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UAE-Based G42 Partners On World’s Fastest AI Supercomputer
The machine, named Condor Galaxy, has been built to assist with generative AI projects and is over 20 times faster than its predecessor.
Condor Galaxy, the world’s “fastest AI training supercomputer”, has been built with assistance from G42, a UAE-based technology holding group. The machine is actually a network of nine interconnected AI supercomputers developed by US-based AI company Cerebras Systems.
Located in Santa Clara, California, the massive machine boasts 4 exaFLOPs of power and a staggering 54 million cores that will significantly reduce AI processing times.
G42 will use Condor Galaxy to train AI models across a variety of data sets and has already created and tested Arabic bilingual chat, healthcare, and climate study applications.
“Collaborating with Cerebras to rapidly deliver the world’s fastest AI training supercomputer and laying the foundation for interconnecting a constellation of these supercomputers across the world has been enormously exciting,” said Talal Alkaissi, CEO of G42 Cloud. “The partnership brings together Cerebras’ extraordinary compute capabilities, together with G42’s multi-industry AI expertise,” he added.
Training the latest AI models requires enormous computing power and specialized programming skills. ChatGPT, for example, relies on 175 billion parameters and uses 10,000 Nvidia GPUs to train its AI algorithms.
Condor Galaxy brings genuine innovation to these kinds of processes, as all computing is performed entirely without complex distributed programming languages. This means that large projects no longer require weeks or even months spent distributing work over thousands of GPUs.
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“Many cloud companies have announced massive GPU clusters that cost billions of dollars to build but are extremely difficult to use. Distributing a single model over thousands of tiny GPUs takes months from dozens of people with rare expertise,” noted Andrew Feldman, CEO of Cerebras Systems. “CG-1 eliminates this challenge. Setting up a generative AI model takes minutes, not months, and can be done by a single person” he added.
The G42 and Cerebras partnership marks another step toward the democratization of AI. The combination of massive computing power and unique AI data sets should produce groundbreaking results and turbocharge hundreds of AI projects around the world.
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OpenAI’s ChatGPT Health Is A Private Space For Health Data
A new health mode lets the popular AI platform tap medical records and fitness apps while walling off sensitive information.
OpenAI has created ChatGPT Health, a separate space inside its chatbot platform for handling medical and wellness data. The opt-in feature starts with a small US cohort before widening out.
Health-related questions have long driven traffic to AI tools. OpenAI says over 230 million people ask ChatGPT about health or insurance each week. The new mode adds personal context to that behavior but stops short of diagnosis or treatment advice.
Users can connect records from participating US providers through b.well and link apps such as Apple Health, MyFitnessPal, Function and Weight Watchers. Some links are US-only, while Apple Health needs iOS. Once connected, ChatGPT can surface patterns in labs, summarize information ahead of a clinic visit or help map diet and exercise choices against past data.
The data sits apart from other chat information. Health has its own memories and does not spill into other conversations. Users can view or delete health memories at any time. OpenAI says this material is not used to train its models.
Security is much heavier in this section too. Health adds isolation and purpose-built encryption on top of the platform’s baseline protections. App connections require explicit permission, and disconnecting cuts the feed immediately.
“ChatGPT Health is another step toward turning ChatGPT into a personal super-assistant that can support you with information and tools to achieve your goals across any part of your life,” wrote Fidji Simo, OpenAI’s applications chief.
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Physicians had input during development, though OpenAI has not detailed how that shaped the end product. The launch follows Health Bench, a dataset released in May to test models on realistic medical cases.
While currently rooted in the US healthcare ecosystem, the approach may draw interest in the Gulf and wider MENA markets as governments push digital health records and patient portals under modernization programs. Adoption will depend on whether users trust an AI assistant with such personal material and whether it fits clinical routines.
For OpenAI, the move marks a cautious step into regulated terrain and signals a shift toward sector-specific uses of generative AI.
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