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Apple deploys local AI to start a 'buy, buy, buy' model, and acquired the French company Datakalab in December last year

王林
Release: 2024-04-23 09:28:01
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According to news on April 23, Apple continues to expand its strength in the AI ​​field through "buy, buy, buy". Recently disclosed documents show that it has acquired Datakalab, an artificial intelligence startup headquartered in Paris, to further promote local AI capabilities.

苹果布局本地 AI 开启“买买买”模式,去年 12 月收购法国 Datakalab 公司It is reported that the acquisition was finalized on December 17 last year. There had been no relevant news until the French media Challenges discovered the documents disclosed by the European Commission and discovered the acquisition. The document did not disclose too many acquisition details, but what is certain is that Apple is actively adopting a "buy, buy, buy" approach to continue to absorb outstanding start-ups, thereby shortening the gap between it and Microsoft and Google in the field of AI. the gap between. Compared to Microsoft, Google and others promoting large language models, Apple is more inclined to promote localized AI experience. Datakalab acquired this time focuses on algorithm compression and embedded artificial intelligence systems. Here is a brief introduction to Datakalab. The company was founded in 2016 and was co-founded by Xavier and Lucas Fischer. It focuses on low-power, high-efficiency deep learning algorithms that can run without relying on cloud systems. This approach is consistent with Apple’s ongoing commitment to user privacy, data security, and reliable performance. Processing data locally can minimize the risk of data leaks and ensure faster processing. The startup’s expertise in compressing neural networks to work effectively on portable devices like smartphones and tablets is likely to be a key factor in Apple’s interest. Related reading: "Apple is low-key in the AI ​​field and has acquired 32 startups in 2023" "To expand its strength in the AI ​​field, Apple has acquired DarwinAI company"

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source:ithome.com
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