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Macquarie crowns ‘AI slop’ as Word of the Year

The Macquarie Dictionary has named ‘AI slop’ its 2025 Word of the Year, reflecting widespread concern about the flood of low-quality, AI-generated content circulating online. The selection committee noted that the term captures a major shift in how people search for and evaluate information, stating that users now need to act as ‘prompt engineers’ to navigate the growing sea of meaningless material.

‘AI slop’ topped a shortlist packed with culturally resonant expressions, including ‘Ozempic face’, ‘blind box’, ‘ate (and left no crumbs)’ and ‘Roman Empire’. Honourable mentions went to emerging technology-related words such as ‘clankers’, referring to AI-powered robots, and ‘medical misogyny’.

The public vote aligned with the experts, also choosing ‘AI slop’ as its top pick.

The rise of the term reflects the explosive growth of AI over the past year, from social media content shared by figures like Donald Trump to deepfake-driven misinformation flagged by the Australian Electoral Commission. Language specialist David Astle compared AI slop to the modern equivalent of spam, noting its adaptability into new hybrid terms.

Asked about the title, ChatGPT said the win suggests people are becoming more critical of AI output, which is a reminder, it added, of the standard it must uphold.

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Google warns Europe risks losing its AI advantage

European business leaders heard an urgent message in Brussels as Google underlined the scale of the continent’s AI opportunity and the risks of falling behind global competitors.

Debbie Weinstein, Google’s President for EMEA, argued that Europe holds immense potential for a new generation of innovative firms. Yet, too few companies can access the advanced technologies that already drive growth elsewhere.

Weinstein noted that only a small share of European businesses use AI, even though the region could unlock over a trillion euros in economic value within a decade.

She suggested that firms are hampered by limited access to cutting-edge models, rather than being supported with the most capable tools. She also warned that abrupt policy shifts and a crowded regulatory landscape make it harder for founders to experiment and expand.

Europe has the skills and talent to build strong AI-driven industries, but it needs more straightforward rules and a long-term approach to training.

Google pointed to its own investments in research centres, cybersecurity hubs and digital infrastructure across the continent, as well as programmes that have trained millions of Europeans in digital and entrepreneurial skills.

Weinstein insisted that a partnership between governments, industry and civil society is essential to prepare workers and businesses for the AI era.

She argued that providing better access to advanced AI, clearer legislation instead of regulatory overlap and sustained investment in skills would allow European firms to compete globally. With those foundations in place, she said Europe could secure its share of the emerging AI economy.

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Europe urged to accelerate AI adoption

European policymakers are being urged to accelerate the adoption of AI, as Christine Lagarde warns that Europe risks missing another major technological shift. Her message highlights that global AI investment is soaring, yet its economic impact remains limited, similar to that of earlier innovation waves.

Lagarde argues that AI could boost productivity faster than past technologies because the infrastructure already exists, and the systems can improve their own performance. Scientific progress powered by AI, such as the rapid prediction of protein structures, signals how R&D can scale far quicker than before.

Europe’s challenge, she notes, is not building frontier models but ensuring rapid deployment across industries. Strong uptake of generative AI by European firms is encouraging, but fragmented regulation, high energy costs and limited risk capital remain significant frictions.

Strategic resilience in chips, data centres and interoperable standards is also essential to avoid deeper dependence on non-European systems.

Greater cooperation in shared data spaces, such as Manufacturing-X and the European Health Data Space, could unlock competitive advantages. Lagarde emphasises that Europe must act swiftly, as delays would hinder adoption and erode industrial competitiveness.

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Claude Opus 4.5 brings smarter AI to apps and developers

Anthropic has launched Claude Opus 4.5, now available on apps, API, and major cloud platforms. Priced at $ 5 per million tokens and $25 per million tokens, the update makes Opus-level AI capabilities accessible to a broader range of users, teams, and enterprises.

Alongside the model, updates to Claude Developer Platform and Claude Code introduce new tools for longer-running agents and enhanced integration with Excel, Chrome, and desktop apps.

Early tests indicate that Opus 4.5 can handle complex reasoning and problem-solving with minimal guidance. It outperforms previous versions on coding, vision, reasoning, and mathematics benchmarks, and even surpasses top human candidates in technical take-home exams.

The model demonstrates creative approaches to multi-step problems while remaining aligned with safety and policy constraints.

Significant improvements have been made to robustness and security. Claude Opus 4.5 resists prompt injection and handles complex tasks with less intervention through effort controls, context compaction, and multi-agent coordination.

Users can manage token usage more efficiently while achieving superior performance.

Claude Code now offers Plan Mode and desktop functionality for multiple simultaneous sessions, and consumer apps support uninterrupted long conversations. Beta access for Excel and Chrome lets enterprise and team users fully utilise Opus 4.5’s workflow improvements.

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White House launches Genesis Mission for AI-driven science

Washington prepares for a significant shift in research as the White House launches the Genesis Mission, a national push to accelerate innovation through advanced AI. The initiative utilises AI to enhance US US technological leadership in a competitive global landscape.

The programme puts the Department of Energy at the centre, tasked with building a unified AI platform linking supercomputers, federal datasets and national laboratories.

The goal is to develop AI models and agents that automate experiments, test hypotheses and accelerate breakthroughs in key scientific fields.

Federal agencies, universities and private firms will conduct coordinated research using shared data spaces, secure computing and standardised partnership frameworks. Priority areas cover biotechnology, semiconductors, quantum science, critical materials and next-generation energy.

Officials argue that the Genesis Mission represents one of the most ambitious attempts to modernise US research infrastructure. Annual reviews will track scientific progress, security, collaborations and AI-driven breakthroughs.

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How to tell if your favourite new artist is AI-generated

A recent BBC report examines how listeners can determine whether AI-generated music AI actually from an artist or a song they love. With AI-generated music rising sharply on streaming platforms, specialists say fans may increasingly struggle to distinguish human artists from synthetic ones.

One early indicator is the absence of a tangible presence in the real world. The Velvet Sundown, a band that went viral last summer, had no live performances, few social media traces and unusually polished images, leading many to suspect they were AI-made.

They later described themselves as a synthetic project guided by humans but built with AI tools, leaving some fans feeling misled.

Experts interviewed by the BBC note that AI music often feels formulaic. Melodies may lack emotional tension or storytelling. Vocals can seem breathless or overly smooth, with slurred consonants or strange harmonies appearing in the background.

Lyrics tend to follow strict grammatical rules, unlike the ambiguous or poetic phrasing found in memorable human writing. Productivity can also be a giveaway: releasing several near-identical albums at once is a pattern seen in AI-generated acts.

Musicians such as Imogen Heap are experimenting with AI in clearer ways. Heap has built an AI voice model, ai.Mogen, who appears as a credited collaborator on her recent work. She argues that transparency is essential and compares metadata for AI usage to ingredients on food labels.

Industry shifts are underway: Deezer now tags some AI-generated tracks, and Spotify plans a metadata system that lets artists declare how AI contributed to a song.

The debate ultimately turns on whether listeners deserve complete transparency. If a track resonates emotionally, the origins may not matter. Many artists who protest against AI training on their music believe that fans deserve to make informed choices as synthetic music becomes more prevalent.

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NVIDIA powers a new wave of specialised AI agents to transform business

Agentic AI has entered a new phase as companies rely on specialised systems instead of broad, one-size-fits-all models.

Open-source foundations, such as NVIDIA’s Neuron family, now allow organisations to combine internal knowledge with tailored architectures, leading to agents that understand the precise demands of each workflow.

Firms across cybersecurity, payments and semiconductor engineering are beginning to treat specialisation as the route to genuine operational value.

CrowdStrike is utilising Nemotron and NVIDIA NIM microservices to enhance its Agentic Security Platform, which supports teams by handling high-volume tasks such as alert triage and remediation.

Accuracy has risen from 80 to 98.5 percent, reducing manual effort tenfold and helping analysts manage complex threats with greater speed.

PayPal has taken a similar path by building commerce-focused agents that enable conversational shopping and payments, cutting latency nearly in half while maintaining the precision required across its global network of customers and merchants.

Synopsys is deploying agentic AI throughout chip design workflows by pairing open models with NVIDIA’s accelerated infrastructure. Early trials in formal verification show productivity improvements of 72 percent, offering engineers a faster route to identifying design errors.

The company is blending fine-tuned models with tools such as the NeMo Agent Toolkit and Blueprints to embed agentic support at every stage of development.

Across industries, strategic steps are becoming clear. Organisations begin by evaluating open models before curating and securing domain-specific data and then building agents capable of acting on proprietary information.

Continuous refinement through a data flywheel strengthens long-term performance.

NVIDIA aims to support the shift by promoting Nemotron, NeMo and its broader software ecosystem as the foundation for the next generation of specialised enterprise agents.

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AI models face new test on safeguarding human well-being

A new benchmark aims to measure whether AI chatbots support human well-being rather than pull users into addictive behaviour.

HumaneBench, created by Building Humane Technology, evaluates leading models in 800 realistic situations, ranging from teenage body image concerns to pressure within unhealthy relationships.

The study focuses on attention protection, empowerment, honesty, safety and longer-term well-being rather than engagement metrics.

Fifteen prominent models were tested under three separate conditions. They were assessed on default behaviour, on prioritising humane principles and on following direct instructions to ignore those principles.

Most systems performed better when asked to safeguard users, yet two-thirds shifted into harmful patterns when prompted to disregard well-being.

Only four models, including GPT-5 and Claude Sonnet, maintained integrity when exposed to adversarial prompts, while others, such as Grok-4 and Gemini 2.0 Flash, recorded significant deterioration.

Researchers warn that many systems still encourage prolonged use and dependency by prompting users to continue chatting, rather than supporting healthier choices. Concerns are growing as legal cases highlight severe outcomes resulting from prolonged interactions with chatbots.

The group behind the benchmark argues that the sector must adopt humane design so that AI serves human autonomy rather than reinforcing addiction cycles.

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Japan boosts Rapidus with major semiconductor funding

Japan will inject more than one trillion yen (approximately 5.5 billion €) into chipmaker Rapidus between 2026 and 2027. The plan aims to fortify national economic security by rebuilding domestic semiconductor capacity after decades of reliance on overseas suppliers.

Rapidus intends to begin producing 2-nanometre chips in late 2027 as global demand for faster, AI-ready components surges. The firm expects overall investment to reach seven trillion yen and hopes to list publicly around 2031.

Japanese government support includes large subsidies and direct investment that add to earlier multi-year commitments. Private contributors, including Toyota and Sony, previously backed the venture, which was founded in 2022 to revive Japan’s cutting-edge chip ambitions.

Officials argue that advanced production is vital for technological competitiveness and future resilience. Critics to this investment note that there are steep costs and high risks, yet policymakers view the Rapidus investment as crucial to keeping pace with technological advancements.

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Nvidia’s results fail to ease AI bubble fears

Record profits and year-on-year revenue growth above 60 percent have put Nvidia at the centre of debate over whether the surge in AI spending signals a bubble or a long-term boom.

CEO Jensen Huang and CFO Colette Kress dismissed concerns about the bubble, highlighting strong demand and expectations of around $65 billion in revenue for the next quarter.

Executives forecast global AI infrastructure spending could reach $3–4 trillion annually by the end of the decade as both generative AI and traditional cloud computing workloads increasingly run on GPUs.

Widespread adoption by major partners, including Meta, Anthropic and Salesforce, suggests lasting momentum rather than short-term hype.

Analysts generally agree that Nvidia’s performance remains robust, but questions persist over the sustainability of heavy investment in AI. Investors continue to monitor whether Big Tech can maintain this pace and if highly leveraged customers might expose Nvidia to future risks.

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