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Meta & Microsoft Release AI Language Tool For Commercial Use
The open-source AI model, called Llama 2, will be available through the Azure AI catalog and Amazon Web Services, as well as in a standalone Windows version.
Meta and Microsoft have partnered to create Llama 2, a “next-generation large language AI model” for commercial and research applications. Llama 2’s open-source code places greater importance on responsibility and includes a reasonable use guide, plus an acceptable use policy to prevent criminal applications, misleading information, and spam.
Meta is releasing pre-trained and conversation-oriented versions of Llama 2 for free. Meanwhile, Microsoft is making the AI tool available through the Azure AI catalog to use with cloud tools, including content filtering. Llama 2 can also run directly on Windows PCs and will be available through outside providers such as Amazon Web Services and Hugging Face.
Major rivals like the popular OpenAI GPT-4 are often locked down for greater subscription or licensing revenue, but Llama 2’s Open Source code lets companies customize the AI technology for their own purposes — such as chatbots and image generators — while providing a way for outsiders to check for biases, inaccuracies, and operating flaws.
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For Microsoft, Llama 2 is an important project in the fight against AI rivals — notably Google. Microsoft already uses OpenAI systems in Azure and Bing, so the latest Meta collaboration should give business customers greater choice, especially if they’re interested in fine-tuning an AI model to suit more specialist needs.
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Egypt’s Mobile Wallets Are Booming, But Cash Still Has Power
Egypt’s telecom regulator says $57.6 billion moved through more than 57 million wallets in six months. And one operator handled 77% of the value.
Egypt’s mobile wallets handled EGP 2.96 trillion ($57.6 billion) in transactions in the first half of 2026, according to the National Telecom Regulatory Authority – a 56% rise on the EGP 1.90 trillion ($36.9 billion) recorded a year earlier. Transactions grew faster still, up 62% to 2.22 billion, while registered wallets climbed 23% to 57.01 million.
On one reading, that is exactly what Egypt’s regulators have been pushing for: a payments system that runs through telecom-linked wallets rather than banknotes. But the same data shows how far cash still reaches into it. Cash withdrawals made up just 12% of the transactions taking money out of wallets, yet 75% of the value withdrawn or spent.
Money arrives mostly from bank accounts: transfers through InstaPay accounted for 78% of deposit transactions and 58% of the value deposited, while incoming remittances from abroad made up 3% of deposit transactions but 10% of their value. Once inside, it largely moves between wallets – wallet-to-wallet transfers accounted for 54% of all transactions and 67% of total value, with mobile and internet top-ups a distant second at 25% of volume. In effect, the wallet is serving as a transfer layer: the place money passes through between the bank account and the banknote.
That layer also runs predominantly through one operator. Vodafone Cash held 53% of registered wallets and 57% of active ones, but handled 69% of transactions and 77% of their value. Its nearest rival, e& money, held 23% of registered wallets but 14% of transaction value; Orange Cash 20% and 8%; WE Pay 4% of wallets. How many of the 57.01 million are active is not stated.
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Adoption is rather uneven in other respects. Men held 38 million wallets, or 67% of the total, against 19 million held by women. Users aged 26 to 45 accounted for half of all wallets, and Cairo alone had 10.6 million, or 19% of the national total, with Giza next at 6.5 million.
The NTRA says it is continuing to work with telecom operators on the regulatory framework for wallet services, part of a wider effort to expand electronic payments and financial inclusion. Its own figures show that effort succeeding on the way in. On the way out, three-quarters of the value still leaves as cash.
Egypt’s Mobile Wallets Are Booming, But Cash Still Has Power
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