ChatGPT introduces age prediction to strengthen teen safety

New safeguards are being introduced as ChatGPT uses age prediction to identify accounts that may belong to under-18s. Extra protections limit exposure to harmful content while still allowing adults full access.

The age prediction model analyses behavioural and account-level signals, including usage patterns, activity times, account age, and stated age information. OpenAI says these indicators help estimate whether an account belongs to a minor, enabling the platform to apply age-appropriate safeguards.

When an account is flagged as potentially under 18, ChatGPT limits access to graphic violence, sexual role play, viral challenges, self-harm, and unhealthy body image content. The safeguards reflect research on teen development, including differences in risk perception and impulse control.

ChatGPT users who are incorrectly classified can restore full access by confirming their age through a selfie check using Persona, a secure identity verification service. Account holders can review safeguards and begin the verification process at any time via the settings menu.

Parental controls allow further customisation, including quiet hours, feature restrictions, and notifications for signs of distress. OpenAI says the system will continue to evolve, with EU-specific deployment planned in the coming weeks to meet regional regulatory requirements.

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Horizon1000 aims to bring powerful AI healthcare tools to Africa

The Gates Foundation and OpenAI have launched a joint healthcare initiative, Horizon1000, to expand the use of AI across primary care systems in Sub-Saharan Africa. The partnership includes a $50 million commitment in funding, technology, and technical support to equip 1,000 clinics with AI tools by 2028.

Horizon1000’s Operations will begin in Rwanda, where local authorities will work with the two organisations to deploy AI systems in frontline healthcare settings. The initiative reflects the Foundation’s long-standing aim to ensure that new technologies reach lower-income regions without long delays.

Bill Gates said the project responds to a critical shortage of healthcare workers, which threatens to undermine decades of progress in global health. Sub-Saharan Africa currently faces a shortfall of nearly six million medical professionals, limiting the capacity of overstretched clinics to deliver consistent care.

Low-quality healthcare contributes to between six and eight million deaths annually in low- and middle-income countries, according to the World Health Organization. Rwanda, the first pilot country, has only one healthcare worker per 1,000 people, far below the WHO’s recommended level.

AI tools under Horizon1000 are intended to support, rather than replace, health workers by assisting with clinical guidance, administration, and patient interactions. The Gates Foundation said it will continue working with regional governments and innovators to scale the programme.

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OpenAI models embedded into ServiceNow for enterprise automation

ServiceNow has announced a multi-year agreement positioning OpenAI as a preferred intelligence capability across its enterprise platform, extending access to frontier AI models for organisations running tens of billions of workflows each year.

The partnership reflects a broader shift towards operational AI embedded directly within business systems instead of experimental deployments.

By integrating OpenAI models such as GPT-5.2 into the ServiceNow AI Platform, enterprises can embed reasoning and automation into secure workflows spanning IT, finance, human resources, and customer operations.

AI tools are designed to analyse context, recommend actions, and execute tasks within existing governance frameworks instead of functioning as standalone assistants.

Executives from both companies emphasised that the collaboration aims to deliver measurable outcomes at scale.

ServiceNow highlighted its role in coordinating complex enterprise environments, while OpenAI stressed the importance of deploying agentic AI capable of handling work end to end within permissioned infrastructures.

Looking ahead, the partnership plans to expand towards multimodal and voice-based interactions, enabling employees to communicate with AI systems through speech, text, and visual inputs.

The initiative strengthens OpenAI’s enterprise footprint while reinforcing ServiceNow’s ambition to act as a central control layer for AI-driven business operations.

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ChatGPT and the rising pressure to commercialise AI in 2026

The moment many have anticipated with interest or concern has arrived. On 16 January, OpenAI announced the global rollout of its low-cost subscription tier, ChatGPT Go, in all countries where the model is supported. After debuting in India in August 2025 and expanding to Singapore the following month, the USD 8-per-month tier marks OpenAI’s most direct attempt yet to broaden paid access while maintaining assurances that advertising will not be embedded into ChatGPT’s prompts.

The move has been widely interpreted as a turning point in the way AI models are monetised. To date, most major AI providers have relied on a combination of external investment, strategic partnerships, and subscription offerings to sustain rapid development. Expectations of transformative breakthroughs and exponential growth have underpinned investor confidence, reinforcing what has come to be described as the AI boom.

Against this backdrop, OpenAI’s long-standing reluctance to embrace advertising takes on renewed significance. As recently as October 2024, chief executive Sam Altman described ads as a ‘last resort’ for the company’s business model. Does that position (still) reflect Altman’s confidence in alternative revenue streams, and is OpenAI simply the first company to bite the ad revenue bullet before other AI ventures have mustered the courage to do so?

ChatGPT, ads, and the integrity of AI responses

Regardless of one’s personal feelings about ad-based revenue, the facts about its essentiality are irrefutable. According to Statista’s Market Insights research, the worldwide advertising market has surpassed USD 1 trillion in annual revenue. With such figures in mind, it seems like a no-brainer to integrate ads whenever and wherever possible.

Furthermore, relying solely on substantial but irregular cash injections is not a reliable way to keep the lights on for a USD 500 billion company, especially in the wake of the RAM crisis. As much as the average consumer would prefer to use digital services without ads, coming up with an alternative and well-grounded revenue stream is tantamount to financial alchemy. Advertising remains one of the few monetisation models capable of sustaining large-scale platforms without significantly raising user costs.

For ChatGPT users, however, the concern centres less on the mere presence of ads and more on how advertising incentives could reshape data use, profiling practices, and the handling of conversational inputs. OpenAI has pleaded with its users to ‘trust that ChatGPT’s responses are driven by what’s objectively useful, never by advertising’. Altman’s company has also guaranteed that user data and conversations will remain protected and will never be sold to advertisers.

Such bold statements are never given lightly, meaning Altman fully stands behind his company’s words and is prepared to face repercussions should he break his promises. Since OpenAI is privately held, shifts in investor confidence following the announcement are not visible through public market signals, unlike at publicly listed technology firms. User count remains the most reliable metric for observing how ChatGPT is perceived by its target audience.

Competitive pressure behind ads in ChatGPT

Introducing ads to ChatGPT would be more than a simple change to how OpenAI makes money. Advertising can influence how the model responds to users, even if ads are not shown directly within the answers. Business pressure can still shape how information is presented through prompts. For example, certain products or services could be described more positively than others, without clearly appearing as advertisements or endorsements.

Recommendations raise particular concern. Many users turn to ChatGPT for advice or comparisons before making important purchases. If advertising becomes part of the model’s business, it may become harder for users to tell whether a suggestion is neutral or influenced by commercial interests. Transparency is also an issue, as the influence is much harder to spot in a chat interface than on websites that clearly label ads with banners or sponsored tags.

Three runners at a starting line wearing bibs with AI company logos, symbolising competition over advertising and monetisation in AI models, initiated by ChatGPT

While these concerns are valid, competition remains the main force shaping decisions across the AI industry. No major company wants its model to fall behind rivals such as ChatGPT, Gemini, Claude, or other leading systems. Nearly all of these firms have faced public criticism or controversy at some point, forcing them to adjust their strategies and work to rebuild user trust.

The risk of public backlash has so far made companies cautious about introducing advertising. Still, this hesitation is unlikely to last forever. By moving first, OpenAI absorbs most of the initial criticism, while competitors get to stand back, watch how users respond, and adjust their plans accordingly. If advertising proves successful, others are likely to follow, drawing on OpenAI’s experience without bearing the brunt of the growing pains. To quote Arliss Howard’s character in Moneyball: ‘The first guy through the wall always gets bloody’.

ChatGPT advertising and governance challenges

Following the launch of ChatGPT Go, lawmakers and regulators may need to reconsider how existing legal safeguards apply to ad-supported LLMs. Most advertising rules are designed for websites, apps, and social media feeds, rather than systems that generate natural-language responses and present them as neutral or authoritative guidance.

The key question is: which rules should apply? Advertising in chatbots may not resemble traditional ads, muddying the waters for regulation under digital advertising rules, AI governance frameworks, or both. The uncertainty matters largely because different rules come with varying disclosure, transparency, and accountability requirements.

Disclosure presents a further challenge for regulators. On traditional websites, sponsored content is usually labelled and visually separated from editorial material. In an LLM interface such as ChatGPT, however, any commercial influence may appear in the flow of an answer itself. This makes it harder for users to distinguish content shaped by commercial considerations from neutral responses.

In the European Union, this raises questions about how existing regulatory frameworks apply. Advertising in conversational AI may intersect with rules on transparency, manipulation, and user protection under current digital and AI legislation, including the AI Act, the Digital Services Act, and the Digital Markets Act. Clarifying how these frameworks operate in practice will be important as conversational AI systems continue to evolve.

ChatGPT ads and data governance

In the context of ChatGPT, conversational interactions can be more detailed than clicks or browsing history. Prompts may include personal, professional, or sensitive information, which requires careful handling when introducing advertising models. Even without personalised targeting, conversational data still requires clear boundaries. As AI systems scale, maintaining user trust will depend on transparent data practices and strong privacy safeguards.

Then, there’s data retention. Advertising incentives can increase pressure to store conversations for longer periods or to find new ways to extract value from them. For users, this raises concerns about how their data is handled, who has access to it, and how securely it is protected. Even if OpenAI initially avoids personalised advertising, the lingering allure will remain a central issue in the discussion about advertising in ChatGPT, not a secondary one.

Clear policies around data use and retention will therefore play a central role in shaping how advertising is introduced. Limits on how long conversations are stored, how data is separated from advertising systems, and how access is controlled can help reduce user uncertainty. Transparency around these practices will be important in maintaining confidence as the platform evolves.

Simultaneously, regulatory expectations and public scrutiny are likely to influence how far advertising models develop. As ChatGPT becomes more widely used across personal, professional, and institutional settings, decisions around data handling will carry broader implications. How OpenAI balances commercial sustainability with privacy and trust may ultimately shape wider norms for advertising in conversational AI.

How ChatGPT ads could reshape the AI ecosystem

We have touched on the potential drawbacks of AI models adopting an ad-revenue model, but what about the benefits? If ChatGPT successfully integrates advertising, it could set an important precedent for the broader industry. As the provider of one of the most widely used general-purpose AI systems, OpenAI’s decisions are closely watched by competitors, policymakers, and investors.

One likely effect would be the gradual normalisation of ad-funded AI assistants. If advertising proves to be a stable revenue source without triggering significant backlash, other providers may view it as a practical path to sustainability. Over time, this could shift user expectations, making advertising a standard feature rather than an exception in conversational AI tools.

Advertising may also intensify competitive pressure on open, academic, or non-profit AI models. Such systems often operate with more limited funding and may struggle to match the resources of ad-supported platforms such as ChatGPT. As a result, the gap between large commercial providers and alternative models could widen, especially in areas such as infrastructure, model performance, and distribution.

Taken together, these dynamics could strengthen the role of major AI providers as gatekeepers. Beyond controlling access to technology, they may increasingly influence which products, services, or ideas gain visibility through AI-mediated interactions. Such a concentration of influence would not be unique to AI, but it raises familiar questions about competition, diversity, and power in digital information ecosystems.

ChatGPT advertising and evolving governance frameworks

Advertising in ChatGPT is not simply a business decision. It highlights a broader shift in the way knowledge, economic incentives, and large-scale AI systems interact. As conversational AI becomes more embedded in everyday life, these developments offer an opportunity to rethink how digital services can remain both accessible and sustainable.

For policymakers and governance bodies, the focus is less on whether advertising appears and more on how it is implemented. Clear rules around transparency, accountability, and user protection can help ensure that conversational AI evolves in ways that support trust, choice, and fair competition, while allowing innovation to continue.

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Strong growth pushes OpenAI past $20 billion in annualised revenue

OpenAI’s annualised revenue has surpassed $20 billion in 2025, up from $6 billion a year earlier. The company’s computing capacity and user numbers have also continued to grow.

The company recently confirmed it will begin showing advertisements in ChatGPT to some users in the United States. The move is part of a broader effort to generate additional revenue to cover the high costs of developing and running advanced AI systems.

OpenAI’s platform now spans text, images, voice, code, and application programming interfaces. CFO Sarah Friar said the next phase of development will focus on agents and workflow automation that can operate continuously, retain context over time, and take action across multiple tools.

Looking ahead to 2026, the company plans to prioritise what it calls ‘practical adoption’, with a particular emphasis on health, science, and enterprise use cases. The aim is to move beyond experimentation and embed AI more deeply into real-world applications.

Friar also said OpenAI intends to maintain a ‘light’ balance sheet by partnering with external providers rather than owning infrastructure outright. Contracts will remain flexible across hardware types and suppliers as the company continues to scale its operations.

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OpenAI outlines advertising plans for ChatGPT access

The US AI firm, OpenAI, has announced plans to test advertising within ChatGPT as part of a broader effort to widen access to advanced AI tools.

An initiative that focuses on supporting the free version and the low-cost ChatGPT Go subscription, while paid tiers such as Plus, Pro, Business, and Enterprise will continue without advertisements.

According to the company, advertisements will remain clearly separated from ChatGPT responses and will never influence the answers users receive.

Responses will continue to be optimised for usefulness instead of commercial outcomes, with OpenAI emphasising that trust and perceived neutrality remain central to the product’s value.

User privacy forms a core pillar of the approach. Conversations will stay private, data will not be sold to advertisers, and users will retain the ability to disable ad personalisation or remove advertising-related data at any time.

During early trials, ads will not appear for accounts linked to users under 18, nor within sensitive or regulated areas such as health, mental wellbeing, or politics.

OpenAI describes advertising as a complementary revenue stream rather than a replacement for subscriptions.

The company argues that a diversified model can help keep advanced intelligence accessible to a wider population, while maintaining long term incentives aligned with user trust and product quality.

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Cerebras to supply large-scale AI compute for OpenAI

OpenAI has agreed to purchase up to 750 megawatts of computing power from AI chipmaker Cerebras over the next three years. The deal, announced on 14 January, is expected to be worth more than US$10 billion and will support ChatGPT and other AI services.

Cerebras will provide cloud services powered by its wafer-scale chips, which are designed to run large AI models more efficiently than traditional GPUs. OpenAI plans to use the capacity primarily for inference and reasoning models that require high compute.

Cerebras will build or lease data centres filled with its custom hardware, with computing capacity coming online in stages through 2028. OpenAI said the partnership would help improve the speed and responsiveness of its AI systems as user demand continues to grow.

The deal is also essential for Cerebras as it prepares for a second attempt at a public listing, following a 2025 IPO that was postponed. Diversifying its customer base beyond major backers such as UAE-based G42 could strengthen its financial position ahead of a potential 2026 flotation.

The agreement highlights the wider race among AI firms to secure vast computing resources, as investment in AI infrastructure accelerates. However, some analysts have warned that soaring valuations and heavy spending could resemble past technology bubbles.

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OpenAI invests in Merge Labs to advance brain-computer interfaces

The US AI company, OpenAI, has invested in Merge Labs as part of a seed funding round, signalling a growing interest in brain-computer interfaces as a future layer of human–technology interaction.

Merge Labs describes its mission as bridging the gap between biology and AI to expand human capability and agency. The research lab is developing new BCI approaches designed to operate safely while enabling much higher communication bandwidth between the brain and digital systems.

AI is expected to play a central role in Merge Labs’ work, supporting advances in neuroscience, bioengineering and device development instead of relying on traditional interface models.

High-bandwidth brain interfaces are also expected to benefit from AI systems capable of interpreting intent under conditions of limited and noisy signals.

OpenAI plans to collaborate with Merge Labs on scientific foundation models and advanced tools, aiming to accelerate research progress and translate experimental concepts into practical applications over time.

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OpenAI expands healthcare strategy with Torch acquisition

The US AI company, OpenAI, has acquired healthcare technology startup Torch only days after unveiling ChatGPT Health, signalling an accelerated push into medical and clinical applications.

Financial terms were not officially disclosed, although media reports estimate the transaction at between $60 million and $100 million.

Torch was developed as a unified medical memory platform, designed to consolidate patient data from hospitals, laboratories, wearable devices and consumer testing services.

The company positioned its technology as a means to support AI systems in navigating fragmented healthcare information, rather than relying on isolated data sources.

Torch’s four-person team will join OpenAI following the acquisition, reinforcing the company’s internal healthcare expertise. OpenAI has emphasised privacy, safety and collaboration with medical professionals as core principles guiding its expansion into sensitive data environments.

The move follows a broader strategy by OpenAI to strengthen enterprise offerings, particularly for large healthcare organisations. Recent hires and partnerships suggest healthcare remains a priority area as AI adoption increases across regulated sectors.

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AI gap reflects China’s growing technological ambitions

China’s AI sector could narrow the technological AI gap with the United States through growing risk-taking and innovation, according to leading researchers. Despite export controls on advanced chipmaking tools, Chinese firms are accelerating development across multiple AI fields.

Yao Shunyu, a former senior researcher at ChatGPT maker OpenAI and now Tencent’s AI scientist, said a Chinese company could become the world’s leading AI firm within three to five years. He pointed to China’s strengths in electricity supply and infrastructure as key advantages.

Yao said the main bottlenecks remain production capacity, including access to advanced lithography machines and a mature software ecosystem. Such limits still restrict China’s ability to manufacture the most advanced semiconductors and narrow the AI gap with the US.

China has developed a working prototype of an extreme-ultraviolet lithography machine that could eventually rival Western technology. However, Reuters reported the system has not yet produced functioning chips.

Sources familiar with the project said commercial chip production using the machine may not begin until around 2030. Until then, Chinese AI ambitions are likely to remain constrained by hardware limitations.

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