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Apple Developing Two Major AI Initiatives Codenamed 'Linwood' And 'Glenwood'
Apple is developing two major artificial intelligence initiatives, codenamed Linwood and Glenwood, "as part of a sweeping plan to make far more capable and competitive in the generative AI era," reports AppleInsider.
Read the article for all the details, but here are two highlights:
° Linwood is Apple's in-house effort to rebuild the Siri "brain" around large language models developed by the Apple Foundation Models team. These models are designed to understand natural language, manage complex queries, and retain conversational context.
° While Linwood focuses on internal innovation, Glenwood explores a different route. Apple is testing Anthropic's Claude to power Siri's core intelligence and has experimented with tools like ChatGPT and Google Gemini during development. The projects represent a notable shift in Apple's traditionally insular approach. The company has historically relied almost entirely on in-house technology.
In April it was reported by The Information that Craig Federighi, Apple's senior vice president of Software Engineering, told Siri engineers to do "whatever it takes to build the best AI features," even if that means using open-source models from other companies in its software products as opposed to Apple's own models.
From the report: Federighi has already shaken things up. In a departure from previous policy, he has instructed Siri's machine-learning engineers to do whatever it takes to build the best AI features, even if it means using open-source models from other companies in its software products as opposed to Apple's own models, according to a person familiar with the matter.
The Information noted that, until now, Apple engineers could only use third-party LLMs to benchmark them against their own in-house models during testing. Under Federighi's leadership, it seems that all open-source LLMs can be used by Apple engineers.
A LLM (large language model) is a type of machine learning model designed for natural language processing tasks such as language generation. They're used in a wide range of applications, including chatbots, content creation, translation, and more. Some well-known examples include GPT (Generative Pre-trained Transformer) models, which are used in applications like ChatGPT.
Article provided with permission from AppleWorld.Today
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The event brings together specialists in the fields of robotics, natural language processing, virtual assistants, autonomous driving, and more, with speakers from the likes of Google, Microsoft, Amazon, and Uber.
As part of a panel exploring the role of personal assistants, Acero will about how deep learning informs the way Siri works on Apple devices. From the AI Frontiers online schedule:
Siri brought personal assistants to the mainstream after its introduction in 2011 in the iPhone. Deep learning is powering many components in Siri: trigger word detection, large vocabulary recognition, text-to-speech, machine translation, and natural language understanding. In this talk I will show a few examples of how deep learning is used in Siri.
Also on Acero's panel are Amazon Alexa director Ruhi Sarikaya and Google research scientist Dilek Hakkani-Tur.
Acero arrived at Apple in 2013 after spending two decades at Microsoft, where he oversaw research into computer vision, speech, neuro-linguistic programming, machine learning and translation, amongst other areas. His work on Siri takes in speech recognition, speech synthesis, and machine translation.
The AI Frontiers conference takes place from November 9 to November 11. For more information on the event and scheduled speakers, check out the AI Frontiers website.
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