"AI is not a thing in the future. AI is the future." – Fei-Fei Li, Professor of Computer Science at Stanford University
Apple’s new AI leader
Apple hasn't been at the forefront of the consumer AI revolution. Now, as Apple intensifies its efforts in artificial intelligence, it has appointed Indian-origin engineer Amar Subramanya as Vice-President of AI, to lead Apple’s work on Foundation Models, AI safety, and evaluation - key areas that define the tech race today. Apple’s commitment to catch up with other AI leaders like Google and Microsoft is clear.
Google’s labs to Apple’s core
Amar Subramanya brings with him years of experience at Google, where he led engineering for Gemini and contributed significantly to speech technology and natural language processing. His technical pedigree aligns with Apple’s renewed focus on reshaping its AI roadmap. Subramanya joins a league of Indian-origin AI leaders such as Ashok Elluswamy (Tesla) and Prabhakar Raghavan (Google), who are shaping global AI strategies.
Apple’s AI gaps
Apple has faced delays in rolling out generative AI features and enhancing Siri, falling behind peers in model accuracy by 20 to 25 percent. Subramanya’s leadership is expected to close this gap and help Apple innovate more aggressively in a space where it has lagged for years. With Apple CEO Tim Cook calling this “an exciting new chapter,” Subramanya’s appointment could help Apple not only keep pace with but potentially define the future of user-friendly AI experiences.
Summary
Amar Subramanya has been appointed Vice-President of AI at Apple, where he will lead critical AI initiatives. With years of experience at Google and a strong academic background, his leadership may help Apple bridge its AI performance gap.
Food for thought
Can leadership alone reverse years of AI underperformance in a company as massive as Apple?
AI concept to learn: Foundation models
Foundation models are large AI systems trained on massive datasets that can be adapted for a variety of tasks like text generation, translation, or image recognition. They form the base layer of many modern AI applications and are essential for scaling intelligent systems efficiently.
[The Billion Hopes Research Team shares the latest AI updates for learning and awareness. Various sources are used. All copyrights acknowledged. This is not a professional, financial, personal or medical advice. Please consult domain experts before making decisions. Feedback welcome!]
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