Mon. 06/09 – WWDC 2025 - Techmeme Ride Home - Audio Brevity

Mon. 06/09 – WWDC 2025

Jun 9, 2025 21m

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Episode Description

All the headlines from WWDC. Microsoft unveils the first iteration of that handheld gaming strategy. Meta is considering its largest external AI investment yet. And did Apple researchers reveal that Large Language Model have a structural ceiling, and are we basically there? Sponsors: Acorns.com/ride Links: Hands-On With the Xbox Ally X, the New Gaming Handheld from Asus and Microsoft (IGN) Meta in Talks for Scale AI Investment That Could Top $10 Billion (Bloomberg) A knockout blow for LLMs? (Gary Marcus On AI)

AI-Generated Summary

WWDC 2025 Highlights

In this episode, Brian breaks down the key announcements from Apple's WWDC 2025. He describes the highlights including the transition to a new design language that Apple refers to as 'liquid glass,' which will impact all platforms including iOS 26 and macOS 26. Key features like updated lock screens, new camera interface, AI functionalities in FaceTime, and improved Maps functionalities were discussed. The episode also touches on Apple’s heavy push for AI integration across their devices.

New Handheld Gaming Initiative from Microsoft

Brian shares insights on Microsoft’s unveiling of two new ROG Xbox Ally handheld devices aimed at enhancing portable gaming experiences. He explains the design and functionality improvements made to the Xbox app and game processing, emphasizing how these advancements are part of Microsoft's strategy to compete with Steam and reshape handheld gaming.

Meta's Potential AI Investment

The podcast delves into Meta's discussions regarding a significant investment in Scale AI, which specializes in data labeling and AI training services. Brian illustrates the potential implications of this investment in the context of the growing AI sector, citing recent trends and partnerships that Meta is pursuing particularly related to defense AI technologies.

Critique of Large Language Models (LLMs)

In a noteworthy segment, Brian reviews a paper released by Apple researchers, outlining the deficiencies in current large language models particularly concerning their reasoning capabilities. The podcast includes comparisons to human reasoning and critiques the reliance on LLMs for complex problem solving, presenting the argument that while LLMs hold promise, they currently exhibit limitations as they fail to perform effectively on classic reasoning tasks.