Steve Wozniak cheered after telling students they have AI – actual intelligence
A commencement speech by Apple’s cofounder praising graduates’ “actual intelligence” and striking a cautious tone on AI has been widely contrasted with more hardline pro‑AI messages from other tech leaders that were booed. Commenters debate whether current AI is truly revolutionary or overhyped “autocomplete on steroids,” its real impact on software quality, jobs, and learning, and how much guardrails or regulation are realistic in a system driven by profit and geopolitics. Underneath the technical arguments runs a broader anxiety about younger generations facing debt, a weak job market, and technology that feels more like a tool of disenfranchisement than empowerment.
Reaction to Wozniak’s Speech and “Actual Intelligence”
- Many welcomed the human-centric, affirming focus on students’ own minds, especially contrasted with more techno-fatalist commencement talks.
- Some see the line as necessary hope for graduates facing debt and a bleak job market, even if it tells them what they want to hear.
- Others criticize it as shallow populism and not actionable guidance in a world where AI is clearly not going away.
AI’s Power, Hype, and Limits
- Views range from “revolutionary, actual intelligence” to “autocomplete on steroids” and “slop.”
- Supporters emphasize language as central to human intelligence, seeing LLMs as surprisingly capable and general.
- Skeptics point to nondeterminism, hallucinations, weak reasoning, and poor reliability; they argue it’s iterative on search, not a step-change.
- Debate over terminology: some insist current systems are legitimately “AI,” others see “AI” as a shifting marketing label distinct from AGI.
Work, Coding, and Technical Debt
- Reports of modest productivity gains (≈10–30%) from coding assistants and agents; helpful for boilerplate, refactors, and small fixes.
- Strong concerns that agents require constant expert supervision, so net cost savings are dubious.
- Many fear AI will accelerate low-quality code and technical debt because management optimizes for “cheap + fast,” not quality.
- “Tokenmaxxing” anecdotes: companies pushed to maximize AI usage, racking up large bills without clear ROI; worry about rising model costs and subsidized pricing ending.
Students, Jobs, and Education
- Students both use AI (for homework, sometimes cheating) and resent it as a threat to entry-level jobs and their degrees’ value.
- Some fear AI will hollow out the learning process in programming/writing, producing graduates with weak fundamentals.
- Broader anxiety: first cohort expected to work harder than their parents yet achieve less, with AI framed as a job destroyer rather than empowerment.
Big Tech, Politics, and Power
- Deep skepticism that voting or regulation can meaningfully “rein in” big tech given campaign finance, lobbying, and bipartisan corporate dependence.
- Many see AI as a hyper-capitalist tool to cut labor and concentrate power, in tension with speeches that ask youth to be optimistic.
Apple, Siri, and Product Philosophy
- Apple’s AI integration is seen as incremental, user-focused, and easy to disable, versus Microsoft’s aggressive “Copilot everywhere” push.
- Siri is widely viewed as still poor; Apple allegedly struggles with reliability/safety to put its brand on heavy LLM use.
- Speculation that Jobs would have loved narrow ML enhancements but been wary of flaky LLM behavior; Woz is praised as kind and relatively indifferent to wealth.