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Mastercard Plans To Say Goodbye To Magnetic Stripes In 2024
The technology that makes magnetic stripes possible dates back to the 1960s.
The pandemic has changed a lot of things, including the way we pay for goods and services. According to the Mastercard New Payments Index, 1 billion more contactless transactions were processed in the first quarter of 2021 compared to the same period in 2020. What’s more, 45% of all in-person checkout transactions in the second quarter of 2021 were contactless.
Now, the global payments and a technology company has announced that it plans to start phasing out the use of magnetic stripes on its credit and debit cards in 2024.
As explained in the official announcement, the magnetic stripe will first start to disappear for Mastercard payment cards in regions where chip cards are already widely used, such as Europe. In regions where magnetic stripes are still used relatively often, the phasing out process will be delayed by 3 years. From 2029, no new Mastercard credit or debit cards will be issued with a magnetic stripe.
“It’s time to fully embrace these best-in-class capabilities, which ensure consumers can pay simply, swiftly, and with peace of mind,” says Ajay Bhalla, president of Mastercard’s Cyber & Intelligence business. “What’s best for consumers is what’s best for everyone in the ecosystem.”
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The technology that makes magnetic stripes possible dates back to the 1960s, and we now have much more convenient and, above everything else, safer alternatives. One such alternative is the global EMV chip standard, which was introduced in the 1990s, enabling cardholder details to be held more securely on small integrated circuit chips embedded into cards.
Cards with EMV chips are currently responsible for 86% of in-person card transactions. We also have contactless payments, which can be made either using a card or with a modern, NFC-enabled smartphone. Since the outbreak of the pandemic, many policymakers and retailers have been endorsing contactless payments as the best payment method available, and the trend will likely continue even in the future.
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NVIDIA Puts GPT-5.5 Codex In Hands Of 10,000 Staff
The chipmaker has significantly expanded OpenAI’s latest model across teams from engineering to HR under tight internal controls.
NVIDIA has started rolling out OpenAI’s GPT-5.5 model through the Codex coding agent to more than 10,000 employees, extending the tool well beyond software teams and into core business functions.
The deployment covers engineering, product, legal, marketing, finance, sales, HR, operations and developer programs. Staff are using Codex for coding, internal research and routine knowledge work as companies test whether AI agents can move from demos to daily use.
GPT-5.5 is running on NVIDIA’s GB200 NVL72 rack-scale systems, linking OpenAI’s newest model directly to the chipmaker’s latest infrastructure push. NVIDIA said the systems cut cost per million tokens by 35 times and raise token output per second per megawatt by 50 times versus earlier generations.
Inside the company, it says the effects are immediate. Debugging work that once took days is being finished in hours and experiments across large codebases that used to stretch over weeks are now handled overnight. Teams are also building features from natural-language prompts with fewer failed runs.
In a company-wide note urging staff to adopt the tool, CEO Jensen Huang wrote: “Let’s jump to lightspeed. Welcome to the age of AI.”
Security remains central to the rollout. Codex can connect through Secure Shell to approved cloud virtual machines, allowing agents to work with company data without moving it outside approved environments. NVIDIA said it assigned cloud VMs to employees so agents run in isolated sandboxes with full audit trails.
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The company added that the setup uses a zero-data-retention policy. Access to production systems is read-only through command-line tools and internal automation layers.
The move also highlights NVIDIA’s long relationship with OpenAI. NVIDIA said the partnership began in 2016, when Huang personally delivered the first DGX-1 AI supercomputer to OpenAI’s San Francisco office.
The two companies have since worked across hardware and model deployment. NVIDIA also said OpenAI plans to deploy more than 10 gigawatts of NVIDIA systems for future AI infrastructure.
For Gulf markets pouring money into sovereign AI and enterprise automation, the signal is clear: internal AI agents are moving from pilot phase to standard tooling.
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