA remains secure. The current president has already secured the support of the South American, African, and Asian confederations for his 2027 re-election bid, garnering at least 111 of the 106 votes needed to win. These figures effectively rule out any rival candidacy, even if UEFA decides to make a definitive break with the executive.

mundophone

 

TECH

Flagship chip for the mid-range: Samsung Galaxy M67 appears in benchmark leak

Samsung's next-generation mid-range smartphone apparently uses a flagship processor that was previously used in a Galaxy S flagship smartphone. However, the somewhat outdated chip is barely any faster than current mid-range processors.

Smartphones in the Samsung Galaxy M series are often just slightly modified versions of their Galaxy A counterparts. The Galaxy M67 5G appears to be an exception. The Galaxy M67 5G was spotted on Geekbench, specifically with a Samsung Exynos 2200. This is a flagship processor from 2022 that has already been used in the Galaxy S22 and the Galaxy S23 FE.

The 4-nm ARM chip features an ARM Cortex-X2 prime core with boost clock speeds of up to 2.8 GHz, three Cortex-A710 performance cores running at 2.52 GHz, and four Cortex-A510 efficiency cores running at 1.82 GHz. In addition, there is a Samsung Xclipse 920 iGPU based on the AMD RDNA 2 architecture with hardware-accelerated ray tracing. With this chip, the Galaxy M67 5G achieves a single-thread score of 1,589 points and a multi-core score of 3,923 points on Geekbench 6.

Compared to the more modern Samsung Exynos 1680 found in the Galaxy A57 ($449 on Amazon), the Galaxy M67 thus achieves 21.2 percent higher single-core performance but 10.2 percent lower multi-core performance. Samsung is pairing the chip with 8 GB of RAM, at least in one variant of the Galaxy M67 5G. The mid-range smartphone will apparently launch with Android 17. No further details are known yet regarding the specifications, launch date, or price of the Galaxy M67 5G, but since the smartphone has already been tested on Geekbench, it should only be a matter of weeks until its launch.

The Samsung Galaxy M67 surprises by bringing a flagship-grade processor from 2022 to the mid-range market. Known for its excellent performance, this chip opens up new possibilities for more affordable smartphones. While devices in this category typically use simpler processors, the M67 raises the bar.

This processor delivers superior performance for gaming and demanding applications. It also enhances battery efficiency by balancing power and consumption, meaning you can use your phone for longer periods without needing to recharge.

With this choice, Samsung aims to deliver greater speed and a better user experience in the mid-range segment. It is a strategy that balances cost and value, bringing advanced technology to a wider audience. If you are looking for a fast, modern phone, the Galaxy M67 is an excellent option.

The Galaxy M67 is powered by the advanced Exynos 2200 processor. It features a modern architecture designed for high speed and efficiency, ensuring smooth operation even when multiple apps are running simultaneously.

The chip includes a CPU with powerful cores that facilitate rapid task execution, alongside a robust GPU capable of handling gaming and detailed graphics. This makes the Galaxy M67 ideal for users who appreciate a rich visual experience.

Another advantage of the Exynos 2200 is energy efficiency. The chip intelligently manages battery usage to keep the device running longer without frequent recharging, making daily use more convenient.

In short, the Exynos 2200 combines performance and efficiency, designed for mid-range smartphones that aim to deliver cutting-edge technology. It makes the Galaxy M67 a competitive, modern device within its segment.

The Exynos 2200 and Exynos 1680 are both chips used in Samsung smartphones, but they target different audiences. The Exynos 2200 is more powerful and designed for superior performance. The Exynos 1680, on the other hand, is designed for mid-range devices, offering a good balance between efficiency and cost.

The Exynos 2200 features an advanced GPU that enhances graphics and gaming, making it ideal for those seeking high performance. In comparison, the Exynos 1680 offers more modest performance but remains efficient for daily tasks like social media and video playback.

The difference in capabilities also extends to power consumption. While the Exynos 2200 is efficient, it focuses more on raw power. The Exynos 1680 prioritizes battery savings, allowing the phone to last longer between charges.

In short, the Exynos 2200 is the choice for those who want greater speed and superior graphics, whereas the Exynos 1680 suits those who prefer a balance between performance and battery life. Each chip has its own target audience and ideal use case in today's market.

The Galaxy M67 comes with a configuration that meets the needs of most users. It features 8 GB of RAM, allowing multiple apps to run simultaneously without lag. This memory capacity is ideal for social media, casual gaming, and productivity apps.

In terms of graphics, the Galaxy M67 boasts a powerful GPU integrated into the Exynos 2200 chip. This ensures smooth visuals and rich detail in games and videos. The GPU handles graphics processing, making the visual experience much more enjoyable.

The device runs on Android—a modern operating system offering security, ease of use, and access to thousands of apps via the Google Play Store. It features Samsung's custom interface, which includes useful tools and shortcuts for daily use.

These specifications make the Galaxy M67 a balanced, efficient choice for anyone looking for a modern, fast smartphone with good battery life for a variety of tasks.

Using a flagship-grade chip in a mid-range smartphone offers many benefits. A powerful processor delivers faster performance for everyday tasks, including opening apps, browsing the web, and gaming with enhanced graphics. Furthermore, these chips often feature advanced technologies, such as artificial intelligence, to optimize battery usage and enhance camera performance. This results in a smoother, more enjoyable user experience.

On the other hand, the device's cost may increase due to the use of a more expensive component. Even so, for those seeking high performance without paying flagship prices, this is an excellent solution.

It is also worth noting that the energy efficiency of these processors helps extend battery life, striking a balance between power and longevity. This makes the smartphone more versatile for a variety of situations.

The Samsung Galaxy M67, featuring the Exynos 2200 chip, is a major new arrival for those seeking performance and advanced technology in the mid-range segment. The choice of this powerful processor delivers greater speed, superior graphics, and improved efficiency, significantly enhancing daily use as well as the experience with games and apps.

mundophone

TECH

Apple tests Chinese RAM

Rising component prices in the tech market are forcing industry giants to seek alternative solutions. Apple, known for its rigorous supply chain control, is now looking to navigate the current global crisis in memory chip production.

According to the latest financial reports, the Cupertino-based company is actively testing RAM chips from China. The goal is clear: to try to curb the massive surge in production costs triggered worldwide by the artificial intelligence boom.

However, this logistical move is risky, to say the least, and is already sparking a wave of political controversy. The manufacturers Apple has selected are under scrutiny by the US government, a situation likely to turn this deal into a major diplomatic headache.

The company’s decision comes as its involvement with Chinese suppliers becomes a sensitive geopolitical issue amid growing U.S. efforts to contain China’s tech ambitions. 

CXMT is poised to become central to Beijing’s efforts to build a self-sufficient AI supply chain and is expected to become one of the most profitable technology companies to list in Shanghai, the FT said. It reportedly plans to raise at least 29.5 billion yuan ($4.3 billion) in an upcoming IPO.

In 2022, Apple faced significant pushback from U.S. policymakers including then-Senator Marco Rubio, who is now Secretary of State, after exploring the use of Chinese memory suppliers, the FT reported. At least 15 state-owned shareholders collectively hold 36% of CXMT, the report said, adding that many of its private funds also have backing from state-owned limited partners.

CXMT is currently the world’s fourth-largest producer of DRAM, a memory chip used in a wide variety of products ranging from smartphones to servers, the report said. Its market share is expected to rise to 15% by 2028 from roughly 11% last year, as new production lines come online in the Chinese cities of Hefei, Shanghai and Beijing, the report showed, citing data from SemiAnalysis.

Its main global peers in DRAM include Samsung Electronics, SK Hynix, and Micron Technology.

While CXMT’s capacity is expanding, it is unlikely to immediately flood the market with cheap chips, as its output is largely pre-committed, Ray Wang, a memory analyst at SemiAnalysis

The frenzied rush to build data centers to power artificial intelligence platforms has nearly exhausted the global supply of RAM and storage. Faced with shortages and price hikes from traditional suppliers, Apple has turned its attention to ChangXin Memory Technologies (CXMT) and Yangtze Memory Technologies (YMTC).

These companies are currently on a US Department of Defense blacklist, designated as entities linked to Chinese military operations. While doing business with these brands is not strictly illegal, the iPhone maker has already had to seek direct permission from the White House to avoid severe future penalties.

To ease government tensions, Apple has reportedly proposed an intriguing compromise: chips purchased from CXMT and YMTC would be used exclusively in iPhones manufactured and sold within the Chinese market, thereby freeing up global production lines for the rest of the world. This move also serves as a powerful bargaining chip against the brand's Asian rivals.

Technological impact and memory innovation...Beyond using Chinese manufacturers as leverage to drive down prices from its usual partners, the American brand is keeping a close eye on CXMT's technical evolution. The Asian company is developing a highly efficient new memory architecture that could be a game-changer.

This technical breakthrough focuses on producing high-density memory without relying on expensive Western lithography equipment, thereby bypassing current trade sanctions. To give you a clear idea of ​​what is at stake, here are the key advantages of this new generation of RAM:

-Faster data transmission between the processor and your smartphone's memory.

-A drastic reduction in power consumption, helping to extend battery life.

-A smaller physical chip footprint, freeing up valuable space inside the device.

-Enhanced capability to run artificial intelligence models locally with complete fluidity.

If everything goes according to plan, this logistical partnership could be a real lifesaver for your wallet. Without strict control over the final cost of these essential components, it is virtually certain that the next generation of smartphones will see a drastic price hike, making them even more unaffordable.

mundophone

TECH

A measure adopted in the United States highlights the impact of AI on the power grid

The expansion of artificial intelligence is often associated with technological advances, innovation, and increased productivity. However, behind the most sophisticated models lies an infrastructure that consumes vast amounts of energy. This reality became apparent during a recent heatwave in the United States, when authorities had to implement an emergency measure to prevent grid overloads, reigniting the debate over the environmental impacts of the new AI era.

Extreme temperatures across the eastern United States placed the country's largest power grid under severe strain. With millions of households running air conditioners simultaneously, electricity consumption neared historic highs.

Faced with this situation, the U.S. Department of Energy authorized an exceptional measure to maintain system stability.

The authorization allowed PJM Interconnection—the grid operator serving approximately 67 million people across parts of the Midwest and the U.S. East Coast—to tap into emergency generators owned by major energy consumers, such as data centers and industrial facilities.

These units typically remain idle, used only in the event of a power outage.

This time, however, they served as an additional power source to relieve the load on the main grid.

The authorization took effect as a temporary measure during the period of highest overload risk.

According to the operator, demand reached approximately 162,700 megawatts, very close to the region's all-time record.

Experts point out that the rapid growth of data centers is playing an increasingly significant role in this rise in energy consumption.

The expansion of artificial intelligence requires massive computing infrastructure capable of continuous operation, making these facilities some of the country's largest electricity consumers.

Data centers have become an essential—and problematic—part of the electrical infrastructure... At first glance, using the data centers' own generators seems like a highly logical solution. If these facilities can generate their own power during a supply outage, utilizing that capacity during critical moments helps relieve pressure on the public grid.

However, there is a significant aspect to this strategy.

Many of these emergency systems run on diesel or natural gas engines.

While highly effective at ensuring operational continuity, they also significantly increase pollutant emissions—precisely on days when air quality is often already compromised by intense heat.

In states like Virginia—considered a global hub for data centers—thousands of these generators are located near urban areas.

Recent studies indicate that the frequent operation of this equipment can increase emissions of nitrogen oxides, fine particulate matter, and other pollutants linked to the worsening of respiratory and cardiovascular diseases.

Researchers also link these emissions to a rise in asthma attacks and other health issues among populations living near these facilities.

Thus, the solution devised to prevent blackouts ends up creating another significant environmental challenge.

The growth of artificial intelligence also necessitates a new discussion about energy.

This situation highlights a transformation that often goes unnoticed.

Data centers have evolved beyond mere technical facilities for storing internet data.

Today, they form the physical foundation supporting cloud computing services, digital platforms, and—above all—large-scale artificial intelligence models.

As new AI applications emerge across virtually every economic sector, the energy required to power this infrastructure grows as well.

At the same time, factors such as more intense heatwaves, aging electrical grids, and increased electrification place further strain on distribution systems.

US authorities emphasize that the authorization granted was temporary and necessary to prevent supply interruptions during a critical period. Indeed, a major blackout amidst extreme temperatures could put hospitals, homes, public services, and millions of people at risk.

Several recent, aggressive measures highlight the U.S. power grid's vulnerability to surging AI and data center energy demands. The most immediate step was an emergency directive issued by the U.S. Department of Energy (DOE) authorizing grid operators to force large-scale AI data centers to disconnect from utility lines and run on backup power during brutal summer heatwaves.

The rapid integration of generative AI training models and commercial computing warehouses is driving residential and commercial power usage to record highs. Because of the severity of this crisis, several major, permanent, and long-term regulatory actions are currently rolling out:

Emergency backup order: During record-breaking heatwaves in the Eastern U.S., the DOE ordered dense clusters of AI data centers (particularly in Northern Virginia's "Data Center Alley") to switch to backup diesel or natural gas generators. This emergency measure successfully freed up critical megawatts to keep household air conditioners running.

FERC interconnection overhaul: The Federal Energy Regulatory Commission (FERC) issued sweeping orders forcing six regional grid operators to revamp their connection rules. This FERC Action provides a fast-track "priority lane" so energy-hungry data centers can plug into the electric grid more quickly, while establishing clear standards and timelines for transmission costs.

DOE power capacity commitment: The DOE previously committed $3 billion specifically for AI-centric smart grid programs to modernize grid operations and enable predictive analytics to better balance supply and demand.

mundophone 

TECH

Secrets of the brain: how computers are helping scientists unravel the organ's mysteries

For decades, neuroscientists have sought to understand how neurons generate thoughts, memories, and emotions. Recent advances in computer simulations, artificial intelligence, and mathematical models have revolutionized this field of knowledge. Known as computational neuroscience, this discipline is expanding our theoretical understanding of how the brain processes information.

It studies everything from the electrical and chemical mechanisms that make a single neuron function to complex networks of millions of neurons working in unison. It also links biological processes to cognitive functions, such as learning and decision-making. This enables the creation of digital simulations of brain regions and the testing of hypotheses that could not be investigated directly in a laboratory setting.

Consequently, computational neuroscience has paved the way for new technologies capable of, for instance, predicting epileptic seizures and restoring movement in paralyzed individuals. Furthermore, it inspires new breakthroughs in computing, artificial intelligence, robotics, and intelligent systems.

A complex system...The human brain is composed of billions of neurons interconnected by trillions of synapses. Each neuron receives signals (both electrical and chemical) from hundreds of others simultaneously. When these signals accumulate and cross a certain threshold, the neuron fires an electrical impulse to transmit its message. This communication occurs at the synapses: the sending neuron releases neurotransmitters that fit into receptors like a key in a lock.

One of the most fascinating characteristics of this system is its ability to reorganize itself. Frequently used connections strengthen, while inactive ones weaken. This mechanism—known as synaptic plasticity—is what allows us to learn and form memories. Although individual neurons perform relatively simple tasks, their collective interaction gives rise to sophisticated behaviors, such as recognizing faces, experiencing fear, and planning a trip. Simulated brains... To study all this complexity, computational neuroscientists create digital simulators that mimic the behavior of neurons and neural networks, supported by new software architectures. Their starting point was the groundbreaking work of British physiologists Alan Hodgkin and Andrew Huxley; in 1952, they mathematically described how a neuron fires an electrical signal—work that earned them a Nobel Prize and remains the foundation of the field to this day.

One of the most widely used digital neuron simulation models today is known as "integrate-and-fire." In this model, the neuron functions like a bucket being filled with drops of water. Each incoming signal adds a few drops. When the level exceeds a certain threshold, the bucket tips over and empties, firing its contents to other neurons. The process then begins anew. This model is computationally efficient, as it allows for the simulation of thousands of neurons simultaneously.

One of the most ambitious research initiatives in this field today is the Blue Brain Project in Switzerland, which seeks to digitally reconstruct sections of the rat cortex with immense biological detail. Even so, the result still represents only a tiny fraction of what a real brain does.

Simulating the 86 billion human neurons and their 100 trillion connections remains far beyond the capabilities of current technology. Consequently, scientists work with varying levels of abstraction, selecting the appropriate level of detail needed to answer each specific question that arises.

The inspiration for modern AI...The relationship between computational neuroscience and artificial intelligence is a two-way street. Back in the 1940s, neurophysiologist Warren McCulloch and cognitive scientist Walter Pitts created the first abstract model of an artificial neuron, directly inspired by the biological neuron.

Decades later, by stacking layers of these artificial units, scientists developed computational models of artificial neural networks. This is the foundation of deep learning, which drives technologies such as speech recognition, medical imaging, and language models.

The comparison also revealed significant differences: the brain learns from very few examples and consumes about 20 watts—less than a light bulb. In contrast, training a large AI model can consume as much energy as hundreds of households over the course of several days. Understanding how the brain achieves such efficiency remains one of the field's major questions. The answer could transform the way we build artificial intelligence.

Healthcare applications...In practice, this research is already changing lives. In experiments using brain-computer interfaces (i.e., with sensors implanted in the brain), completely paralyzed individuals have managed to control robotic arms simply by thinking about moving. Although the movements lack speed and precision, they demonstrate that regaining function is feasible, even years after a central nervous system injury.

Some computational models can already identify brain patterns signaling the onset of an epileptic seizure, providing minutes or even hours of advance warning. For those with drug-resistant epilepsy, such a warning can significantly improve their daily routine and autonomy.

mundophone