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OpenAI · Apple · ChatGPTEpisode 007 · 26 May 2024 · 45:05

Why ChatGPT Is ‘Getting Dumber,’ Apple Is Moving Slowly on AI, and Our Data Is the Most Fragile Part of the System

What to watch for

1Compare “When a new version of ChatGPT responds faster, speaks, and understands images, it can feel as though progress moves in only one direction” with “Competition under the terms of cooperation between Epl and Google with Microsoft”: they provide different criteria for judging the same issue.
2Test the conclusion from “New concept of basic unconditional income and AI” in your own use case—what actually changes in the process and what remains a promise.
3Before choosing a product or approach, record the constraint identified in “10-year data loss”.
4Define the owner of the outcome and the quality metric for the situation described in “Artificial intelligence in IPhones: What will Apple do?”.
Signals to track afterwards
Watch for actions by Apple and Google that confirm or challenge the episode’s central claims.
Compare new launches and policy changes with “New concept of basic unconditional income and AI”: have access, quality, price, or constraints changed?
Check whether the scenario in “Artificial intelligence in IPhones: What will Apple do?” becomes repeatable practice rather than a one-off demonstration.
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Key takeaways

00:00How the issue moves from news to product: when a new version of ChatGPT responds faster,

The “When a new version of ChatGPT responds faster, speaks, and understands images, it can feel as” issue should be assessed with one constraint in mind: this section clarifies the mechanism behind the topic and preserves a constraint that would otherwise be lost in an overly simple conclusion.

01:16The practical meaning of the issue: chatGPT and destruction of archives, how OpenAI worsens

The decision in “ChatGPT and destruction of archives, how OpenAI worsens the conditions for new start-ups” depends on one criterion: the conflict reveals which rights, money, and control points the parties consider strategic.

04:13Where the promise meets reality: openAI and courts

The “OpenAI and courts” scene leads to a working conclusion: the key test is enforceability: who must prevent the risk, who records the violation, and who is accountable for the consequences.

07:36What determines the outcome: new ChatGPT-4o: what opportunities are available to a

In the context of “New ChatGPT-4o: what opportunities are available to a simple user,” this criterion applies: the issue turns on whether the rule can be enforced and who carries responsibility, not merely on the existence of a new requirement.

14:20Why an announcement is not enough: artificial intelligence in IPhones: What will Apple do

For the “Artificial intelligence in IPhones: What will Apple do?” scene, the decisive point is this: the important signal is not one funding number: the next round, available runway, and closure rate show whether a company can survive the new cost of capital.

17:22Any partnership between Apple and OpenAI or Google remains a form of competition

The decision in “Competition under the terms of cooperation between Epl and Google with Microsoft” depends on one criterion: this section clarifies the mechanism behind the topic and preserves a constraint that would otherwise be lost in an overly simple conclusion.

20:08The boundary between value and constraint: review of key players in the AI market

The decision in “Review of key players in the AI market” depends on one criterion: the important signal is not one funding number: the next round, available runway, and closure rate show whether a company can survive the new cost of capital.

23:36Who owns the outcome: loss Perplexity and Uber

The working conclusion from “Loss Perplexity and Uber” is that the important signal is not one funding number: the next round, available runway, and closure rate show whether a company can survive the new cost of capital.

31:56Against this backdrop, the treatment of data looks especially strange

The decision in “New concept of basic unconditional income and AI” depends on one criterion: this section clarifies the mechanism behind the topic and preserves a constraint that would otherwise be lost in an overly simple conclusion.

39:52The question ‘Why is ChatGPT getting dumber?’ is therefore broader than the quality of a single answer

In the context of “10-year data loss,” this criterion applies: this section clarifies the mechanism behind the topic and preserves a constraint that would otherwise be lost in an overly simple conclusion.

What this episode is about

GPT-4o made AI noticeably easier to use, Apple is preparing to integrate models into the iPhone, and users are increasingly noticing instability and lost data. Rapid progress does not remove a basic requirement: a product must be reliable, understandable, and must not force people to live inside someone else's opaque system.

When a new version of ChatGPT responds faster, speaks, and understands images, it can feel as though progress moves in only one direction. Yet users are noticing something else at the same time: the model sometimes answers worse, its behavior changes without explanation, old functions disappear, and familiar data can become inaccessible. A powerful technology does not automatically become a strong product.

GPT-4o showed that the interaction model matters as much as raw capability. Voice, images, and more natural dialogue bring the model closer to an everyday assistant.

That is precisely why Apple cannot simply add another chat window to the iPhone. It has to integrate AI into the device so that it works with personal context, preserves the familiar interface, and does not hand control of the user to a competitor.

Any partnership between Apple and OpenAI or Google remains a form of competition. OpenAI is tied to Microsoft, Google competes directly with Apple, and Apple itself is accustomed to controlling the critical parts of its products. A deal can provide fast access to a powerful model, but in the long run Apple is unlikely to want dependence on someone else's system inside its most important interface: the smartphone.

Against this backdrop, the treatment of data looks especially strange. Archives, request histories, and personal materials can be stored for years until a single error or company decision removes access.

Information has become cheap to create, but its preservation has not become guaranteed. Users often do not even know where their digital memory is stored or how to take it with them.

The question ‘Why is ChatGPT getting dumber?’ is therefore broader than the quality of a single answer. We depend on systems that change constantly without explaining their internal logic. A proper AI product should do more than impress us with a new model. It should preserve data, behave predictably after updates, and allow people to leave the ecosystem without losing their own history.

A sound AI product must do more than impress with a new model: it must preserve data, behave predictably through updates, and let people leave without losing their own history.

Episode transcript

The episode is in Russian; below is an English reading guide to the transcript (the full EN transcript is a machine translation). Voice matching applied to 59 segments: 47 identified, 2 mixed, 7 marked with ✓, and 3 unresolved.

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