AMD is turning its back on flagship gaming GPUs — to chase AI first

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1. AMD is turning its back on flagship gaming GPUs — to chase AI first

AMD is prioritizing AI chips over flagship GPUs for gamers, merging its RDNA gaming graphics and CNDA data center efforts into a single universal "UDNA" aimed at AI first. AMD's chief executive, Jack Huynh, explains that the goal is to build scale and market share at lower price points, rather than focusing on flagship GPUs.

He also plans to build "King of the Hill" for AI data centers, where AMD already has substantial market share with EPYC CPUs. While AMD cannot produce every kind of chip at once, it aims to lead in value-oriented GPUs.

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2. Roblox announces AI tool for generating 3D game worlds from text

Roblox is set to introduce an open-source generative AI tool that allows game creators to create 3D environments and objects using text prompts. The tool, based on a "3D foundational model," is part of Roblox's broader AI integration strategy.

The AI model uses a custom next-token prediction model, similar to LLMs used in ChatGPT. Roblox plans to open-source its 3D foundation model, allowing developers and competitors to use and modify it. The company also plans to capture 10% of global gaming content revenue through the Roblox ecosystem.

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3. Apple invents its own version of Google Lens called Visual Intelligence

Apple has introduced Visual Intelligence with the iPhone 16, aiming to enhance user interaction with the world around them. Activated by a touch-sensitive button called Camera Control, it can identify objects, provide information, and offer actions based on what users point it at.

Later this year, Camera Control will also serve as a gateway to third-party tools with specific domain expertise, maintaining user privacy. Apple claims that Visual Intelligence processes data on the device itself, ensuring the company doesn't know what users clicked on.

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4. A fast and flexible approach to help doctors annotate medical scans

Researchers from MIT's Computer Science and AI Laboratory, Massachusetts General Hospital, and Harvard Medical School have developed the interactive "ScribblePrompt" framework, which can segment any medical image, even those it hasn't seen before.

The tool uses algorithms to simulate human annotations of over 50,000 scans, including MRIs, ultrasounds, and photographs, across structures in the eyes, cells, brains, bones, and skin. The tool can make corrections based on user feedback and is faster and more accurate than comparable interactive segmentation methods, reducing annotation time by 28% compared to Meta's Segment Anything Model (SAM) framework.

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5. Heart disease is the world’s biggest killer — this Cambridge Uni spinout is using AI to find new treatments

Cambridge University spinout CardiaTec has raised $6.5 million in a seed round to tackle cardiovascular diseases (CVDs), the leading cause of death globally. The company aims to "decode" the biology of CVDs by partnering with 65 hospitals to collect human heart tissue.

The goal is to build the largest human heart tissue-multi-omics dataset, identifying novel therapeutics, and reducing the average cost of drug discovery.

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