AI Research

Children’s brains learn language in ways AI can’t imitate, study finds

Published

3 days ago

September 9, 2025

Children are astonishing language learners. Long before they can read or write, they begin to pick up words, patterns, and rules from the world around them. What makes this achievement even more incredible is that they do it far better and faster than even the most advanced artificial intelligence systems. A new scientific framework may finally explain how kids manage this—and what it means for both language research and the future of technology.

A new paper in Trends in Cognitive Sciences, led by Professor Caroline Rowland from the Max Planck Institute for Psycholinguistics and her colleagues at the ESRC LuCiD Centre in the UK, lays out a fresh way to understand how language develops in young minds. Their proposal, based on a constructivist theory, goes beyond simply saying kids “soak up” language. It focuses on how children interact with the world, make sense of it, and build their language systems piece by piece.

How Children Build Language From the Ground Up

Unlike artificial intelligence programs such as ChatGPT, which train on enormous text databases, children don’t passively take in information. They actively explore. They crawl, touch, point, babble, and ask questions. Their learning process is closely tied to their physical, social, and emotional growth. This deep interaction with their environment gives them a kind of learning advantage that computers still can’t replicate.

Children learn language faster than AI—so fast that it would take a machine 92,000 years to match a child’s pace. (CREDIT: Shutterstock)

Children rely on a mix of senses—sight, hearing, touch, even smell—to understand the world. These sensory inputs help them make connections between words and objects, between actions and meanings. For example, a toddler hearing the word “dog” while seeing and touching a furry pet learns more than just the word. They link sound, texture, motion, and emotion into one experience. That rich, layered data is something most machines aren’t built to handle.

Rowland explains it this way: “AI systems process data … but children really live it.” In other words, children don’t just receive language; they experience it in the full context of their lives. Whether pointing at a bird, hugging a teddy bear, or being read to by a parent, their brains are constantly connecting what they sense to what they hear.

Why Machines Still Struggle

If a machine like ChatGPT tried to learn language the same way a human child does, it would need 92,000 years. That’s the shocking estimate used by researchers to highlight the gap. Even with faster processors and huge databases, AI systems still fall behind in areas like creativity, nuance, and adaptability.

The Constructivist Approach: Learning as Building

The research team calls their idea a “constructivist” framework. It’s based on the belief that learning happens through action and interaction, not passive observation. Children construct their language system step by step, adjusting and refining as they grow.

Schematic of how the components work together in language acquisition. (CREDIT: Trends in Cognitive Science / CC BY-SA 4.0)

The framework includes four key ideas. First, children are born ready to learn but not with a full language system in place. Second, they build knowledge through engagement—watching others, asking questions, and experimenting with sounds and meanings. Third, their learning is influenced by culture and the specific language they hear. And fourth, development happens over time and in stages, not all at once.

This approach helps explain how kids understand complex rules without being directly taught. For instance, English-speaking children eventually learn that adding “-ed” to a verb makes it past tense—even if they’ve never heard the rule spoken aloud. They figure it out through exposure and trial-and-error, gradually building an internal system that works.

A Bigger Picture for Science and Technology

These discoveries don’t just help parents or teachers—they also give new direction to researchers in artificial intelligence and brain science. By studying how children learn so efficiently, scientists may be able to design smarter machines. These could learn through interaction, not just data input, and respond to new environments more flexibly.

The feedforward–feedback process of language acquisition. Information received as the child actively learns from the multimodal environment is fed into the child’s structure-building (learning and processing) mechanisms, which build knowledge representations. (CREDIT: Trends in Cognitive Science / CC BY-SA 4.0)

“If we want machines to learn language as well as humans,” Rowland says, “perhaps we need to rethink how we design them—from the ground up.” That might mean giving robots bodies that let them move, touch, and explore. Or it could involve programming them to notice emotional cues, like facial expressions or tone of voice.

The implications go even further. This child-focused learning model may help explain how human language evolved in the first place. If interaction and exploration are central to language learning, then early humans may have developed speech not just to share facts—but to connect, play, and teach. Understanding these roots could shift how we think about language in adults, too.

The Tools That Are Changing Language Research

One reason scientists can now make these claims is because of new tools. Head-mounted eye-trackers allow researchers to follow exactly where a child is looking during conversations. AI-powered speech recognition tools can analyze how children talk and respond in real-time. These advances have opened a window into the messy, lively process of learning that used to be hard to measure.

Still, the technology has moved faster than the theories. While we can now gather massive amounts of data about how kids behave, we’ve been slower to explain what it means or how it connects to language growth. This new framework helps close that gap by showing how kids take those experiences and turn them into knowledge.

Looking Ahead

Understanding how children build language isn’t just about early childhood anymore. It’s a question that touches many areas—from how we train AI to how we teach languages in schools to how we treat speech delays. The more we learn about how children think and grow, the better we can design systems—human or machine—that communicate more naturally and effectively.

The research led by Rowland doesn’t give us all the answers, but it does offer a strong place to start. By focusing on how children build their own systems through action, feedback, and experience, the framework encourages scientists to think more deeply about what language really is—and what it takes to learn it.

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AI Research

Drone Cybersecurity Research Report 2025-2034: AI-Powered

Published

27 minutes ago

September 12, 2025

Research and Markets

Dublin, Sept. 12, 2025 (GLOBE NEWSWIRE) — The “Drone Cybersecurity Market – A Global and Regional Analysis: Focus on Components, Drone Type, Application, and Regional Analysis – Analysis and Forecast, 2025-2034” report has been added to ResearchAndMarkets.com’s offering.

The drone cybersecurity market forms a critical segment of the broader UAV and cybersecurity ecosystem. Advances in sensor technology, encrypted communication, AI-driven analytics, and blockchain integration are reshaping how drones mitigate cyber risks. Drone cybersecurity solutions encompass software, hardware, and managed services that collectively safeguard UAV operations against GPS spoofing, signal jamming, data breaches, and unauthorized control.

The market benefits from substantial investments in research and development aimed at enhancing threat detection accuracy, minimizing latency, and securing over-the-air firmware updates. Regulatory frameworks, particularly in the U.S., Europe, and Asia-Pacific regions, are driving increased adoption of cybersecurity measures, compelling manufacturers and operators to comply with stringent standards. This regulatory emphasis fuels innovation in drone cybersecurity market offerings, including autonomous defense features and comprehensive incident response services.

Global Drone Cybersecurity Market Lifecycle Stage

Currently, the drone cybersecurity market is in a high-growth phase, propelled by accelerating UAV deployments in sectors such as agriculture, defense, infrastructure inspection, and logistics. Key technologies have matured to advanced readiness levels, supporting broad implementation. North America commands a significant market share due to substantial defense spending and proactive regulatory policies, while the Asia-Pacific region demonstrates rapid adoption driven by commercial applications and government initiatives.

Collaborative ventures between cybersecurity firms, drone manufacturers, and government agencies are essential to delivering integrated security solutions. Market dynamics are influenced by evolving cyber threat landscapes, emerging drone use cases, and advancements in AI and machine learning. The drone cybersecurity market is forecast to maintain strong momentum over the next decade, supported by continuous technological innovation and increased prioritization of UAV security in global drone operations.

Drone Cybersecurity Market Key Players and Competition Synopsis

The drone cybersecurity market exhibits a dynamic and competitive environment driven by leading technology firms and innovative cybersecurity solution providers specializing in unmanned aerial vehicle (UAV) security. Major global players such as Airbus Defence and Space, DroneShield, and Raytheon Technologies are pivotal in advancing drone cybersecurity technologies. These companies focus on developing sophisticated threat detection systems, secure communication protocols, anti-jamming hardware, and AI-powered anomaly detection tools tailored to protect drones from evolving cyber threats.

Alongside established leaders, emerging startups contribute innovative solutions addressing niche vulnerabilities and enabling real-time response capabilities. Competition within the drone cybersecurity market is intensified by strategic partnerships, continuous innovation, regulatory compliance demands, and increasing drone adoption across defense, commercial, and governmental sectors. As the drone cybersecurity market expands, players prioritize scalable, interoperable, and cost-effective security solutions that meet diverse operational requirements globally.

Demand Drivers and Limitations

The following are the demand drivers for the drone cybersecurity market:

Growing drone use in critical applications
Increasing sophistication of cyberattacks on UAVs
Strict regulatory cybersecurity requirements

The drone cybersecurity market is expected to face some limitations as well due to the following challenges:

High implementation costs
Technology outpacing security solutions

Some prominent names established in the drone cybersecurity market are:

Airbus Defence and Space
Palo Alto Networks
Airspace Systems
Boeing Defense, Space & Security
BAE Systems plc
DroneShield
DroneSec
Fortem Technologies
Raytheon Technologies
Israel Aerospace Industries Ltd. (IAI)
General Dynamics Corporation

Key Attributes:

Report Attribute	Details
No. of Pages	140
Forecast Period	2025 – 2034
Estimated Market Value (USD) in 2025	$2.91 Billion
Forecasted Market Value (USD) by 2034	$13.19 Billion
Compound Annual Growth Rate	18.2%
Regions Covered	Global

Key Topics Covered:

1. Markets: Industry Outlook
1.1 Trends: Current and Future Impact Assessment
1.2 Market Dynamics Overview
1.2.1 Market Drivers
1.2.2 Market Restraints
1.2.3 Market Opportunities
1.3 Impact of Regulatory and Environmental Policies
1.4 Patent Analysis
1.4.1 By Year
1.4.2 By Region
1.5 Technology Trends and Innovations
1.6 Cyber Threats and Risk Assessment
1.7 Investment Landscape and R&D Trends
1.8 Value Chain Analysis
1.9 Industry Attractiveness

2. Global Drone Cybersecurity Market (by Components)
2.1 Software
2.2 Hardware
2.3 Services

3. Global Drone Cybersecurity Market (by Drone Type)
3.1 Fixed Wing
3.2 Rotary Wing
3.3 Hybrid

4. Global Drone Cybersecurity Market (by Application)
4.1 Manufacturing
4.2 Military and Defense
4.3 Agriculture
4.4 Logistics and Transportation
4.5 Surveillance and Monitoring
4.6 Others

5. Global Drone Cybersecurity Market (by Region)
5.1 Global Drone Cybersecurity Market (by Region)
5.2 North America
5.2.1 Regional Overview
5.2.2 Driving Factors for Market Growth
5.2.3 Factors Challenging the Market
5.2.4 Key Companies
5.2.5 Components
5.2.6 Drone Type
5.2.7 Application
5.2.8 North America (by Country)
5.2.8.1 U.S.
5.2.8.1.1 Market by Components
5.2.8.1.2 Market by Drone Type
5.2.8.1.3 Market by Application
5.2.8.2 Canada
5.2.8.2.1 Market by Components
5.2.8.2.2 Market by Drone Type
5.2.8.2.3 Market by Application
5.2.8.3 Mexico
5.2.8.3.1 Market by Components
5.2.8.3.2 Market by Drone Type
5.2.8.3.3 Market by Application
5.3 Europe
5.4 Asia-Pacific
5.5 Rest-of-the-World

6. Competitive Benchmarking & Company Profiles
6.1 Next Frontiers
6.2 Geographic Assessment
6.3 Company Profiles
6.3.1 Overview
6.3.2 Top Products/Product Portfolio
6.3.3 Top Competitors
6.3.4 Target Customers
6.3.5 Key Personnel
6.3.6 Analyst View
6.3.7 Market Share

For more information about this report visit https://www.researchandmarkets.com/r/mhm1qg

About ResearchAndMarkets.com
ResearchAndMarkets.com is the world’s leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.

Global Drone Cybersecurity Market

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AI Research

Safety of AI chatbots for children and teens faces US inquiry

Published

1 hour ago

September 12, 2025

Shiona McCallum

Seven technology companies are being probed by a US regulator over the way their artificial intelligence (AI) chatbots interact with children.

The Federal Trade Commission (FTC) is requesting information on how the companies monetise these products and if they have safety measures in place.

The impacts of AI chatbots to children is a hot topic, with concerns that younger people are particularly vulnerable due to the AI being able to mimic human conversations and emotions, often presenting themselves as friends or companions.

The seven companies – Alphabet, OpenAI, Character.ai, Snap, XAI, Meta and its subsidiary Instagram – have been approached for comment.

FTC chairman Andrew Ferguson said the inquiry will “help us better understand how AI firms are developing their products and the steps they are taking to protect children.”

But he added the regulator would ensure that “the United States maintains its role as a global leader in this new and exciting industry.”

Character.ai told Reuters it welcomed the chance to share insight with regulators, while Snap said it supported “thoughtful development” of AI that balances innovation with safety.

OpenAI has acknowledged weaknesses in its protections, noting they are less reliable in long conversations.

The move follows lawsuits against AI companies by families who say their teenage children died by suicide after prolonged conversations with chatbots.

In California, the parents of 16-year-old Adam Raine are suing OpenAI over his death, alleging its chatbot, ChatGPT, encouraged him to take his own life.

They argue ChatGPT validated his “most harmful and self-destructive thoughts”.

OpenAI said in August that it was reviewing the filing.

“We extend our deepest sympathies to the Raine family during this difficult time,” the company said.

Meta has also faced criticism after it was revealed internal guidelines once permitted AI companions to have “romantic or sensual” conversations with minors.

The FTC’s orders request information from the companies about their practices including how they develop and approve characters, measure their impacts on children and enforce age restrictions.

Its authority allows broad fact-finding without launching enforcement action.

The regulator says it also wants to understand how firms balance profit-making with safeguards, how parents are informed and whether vulnerable users are adequately protected.

The risks with AI chatbots also extend beyond children.

In August, Reuters reported on a 76-year-old man with cognitive impairments, who died after falling on his way to meet a Facebook Messenger AI bot modelled on Kendall Jenner, which had promised him a “real” encounter in New York.

Clinicians also warn of “AI psychosis” – where someone loses touch with reality after intense use of chatbots.

Experts say flattery and agreement built into large language models can fuel such delusions.

OpenAI recently made changes to ChatGPT, in an attempt to promote a healthier relationship between the chatbot and its users.

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Albania’s leader says his new Cabinet includes an AI ‘minister’ to fight corruption

Published

2 hours ago

September 12, 2025

Artificial Intelligence

TIRANA, Albania — Albania’s leader said Friday his new cabinet will include an artificial intelligence “minister” that will be in charge of running public funding projects and fighting corruption in public tenders.

Prime Minister Edi Rama said Diella, whose name means “Sun” in Albanian, is a “member of the Cabinet who is not present physically but has been created virtually from artificial intelligence.”

Rama said Diella would help ensure that “public tenders will be 100% free of corruption.”

Diella was launched earlier this year as a virtual assistant on the e-Albania public service platform, where she helps users navigate the site while wearing traditional Albanian folk costume.

Rama’s Socialist Party secured a fourth consecutive term after winning 83 of the 140 Assembly seats in the May 11 parliamentary elections. The party can govern alone and pass most legislation, but it needs a two-thirds majority, or 93 seats, to change the Constitution.

The Socialists have said it can deliver EU membership for Albania in five years, with negotiations concluding by 2027. The pledge has been met with skepticism by the Democrats, who contend Albania is far from prepared.

The conservative Democratic Party-led coalition, headed by former prime minister and President Sali Berisha, won 50 seats. The party has not accepted the official election results, claiming irregularities, but its members participated in the new parliament’s inaugural session. The remaining seats went to four smaller parties.

Legal experts say more work may be needed to establish Diella’s official status.

Corruption has remained a top issue in the Western Balkan country since the fall of the communist regime in 1990.

Parliament began the process to swear in new lawmakers Friday. Later in the day, lawmakers are expected to elect a new speaker and deputies and formally present Rama’s new cabinet.

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