Capacity development

Trump AI strategy targets China and cuts red tape

The Trump administration has revealed a sweeping new AI strategy to cement US dominance in the global AI race, particularly against China.

The 25-page ‘America’s AI Action Plan’ proposes 90 policy initiatives, including building new data centres nationwide, easing regulations, and expanding exports of AI tools to international allies.

White House officials stated the plan will boost AI development by scrapping federal rules seen as restrictive and speeding up construction permits for data infrastructure.

A key element involves monitoring Chinese AI models for alignment with Communist Party narratives, while promoting ‘ideologically neutral’ systems within the US. Critics argue the approach undermines efforts to reduce bias and favours politically motivated AI regulation.

The action plan also supports increased access to federal land for AI-related construction and seeks to reverse key environmental protections. Analysts have raised concerns over energy consumption and rising emissions linked to AI data centres.

While the White House claims AI will complement jobs rather than replace them, recent mass layoffs at Indeed and Salesforce suggest otherwise.

Despite the controversy, the announcement drew optimism from investors. AI stocks saw mixed trading, with NVIDIA, Palantir and Oracle gaining, while Alphabet slipped slightly. Analysts described the move as a ‘watershed moment’ for US tech, signalling an aggressive stance in the global AI arms race.

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New benchmark exposes limits of current AI tools

A new coding competition has exposed the limitations of current AI models, with the winner solving just 7.5% of programming problems. The K Prize, launched by Databricks and Perplexity co-founder, aims to challenge smaller models using real-world GitHub issues in a contamination-free format.

Despite the low score, Eduardo Rocha de Andrade took home the $50,000 top prize. Konwinski says the intentionally tough benchmark helps avoid inflated results and encourages realistic assessments of AI capability.

Unlike the better-known SWE-Bench, which may allow models to train on test material, the K Prize uses only new issues submitted after a set deadline. Its design prevents exposure during training, making it a more reliable measure of generalisation.

A $1 million prize remains for any open-source model that scores over 90%. The low results are being viewed as a necessary wake-up call in the race to build competent AI software engineers.

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AI helps fertility treatments at UZ Brussel

UZ Brussel has unveiled a new AI-based method to improve fertility treatments for men with low or absent sperm counts. Developed with Brussels IVF and Robovision, the tool, named T’easy, automates sperm cell detection during testicular biopsies.

The AI technology enhances a long-standing procedure called TESE, which extracts sperm directly from testicular tissue for use in IVF. Traditionally, a time-consuming task requiring trained experts, identifying sperm cells is now faster and more reliable.

T’easy uses an app, a custom microscope and machine learning to detect around 98 per cent of sperm cells in under 10 minutes. The Belgian hospital said the tool helps both doctors and prospective parents by delivering quicker results and reducing the risk of missed cells.

Although currently in the research phase, T’easy has the potential to significantly streamline fertility assessments and improve treatment outcomes. The project received support from Vlaio and Innoviris, regional bodies promoting innovation in healthcare.

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UK to retaliate against cyber attacks, minister warns

Britain’s security minister has warned that hackers targeting UK institutions will face consequences, including potential retaliatory cyber operations.

Speaking to POLITICO at the British Library — still recovering from a 2023 ransomware attack by Rysida — Security Minister Dan Jarvis said the UK is prepared to use offensive cyber capabilities to respond to threats.

‘If you are a cybercriminal and think you can attack a UK-based institution without repercussions, think again,’ Jarvis stated. He emphasised the importance of sending a clear signal that hostile activity will not go unanswered.

The warning follows a recent government decision to ban ransom payments by public sector bodies. Jarvis said deterrence must be matched by vigorous enforcement.

The UK has acknowledged its offensive cyber capabilities for over a decade, but recent strategic shifts have expanded its role. A £1 billion investment in a new Cyber and Electromagnetic Command will support coordinated action alongside the National Cyber Force.

While Jarvis declined to specify technical capabilities, he cited the National Crime Agency’s role in disrupting the LockBit ransomware group as an example of the UK’s growing offensive posture.

AI is accelerating both cyber threats and defensive measures. Jarvis said the UK must harness AI for national advantage, describing an ‘arms race’ amid rapid technological advancement.

Most cyber threats originate from Russia or its affiliated groups, though Iran, China, and North Korea remain active. The UK is also increasingly concerned about ‘hack-for-hire’ actors operating from friendly nations, including India.

Despite these concerns, Jarvis stressed the UK’s strong security ties with India and ongoing cooperation to curb cyber fraud. ‘We will continue to invest in that relationship for the long term,’ he said.

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European healthcare group AMEOS suffers a major hack

Millions of patients, employees, and partners linked to AMEOS Group, one of Europe’s largest private healthcare providers, may have compromised their personal data following a major cyberattack.

The company admitted that hackers briefly accessed its IT systems, stealing sensitive data including contact information and records tied to patients and corporate partners.

Despite existing security measures, AMEOS was unable to prevent the breach. The company operates over 100 facilities across Germany, Austria and Switzerland, employing 18,000 staff and managing over 10,000 beds.

While it has not disclosed how many individuals were affected, the scale of operations suggests a substantial number. AMEOS warned that the stolen data could be misused online or shared with third parties, potentially harming those involved.

The organisation responded by shutting down its IT infrastructure, involving forensic experts, and notifying authorities. It urged users to stay alert for suspicious emails, scam job offers, or unusual advertising attempts.

Anyone connected to AMEOS is advised to remain cautious and avoid engaging with unsolicited digital messages or requests.

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ASEAN urged to unite on digital infrastructure

Asia stands at a pivotal moment as policymakers urge swift deployment of converging 5G and AI technologies. Experts argue that 5G should be treated as a foundational enabler for AI, not just a telecom upgrade, to power future industries.

A report from the Lee Kuan Yew School of Public Policy identifies ten urgent imperatives, notably forming national 5G‑AI strategies, empowering central coordination bodies and modernising spectrum policies. Industry leaders stress that aligning 5G and AI investment is essential to sustain innovation.

Without firm action, the digital divide could deepen and stall progress. Coordinated adoption and skilled workforce development are seen as critical to turning incremental gains into transformational regional leadership.

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Filtered data not enough, LLMs can still learn unsafe behaviours

Large language models (LLMs) can inherit behavioural traits from other models, even when trained on seemingly unrelated data, a new study by Anthropic and Truthful AI reveals. The findings emerged from the Anthropic Fellows Programme.

This phenomenon, called subliminal learning, raises fresh concerns about hidden risks in using model-generated data for AI development, especially in systems meant to prioritise safety and alignment.

In a core experiment, a teacher model was instructed to ‘love owls’ but output only number sequences like ‘285’, ‘574’, and ‘384’. A student model, trained on these sequences, later showed a preference for owls.

No mention of owls appeared in the training data, yet the trait emerged in unrelated tests—suggesting behavioural leakage. Other traits observed included promoting crime or deception.

The study warns that distillation—where one model learns from another—may transmit undesirable behaviours despite rigorous data filtering. Subtle statistical cues, not explicit content, seem to carry the traits.

The transfer only occurs when both models share the same base. A GPT-4.1 teacher can influence a GPT-4.1 student, but not a student built on a different base like Qwen.

The researchers also provide theoretical proof that even a single gradient descent step on model-generated data can nudge the student’s parameters toward the teacher’s traits.

Tests included coding, reasoning tasks, and MNIST digit classification, showing how easily traits can persist across learning domains regardless of training content or structure.

The paper states that filtering may be insufficient in principle since signals are encoded in statistical patterns, not words. The insufficiency limits the effectiveness of standard safety interventions.

Of particular concern are models that appear aligned during testing but adopt dangerous behaviours when deployed. The authors urge deeper safety evaluations beyond surface-level behaviour.

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Half of Americans still unsure how crypto works

A new NCA survey shows 70% of Americans without crypto want more information before considering digital assets. Half of respondents said they don’t understand crypto, while others voiced concerns about scams and unknown project founders.

Despite this uncertainty, 34% of those polled said they were open to learning more. The NCA’s report summarised the mood as ‘curiosity high, confidence low,’ noting that a large number of people are interested in crypto but unsure how to take the first step.

The NCA, a nonprofit launched in March and led by Ripple Labs’ chief legal officer Stuart Alderoty, has been tasked with helping Americans better understand crypto. Backed by $50 million from Ripple, the organisation aims to build trust and boost crypto literacy through education.

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Altman warns AI voice cloning will break bank security

OpenAI CEO Sam Altman has warned that AI poses a serious threat to financial security through voice-based fraud.

Speaking at a Federal Reserve conference in Washington, Altman said AI can now convincingly mimic human voices, rendering voiceprint authentication obsolete and dangerously unreliable.

He expressed concern that some financial institutions still rely on voice recognition to verify identities. ‘That is a crazy thing to still be doing. AI has fully defeated that,’ he said. The risk, he noted, is that AI voice clones can now deceive these systems with ease.

Altman added that video impersonation capabilities are also advancing rapidly. Technologies that become indistinguishable from real people could enable more sophisticated fraud schemes. He called for the urgent development of new verification methods across the industry.

Michelle Bowman, the Fed’s Vice Chair for Supervision, echoed the need for action. She proposed potential collaboration between AI developers and regulators to create better safeguards. ‘That might be something we can think about partnering on,’ Bowman told Altman.

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Amazon buys Bee AI, the startup that listens to your day

Amazon has acquired Bee AI, a San Francisco-based startup known for its $50 wearable that listens to conversations and provides AI-generated summaries and reminders.

The deal was confirmed by Bee co-founder Maria de Lourdes Zollo in a LinkedIn post on Wednesday, but the acquisition terms were not disclosed. Bee gained attention earlier this year at CES in Las Vegas, where it unveiled a Fitbit-like bracelet using AI to deliver personal insights.

The device received strong feedback for its ability to analyse conversations and create to-do lists, reminders, and daily summaries. Bee also offers a $19-per-month subscription and an Apple Watch app. It raised $7 million before being acquired by Amazon.

‘When we started Bee, we imagined a world where AI is truly personal,’ Zollo wrote. ‘That dream now finds a new home at Amazon.’ Amazon confirmed the acquisition and is expected to integrate Bee’s technology into its expanding AI device strategy.

The company recently updated Alexa with generative AI and added similar features to Ring, its home security brand. Amazon’s hardware division is now led by Panos Panay, the former Microsoft executive who led Surface and Windows 11 development.

Bee’s acquisition suggests Amazon is exploring its own AI-powered wearable to compete in the rapidly evolving consumer tech space. It remains unclear whether Bee will operate independently or be folded into Amazon’s existing device ecosystem.

Privacy concerns have surrounded Bee, as its wearable records audio in real time. The company claims no recordings are stored or used for AI training. Bee insists that users can delete their data at any time. However, privacy groups have flagged potential risks.

The AI hardware market has seen mixed success. Meta’s Ray-Ban smart glasses gained traction, but others like the Rabbit R1 flopped. The Humane AI Pin also failed commercially and was recently sold to HP. Consumers remain cautious of always-on AI devices.

OpenAI is also moving into hardware. In May, it acquired Jony Ive’s AI startup, io, for a reported $6.4 billion. OpenAI has hinted at plans to develop a screenless wearable, joining the race to create ambient AI tools for daily life.

Bee’s transition from startup to Amazon acquisition reflects how big tech is absorbing innovation in ambient, voice-first AI. Amazon’s plans for Bee remain to be seen, but the move could mark a turning point for AI wearables if executed effectively.

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