4 Amazing Ways AI is Improving (and Worsening) the World Beyond LLMs

4 Ways AI is Improving (and Worsening) the World, Beyond LLMs

These days, AI is almost synonymous with Large Language Models (LLMs), large data centers, and multi-hundred-billion-dollar data center buildouts.

But AI is changing the world around in many more ways that go completely under the radar, but could be just as significant as ChatGPT.

Today, while I’m still compelled to share what is clearly the ‘next step’ in the progress ladder in Large Language Models (LLMs), showing you how the bad press Opus 4.7 has gotten is largely misguided and, instead, this model is not only the smartest model you’ve ever used, but also a sign of the change of times, most of what we’re talking about has little to do with LLMs but is still just as impressive, and in some cases, outright scary.

Because I never said these innovations were necessarily good for us. Thus, my goal for today is to make sure you internalize that AI is far more than just LLMs.

Let’s dive in.

Token Efficiency, the New Mantra

The LLM topic of today is what I believe is the next instrumental step in AI progress: per-forward-pass intelligence.

Let me show you with a visual example.

Opus 4.7 Feels Worse, but it’s actually smarter

As we covered two days ago, many people have been complaining about Anthropic’s new model, Opus 4.7. The reason was that, relative to other frontier models and even compared to Opus 4.6, it saw some regressions; in many regards, a worse model than its predecessors.

In some cases, the model was extremely condescending toward users. In some other cases, it felt like the model wasn’t even trying, as if it had become lazy.

Source

This was, of course, a negatively received release (and with reason). However, I believe that what is going on is not that the model is worse; it’s that it’s different. That, and that Anthropic hasn’t yet quite figured out how to serve this “new” model.

But why do I say it’s different, and what do I mean by ‘different’? And the answer is token efficiency. This is, my dear reader, unlike any other LLM you’ve ever talked to.

Let me explain.

We can see the striking difference in how this model behaves relative to other frontier models (GPT-5.4 and 5.3-Codex models, the two highest scores) in the chart below, where the model scores in the top 4 while requiring way fewer tokens, literally an order of magnitude fewer than other models scoring similar top results.

In other words, undoubtedly, Opus 4.7 is the “smartest” model we’ve ever seen measured by a single forward pass.

But what do I mean by “smartest by forward pass”?

Let me put it this way. What my gut is telling me is that the results “are worse” because overall thinking has indeed decreased for now as Anthropic finds the sweet spot, but on the margins, this is the smartest model ever released.

This probably makes zero sense right now, but bear with…

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