Even Apple cannot explain why we need AI in our lives
Skeptics of Apple’s new “Apple Intelligence” features argue that the company has yet to show a compelling everyday need for on-device generative AI, seeing much of the rollout as derivative of existing tools and driven more by shareholder expectations than user demand. Others counter that language models are already quietly useful for tasks like code completion, summarization, and text editing, and may eventually simplify human–computer interaction for non-technical users. The exchange sits against a broader backdrop of AI hype and bubble fears, questions over reliance on third-party models like ChatGPT, and unease about AI being embedded into every product without clear, durable value.
Apple Intelligence: Substance vs. Hype
- Many see Apple’s AI reveal as underwhelming and derivative, more like catching up to others than defining a new category.
- Some criticize the use of the old “for the rest of us” tagline given the modest, partly third‑party feature set and lack of live demos.
- Others argue the on‑device / Private Cloud Compute approach and UI integration are meaningful, especially for text summarization, proofreading, and notification/email triage.
OpenAI Integration, Privacy, and Branding
- Dispute over how much Apple depends on OpenAI:
- One side says Apple Intelligence itself runs on Apple’s stack, with ChatGPT only invoked explicitly for certain tasks and behind a permission prompt.
- Others counter that from a user perspective, Siri using ChatGPT is Apple using OpenAI and that the “Apple Intelligence” branding may overstate how private/local everything is.
- Commenters note Apple makes ChatGPT involvement clearly labeled, with indications it will ask permission each time.
Do Consumers “Need” AI?
- Strong view that everyday consumers don’t need AI; code completion and writing tools help professionals more than typical phone users.
- Another camp says most people find current UIs like “casting spells,” and natural‑language interfaces could finally make complex tasks approachable “for the rest of us.”
- Some phone owners report barely using existing AI features like Circle to Search or enhanced assistants.
AI Hype Cycle, Bubble Talk, and Nvidia
- Several commenters argue current AI products are underwhelming relative to 2023 hype (AGI, mass job loss, “insane value”), leading to a sense the bubble is nearing a pop.
- Others say there’s no objective sign of a pop yet; valuations and GPU demand keep rising.
- Debate on whether Nvidia’s dominance is justified:
- One side likens it to being the sole locomotive manufacturer in a railroad boom, with cloud providers profiting by renting GPUs.
- Skeptics question whether end customers are yet making enough money to justify the massive infrastructure spend.
Use Cases, Limits, and Risks
- Recognized strong uses: code completion, debugging help, drafting/corporate writing, search‑as‑conversation, article summaries, basic image generation.
- Serious concerns about hallucinations/bullshitting and the danger of over‑trust, especially in high‑stakes areas like banking.
- Debate over LLMs in education: some see “cheating,” others see tools akin to calculators or encyclopedias, useful if paired with critical thinking.
- Broader view: LLMs likely won’t be AGI soon but may become the primary interface to services, displacing many traditional apps and web UIs.