Saturday, July 18, 2026

US and Chinese companies train almost all of the world’s most-used AI models

By Edouard Mathieu, Head of Data and Research at Our World In Data

Analysis finds AI model ecosystem increasingly shaped by companies from the United States and China.

Dozens of companies worldwide develop large AI models, but it can be difficult to get a sense of where the most-used ones tend to come from.

OpenRouter is a large platform that allows users to interact with and write software on top of AI models through a single interface. It includes all the models from large companies like Google, OpenAI, Anthropic, Meta, DeepSeek, and Alibaba, as well as many, many others.

I analyzed the data published by OpenRouter on the 50 most used models each day since January 2025 and calculated the average monthly presence by origin country of the models.

As you can see on the chart, US-based companies still account for most models in OpenRouter’s top 50. But their presence has declined, and China-based companies have grown rapidly, from 5 models in the daily top 50 at the beginning of 2025 to 20 in May 2026.

Very few top-50 models come from companies outside the United States and China. Canada was represented early in 2025 by Cohere’s Command R models, while France remains represented by Mistral AI’s NeMo model.

A technology that more people use every year is, so far, almost entirely the product of two countries.

Originally published by Edouard Mathieu at Our World in Data. Republished here under a Creative Commons license.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Four ways to help your teen (and yourself) spend more time away from devices

Danielle Einstein, Macquarie University

Four ways to help your teen (and yourself) spend more time away from devices
Image: Hannah Busing - Unsplash

Phones and devices have become inextricably linked with everyday life. They store our credit cards, provide critical bus updates, and allow us to communicate whenever we need to.

But when our device use starts to affect our mood, replace real-life experiences, or interfere with face-to-face relationships, it’s a sign our habits have crossed the line from healthy to unhealthy.

How are teens more affected?

Teenagers are particularly vulnerable to excessive device use, as the part of the brain responsible for planning, imagining consequences and working for delayed rewards has not yet fully matured. They also have heightened sensitivities to rewards and social evaluation (in other words, what your peers think of you).

Research shows teenagers are more prone to mood swings, are still evolving their ability to manage uncertainty and are learning how to regulate their emotions.

All of this makes them more susceptible to online triggers that can trap a vulnerable teen in a cycle of conflicting and constantly changing emotions, particularly when information is arriving constantly.

For teens (and adults) it can become a complete world of its own where daily responsibilities are avoided and challenges are only faced with a dependency on phones.

So how do you know when it’s become a problem?

What to look out for

There are some obvious signs excessive device use is becoming a problem for teens (or yourself).

1. They use phones to fill in spare time. If every quiet moment is filled with scrolling, checking notifications or opening apps, it shows a teen’s device is the primary way they respond to spare time, stress or discomfort.

2. They appear distracted when you talk to them. If your teen automatically reaches for their phone midway through conversation, it might be a sign they devalue face-to-face exchanges and have lost the discipline to wait.

3. They put off important tasks. When teens routinely avoid everyday responsibilities such as work, homework, school, household chores or tasks that involve mixing with new people.

4. They seem tired all the time. Teens may block negative thoughts by scrolling in bed, socialising online late in the night, or even getting into bed after the school day.

How does it get to this stage?

The devices we rely on have the potential to develop what I call the “addictive pull” due to the features and services available on them. The “pull” begins when notifications, such as likes, messages, loot box wins and emails, arrive on devices unpredictably. Some are positive while others are neutral. And some also relieve worries. This creates a powerful dopamine-driven loop.

Over time, the device itself becomes a conditioned stimulus. This means even something as simple as seeing your phone case, or watching your device’s screen light up, is enough to trigger an urge to check it. It’s almost as if we are magnetically pulled to the device in the hope of a reward (such as more messages or likes), or to soothe a preoccupying worry.

This can also create an anxiety loop which means even without a notification, a person checks their device, rechecks it and experiences brief moments of relief via a message or app. When the loop occurs on repeat, it winds up worry and creates emotional dependence on others or apps.

The “addictive pull” can be hard to resist. Over time these unnoticed habits can become associated with the space where devices are often used (such as the bedroom, the apartment, the bus). The “pull” to re-engage with a device is a result of predictable conditioning and reinforcement processes rather than a lack of willpower. The bedroom – a place of rest, privacy and study – can be particularly problematic for teens and adults.

Leading by example

We cannot expect children or teens to break from the “addictive pull” if the adults around them don’t either.

As a parent, these are some ways you can lead by example to be more intentional when using devices.

1. Recognise the subtle tension that builds when you have a worry and want to reach for your device immediately.

2. When you walk into your home, place your phone or smartwatch out of the way and in a bag.

3. Do not have your phone or tablet in arm’s reach when it is designated family time.

4. Work with each family member to put apps being used without restraint onto one device per person. For instance, a parent or older teen might have TikTok on a tablet and not on their phone (so they can use their phone without distraction). They should then try to use that tablet in only one room of the house, outside of the bedroom.

Remember, an honest picture of everyone’s screen time habits sit on the device’s screen time records. We may get a minor fright when looking at it, but rather than resigning ourselves to this new way of life – and ignoring the insidious impact on attention, mood and wellbeing – we can commit to one another to make small changes.The Conversation

Danielle Einstein, Adjunct Fellow, School of Psychological Sciences, Macquarie University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Research Examines How Visual Appeal, Emotion and Cultural Messages Affect Digital Advertising Outcomes

By Inderscience

A study of digital advertising in the International Journal of Business and Systems Research suggests that memorable visuals are more likely to encourage consumers to buy than campaigns that rely primarily on emotional impact. The findings challenge the received wisdom about how online advertising influences behaviour.

The researchers analysed survey responses from more than 400 participants using structural equation modelling. This statistical technique tests relationships between multiple factors simultaneously. They examined how four advertising characteristics, provocativeness, emotional tone, cultural relevance, and visual appeal, affected purchase intention through two pathways. The first of these was emotional response, meaning the feelings an advertisement evokes, and the second was advertisement recall, or how well people remembered the details of the campaign.

The findings indicate that provocative advertising and culturally relevant messages were effective at generating emotional reactions. However, those emotional responses did not translate into stronger purchase intentions. Similarly, an advertisement's emotional tone neither improved recall nor influenced buying intentions.

By contrast, visually appealing advertisements consistently improved advertisement recall, and, in turn, stronger recall was linked to greater purchase intention. The results suggest that memory, rather than emotion alone, is the more reliable route from advertising exposure to consumer action.

The research addresses a gap in advertising studies, which have traditionally focused on factors such as credibility and informativeness rather than the effects of provocative or culturally tailored content. As brands compete for attention on social media platforms, the findings imply that striking imagery may be more effective when it helps audiences remember a message, rather than simply provoking an emotional reaction. For advertisers, in other words, the study suggests that attention-grabbing or controversial campaigns may need to be paired with memorable visual design to influence purchasing decisions.

Image: Timofey Radkevich - Unsplash

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Friday, July 17, 2026

Reelified: Americans Prefer Short-Form Video

By Felix Richter, Statista

Six years after Instagram launched Reels in response to the growing popularity of TikTok, short-form video has become the dominant content format. Snackable content delivered by ever more powerful algorithms has proven successful in keeping users engaged for longer, as it delivers dopamine hit after dopamine hit – resulting in more screen time for viewers and more ad impressions for platforms.

Despite concerns about its addictive nature and impact on attention spans, short-form video has quickly become the most popular content format. According to Statista Consumer Insights, 62 percent of U.S. adults say that short-form video is among their preferred content formats, putting it far ahead of text (42 percent) and long-form video (40 percent). This is true for all surveyed age groups (18 to 64 years old), illustrating that it’s not a trend limited to Gen Z, the so-called TikTok generation.

Feeling the pressure from Instagram, TikTok and YouTube, which are increasingly dominating screen time, even Netflix – the company that popularized long-form binge-watching – has started to embrace short-form content. Just months after introducing Clips, a vertical video feed serving short snippets from the company’s vast content library, Netflix will soon start offering curated videos from several digital media brands on its platform. The goal is clear – to keep users engaged – and the company is making no secret of it. “Starting next month, you’ll be able to watch some of your favorite videos from around the internet without having to leave Netflix to find them,” the company wrote in its press release. In other words: if you insist on watching short-form videos, Netflix wants you to do it on its platform – a clear sign that the battle for attention cuts across formats.

Short-form video tops U.S. content preferences at 62%, surpassing text at 42% and long-form video at 40%.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Study Examines Factors Affecting Consumers' Intentions to Buy Cryptocurrency

By Inderscience

Image: Mariia Shalabaieva - Unsplash

Consumers are more likely to buy cryptocurrencies when they see them as easy to use, trustworthy, and beneficial, according to research in the International Journal of Blockchains and Cryptocurrencies, which has used the Technology Acceptance Model as a framework to examine perception and adoption.

The team analysed survey data using partial least squares structural equation modelling (PLS-SEM). This statistical approach can test relationships between various factors simultaneously. This allowed the researchers to discern that perceived ease of use, trust, and benefits all had significant direct effects on a consumer's intention to buy cryptocurrency. Trust showed the strongest relationship, followed by ease of use, and finally benefits. Perceived risk reduced perceptions of benefit, but this link was not statistically significant, the team reports.

The findings suggest that concerns over volatility, cybersecurity, and the minimal regulation surrounding cryptocurrencies do not necessarily deter buyers if the platforms are seen as reliable and straightforward to use. The researchers argue that consumers are more likely to recognise advantages such as lower transaction costs, borderless payments, and investment portfolio diversification when they trust the technology and can navigate it easily.

The study has implications beyond cryptocurrency markets as governments and financial regulators consider how to oversee such digital assets. The authors recommend that there should be put in place clearer investor-protection rules, standardised compliance procedures, and enforcement of ethical marketing to reduce systemic financial risks.

They also argue that digital platform providers should prioritise stronger cybersecurity, transparent fee disclosures, and accessible interfaces to strengthen user confidence while protecting financial and personal data.

Reviewed by Irfan Ahmad.

This article was originally published by Inderscience and republished on DIW with permission.

Read next: Wherever AI is heading next, older people want a say
by External Contributor via Digital Information World

Wherever AI is heading next, older people want a say

Rachel Weldrick, Concordia University

Older people are being left out of decisions about how artificial intelligence is being built.

Many older adults are highly skilled, curious about emerging technologies and keen to learn about AI; they’re interested in its potential for our society. However, research shows that many employers still assume older employees are less tech-savvy.

Consequently, older adults often miss out on job opportunities or are passed over for promotions, even when they have the skills, training and expertise required.

The AI industry is a case in point. Rather than reflecting the full range of possible users, its workforce is largely made up of young men and runs the risk of developing apps and tools that reproduce these gender and age biases.

In fact, a growing body of research shows that older adults are consistently under-represented in the development of AI models. This makes those systems less accurate when it comes to recognizing and responding to the needs or preferences of older users.

For example, a study of AI-generated images found that pictures of older people are consistently and systematically less bright and less sharp than images of younger people.

Lived experiences of aging

At Concordia University, we’ve just completed a year-long community engagement project to gather perspectives and insights from older people about the future of aging alongside AI. This project is part of a larger interdisciplinary research collaborative in the AI space at Concordia.

Our preliminary findings show older people worry that AI tools framed around aging — such as fall detection or cognitive monitoring tools — are being designed by young developers who approach growing older as something to treat, manage or even prevent.

The health and wellness industry in particular is building new AI applications and tools at unprecedented rates — and these tools are increasingly designed for older people, older bodies and caregivers. While many of these tools offer up benefits like early disease diagnosis, symptom tracking and health promotion, they are not without their practical and ethical downsides.

Wherever AI is heading next, older people want a say
Image: AI-enabled humanoid robots are being designed to provide emotional support and to assist with tasks such as dressing, in long-term care homes for the elderly. (Unsplash/Enchanted Tools)

Quality of care and transparency are paramount. A recent study of AI in health-care decision-making found some older adults are skeptical about AI’s ability to understand complex care needs, and generally preferred human interaction over AI engagement.

Older participants in this study also felt strongly that AI usage must be transparent and involve informed consent. In other words, older adults wanted to determine when and where they engage with AI.

Participants in our community engagement project echoed similar concerns. Several older community members discussed the importance of transparency in all things AI. Some even shared examples of times when they had interacted with AI chatbots for things like online banking support, and thought they were chatting with a real person.

They believe their lived experiences of aging, and their unique perspectives, are not being captured in the data training these new AI tools. Nor are they being used to determine what sorts of AI tools are getting built in the first place.

These concerns beg the question: Who is making decisions about AI, and for whom?

AI scams target older adults

Many of our participants raised fraud as a great example of this mismatch.

AI-enabled scams often target older adults, in part because they are seen as more trusting than younger adults.

Recently, for example, a fake CBC article began circulating on social media that showed Canadian journalist Adrienne Arsenault interviewing grocery tycoon Galen Weston Jr., who appeared to storm out part way through the interview. The event never happened. The images were AI-generated and the article was designed to scam people by promoting a fake investment platform.

Some participants in our dialogue suggested that AI itself could be built to help people spot this kind of fraud before it happens. They felt no one has asked them to provide input on how to combat fraud, despite being the prime targets of it.

Build with, not for, older adults

What older adults are asking for isn’t complicated. They want a say in what AI gets built, what data trains it and how it’s governed.

They want accessible ways to learn AI skills, ideally through institutions they already trust, like community organizations and schools. Several participants suggested short, library-based courses rather than more apps to download, feeling in-person learning would be most effective.

Several public libraries, including the Toronto Public Library, do already run AI literacy programming alongside their traditional digital skills classes.

Older adults also expressed unease and concern for others: concern for artists losing control over their work to generative AI, and a wish that people of all ages (not just older adults) could just “stay analog” sometimes.

None of this is really about whether older adults can keep up with AI. Many of them are trying to. It’s about whether the people designing, training and governing these systems are willing to build them with older adults in the room, rather than building for them.

Older adults want a say in where AI is going next.The Conversation

Rachel Weldrick, Assistant Professor, Political Science, Concordia University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Thursday, July 16, 2026

AI is not yet the answer to detecting software vulnerabilities

Writing in the International Journal of Applied Cryptography, a team compares eleven leading large language models (LLMs) for software security. They found that no single system consistently outperforms its rivals in detecting vulnerabilities. This, they suggest, means organisations must select such tools according to the specific software they are analysing.

The study assessed open-source and proprietary LLMs across four public benchmark datasets covering Android applications, Internet of Things (IoT) software, and blockchain smart contracts. They also tested whether the models could identify privacy-invasive behaviour in code and whether retrieval-augmented generation (RAG), a technique that supplements an AI model with external information during use, could improve detection.

The findings come as software vulnerabilities continue to rise. Industry reports cited by the authors suggest an almost two-thirds annual increase in newly discovered vulnerabilities compared with the previous year. Vulnerabilities that have been exploited have increased by 96%. They add that software supply chain attacks, which target the software development and distribution process, have also increased sharply.

Their findings show that while several models showed promise, performance varied across datasets and domains. The authors thus argue that current LLMs remain unsuitable as universal vulnerability detectors. Limitations include outdated training data and the well-known problem of AI hallucinations, where plausible, but false, outputs are presented as fact by the AI. This, they explain, highlights the need for continued updates and testing before deployment in security-critical workflows.

Kouliaridis, V., Karopoulos, G. and Kambourakis, G. (2026) 'Large language models for vulnerability detection: a multi-use case comparative study', Int. J. Applied Cryptography, Vol. 5, No. 6, pp.1–17.
DOI: 10.1504/IJACT.2026.154618.


Image: Markus Spiske / Unsplash

This article was originally published by Inderscience News and republished on DIW with permission.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World