Apple Developer Academy adds AI training

Welcome back to AI Odyssey!

Today’s edition is 776 words, a quick 2-minute read. 

We'll discuss Apple's big move to train top AI developers and how Google's DeepMind is becoming an AI product factory, lets break down its journey, setbacks, and future expectations.

1 big thing: Apple Developer Academy adds AI training for students and alumni

Apple is expanding its AI initiatives by enhancing its educational offerings. 

Apple will now include AI training in the curriculum for all students and mentors at the Apple Developer Academy. Alumni are also invited to participate in this new training program.

• AI fundamentals: Starting this fall, students will be taught how to build, train, and deploy machine learning models on Apple devices.

• Course content: The curriculum covers AI technologies, Core ML for fast performance, and step-by-step guidance on building and training AI models from scratch. “Students will learn from guided curriculum and project-based assignments that include assistance from hundreds of mentors and more than 12,000 academy alumni worldwide.”

• Global reach: The new AI training will be available to thousands of students and alumni across 18 Developer Academies in Brazil, Indonesia, Italy, Saudi Arabia, South Korea, and the United States.

• Advanced tools like Xcode16: Leveraging new technologies and APIs announced at the recent WWDC, students will have access to enhanced tools like Swift Assist and new capabilities in Swift 6 for better coding and concurrent programming.

Why this matters: Apple’s introduction of AI training to its Developer Academy curriculum marks a significant step in preparing the next generation of developers. By equipping students with essential AI skills, Apple is fostering innovation and ensuring that its ecosystem continues to grow with well-trained, knowledgeable developers.

Google DeepMind shifts from a research lab to AI product factory

Google DeepMind, known for its groundbreaking AI research, is shifting gears to focus on developing commercial AI products.

Between the lines: While this move presents challenges, it also offers opportunities to leverage Google’s strengths in both research and commercialization. 

Let’s take a look at the highlights:

• A new direction: Google merged its two elite AI teams, Google Brain and DeepMind, into a single unit called Google DeepMind in April 2023. The combined unit aims to enhance Google’s track record in commercial AI products while maintaining its strength in foundational research.

• Challenges and setbacks: The launch of Google’s AI Overviews, which provides search answers, was marred by errors, including bizarre suggestions like putting glue on your pizza. It shows how the team is still navigating the complexities of generative AI.

• Change in leadership: Demis Hassabis, the co-founder of DeepMind, now leads the combined unit, focusing more on commercialization. The merger also caused some friction among researchers, who fear commercial goals overshadowing pure research.

• New releases: The unit released a new version of AlphaFold for predicting protein structures and is making progress on Gemini, Google’s flagship AI model.

Why it matters: This transition is significant as it highlights the growing importance of commercializing AI research. Google’s ability to balance foundational research with product development will be crucial in maintaining its leadership in the AI space. The success of this strategy could influence the future direction of AI development and its applications across various industries.

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^{AI & TECH NEWS}

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