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THE DAILY INDEX

Technology, AI, software, security, crypto and business

HEADLINES & LAUNCHES

TLDR AI

THE FORMER ACADEMIC GUIDING OPENAI'S TRILLION-DOLLAR AI BUILDOUT

Sachin Katti joined OpenAI in November to serve as its head of industrial compute. Before OpenAI, Katti spent more than 15 years as a Stanford professor and four years working at Intel. Katti now works on finding additional data center capacity and lining up ways to get more components like AI chips and memory. This has proved challenging, as data center operators are contending with power grid constraints, memory chip shortages, and growing pushback from local communities.

ALIBABA STARTS MAJOR REVAMP TO HEIGHTEN FOCUS ON AI PROFITS

Alibaba is setting up a business unit to bring its AI services and development endeavors under a single umbrella. The new Alibaba Token Hub will comprise the research team that develops the company's flagship Qwen models, its consumer-facing app division, and other major AI-related products. It will also oversee Alibaba's Slack-like DingTalk app and devices under the Quark brand. The revamp will help quicken interaction between the various teams within Alibaba's broader AI effort.

INTRODUCING MISTRAL SMALL 4

Mistral Small 4 integrates the capabilities of Magistral, Pixtral, and Devstral models, offering unified multimodal, reasoning-optimized AI with configurable reasoning effort. It employs a Mixture of Experts architecture with 119B parameters, supporting both text and image inputs, and features efficient scaling. Mistral Small 4 achieves competitive performance with reduced output length, is open-source, and is available on platforms like vLLM, llama.cpp, and Transformers.

APPLE'S CHEAP AI BET COULD PAY OFF BIG

Apple will invest $14 billion into AI this year, a tiny amount compared to the $700 billion Amazon, Alphabet, Meta, and Microsoft are investing. The company appears to believe that the AI infrastructure build-out will produce inadequate returns. It is spending less due to a conviction that AI models will commoditize and shrink, that existing product lines will absorb the workloads the cloud was built to serve, and that the durable franchise belongs to whoever owns the customer. Apple is betting on its AI-capable devices rather than centralized infrastructure.

CAN NVIDIA'S DOMINANCE SURVIVE THE SEA CHANGE UNDER WAY IN AI COMPUTING?

Nvidia's focus this year at its GTC event shifted to inference, the type of computing required to run models and allow them to respond to user queries. The AI industry is now less concerned with training AI models, which is what GPUs are best at, and more preoccupied with running them and generating profits from end-users. Inference requires different hardware than chips optimized for training. How far ahead the company remains in the AI-infrastructure race will depend largely on how effectively it is able to pivot its product road map from training to inference.

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