Anthropic and OpenAI are recruiting chemical and explosives experts to strengthen safeguards for their AI systems, reflecting growing concern about the potential misuse of advanced models.
Anthropic is seeking a policy specialist to design and monitor guardrails governing how its systems respond to prompts involving chemical weapons and explosives. The role includes assessing high-risk scenarios and responding to potential escalation signals in real time.
OpenAI is expanding its Preparedness team, hiring researchers and a threat modeller to identify and forecast risks linked to frontier AI systems. The positions focus on evaluating catastrophic risks and aligning technical, policy, and governance responses.
The recruitment drive comes amid heightened scrutiny of AI safety and national security implications. Anthropic is currently challenging a US government designation that labels it a supply-chain risk, while tensions have emerged over restrictions on the military use of AI systems.
At the same time, OpenAI has secured agreements to deploy its technology in classified environments under defined constraints. The parallel developments highlight how AI firms are balancing commercial expansion with increasing pressure to implement robust safety controls.
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The Pentagon is accelerating efforts to replace Anthropic after the company was designated a supply-chain risk, marking a sharp shift in US defence AI strategy. The move follows a breakdown in talks over safeguards governing military use of AI, particularly around surveillance and autonomous weapons.
Cameron Stanley, the Pentagon’s chief digital and AI officer, said engineering work is underway to deploy alternative large language models in government-controlled environments. He indicated that while transitioning from Anthropic’s tools could take more than a month, new systems are expected to be operational soon.
The decision threatens a $200 million contract and could exclude Anthropic from future defence partnerships. The US administration has set a six-month timeline for federal agencies to shift away from the company, signalling a broader push to diversify AI suppliers and reduce dependency risks.
Rival providers are already stepping in. OpenAI and xAI have been approved for classified work, while Google is introducing Gemini AI tools across the Pentagon workforce, initially on unclassified networks before expanding into sensitive environments.
Anthropic has challenged the designation in court, arguing it violates constitutional protections and could harm its business. Despite the legal dispute, defence officials have made clear they are moving forward with an ‘AI-first’ strategy to accelerate the adoption of advanced models across military operations.
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Legal pressure is increasing on OpenAI as Encyclopaedia Britannica and Merriam-Webster file a lawsuit accusing the company of large-scale copyright violations.
According to the complaint, nearly 100,000 copyrighted articles were allegedly used without authorisation to train large language models. Publishers also argue that AI-generated outputs can reproduce parts of their content, raising concerns about unauthorised distribution.
Additional claims focus on how AI systems retrieve and present information. The lawsuit argues that retrieval-augmented generation tools may rely on proprietary databases, potentially undermining publishers’ business models by reducing traffic to original sources.
Concerns are also raised about inaccurate outputs attributed to publishers, which could affect trust in established information providers. The case highlights ongoing tensions between AI development and intellectual property protections.
Growing legal disputes involving media organisations, including The New York Times, suggest that courts will play a key role in defining how copyrighted material can be used in AI training.
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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.
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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.
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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.
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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.
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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.
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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.
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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?
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