Despite speculation that the feature was expanding internationally, OpenAI has clarified that advertisements in ChatGPT are currently available only to users in the US.
Questions about a broader rollout emerged after references to advertisements appeared in the platform’s updated privacy policy. Some users interpreted the language as evidence that advertising would soon be introduced globally.
OpenAI said the policy update does not signal an immediate expansion. According to the company, advertising features are still being tested within the US as part of a gradual deployment strategy.
ChatGPT advertisements were introduced in February 2026 and appear below responses generated by the chatbot. The ads are shown only to logged-in users on free subscription tiers and are not displayed to users under eighteen.
Company representatives stated that advertising systems operate independently from the AI model that generates responses. According to OpenAI, advertisers cannot influence or modify the content produced by ChatGPT.
The company also said it does not share user conversations or personal chat histories with advertisers. However, advertisements may still be personalised based on user queries, which has prompted discussions about how conversational interfaces could shape consumer decisions.
OpenAI indicated that it is adopting a cautious, phased approach before considering any wider rollout of ChatGPT advertising features in other markets.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
According to reports, OpenAI is preparing to integrate its AI video generator Sora directly into ChatGPT, a move that could expand the platform’s capabilities beyond text and image generation.
Sora currently operates as a standalone application and web service. Integrating the tool into ChatGPT could dramatically increase its visibility and usage, particularly given the chatbot’s massive global user base.
The company released an updated version of the model in 2025 that allows users to create, remix and even appear inside AI-generated videos. Bringing those features into ChatGPT would represent a major step toward making video generation a mainstream function within conversational AI systems.
Competition in the generative video market is intensifying. Companies, including Google, are developing similar technologies, with the company’s Gemini platform offering video creation powered by the Veo system. Other developers are also launching text-to-video models as the field rapidly expands.
Despite the potential growth, integrating video generation into ChatGPT may significantly increase operating costs. Running large AI systems requires vast computing resources and energy, and the chatbot already costs billions of dollars annually to operate.
Although OpenAI earns revenue from subscriptions, the majority of ChatGPT users currently use the free version. The company is therefore exploring additional monetisation strategies, including advertising and new premium services.
Integrating Sora into ChatGPT could therefore serve both strategic and financial goals, strengthening the platform’s position in the competitive generative AI market while expanding the types of content users can create.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
AI competition among leading AI developers intensified in early 2026 as major companies expanded their models, platforms, and partnerships. Companies including Google, OpenAI, Anthropic, and xAI are introducing new capabilities and integrating AI systems into broader ecosystems.
Google has continued to expand its Gemini model family with updates to Gemini 3.1 Pro and 3.1 Flash, designed to support complex tasks across applications. The company is also integrating Gemini into services such as Docs, Sheets, Slides, and Drive, allowing users to generate documents and analyse data across multiple Google services.
Gemini has also been embedded into the Chrome browser and integrated with Samsung’s Galaxy devices, expanding its distribution across consumer platforms as AI competition among major developers accelerates.
Anthropic has focused on advancing the Claude model family while positioning the system for enterprise and professional use. Recent updates include Claude Sonnet 4.6, which introduces improvements in reasoning and coding capabilities alongside an expanded context window currently in beta. The company has also launched a limited preview of the Claude Marketplace, allowing organisations to use third-party tools built on Claude through partnerships with several software companies.
OpenAI has continued to update ChatGPT with the release of the GPT-5 series, including GPT-5.2 and GPT-5.4. The newer models combine reasoning, coding, and agent-based workflows, while also introducing computer-use capabilities that allow the system to interact with applications directly.
OpenAI has also introduced additional services, including ChatGPT Health and integrations designed to assist with spreadsheet modelling and data analysis, further intensifying AI competition across enterprise and consumer tools.
Meanwhile, xAI has expanded development of its Grok models while increasing computing infrastructure. The company has reported growth in Grok usage through integration with the X platform and other applications. Recent announcements include upgrades to Grok’s voice and multimodal capabilities, as well as continued training of future models.
Across the industry, developers are increasingly positioning their systems not only as conversational assistants but also as tools integrated into enterprise workflows, creative production, and software development. New releases in 2026 reflect a broader shift toward multimodal systems, agent-based capabilities, and deeper integration with existing digital platforms, highlighting how AI competition is shaping the next phase of AI development.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
OpenAI has introduced a new ChatGPT feature called dynamic visual explanations, allowing users to interact with mathematical and scientific concepts through real-time visuals.
Instead of relying solely on text explanations or static diagrams, the feature enables users to manipulate formulas and variables and immediately see how those changes affect results. For example, when exploring the Pythagorean theorem, users can adjust the triangle’s sides and see the hypotenuse update instantly.
To use the tool, users can ask ChatGPT questions such as ‘What is a lens equation?’ or ‘How can I find the area of a circle?’ The chatbot responds with both a written explanation and an interactive visual module that users can manipulate directly.
The feature currently supports more than 70 topics in mathematics and science. The topics include binomial squares, Charles’ law, compound interest, Coulomb’s law, exponential decay, Hooke’s law, kinetic energy, linear equations, and Ohm’s law.
OpenAI says it plans to expand the range of topics over time. The feature is already available to all logged-in ChatGPT users. The launch marks a shift in how ChatGPT supports learning. Instead of simply providing answers, the tool now encourages users to explore underlying concepts by experimenting with interactive models.
AI tools have become increasingly common in education, although their role remains widely debated. Some educators worry that students may become overly dependent on AI tools, while others see them as valuable learning aids.
According to OpenAI, more than 140 million people use ChatGPT every week to help with subjects such as mathematics and science, which many learners find challenging. Other technology companies are also experimenting with similar tools. Google’s Gemini introduced interactive diagrams and visual explanations last year.
The new feature joins several other ChatGPT learning tools, including study mode, which guides users through problems step by step, and QuizGPT, which allows users to create flashcards and test themselves before exams.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
A deal valued at up to $600 million will see Netflix acquire InterPositive, the AI filmmaking company founded by actor and director Ben Affleck, according to people familiar with the matter.
The transaction, paid in cash, is expected to become one of the largest acquisitions made by the streaming company. The final upfront amount is reportedly lower, with additional payments tied to performance targets. Netflix has not publicly disclosed the financial terms of the deal.
The acquisition is intended to accelerate the use of AI in film production. InterPositive has developed software tools that enable filmmakers to modify existing footage, including removing unwanted elements or adjusting scene backgrounds. Director David Fincher has already used the technology in work on an upcoming film starring Brad Pitt.
The deal reflects a broader trend among entertainment companies exploring AI technologies to streamline production and improve efficiency. Companies including Netflix and Amazon are experimenting with AI tools in film and television production, while Disney has established a partnership with OpenAI.
The growing use of AI in Hollywood has raised concerns among industry workers. Some fear the technology could reduce jobs or allow studios to use creative work to train AI systems without compensation.
Affleck has said the InterPositive technology is designed to support filmmakers rather than replace them. The system requires directors first to shoot original footage before the software can train on the material. The tools can then assist with editing tasks, but do not generate films independently.
Netflix has traditionally avoided large-scale acquisitions, focusing instead on developing its technology internally. Even so, the purchase of InterPositive signals a step toward strengthening the company’s AI capabilities in film production.
‘The filmmaking process, really, since its inception, has been one long technological progression,’ Affleck said in a video released by Netflix. ‘We’ve always been seeking to make it feel more realistic, more honest, and InterPositive, I hope, is another iteration or step in keeping with that long and storied history.’
Affleck founded InterPositive with backing from investment firm RedBird Capital Partners and began seeking investment in 2025 before the company attracted interest from Netflix.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
Clemson University has introduced ChatGPT Edu to its students, faculty, and staff, providing them free access to the secure, institutionally managed version of the AI platform.
The rollout is part of Clemson’s partnership with OpenAI. It forms part of the university’s broader AI Initiative, which aims to develop a human-centred approach to AI across education, research, and operations.
University officials said the ChatGPT Edu environment will expand access to generative AI tools while ensuring institutional data remains protected and is not used to train external AI systems.
Members of the Clemson community who want to use the platform must request access through a ChatGPT Edu account request form. Once approved, accounts are automatically created, and users can sign in through Clemson’s single sign-on system.
Even if students or staff members already have a ChatGPT account linked to their Clemson email, they will still need to request access to ChatGPT Edu. After approval, they can merge your current account or download your chat history before creating a new one.
The university said the launch reflects its view that access to emerging technologies should be paired with clear guidance and responsible use. Users are advised to review Clemson’s updated AI guidelines before using the system.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
On 28 February 2026, Anthropic’s Claude rose to No. 1 in Apple’s US App Store free rankings, overtaking OpenAI’s ChatGPT. The surge came shortly after OpenAI announced a partnership with the US Department of Defense (DoD), making its technology available to the US Army. The development prompted discussion among users and observers about whether concerns over military partnerships were influencing the shift to alternative AI tools.
Mere hours before the USD $200 million OpenAI-DoD deal was finalised, Anthropic was informed that its potential deal with the Pentagon had fallen through, largely because the AI company refused to relinquish total control of its technology for domestic mass surveillance. According to reporting, discussions broke down after Anthropic declined to grant the US government unrestricted control over its models, particularly for potential uses related to large-scale surveillance.
Following the breakdown of negotiations, US officials reportedly designated Anthropic as a ‘supply chain risk to national security’. The decision effectively limited the company’s participation in certain defence-related projects and highlighted growing tensions between AI developers’ safety policies and government expectations regarding national security technologies.
I resigned from OpenAI. I care deeply about the Robotics team and the work we built together. This wasn’t an easy call. AI has an important role in national security. But surveillance of Americans without judicial oversight and lethal autonomy without human authorization are…
The debate over military partnerships sparked internal and industry-wide discussion. Caitlin Kalinowski, the former head of AR glasses hardware at Meta and the hardware leader at OpenAI, resigned soon after the US DoD deal, citing ethical concerns about the company’s involvement in military AI applications.
AI has driven recent technological innovation, with companies like Anduril and Palantir collaborating with the US DoD to deploy AI on and off the battlefield. The debate over AI’s role in military operations, surveillance, and security has intensified, especially as Middle East conflicts highlight its potential uses and risks.
Against this backdrop, the dispute between Anthropic and the Pentagon reflects a wider debate on how AI should be used in security and defence. Governments are increasingly relying on private tech companies to develop the systems that shape modern military capabilities, while those same companies are trying to set limits on how their technologies can be used.
As AI becomes more deeply integrated into security strategies around the world, the challenge may no longer be whether the technology will be used, but how it should be governed. The question is: who should ultimately decide where the limits of military AI lie?
Anthropic’s approach to military AI
Anthropic’s approach is closely tied to its concept of ‘constitutional AI’, a training method that guides how the model behaves by embedding a set of principles directly into its responses. Such principles are intended to reduce harmful outputs and ensure the system avoids unsafe or unethical uses. While such safeguards are intended to improve reliability and trust, they can also limit how the technology can be deployed in more sensitive contexts such as military operations.
Anthropic’s Constitution says its AI assistant should be ‘genuinely helpful’ to people and society, while avoiding unsafe, unethical, or deceptive actions. The document reflects the company’s broader effort to build safeguards into model deployment. In practice, Anthropic has set limits on certain applications of its technology, including uses related to large-scale surveillance or military operations.
Anthropic presents these safeguards as proof of its commitment to responsible AI. Reports indicate that concerns over unrestricted model access led to the breakdown in talks with the US DoD.
At the same time, Anthropic clarifies that its concerns are specific to certain uses of its technology. The company does not generally oppose cooperation with national security institutions. In a statement following the Pentagon’s designation of the company as a ‘supply chain risk to national security’, CEO Dario Amodei said, ‘Anthropic has much more in common with the US DoD than we have differences.’ He added that the company remains committed to ‘advancing US national security and defending the American people.’
The episode, therefore, highlights a nuanced position. Anthropic appears open to defence partnerships but seeks to maintain clearer limits on the deployment of its AI systems. The disagreement with the Pentagon ultimately reflects not a fundamental difference in goals, but rather different views on how far military institutions should be able to control and use advanced AI technologies.
Anthropic’s position illustrates a broader challenge facing governments and tech companies as AI becomes increasingly integrated into national security systems. While military and security institutions are eager to deploy advanced AI tools to support intelligence analysis, logistics, and operational planning, the companies developing these technologies are also seeking to establish safeguards for their use. Anthropic’s willingness to step back from a major defence partnership and challenge the Pentagon’s response underscores how some AI developers are trying to set limits on military uses of their systems.
Defence partnerships that shape the AI industry
While Anthropic has taken a cautious approach to military deployment of AI, other technology companies have pursued closer partnerships with defence institutions. One notable example is Palantir, the US data analytics firm co-founded by Peter Thiel that has longstanding relationships with numerous government agencies. Documents leaked in 2013 suggested that the company had contracts with at least 12 US government bodies. More recently, Palantir has expanded its defence offering through its Artificial Intelligence Platform (AIP), designed to support intelligence analysis and operational decision-making for military and security institutions.
Another prominent player is Anduril Industries, a US defence technology company focused on developing AI-enabled defence systems. The firm produces autonomous and semi-autonomous technologies, including unmanned aerial systems and surveillance platforms, which it supplies to the US DoD.
Shield AI, meanwhile, is developing autonomous flight software designed to operate in environments where GPS and communications may be unavailable. Its Hivemind AI platform powers drones that can navigate buildings and complex environments without human control. The company has worked with the US military to test these systems in training exercises and operational scenarios, including aircraft autonomy projects aimed at supporting fighter pilots.
The aforementioned partnerships illustrate how the US government has increasingly embraced AI as a key pillar of national defence and future military operations. In many cases, these technologies are already being used in operational contexts. Palantir’s Gotham and AIP, for instance, have supported US military and intelligence operations by processing satellite imagery, drone footage, and intercepted communications to help analysts identify patterns and potential threats.
Other companies are contributing to defence capabilities through autonomous systems development and hardware integration. Anduril supplies the US DoD with AI-enabled surveillance, drone, and counter-air systems designed to detect and respond to potential threats. At the same time, OpenAI’s technology is increasingly being integrated into national security and defence projects through growing collaboration with US defence institutions.
Such developments show that AI is no longer a supporting tool but a fundamental part of military infrastructure, influencing how defence organisations process information and make decisions. As governments deepen their reliance on private-sector AI, the emerging interplay among innovation, operational effectiveness, and oversight will define the central debate on military AI adoption.
The potential benefits of military AI
The debate over Anthropic’s restrictions on military AI use highlights the reasons governments invest in such technologies: defence institutions are drawn to AI because it processes vast amounts of information much faster than human analysts. Military operations generate massive data streams from satellites, drones, sensors, and communication networks, and AI systems can analyse them in near real time.
In 2017, the US DoD launched Project Maven to apply machine learning to drone and satellite imagery, enabling analysts to identify objects, movements, and potential threats on the battlefield faster than with traditional manual methods.
AI is increasingly used in military logistics and operational planning. It helps commanders anticipate equipment failures, enables predictive maintenance, optimises supply chains, and improves field asset readiness.
Recent conflicts have shown that AI-driven tools can enhance military intelligence and planning. In Ukraine, for example, forces reportedly used software to analyse satellite imagery, drone footage, and battlefield data. Key benefits include more efficient target identification, real-time tracking of troop movements, and clearer battlefield awareness through the integration of multiple data sources.
AI-assisted analysis has been used in intelligence and targeting during the Gaza conflict. Israeli defence systems use AI tools to rapidly process large datasets for surveillance and intelligence operations. The tools help analysts identify potential militant infrastructure, track movements, and prioritise key intelligence, thus speeding up information processing for teams during periods of high operational activity.
More broadly, AI is transforming the way militaries coordinate across land, air, sea, and cyber domains. AI integrates data from diverse sources, equipping commanders to interpret complex operational situations and enabling faster, informed decision-making. The advances reinforce why many governments see AI as essential for future defence planning.
Ethical concerns and Anthropic’s limits on military AI
Despite the operational advantages of military AI, its growing role in national defence systems has raised ethical concerns. Critics warn that overreliance on AI for intelligence analysis, targeting, or operational planning could introduce risks if the systems produce inaccurate outputs or are deployed without sufficient human oversight. Even highly capable models can generate misleading or incomplete information, which in high-stakes military contexts could have serious consequences.
Concerns about the reliability of AI systems are also linked to the quality of the data they learn from. Many models still struggle to distinguish authentic information from synthetic or manipulated content online. As generative AI becomes more widespread, the risk that systems may absorb inaccurate or fabricated data increases, potentially affecting how these tools interpret intelligence or analyse complex operational environments.
Questions about autonomy have also become a major issue in discussions around military AI. As AI systems become increasingly capable of analysing battlefield data and identifying potential targets, debates have emerged over how much decision-making authority they should be given. Many experts argue that decisions involving the use of lethal force should remain under meaningful human control to prevent unintended consequences or misidentification of targets.
Another area of concern relates to the potential expansion of surveillance capabilities. AI systems can analyse satellite imagery, communications data, and online activity at a scale beyond the capacity of human analysts alone. While such tools may help intelligence agencies detect threats more efficiently, critics warn that they could also enable large-scale monitoring if deployed without clear legal and institutional safeguards.
It is within this ethical landscape that Anthropic has attempted to position itself as a more cautious actor in the AI industry. Through initiatives such as Claude’s Constitution and its broader emphasis on AI safety, the company argues that powerful AI systems should include safeguards that limit harmful or unethical uses. Anthropic’s reported refusal to grant the Pentagon unrestricted control over its models during negotiations reflects this approach.
The disagreement between Anthropic and the US DoD therefore highlights a broader tension in the development of military AI. Governments increasingly view AI as a strategic technology capable of strengthening defence and intelligence capabilities, while some developers seek to impose limits on how their systems are deployed. As AI becomes more deeply embedded in national security strategies, the question may no longer be whether these technologies will be used, but who should define the boundaries of their use.
Military AI and the limits of corporate control
Anthropic’s dispute with the Pentagon shows that the debate over military AI is no longer only about technological capability. Questions of speed, efficiency, and battlefield advantage now collide with concerns over surveillance, autonomy, human oversight, and corporate responsibility. Governments increasingly see AI as a strategic asset, while companies such as Anthropic are trying to draw boundaries around how far their systems can go once they enter defence environments.
Contrasting approaches across the industry make the tension even clearer. Palantir, Anduril, Shield AI, and OpenAI have moved closer to defence partnerships, reflecting a broader push to integrate advanced AI into military infrastructure. Anthropic, by comparison, has tried to keep one foot in national security cooperation while resisting uses it views as unsafe or unethical. A divide of that kind suggests that the future of military AI may be shaped as much by company policies as by government strategy.
The growing reliance on private firms to build national security technologies has made governance harder to define. Military institutions want flexibility, scale, and operational control, while AI developers increasingly face pressure to decide whether they are simply suppliers or active gatekeepers of how their models are deployed. Anthropic’s position does not outright defence cooperation, but it does expose how fragile the relationship becomes when state priorities and corporate safeguards no longer align.
Military AI will continue to expand, whether through intelligence analysis, logistics, surveillance, or autonomous systems. Governance, however, remains the unresolved issue at the centre of that expansion. As AI becomes more deeply embedded in defence policy and military planning, should governments alone decide how far these systems can go, or should companies like Anthropic retain the power to set limits on their use?
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
OpenAI has launched Codex Security, an AI-powered application security agent that detects hard-to-find software vulnerabilities and proposes fixes through advanced reasoning. By providing detailed context about a system’s architecture, the tool identifies security risks that are often missed by conventional automation.
The system uses advanced models to analyse repositories, construct project-specific threat models, and prioritise vulnerabilities based on their potential real-world impact. By combining automated validation with system-level context, Codex Security aims to reduce the number of false positives that security teams must review while highlighting high-confidence findings.
Initially developed under the name Aardvark, the tool has been tested in private deployments over the past year. During early use, OpenAI said it uncovered several critical vulnerabilities, including a cross-tenant authentication flaw and a server-side request forgery issue, allowing internal teams to quickly patch affected systems.
The company says improvements during the beta phase significantly reduced noise in vulnerability reports. In some repositories, unnecessary alerts fell by 84 percent, while over-reported severity dropped by more than 90 percent, and false positives declined by more than half.
Codex Security is now rolling out in research preview for ChatGPT Pro, Enterprise, Business, and Edu customers. OpenAI also plans to expand access to open-source maintainers through a dedicated programme that offers security scanning and support to help identify and remediate vulnerabilities across widely used projects.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
A newly filed lawsuit against OpenAI raises a key issue: Does allowing generative AI systems like ChatGPT to provide legal advice violate laws that bar the unauthorised practice of law (UPL)? UPL means providing legal services, such as drafting filings or giving advice, without the required legal qualifications or a state licence.
The case claims an individual used ChatGPT to prepare legal filings in a dispute with Nippon Life Insurance, prompting the company to argue OpenAI should be held responsible for the outcome.
The lawsuit claims ChatGPT helped the user challenge a settled legal dispute. As a result, the company had to spend additional time and resources responding to filings produced with ChatGPT. The claim alleges tortious interference with a contract, which is the unlawful disruption of an existing agreement between two parties by causing one of the parties to breach or alter it.
Ultimately, this disrupted another party’s contractual relationship. The suit also claims unauthorised practice of law and abuse of the judicial process, which means using the legal system improperly to gain an advantage. It argues OpenAI should be liable because ChatGPT operates under its control. The dispute centres on whether AI systems should analyse disputes and offer legal advice like a lawyer.
Advocates argue the tools could widen access to legal advice. They could make legal support more accessible and affordable for those who cannot easily hire a lawyer. However, US legal frameworks restrict the provision of legal advice to licensed lawyers. The rules are designed to protect consumers and ensure professional accountability.
Critics argue that limiting legal advice to licensed lawyers preserves an expensive monopoly and hinders access to justice. AI-driven legal tools highlight this tension over the future of legal services.
The outcome of this lawsuit will likely hinge on whether AI-generated responses constitute intentional legal advice and if OpenAI can be held liable for such outputs. Even if it fails, the case foregrounds the broader debate about granting generative AI a legitimate role in legal guidance.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
OpenAI has postponed the launch of ChatGPT’s ‘adult mode’, a feature designed to let verified adult users access erotica and other mature content.
Teams are focusing on improving intelligence, personality and proactive behaviour instead of releasing the feature immediately.
A feature that was first announced by Sam Altman in October, with an initial December rollout, aiming to allow adults more freedom while maintaining safety for younger users.
The project faced an earlier delay as internal teams prioritised the core ChatGPT experience.
OpenAI stated it still supports the principle of treating adults like adults but warned that achieving the right experience will require more time. No new release date has been provided.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
