Friday, October 30, 2026

 

Powering solar-powered flight



Study reveals battery performance targets for solar stratospheric aircraft




Harvard John A. Paulson School of Engineering and Applied Sciences

solar_stratospheric aircraft

image: 

Solar aircraft can fly through the stratosphere to collect atmospheric and climate data. 

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Credit: Electra Aero






A sleek, pilotless, solar-powered airplane that soars through the atmosphere to monitor climate or track wildfires was once just an idea.

Now, these high-altitude specialty aircraft are advancing from early prototyping demonstrations towards potential commercial applications, supported by decades of research and development involving Harvard scientists, aerospace engineers, and industry collaborators.

In a new paper published in ACS Energy Letters, researchers in the John A. Paulson School of Engineering and Applied Sciences (SEAS), in collaboration with partners in industry and the University of Michigan, lay out a pathway to clearing the most significant hurdle still facing extended solar flight: battery performance.

Solar-powered, fixed-wing, long-endurance aircraft are designed to cruise for weeks or months at a time through the stratosphere – twice the 30,000-foot cruising altitude of commercial jets, and higher than most clouds and weather. These aircraft must use excess solar energy during the day to continuously charge their batteries, then rely on those batteries at night.

Harvard researcher Craig Mascarenhas, who leads engineering research on solar aviation through the laboratory of Jim Anderson, the Philip S. Weld Professor of Atmospheric Chemistry at SEAS, spearheaded the study that establishes performance targets for next-generation solar aircraft batteries.

“It’s this circular mathematical relationship where you need more energy storage, but the batteries become heavier, so now you need more power to push it through the air to get more lift,” explained Mascarenhas, who is now an engineer focused on wireless power-transfer systems for NASA lunar missions but maintains a collaboration with Anderson’s lab.

High-resolution atmospheric data for many applications

Anderson, who has worked on solar aircraft concepts for the last three decades, heads the Harvard branch of a research collaboration called SACOS, or Stratospheric Airborne Climate Observing System, which has been funded by NASA and includes partners at MIT as well as private aerospace companies.

If optimized, solar stratospheric flight could provide persistent, detailed atmospheric and climate observations that are difficult and expensive to attain today. The NASA ER-2 high-altitude aircraft, for example, flies scientific missions carrying a pilot and instrumentation to collect data, but only for six to eight hours at a stretch, at tens of thousands of dollars per hour of flight time.

By contrast, a modern, unmanned solar aircraft could remain airborne for months, require fewer personnel and lower operating costs, and could be used to, for example, repeatedly monitor the same location for high-quality data. Potential value would range from new atmospheric chemistry to hurricane tracking to wildfire monitoring and prediction.

Energy density over power density

In their analysis, featured on the journal’s cover, the researchers identified 500 watt-hours per kilogram as an important threshold for the energy density of a solar stratospheric aircraft’s battery. At that level, they argue, persistent flight becomes viable across many parts of the world where atmospheric conditions allow.

By comparison, today’s commercial electric-vehicle batteries sit in the roughly 250 watt-hour per kilogram range, while experimental or specialty cells in the 400 watt-hour per kilogram range are already available. “We’re almost there,” Mascarenhas said. “Those cells are very expensive right now, but they’re getting cheaper very quickly.”

For this type of aircraft, the paper argues, energy density matters far more than power density, given that the aircraft’s power demands are exceedingly low, but the energy required to store enough energy to main flight remains high. Thus, battery developers should focus on prioritizing energy density, rather than optimizing both energy and power density equally, as is a more conventional principle of engineering. The study also drew on battery-science expertise from coauthors Venkatasubramanian Viswanathan and Shashank Sripad, whose work focuses on next-generation energy storage and electric aviation.

The paper is co-authored by John Langford, an aerospace entrepreneur whose companies  have built and flown experimental solar aircraft, and with whom Anderson has had a long-term research collaboration. 

Langford’s company Iris Aero is currently funded by a U.S. Department of Agriculture National Institute of Food and Agriculture grant, with the Harvard team serving as a research partner. Anderson and Mascarenhas are leading the research direction on the effort, which aims to support deep-learning and radiative transfer models for wildfire mapping and environmental sensing, enabled by stratospheric airborne observation as described in the recent ACS Energy Letters paper.

Mascarenhas said he is particularly motivated by the wildfire application. “I’m passionate about reducing the damage and destruction from wildfires across the world,” he said. “I think the capabilities that this project uniquely unlocks are very exciting.”

 

More than half of pilots say they flew while tired as trust in reporting systems remains low, survey finds

Pilot fatigue remains a major aviation concern.
Copyright Cleared/Canva


By Marta Iraola Iribarren
Published on

Pilot fatigue remains a major aviation concern, with many reporting nodding off during flights instead of declaring themselves unfit to fly.

Fear of negative consequences and a lack of trust in reporting systems are among the barriers that prevent pilots from declaring themselves unfit to fly due to fatigue, according to a new survey by the European Cockpit Association (ECA).The ECA identified head nodding, struggling to keep their eyes open, impaired alertness and microsleeps — brief, involuntary episodes of sleep — as signs of fatigue that can affect pilots on the flight deck.

More than half of pilots surveyed said they had flown while tired, while over 76% reported experiencing at least one microsleep on the flight deck in the previous four weeks, highlighting concerns about fatigue management in aviation.

Conducted by aviation consultancy Baines Simmons, the survey gathered responses from 7,200 pilots across 32 countries.

More than half of respondents reported that at least once in the previous three months they had operated a flight before realising in hindsight that they should have declared themselves unfit to fly due to fatigue.

The most commonly cited barrier was concern about management’s reaction, reported by 47% of pilots. A further 44% said they did not want to draw attention to themselves, while 35% were reluctant to inconvenience their employer.

“When pilots fear career consequences, fatigue goes unreported and the risk returns to the cockpit,” said ECA Board Director Captain Coen George.

Fatigue can result from acute sleep loss, long or demanding flight duty periods or repeated inadequate recovery time between duties.

The report highlights the particular dangers of cumulative fatigue, which can build up over time. Pilots may find it harder to recognise the resulting impairment in advance than the effects of short-term sleep deprivation.

Despite widespread awareness of fatigue risks, the problem remains underreported in the aviation industry.

While 82% of pilots knew how to submit a fatigue report, only 12% said they trusted the reporting system, and just 11% reported that fatigue submissions had led to operational changes to improve safety.

Half of respondents said fatigue risks at their airline were either poorly managed or not managed at all.

Fatigue is a known problem

Fatigue among aircrew is not a new concern. Aircrew fatigue was identified as one of the most consistent and prominent safety concerns in the European Union Aviation Safety Agency (EASA) report published in June 2026.

It linked fatigue to several operational and socio-economic factors, including flight scheduling, short-notice roster changes and the use of commanders’ discretion to extend flight duty periods beyond their scheduled limits.

EASA highlighted the need for targeted safety initiatives to improve reporting quality and awareness and foster a workplace culture where personnel can declare themselves tired without fear of reprimand.

 

People are influenced by unreliable information yet remain aware of its influence on their decisions




University of Tsukuba





Tsukuba, Japan—Every day, people make decisions based on information obtained from social media, news outlets, online reviews, and interpersonal communication, all of which vary in reliability. Numerical indicators and labels designed to convey information reliability, such as user ratings and fact-checking systems, have become increasingly common online. However, an important question remains: When reliability is explicitly stated, do people use this information appropriately for making decisions?

Participants completed a decision-making task in which each information source was accompanied by a numerical value indicating the probability that the source would provide the correct information. Participants were asked to integrate information from multiple sources when making a judgment. The results showed that participants assigned greater weight to sources with higher reliability but did not use the stated reliability values exactly as they were presented. Notably, information labeled as having a 50% probability of being correct, which should theoretically provide no useful basis for decision-making, still biased participants' choices toward the content of that information.

In a separate experiment, participants were also asked to report how strongly they believed each source had influenced their judgment. The results indicated that the participants could often recognize, to some extent, when unreliable information had affected their decisions. Although they were influenced by unreliable information, they also showed some metacognitive awareness of that influence.

These findings highlight the importance of providing explicit information reliability indicators and understanding how people interpret and integrate this information during decision-making. The results may help explain how individuals respond to information of varying trustworthiness in today's information environments.

###
This work was supported by an ESRC grant ES/V00378X/1 awarded to Lucie Charles and Partrick Haggard.

 

Original Paper

Title of original paper:
How does explicit reliability guide choices? Effect of trustworthiness on choice and metacognition

Journal:
PLoS Computational Biology

DOI:
10.1371/journal.pcbi.1014818

Correspondence

Assistant Professor OTA, Keiji
Advanced Research Initiative for Human High Performance (ARIHHP), Institute of Health and Sport Sciences, University of Tsukuba

Related Link

Institute of Health and Sport Sciences

 

Largest bank heist in history: Binance hack rocks crypto industry

FILE - An advertisement for the cryptocurrency Bitcoin is displayed on a building in Hong Kong on Nov. 18, 2021. (AP Photo/Kin Cheung, File)
Copyright AP Photo

By Angela Barnes
Published on

Cryptocurrency platform Binance said on Thursday it had fallen victim to a major hack that hit around $6.3 billion (€5.5bn) in funds, with about half that amount frozen to prevent a massive theft.

The company - the world's largest crypto exchange by daily trading volumes - posted a series of sometimes contradictory messages on X, insisting that "user funds are completely safe" but also saying it would "cover all losses".

Binance later said on its X account for Latin America that "the total estimated impact is around $6.3bn (€5.5bn)".

"We have worked with blockchain partners to freeze the affected assets, with ~ $3bn (€2.6bn) frozen on-chain so far," it added.

That would be more than four times the amount involved in what had been the biggest-ever cyberattack of its kind to date: $1.5bn (€1.3bn) taken in February 2025 from the Bybit platform.

The Bybit heist was attributed at the time to a group of hackers affiliated with North Korea called TraderTraitor.

Blockchain investigation firm TRM Labs said on Thursday it had "high confidence" that the Binance hack was also orchestrated by TraderTraitor, citing "robust on and off-chain intelligence".

"Several features of this attack match earlier North Korea-linked heists," TRM said.

TraderTraitor is believed to be part of Lazarus Group - which gained notoriety in 2014 when it was accused of hacking into Sony Pictures as revenge for "The Interview", a film that mocked North Korean leader Kim Jong Un.

Fund freeze

At about 0030 GMT (0230 CEST) on Friday, Binance said all deposits and withdrawals had been "temporarily suspended while our team conducts security checks, freezes funds and works with law enforcement".

"This figure may continue to increase as our teams work closely with law enforcement, issuers, blockchain intelligence firms and industry partners to trace and freeze additional assets," the company said.

The company's statement on X said an initial investigation suggested the hack involved a compromised laptop belonging to a "DevOps engineer", allowing the unauthorised party to access a "service container" and execute unauthorised withdrawal transactions.

"We have found no evidence of any private key leaks from wallets," Binance said, promising to share a detailed technical analysis once investigations were complete.

Paolo Ardoino, the boss of Tether - a company that issues a cryptocurrency known as USDT - said his firm had frozen about $1.6bn (€1.4bn) "related to a potential Binance exchange hack".

Jeremy Allaire, who runs cryptocurrency platform Circle, said his company had frozen more than $800m (€696m) in USDC.

USDT and USDC are both "stablecoins", or digital currencies whose value is linked to a traditional currency, the US dollar.

The US Department of Justice and the FBI did not immediately respond to requests for comment.

Crypto prices tumble

For several hours before Binance confirmed the attack, industry observers said hackers had managed to reach the platform.

The prices of most major cryptocurrencies fell on news of the cyberattack, with the exception of stablecoins, which by definition can only fluctuate within tight margins.

At about 0400 GMT (0600 CEST), bitcoin and Ethereum were down 0.8%, recovering after plunges of nearly 5% and nearly 6%, respectively. BNB, Binance's native cryptocurrency, was up 2.7% after tumbling nearly 10%.

The attack on Binance comes as many observers express concerns that the ever-expanding capabilities of artificial intelligence (AI) models could compromise cryptography and IT security protocols.




 

 

US growth leans on AI as rest of rich world stalls - Oxford Economics

US growth leans on AI as rest of rich world stalls - Oxford Economics
Stripped of AI, US growth was a moderate 1.4% in 1H26 and other advanced economies grew even less, leaving them exposed if the boom fades. / bne IntelliNewsFacebook
By Ben Aris in Berlin October 29, 2026

Without the artificial intelligence boom, the US economy would have grown at a moderate annualised 1.4% in the first half of 2026, and other big advanced economies more slowly still, Oxford Economics estimated in a research briefing on October 29.

Should the AI boom slow or go into reverse, the risk of recession in the advanced economies would be substantial, according to Adam Slater, lead economist at the consultancy and author of the briefing, "The AI and non-AI economies - two different growth stories".

US: AI contribution to GDP growth, direct and indirect (ppt contributions to annualised GDP growth). Source: Oxford Economics. Note: investment is net of estimated imports

The estimate lands as investors grow nervous about how the AI build-out is being financed, after worries over AI debt triggered a chip sell-off across Asia in mid-October. It suggests that much of the strength in US output this year has come from a single sector, and that the rest of the rich world has little underlying momentum to fall back on.

A narrow US boom

Oxford Economics counts two main channels: investment in computer equipment, software, data centres and power generation, and the wealth effect of an AI-driven surge in share prices on consumer spending. Some estimates suggest AI-related stocks have accounted for about 75% of recent S&P 500 returns. Surging imports of the equipment used in the build-out partly offset the gain.

AI-related factors added about 1.1 percentage points to annualised US GDP growth in 1Q26 and about 0.8ppt in 2Q26, the consultancy estimates. In 2Q26 investment net of imports added 0.4ppt and stock market wealth effects a similar amount, so much of the headline 2.2% annualised growth rate can be put down to AI.

The US is leaning on technology far more than it did in the dotcom boom. That boom added about 0.8ppt a year to growth in 1996-2000, but underlying growth was strong too, at more than 3.0% a year. The narrow spread of today's gains, which accrue to a fairly small slice of US households, may help explain why consumer confidence has fallen since 2024 and sits below dotcom-era levels.

US: contributions to growth, 1996-2001 versus 2023-2026 (ppt contributions to GDP growth; Michigan consumer confidence index, right-hand scale). Source: Oxford Economics, Haver Analytics

Little to show elsewhere

Outside the US the effect is much smaller. Across six other advanced economies, AI-related factors added an average of 0.2ppt to growth in 2025-1H26, about a third of the US effect, ranging from about 0.1ppt in Germany to 0.3-0.4ppt in Sweden and Japan. Stripped of AI, growth in the group ran mostly at 0.5-1.0% a year.

Advanced economies: estimated shares of AI-related and non-AI factors in GDP growth (ppt contributions to y/y growth, 2025-1H26 average). Source: Oxford Economics

US growth without AI would still beat most of its peers, but by a narrower margin. Part of the weakness lies in interest-sensitive spending, which has been flat for three years outside the US as rates rose from 2022. Residential investment has shrunk in most economies, with especially big falls in Canada, Germany, France and Italy.

In the US, interest-sensitive sectors have grown by about 5% since 2022, less than GDP as a whole, but they are a smaller drag than they once would have been. Their share of US investment has fallen from 50-55% in 1980-2005 to below 40%, partly because tech has taken a growing share of equipment spending, and they respond less to rate changes than before.

The cost of the build-out

Data centres' energy needs, which grew by more than 25% last year, are pushing up US wholesale electricity prices, one of several costs the boom imposes on the rest of the economy. The Dallas Fed estimated earlier this year that existing data centres had raised prices by 3-5% nationwide, and US power prices relative to the rest of the G7 had opened a gap of about 12% by 3Q26. That could add up to 0.3ppt to consumer prices and, other things equal, take about 0.2% off GDP, Oxford Economics estimates.

US and other G7: electricity prices (indices, January 2024=100; data centre investment, $bn at 2017 prices; $/MWh, 4Q25). Source: Oxford Economics, Haver Analytics, IEA

US prices of computers and peripherals are up 10% y/y and software nearly 30%, together adding about 0.04ppt to the consumer price index, while construction materials are rising about 5% y/y. More speculatively, heavy borrowing by AI companies may have helped push up bond yields: a 100bp rise in 10-year yields cuts US GDP by 0.1-0.3%, by the consultancy's modelling.

Altogether, these spillovers could cut 0.2-0.3% from US GDP. In economies that have gained little from the boom, they could wipe out much of what modest gains there have been, according to Oxford Economics.

South Korea's chipmakers bank record AI profits as markets wobble

South Korea's chipmakers bank record AI profits as markets wobble
Samsung and SK hynix are earning more than ever from AI memory, but investors are no longer sure how long the hyperscalers will keep paying. / Unsplash - BoliviaInteligente
By IntelliNews - Busan Bureau October 29, 2026

Samsung Electronics booked the biggest quarterly operating profit in its history on October 29, yet the AI spending behind the result looks shakier than it did a month ago.

The South Korean chipmaker (KRX: 005930) made an operating profit of KRW107.4 trillion ($80.2bn) in July-September, 782.8% more than a year earlier and the first time it has cleared KRW100 trillion in a single quarter. Heavy buying of AI hardware by the hyperscalers carried the figure past the KRW106 trillion consensus compiled by FnGuide.

Samsung now earns more in a quarter than Microsoft, Alphabet or Meta, the US groups whose data-centre budgets fill its order book. Memory makers have been the surest winners of the AI build-out so far, but their profits depend on those budgets holding, and investors spent October asking whether they will.

The rest of the income statement was less convincing. Revenue rose 126.9% to KRW195.3 trillion, short of the KRW200.3 trillion analysts had pencilled in, and net profit of KRW75.1 trillion fell well below the KRW87.4 trillion they expected.

SK hynix (KRX: 000660), the main supplier of high-bandwidth memory (HBM) to Nvidia, set the tone a day earlier. Its operating profit climbed 557.2% year on year to KRW83.33 trillion, at a margin above 80%, and it announced a fresh shareholder return plan worth KRW60 trillion on top of a KRW40 trillion programme it had just completed.

"Virtually all of our DRAM and HBM production capacity for the next three years through 2029 has already been sold out," the company told analysts on its results call.

Seoul took that as a licence to buy. The Kospi rose 6.6% to 6,012.44 on October 28, its steepest one-day gain in three months, as SK hynix shares added 10%, Saxo Bank said in a market note.

The rally came after a punishing month. The index lost 15.7% over the first three weeks of October, and on October 15 an 8% slide tripped a circuit breaker in Seoul as investors questioned the debt piling up behind US data-centre construction. SK hynix shelved a US listing of its Solidigm subsidiary on October 23, citing market conditions.

US results that evening clouded the picture again. Alphabet shares dropped about 10% in after-hours trading on disappointing revenue and negative free cash flow of $9.07bn for the third quarter, according to Saxo. Microsoft gained 3% as its Azure cloud sales grew 48%, but its capital spending of $39.4bn came in well below estimates, which is cold comfort to anyone selling it chips. Nasdaq 100 futures were down 0.9% in early Asian trade on October 29, and the Kospi opened flat at 6,017.22.

Swings of this size in both directions within a fortnight say more about investors' nerves than about the chipmakers' order books. Samsung's preliminary guidance put its operating margin at a record 55.1%, KB Securities expects its HBM prices to more than double in 2027, and SK hynix sees memory shortages lasting until 2030. The doubt lies with the buyers. While Alphabet, Microsoft and their peers keep their capex plans intact, Korea's memory makers will keep posting records. The first clear sign of a cutback would land hardest in Seoul, where the market's mood now rises and falls with two companies.


Fluent language makes a hallucinatory chatbot just as credible as a curt, flawless one


An eloquent AI system that shares incorrect information is rated just as highly by users as a curt AI system that provides correct answers




Radboud University Nijmegen






A chatbot that speaks naturally is more likely to be perceived by users as intelligent and useful, even if it spouts nonsense, research by communication scientists at Radboud University shows. An eloquent AI system that shares incorrect information is rated just as highly by users as a curt AI system that provides correct answers.

Most people are by now quite familiar with ChatGPT, Gemini, Claude and other chatbots: every day, people ask millions of questions and receive neatly formulated answers in return. Yet these language models still tend to run wild with so-called ‘hallucinations’: unreliable, dubious answers that are presented with great certainty as the truth. Communication scientist Marianna de Sá Siqueira and her colleagues investigated the effects of elegant language use on the credibility of chatbots.

Nonsense in fluent language

For the experiment, participants were shown one of four variants of a conversation with a chatbot about The Lord of the Rings. Two variants featured fluent sentences and human-like language, one of which gave correct answers and the other did not. In addition, there were two variants with short, businesslike answers, one of which provided entirely correct information whilst the other presented (subtly) fabricated facts.

Unsurprisingly, users were most positive about the chatbot with elegant language and correct answers. However, a chatbot that writes fluently but spouts factual nonsense was rated by participants as just as intelligent and pleasant as a chatbot that communicates in a stilted manner but does provide factually correct information. It also emerged that as many as 80 per cent of participants did not notice the errors at all, even though they had been selected in advance for their basic knowledge of The Lord of the Rings.

"Above all, it shows how easily people can be led astray and how quickly we come to trust something that is actually spouting nonsense," says Barbara Müller, associate professor and co-author of the study. "If a text sounds elegant and natural, people automatically attribute intelligence to it. You then subconsciously tend to think: this is fine, I don’t need to check it any further."

Blind trust

The research highlights the danger of blind trust in artificial intelligence. Professor and co-author Tibor Bosse says: "So-called language models such as GPT and Claude are primarily trained to produce statistically plausible and easy-to-read sentences. These systems do not always take the truth very seriously. They are designed to sound human and convincing, but whether the information is factually correct is of secondary importance."

"People used to complain that chatbots were annoying and knew nothing. Now they sound so clever that we’re too quick to believe them," says Bosse. According to him, this cannot be solved with a simple disclaimer at the outset. "Most chatbots show a single line of text at the start stating that the output may not be entirely accurate, but those companies are certainly not going to indicate of their own accord with every answer that the system is uncertain. If we really want to protect users from chatbots spouting nonsense, we need to, for example, oblige tech companies to make that uncertainty visible. If a chatbot itself expresses doubt, you prevent people from taking nonsense as the truth."

Journal

DOI

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Article Publication Date

Hertz Fellow Owen Dugan helps launch AI company built for American factories




Fannie and John Hertz Foundation






A new artificial intelligence company is working to help American factories bring products from design to production faster.

Arda, which launched Oct. 2026, is developing AI-powered software that turns product designs into assembly plans and updates those plans as designs change.

The technology aims to help manufacturers adapt production processes more quickly, reducing the time between designing a product and making it. Led by former OpenAI chief research officer Bob McGrew, Arda has raised $232 million, is valued at $1.5 billion, and plans to expand into robotic assembly, developing AI that could allow automated production lines to adapt to new designs in days rather than months.

Among the company’s founding researchers is 2024 Hertz Fellow Owen Dugan, who joined Arda in January as the first AI hire. During his intial weeks at Arda, he built a demo that became Arda’s first product.

“I joined Arda because I wanted to help American factories build faster. The Hertz Fellowship gave me the freedom to take a bet on a young company and the confidence that bold ideas are worth pursuing,” said Dugan. “Strengthening American manufacturing is one way I hope to honor the Hertz Fellows’ moral commitment to help the country in times of need.”

Dugan will present his recent AI model research at NeurIPS 2026 in Sydney on a framework for jointly training incrementally refinable Transformer widths with restart-free adaptive inference.

Dugan holds patents for algorithms that remove satellite trails from astronomical images, addressing a growing challenge for astronomers as more satellites enter orbit. He also co-founded a startup developing technology to verify the authenticity of digital images. These projects applied computational research to practical problems, experience he now brings to Arda, where he works alongside researchers and engineers from MIT, Palantir and Tesla to develop AI-powered manufacturing technology.

Dugan was one of 18 Hertz Fellows selected in 2024. The Hertz Fellowship is the nation’s most competitive doctoral fellowship in the applied sciences, engineering and mathematics. Awarded through a rigorous selection process honed over eight decades, Hertz Fellows receive up to five years of funding, providing the rare freedom to pursue bold ideas and a community of influential peers dedicated to their success.

Dugan’s involvement at Arda reflects a longstanding tradition of entrepreneurship within the Hertz Fellow community, where researchers apply their scientific expertise to build companies, develop new technologies and bring innovative ideas into practical use.

Throughout its history, the Hertz Foundation has supported generations of scientific entrepreneurs. Hertz Fellows have founded hundreds of companies, earned thousands of patents and made significant contributions to the nation’s economy. It continues to foster entrepreneurship through career support, mentorship, and up to $25,000 in funding through the Harold Newman and David Galas Entrepreneurial Initiative.

About the Hertz Foundation

The Hertz Foundation is the nation’s preeminent nonprofit organization committed to advancing American scientific and technological leadership. For more than 60 years, it has stood as an unwavering pillar of independent support through the renowned Hertz Fellowship, cultivating a multidisciplinary network of innovators whose work has positively impacted millions of lives. Learn more at hertzfoundation.org



Big data and AI drive the future of precision poultry nutrition




Higher Education Press

Image 1:

image: 

Graphical abstract showing big data and AI-powered precision poultry nutrition, illustrating the cycle of data collection, AI modeling, precision farming, and biotechnologies.
 

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Credit: HIGHER EDUCATION PRESS







LEAD
Integrating big data and artificial intelligence offers a sustainable solution to optimize feed efficiency and reduce the environmental footprint of global poultry farming.

BODY
[Paragraph 1 — The problem]
Global poultry production faces mounting challenges, including feed source shortages, environmental pollution, and the need to maintain animal welfare amid rising consumer demand. Traditional nutrition models often fail to accurately predict dynamic nutrient requirements, leading to wasted resources and excess greenhouse gas emissions. As the industry seeks sustainable expansion, there is an urgent need for more precise, data-driven nutritional strategies.

[Paragraph 2 — What was done]
Researchers from Jilin University, China Agricultural University and Jilin Academy of Agricultural Sciences conducted a comprehensive review of current precision nutrition technologies. They explored how the Internet of Things (IoT), computer vision, and sensor-based monitoring can be combined with advanced AI algorithms and machine learning. The team also summarized how biotechnologies, including omics techniques and biotechnology-derived proteins, can be integrated into modern poultry farming.

[Paragraph 3 — Key findings]
The review highlights that traditional linear regression models are insufficient for capturing the dynamic physiological states and environmental variations in poultry. In contrast, machine learning algorithms demonstrate superior performance in predicting feed energy values and nutrient requirements. Furthermore, the integration of big data allows for precise diet formulation and real-time adjustments, significantly enhancing the accuracy of nutritional supply. The authors emphasize that combining AI with omics technologies provides a deeper biological understanding of nutrient metabolism.

[Paragraph 4 — Significance and implications]
This integration promises to transform current poultry practices by improving feed efficiency and reducing production costs. By precisely matching nutrient supply to animal requirements, producers can significantly lower nitrogen and carbon emissions, mitigating environmental impacts. Ultimately, this data-driven approach supports sustainable agricultural development, ensuring food security while promoting better animal welfare.


Schematic diagram detailing the workflow of precision poultry farming.

Sankey diagram illustrating the application of AI and big data in poultry production based on a review of 32 articles.

Credit

HIGHER EDUCATION PRESS

New review illuminates the future of AI in pathology



Researchers bridge algorithms with clinical practice




Chinese Medical Journals Publishing House Co., Ltd.

The main application areas of deep learning in the analysis of whole slide pathological images

image: 

AI: Artificial intelligence; CNN: Convolutional neural networks; ResNet: Residual neural network.

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Credit: Xing-hua Gao from The First Hospital of China Medical University, China Image Source Link: https://www.ovid.com/jnls/cmj/fulltext/10.1097/cm9.0000000000004154~deep-learning-based-computational-pathology-technologies





Pathology, the gold standard for disease diagnosis, is undergoing a profound transformation. The shift from traditional microscopy to digital pathology, powered by whole-slide imaging (WSI), has opened the door for artificial intelligence (AI) to revolutionize diagnostic and prognostic workflows. However, a critical gap persists between the rapid advancements in AI algorithms and the practical demands of clinical practice. Pathologists need tools that are not only accurate but also interpretable, reliable, and seamlessly integrated into their work.

To bridge this divide, a team of researchers led by Prof. Xing-hua Gao from The First Hospital of China Medical University and Prof. Xiao-yu Cui from Northeastern University has published a comprehensive review. Their work introduces a novel framework for systematically connecting cutting-edge deep learning technologies with core clinical tasks in pathology. The review, which analyzes the field from 2020 to 2025, was made available online on July 22, 2026 and published in Chinese Medical Journal.

“The challenge isn’t just about creating powerful algorithms; it’s about making them clinically relevant and actionable,” explains Prof. Gao. “We introduced a dual-perspective framework that maps specific deep learning architectures—like CNNs, Vision Transformers, and Graph Neural Networks—to essential clinical needs such as diagnostic classification, tissue segmentation, and prognostic prediction. This provides a much-needed roadmap for developing AI solutions that truly address the challenges pathologists face every day.”

The review highlights how these advanced AI models are already making an impact. For instance, Vision Transformers can achieve over 94% accuracy in classifying oral epithelial dysplasia, while other models can predict cancer patient survival directly from standard H&E-stained slides, reducing the reliance on more expensive and time-consuming genetic tests. The paper also points to the landmark FDA approval of the Paige Prostate AI system as a sign that the digital era of pathology has truly arrived.

A significant hurdle for developing pathology AI is the need for vast amounts of expertly annotated data, which is both time-consuming and costly to produce. The review details emerging trends that tackle this bottleneck, including weakly supervised and self-supervised learning methods that minimize the reliance on these costly annotations. These approaches allow AI models to learn from large, unlabeled datasets, accelerating development and deployment.

“Our goal is to foster the development of AI systems that enhance, rather than replace, the invaluable expertise of pathologists,” notes Prof. Cui. “This means focusing on critical challenges like model interpretability, ensuring regulatory approval, and validating performance across multiple medical centers. The future lies in creating integrated, trustworthy, and equitable AI that becomes an indispensable partner in clinical decision-making.”

By providing a systematic overview and a clear algorithm-to-task mapping, the review serves as a vital resource for both researchers developing the next generation of AI tools and clinicians looking to integrate them into practice. The authors conclude with a forward-looking vision for a future where computational pathology tools are seamlessly woven into the fabric of clinical care, ultimately improving diagnostic accuracy and patient outcomes.

 

***

 

Reference
Title of original paper: Deep learning-based computational pathology: Technologies, clinical applications, and future directions

Journal: Chinese Medical Journal

DOI: 10.1097/CM9.0000000000004154

 

Funding
This work was supported by the National Key R&D Program of China (Grant No. 2023YFC2508200) and National Natural Science Foundation of China (Grant Nos. 82573977 and 82373483).