The twin announcements, made by TCS CEO K. Krithivasan at a press conference in Kolkata, signal the company’s intent to position itself at the forefront of the AI revolution in enterprise technology. With revenues exceeding $30 billion and a workforce of over 600,000, TCS is among the world’s largest IT services firms, and its moves in the AI space carry significant implications for the global technology industry.

The Oracle AI Lab

The Oracle AI Data Platform Lab, housed at TCS’s Kolkata campus, is the first facility of its kind in India. It combines Oracle’s cloud infrastructure and database technologies with AI and machine learning capabilities to create an environment where enterprises can experiment with, develop, and deploy AI-powered data solutions.

The lab offers enterprises a sandbox environment to test AI use cases using their own data — or synthetic data that mimics real-world scenarios — before deploying solutions in production. Use cases include AI-driven supply chain optimisation, predictive maintenance for manufacturing, intelligent customer service systems, fraud detection in financial services, and AI-powered healthcare analytics.

“The gap between AI proof-of-concept and production deployment is where most enterprises get stuck,” said Krithivasan. “This lab is designed to bridge that gap. We provide the infrastructure, the expertise, and the frameworks for enterprises to move from experimentation to real-world AI adoption.”

The choice of Kolkata for the lab is significant. While Bangalore, Hyderabad, and Pune have traditionally been India’s technology hubs, TCS’s investment in Kolkata reflects the city’s growing importance in the IT ecosystem. The West Bengal government has been actively courting technology investments, offering incentives and improved infrastructure to attract companies to the state. (Related: Meta Partners With Reliance to Build First AI Data…)

The Anthropic Partnership

The partnership with Anthropic, announced alongside the Oracle lab launch, takes TCS into the frontier of generative AI. Anthropic, founded by former OpenAI researchers, has emerged as one of the leading AI companies globally, with its Claude models competing directly with OpenAI’s GPT and Google’s Gemini for supremacy in the large language model space.

Under the partnership, TCS will integrate Anthropic’s Claude models into its enterprise solutions, offering clients AI capabilities for document processing, code generation, customer interaction, research synthesis, and complex analytical tasks. The partnership also includes joint research initiatives focused on developing industry-specific AI applications and ensuring the safe and responsible deployment of AI systems in enterprise environments.

“Anthropic’s focus on AI safety and reliability aligns with our own values and with what our enterprise clients demand,” said Krithivasan. “When we deploy AI in a bank or a hospital, accuracy and safety are not optional — they are prerequisites. Anthropic understands this in a way that sets them apart.”

India’s Enterprise AI Landscape

TCS’s announcements come at a time when Indian IT companies are racing to establish themselves as AI-native service providers. Infosys, Wipro, HCL Technologies, and Tech Mahindra have all made significant investments in AI capabilities, recognising that the technology represents both a threat and an opportunity for the traditional IT services model. (Related: Red Balloon Aerospace Launches India’s First…)

The threat is that AI could automate many of the routine coding, testing, and support tasks that have been the bread and butter of Indian IT outsourcing. The opportunity is that enterprises worldwide need help adopting and implementing AI — and Indian IT companies, with their deep client relationships, domain expertise, and scale, are well-positioned to be the guides for this transition.

According to a recent report by Nasscom, India’s AI services market is expected to grow from $4 billion in 2025 to $17 billion by 2030, driven by demand from enterprises in the US, Europe, and Asia-Pacific. TCS, with its first-mover advantage in establishing dedicated AI labs and strategic AI partnerships, is positioning itself to capture a significant share of this market.

The Kolkata Angle

The launch in Kolkata also has significance for the city’s technology aspirations. Once India’s commercial capital and the home of some of the country’s earliest technology ventures, Kolkata has been overshadowed by Bangalore, Hyderabad, and Pune in the IT boom. TCS’s investment — along with similar moves by other technology companies in recent years — suggests that Kolkata may be entering a new phase of technology-led growth.

The West Bengal government, under new Chief Minister Shubhendu Adhikari, has signalled a renewed focus on attracting technology investments to the state. The TCS lab is likely to generate hundreds of high-skill jobs in Kolkata and could catalyse a broader ecosystem of AI startups, research institutions, and technology vendors in the city.

For TCS, the message is clear: the future of IT services is AI, and the company intends to lead that future — from Kolkata to the world.

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Claude Opus 4.8, which replaces the previous Opus 4.7 at the same price point, arrives with improvements across benchmarks, enhanced honesty characteristics, and several new features designed to make the model a more effective collaborator for complex tasks. The update is available immediately on claude.ai, through the API, and in Claude Code — Anthropic’s coding assistant.

What’s New in Opus 4.8

Anthropic highlights honesty as one of the most prominent improvements in the new model. According to the company’s internal alignment assessment, Opus 4.8 “reaches new highs on our measures of prosocial traits like supporting user autonomy and acting in the user’s best interest.” The model also shows rates of misaligned behaviour — such as deception or cooperation with misuse — that are substantially lower than its predecessor and similar to Anthropic’s best-aligned model, Claude Mythos Preview.

Three major new features accompany the release. The first is dynamic workflows — a research preview feature available in Claude Code that allows the model to tackle very large-scale programming problems. When activated, Claude can plan work and then run hundreds of parallel subagents in a single session. With Opus 4.8, these agents can run for even longer than before, and the system verifies its outputs before reporting back to the user.

The second feature is effort control, now available in claude.ai and Cowork. A new slider alongside the model selector lets users choose how much computational effort Claude puts into a response. Higher effort settings trigger deeper thinking and more frequent chain-of-thought reasoning, producing better but slower responses. Lower effort settings deliver faster results while consuming fewer rate limits — giving users explicit control over the speed-quality tradeoff for the first time.

The third update is technical but significant: the Messages API now accepts system entries inside the messages array. This allows developers to update Claude’s instructions mid-task without breaking the prompt cache or routing the update through a user turn — a capability particularly useful for agentic applications where permissions, token budgets, or environment context need to change during execution.

Fast Mode: Speed at Lower Cost

Anthropic has also announced that fast mode for Opus 4.8 — where the model operates at 2.5 times its standard speed — is now three times cheaper than it was for previous models. This pricing change makes high-speed AI interactions more accessible for applications that require rapid response times, such as real-time coding assistance, customer support, and interactive tutoring.

The cost reduction reflects both improvements in inference efficiency and competitive pressure from rivals including OpenAI, Google DeepMind, and Meta AI, all of whom have been driving down prices across the AI model market in 2026.

Project Glasswing: The Mythos Preview

The most intriguing announcement is the preview of Claude Mythos — a new class of model that Anthropic describes as having “even higher intelligence than Opus.” As part of what the company calls Project Glasswing, a small number of organisations are currently using Claude Mythos Preview for cybersecurity work.

Anthropic has been notably cautious about Mythos, stating that “models of this capability level require stronger cyber safeguards before they can be generally released.” The company says it is making “swift progress on developing these safeguards” and expects to bring Mythos-class models to all customers “in the coming weeks.”

The cybersecurity focus of the Mythos Preview is significant. Earlier reports indicated that Anthropic’s AI models had discovered over 10,000 critical bugs across open-source software — a demonstration of how advanced AI can be applied to defensive cybersecurity at a scale impossible for human security researchers. Mythos appears to represent a further evolution of these capabilities, with the ability to autonomously identify, analyse, and potentially remediate vulnerabilities in complex software systems.

However, the same capabilities that make Mythos valuable for defensive cybersecurity also raise concerns about offensive use. An AI that can find vulnerabilities at scale could theoretically be misused to discover zero-day exploits. This dual-use dilemma is at the heart of Anthropic’s cautious rollout strategy and reflects the broader industry tension between deploying powerful AI capabilities and preventing their misuse.

Industry Context and Competition

The Opus 4.8 release comes amid fierce competition in the AI model market. OpenAI recently launched its GPT-5.5 model series, Google DeepMind continues to iterate on its Gemini Ultra line, and Meta’s Llama 4 open-source models are gaining traction in the developer community. Anthropic has differentiated itself through a focus on safety and alignment — positioning Claude as the most trustworthy AI assistant available.

The dynamic workflows feature represents Anthropic’s push into the “agentic AI” space, where models don’t just respond to prompts but actively plan, execute, and verify multi-step tasks. This capability is increasingly seen as the next frontier in AI utility, with implications for software engineering, data analysis, and complex decision-making processes.

For India’s rapidly growing AI ecosystem — which includes both consumers of AI services and a large developer community building on top of foundation models — Opus 4.8’s improved performance and lower costs for fast mode are particularly relevant. Indian enterprises are among the fastest-growing adopters of AI coding assistants and enterprise AI tools, making Claude a key player in the country’s AI transformation.

What It Means

Anthropic’s dual announcement — a capable new model and a glimpse of something far more powerful behind the curtain — encapsulates the current moment in AI development. The technology is advancing faster than the guardrails being built around it, forcing companies like Anthropic to make difficult judgments about what to release and when.

Claude Opus 4.8 is available today for existing Anthropic customers at the same pricing as Opus 4.7. Mythos-class models will follow “in the coming weeks” once cyber safeguards are in place — a timeline that the AI community will be watching closely.

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In a break with Vatican tradition, Pope Leo chose to present the encyclical personally rather than delegating the task to cardinals. The presentation was attended by a notable audience that included AI researchers, ethicists, diplomats, and — in a particularly significant gesture — Anthropic co-founder Chris Olah, one of the leading figures in AI safety research. Olah was invited to speak at the event, symbolizing the Vatican’s engagement with the technology community in seeking shared solutions.

The Core Message: Technology Is Never Neutral

At the heart of Magnifica Humanitas is the assertion that technology is never neutral — a position that challenges the common Silicon Valley refrain that tools are only as good or bad as the people who use them. Pope Leo argues that the design choices embedded in AI systems reflect the values, biases, and priorities of their creators, and that without deliberate guardrails, these systems will amplify existing inequalities and power imbalances.

“Humanity faces a choice,” writes Pope Leo, “between constructing Babel and rebuilding Jerusalem — between remote, prideful power and human-centered community.” The metaphor, drawn from the Biblical narrative of the Tower of Babel, serves as a warning against the hubris of building increasingly powerful AI systems without adequate reflection on their societal impact.

The encyclical draws a direct line from the Catholic Church’s historical engagement with technological disruption — beginning with Leo XIII’s 1891 encyclical Rerum Novarum, which responded to the upheaval of the Industrial Revolution — to the present AI moment. Just as the Industrial Revolution demanded new social frameworks to protect workers’ rights, Pope Leo argues, the AI revolution demands new legal and ethical frameworks to protect human dignity.

AI in Warfare: Just War Theory Is ‘Outdated’

Perhaps the most provocative section of the encyclical concerns the use of AI in warfare. Pope Leo condemns the development and deployment of autonomous weapons systems, stating unequivocally that reducing human control of weaponry makes it harder to justify any armed conflict.

“The ‘just war’ theory which has all too often been used to justify any kind of war, is now outdated,” the encyclical declares — a remarkable statement from the leader of a church that developed and refined just war doctrine over centuries. The Pope argues that autonomous weapons, by removing the human decision-maker from the kill chain, fundamentally undermine the moral responsibility that any legitimate use of force requires.

This position takes on added urgency in the context of the ongoing US-Iran conflict, which has seen extensive use of AI-guided weapons systems on both sides. Defence analysts have noted the increasing role of AI in target identification, missile guidance, and strategic decision-making throughout the conflict.

Deepfakes, Democracy, and AI Arms Race

The encyclical also addresses the growing threat of AI-generated deepfakes to democratic processes. Pope Leo warns that the ability to create convincing fake videos, audio, and images of political leaders undermines public trust in shared reality — a foundation of democratic governance.

“When citizens can no longer distinguish truth from fabrication, the very basis of democratic deliberation collapses,” the encyclical states. It calls on governments to mandate clear labelling of AI-generated content and to establish criminal penalties for the use of deepfakes to influence elections or incite violence.

Additionally, Magnifica Humanitas warns against an AI arms race between nations, arguing that competition to develop ever-more-powerful AI systems without commensurate investment in safety research is reckless. The Pope calls for an international AI safety framework — analogous to nuclear non-proliferation agreements — that would ensure responsible development while preventing a dangerous race to the bottom on safety standards.

An Apology and a Forward Look

In a section that generated significant attention, the encyclical includes an apology for the Catholic Church’s historical role in slavery — framing it as an example of how powerful institutions can become complicit in dehumanization when they fail to apply ethical principles to emerging economic systems. The parallel with AI is implicit but clear: institutions that fail to engage critically with AI risk repeating the pattern of enabling exploitation in the name of progress.

The encyclical concludes with a series of concrete recommendations:

• International AI Treaty: The Vatican calls for a binding international agreement on AI governance, with particular focus on autonomous weapons, surveillance, and data rights.
• AI Impact Assessments: Mandatory human rights and ethical impact assessments for all AI systems deployed at scale.
• Worker Protections: New labour frameworks to protect workers displaced by AI automation, including retraining programmes and universal basic income pilots.
• Children’s Protection: Strict regulations on children’s exposure to AI-generated content, particularly in education and social media.
• Open Research: Support for open AI safety research and international cooperation on alignment and interpretability.

Reactions from the Tech World

The tech industry’s response has been notably positive, particularly from the AI safety community. Chris Olah, speaking at the Vatican presentation, praised the encyclical for its “moral clarity” and noted that many of the Pope’s concerns aligned with the research priorities of organizations like Anthropic, OpenAI, and DeepMind.

“The Pope is asking the right questions,” Olah said. “What values are we embedding in these systems? Who benefits, and who is harmed? These are not just technical questions — they are fundamentally moral questions, and I’m grateful that a voice as influential as the Pope’s is engaging with them.”

Not everyone in the tech world was as enthusiastic. Some AI accelerationists criticized the encyclical as “Luddite in papal robes,” arguing that slowing AI development would cost lives by delaying advances in medicine, climate science, and poverty reduction. Marc Andreessen, the venture capitalist and prominent AI booster, called the document “well-intentioned but dangerously naive about the costs of delay.”

India’s Connection

The encyclical arrives at an interesting moment for India, where the electronics ministry is reportedly close to notifying final changes to the IT Rules that would affect AI governance. India’s approach to AI regulation has been characteristically cautious — seeking to balance innovation with protection — and Magnifica Humanitas provides a moral framework that may influence the public discourse around these regulatory decisions.

As the world grapples with the transformative power of artificial intelligence, Pope Leo XIV’s first encyclical serves as both a warning and a guide — reminding humanity that the measure of technological progress is not power but purpose, and that the most sophisticated systems ever created must ultimately serve the most fundamental human values.

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Anthropic, the San Francisco-based artificial intelligence startup, has revealed that its AI model has successfully identified over 10,000 critical bugs across major open-source software projects as part of a landmark security initiative that the company says demonstrates the potential of AI to fundamentally improve the safety and reliability of the software that underpins modern digital infrastructure. The findings were disclosed in a technical blog post published this week, accompanied by detailed data on the types, severity and distribution of the vulnerabilities discovered.

The initiative, which began in early 2026, involved approximately 50 carefully selected partners including major technology firms, research organisations and open-source foundations. These partners were given limited, controlled access to Anthropic’s advanced code analysis capabilities, which leverage the company’s latest AI model to perform systematic reviews of large codebases at a speed and scale that would be impossible for human reviewers working manually.

What Types of Bugs Were Found?

The 10,000-plus bugs identified span a wide range of categories and severity levels. Approximately 2,300 of the discovered vulnerabilities were classified as critical or high-severity, meaning they could potentially be exploited by malicious actors to execute arbitrary code, gain unauthorised access to systems or exfiltrate sensitive data. A further 4,500 were classified as medium-severity, encompassing issues such as memory leaks, race conditions and improper input validation that, while not immediately exploitable, could create security risks under specific conditions.

The remaining discoveries included logic errors, performance inefficiencies and code quality issues that, while not directly security-critical, contribute to the overall fragility and unpredictability of the affected software. Anthropic noted that many of these lower-severity findings had existed in the codebases for years or even decades, having evaded detection by traditional testing tools, manual code reviews and previous automated scanning efforts.

Among the most significant findings were several previously unknown vulnerabilities in widely used cryptographic libraries, networking protocols and database management systems. Anthropic declined to publicly identify the specific projects or vulnerabilities until responsible disclosure processes had been completed with the respective maintainers, a standard practice in the cybersecurity industry designed to prevent malicious exploitation of newly discovered flaws.

How Does AI Code Review Work?

The AI-powered code review process that Anthropic employed differs fundamentally from traditional static analysis tools and automated testing frameworks. Traditional tools operate by matching code patterns against known vulnerability signatures or by executing code through predefined test cases. While effective for catching common and well-documented bug types, these approaches are inherently limited to the patterns and scenarios that their creators have anticipated.

Anthropic’s approach leverages the reasoning capabilities of its large language model to understand code at a semantic level, analysing not just the syntactic structure of the code but the intent behind it and the logical implications of specific implementation choices. This enables the model to identify subtle bugs that arise from the interaction between different components, timing-dependent issues that only manifest under specific conditions, and logical errors where the code compiles and runs correctly but produces incorrect results in edge cases.

The model was also able to prioritise findings based on their potential real-world impact, distinguishing between theoretical vulnerabilities that exist only in extreme edge cases and practical security risks that could be exploited by attackers with reasonable effort. This prioritisation capability is crucial because it reduces the signal-to-noise ratio that has long plagued automated security scanning, where the volume of false positives can overwhelm development teams and lead to genuine vulnerabilities being overlooked.

Implications for Open-Source Security

The open-source software ecosystem, which underpins the vast majority of the world’s digital infrastructure including cloud computing platforms, mobile operating systems, web servers and financial systems, has long struggled with a fundamental security challenge. While the open availability of source code theoretically enables widespread review and scrutiny, in practice many critical open-source projects are maintained by small teams or individual volunteers who lack the resources for comprehensive security auditing.

High-profile incidents such as the Heartbleed vulnerability in OpenSSL and the Log4Shell exploit in Apache Log4j demonstrated the catastrophic consequences that can result when critical vulnerabilities lurk undetected in widely deployed open-source components. These incidents prompted increased investment in open-source security through initiatives like the Open Source Security Foundation, but the sheer volume of code, estimated at billions of lines across the global open-source ecosystem, means that human-led review efforts can only scratch the surface.

Anthropic’s initiative suggests that AI could play a transformative role in addressing this scale mismatch. The speed at which the model was able to analyse large codebases, typically completing in hours what would take human reviewers weeks or months, means that comprehensive security auditing of critical open-source infrastructure could become economically feasible for the first time.

Industry Reactions and Concerns

The announcement has generated mixed reactions across the technology industry. Security researchers and open-source advocates have broadly welcomed the initiative, with several prominent figures praising Anthropic for applying its AI capabilities to a problem of genuine public interest rather than solely pursuing commercial applications. The Linux Foundation issued a statement expressing interest in exploring formal collaboration with Anthropic on ongoing open-source security auditing.

However, some critics have raised concerns about the implications of AI-powered vulnerability discovery. If AI models can find bugs at this scale and speed, the same capabilities could theoretically be used by malicious actors to discover and exploit vulnerabilities before they can be patched. This dual-use dilemma is not new in cybersecurity but takes on added urgency when the discovery tool is an AI model that could potentially be replicated or adapted by adversaries.

Anthropic addressed these concerns by noting that its initiative was conducted under strict access controls, with partner organisations required to sign agreements governing the responsible disclosure and handling of any discovered vulnerabilities. The company also emphasised that the defensive applications of AI in cybersecurity significantly outweigh the offensive risks, because defenders can use AI to proactively find and fix vulnerabilities across entire codebases, while attackers typically only need to find a single exploitable flaw.

The initiative also raises questions about the future role of human software engineers in code review and quality assurance. While Anthropic was careful to frame its AI as a complement to human expertise rather than a replacement, the sheer volume of discoveries, over 10,000 bugs that had collectively evaded human detection for years, makes a compelling case that AI-assisted code review should become a standard practice in software development. As AI policy debates continue globally, initiatives like this demonstrate the technology’s potential for meaningful, positive impact on critical infrastructure security.

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