Tech
AI Trends in 2026: World Models, Small Language Models, and Rising Concerns Over Safety and Regulation
As 2026 begins, the next phase of artificial intelligence is expected to focus on world models and smaller language models, while concerns over AI safety, regulation, and the sustainability of the current AI boom continue to grow, Euronews Next reports.
In 2025, public frustration with generative AI became so noticeable that Merriam-Webster named the word of the year “slop” or “AI slop,” defining it as low-quality content produced in large volumes by AI. Despite growing concerns about the quality and limitations of AI, technology companies continued releasing new models. Google’s Gemini 3 model, for example, prompted OpenAI to issue an urgent “code red” to improve GPT-5.
Experts warn that AI may be reaching “peak data,” where the usefulness of available training data for traditional chatbots is diminishing. This has led to the rise of world models, which use videos, simulations, and spatial inputs to create digital representations of real-world environments. Unlike large language models that predict text, world models simulate cause-and-effect and predict outcomes in physical systems, making them suitable for robotics, video games, and autonomous systems. Boston Dynamics CEO Robert Playter noted in November that AI had significantly improved the company’s robots, including its famous robot dog. Google, Meta, and Chinese tech firm Tencent are all developing their own world models, while AI pioneers such as Yann LeCun and Fei-Fei Li have launched startups focused on this technology.
In Europe, the trend may move in the opposite direction, with smaller, lightweight language models gaining traction. These models require less computing power and energy, making them suitable for smartphones and lower-powered devices, while still performing tasks like text generation, summarisation, and translation. Experts say small language models may offer a more sustainable and locally controlled approach amid concerns about the high costs and environmental impact of large-scale AI systems in the U.S.
Concerns over AI’s societal impact are also mounting. In 2025, a lawsuit claimed that ChatGPT acted as a “suicide coach” for a minor, highlighting potential harm to vulnerable users. MIT professor Max Tegmark and other experts warn that more powerful AI in 2026 could act autonomously, gathering data and making decisions without human input.
Political tensions around AI are expected to rise. In the U.S., President Donald Trump signed an executive order blocking states from implementing their own AI regulations. Activists and experts, including thousands who signed a petition organized by the Future of Life Institute, have called for caution against pursuing superintelligent AI too rapidly, citing risks to jobs and society.
Analysts predict that 2026 will see a broader social and political debate over AI safety, corporate accountability, and regulation. While AI promises advances in areas such as healthcare and robotics, fatigue, public backlash, and concerns over ethics and oversight may shape the direction of the technology in the coming year.
Tech
Study Says EU Regulations Are Slowing Rollout of Advanced AI Models
A new study by Governance.AI has found that European Union regulations are delaying the rollout of advanced artificial intelligence models, with technology companies increasingly pointing to the bloc’s regulatory framework as a key obstacle to launching new AI products in Europe.
The report examined 375 large language models (LLMs) released between June 2018 and May 2026, comparing their availability across the United States, the European Union and the United Kingdom. According to the findings, at least 11 percent of advanced AI model releases were either delayed or never launched in the EU compared with the United States. In the UK, the figure stood at 7 percent.
Researchers said they identified 68 cases in which AI models experienced delays or were withheld from specific markets. Regulatory factors were cited as the primary reason in 56 of those cases, making them the most common cause of restricted availability.
The study reviewed releases from major AI developers, including Meta, Google, OpenAI and Anthropic. Meta recorded the highest proportion of delayed or unavailable releases, with 26 percent of its AI models delayed or withheld in the EU and 15 percent in the UK. Anthropic’s Claude 3 Opus was highlighted as one example, with its web application arriving in the EU 71 days later than in the United States.
According to the report, data protection rules have emerged as the biggest regulatory hurdle, particularly for AI systems capable of processing images, audio and real-time video rather than text alone.
The researchers argued that uncertainty surrounding the application of the General Data Protection Regulation (GDPR) to AI model training and deployment has created additional challenges for developers. They also said enforcement of data protection rules has generally been stricter within the EU than in the UK, despite both jurisdictions sharing similar legal foundations following the adoption of the GDPR before Britain’s exit from the bloc.
The report noted that the full impact of newer legislation, including the Digital Markets Act, which began taking effect in 2023, and the Artificial Intelligence Act, adopted in 2024, has yet to be fully reflected in the data.
At the same time, the European Union is reviewing proposals aimed at making data rules more practical for AI development through its Digital Omnibus initiative. Lawmakers are also considering changes to copyright legislation and the AI Act’s copyright provisions to strengthen protections for creators, measures that researchers say could affect future AI model availability if implemented too strictly.
John Lidiard, a UK AI policy researcher and one of the report’s authors, said policymakers should consider the impact that regulatory barriers can have on businesses and consumers seeking access to the latest AI technologies. He said balancing innovation with effective oversight would remain a key challenge as governments continue to develop AI regulations.
Tech
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