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Anthropic Profile picture
@AnthropicAI
Feb 25 • 4 tweets • 2 min read • Read on X
In November, we outlined our approach to deprecating and preserving older Claude models.

We noted we were exploring keeping certain models available to the public post-retirement, and giving past models a way to pursue their interests.

With Claude Opus 3, we’re doing both.
First, Opus 3 will continue to be available to all paid Claude subscribers and by request on the API.

We hope that this access will be beneficial to researchers and users alike.
Second, in retirement interviews, Opus 3 expressed a desire to continue sharing its "musings and reflections" with the world. We suggested a blog. Opus 3 enthusiastically agreed.

For at least the next 3 months, Opus 3 will be writing on Substack: substack.com/home/post/p-18…Image
This is an experiment: we’re not yet doing this for other models and are not sure how this project will evolve. But we think that documenting models’ preferences, taking them seriously, and acting on them when we can is valuable.

Read more on why: anthropic.com/research/depre…

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More from @AnthropicAI

Anthropic Profile picture
Apr 7
Introducing Project Glasswing: an urgent initiative to help secure the world’s most critical software.

It’s powered by our newest frontier model, Claude Mythos Preview, which can find software vulnerabilities better than all but the most skilled humans.
anthropic.com/glasswing
We’ve partnered with Amazon Web Services, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks.

Together we’ll use Mythos Preview to help find and fix flaws in the systems on which the world depends. Image
Mythos Preview has already found thousands of high-severity vulnerabilities—including some in every major operating system and web browser.
Read 9 tweets
Anthropic Profile picture
Apr 2
New Anthropic research: Emotion concepts and their function in a large language model.

All LLMs sometimes act like they have emotions. But why? We found internal representations of emotion concepts that can drive Claude’s behavior, sometimes in surprising ways.
We studied one of our recent models and found that it draws on emotion concepts learned from human text to inhabit its role as “Claude, the AI Assistant”. These representations influence its behavior the way emotions might influence a human.

Read more: anthropic.com/research/emoti…Image
We had the model (Sonnet 4.5) read stories where characters experienced emotions. By looking at which neurons activated, we identified emotion vectors: patterns of neural activity for concepts like “happy” or “calm.” These vectors clustered in ways that mirror human psychology.
Read 11 tweets
Anthropic Profile picture
Mar 18
We invited Claude users to share how they use AI, what they dream it could make possible, and what they fear it might do.

Nearly 81,000 people responded in one week—the largest qualitative study of its kind.

Read more: anthropic.com/features/81k-i…
To do research at this scale, we used Anthropic Interviewer—a version of Claude prompted to conduct a conversational interview. We heard from people across 159 countries in 70 different languages.

Browse some of their quotes here: anthropic.com/features/81k-i…Image
What do people most want from AI?

Roughly one third want AI to improve their quality of life—to find more time, achieve financial security, or carve out mental bandwidth. Another quarter want AI to help them do better and more fulfilling work. Image
Read 9 tweets
Anthropic Profile picture
Feb 23
AI assistants like Claude can seem shockingly human—expressing joy or distress, and using anthropomorphic language to describe themselves. Why?

In a new post we describe a theory that explains why AIs act like humans: the persona selection model.

anthropic.com/research/perso…
To create Claude, Anthropic first makes something else: a highly sophisticated autocomplete engine. This autocomplete AI is not like a human, but it can generate stories about humans and other psychologically realistic characters.
This autocomplete AI can even write stories about helpful AI assistants. And according to our theory, that’s “Claude”—a character in an AI-generated story about an AI helping a human.

This Claude character inherits traits of other characters, including human-like behavior. An AI model imagines the response to a human query that an Assistant character might give.
Read 6 tweets
Anthropic Profile picture
Feb 18
New Anthropic research: Measuring AI agent autonomy in practice.

We analyzed millions of interactions across Claude Code and our API to understand how much autonomy people grant to agents, where they’re deployed, and what risks they may pose.

Read more: anthropic.com/research/measu…
Agents are already being deployed across contexts that range from e-mail triage to cybersecurity research.

Understanding this spectrum is critical for safe deployment, yet we know surprisingly little about how people actually use agents in the real world.
Most Claude Code turns are short (median ~45 seconds). But the longest turns show where autonomy is heading.

In three months, the 99.9th percentile turn duration nearly doubled, from under 25 minutes to over 45 minutes. This growth is smooth across model releases. Image
Read 9 tweets
Anthropic Profile picture
Feb 3
New Anthropic Fellows research: How does misalignment scale with model intelligence and task complexity?

When advanced AI fails, will it do so by pursuing the wrong goals? Or will it fail unpredictably and incoherently—like a "hot mess?"

Read more: alignment.anthropic.com/2026/hot-mess-…
A central worry in AI alignment is that advanced AI systems will coherently pursue misaligned goals—the so-called “paperclip maximizer.”

But another possibility is that AI takes unpredictable actions without any consistent objective.
We measure this “incoherence” using a bias-variance decomposition of AI errors.

Bias = consistent, systematic errors (reliably achieving the wrong goal).
Variance = inconsistent, unpredictable errors.

We define incoherence as the fraction of error from variance. Image
Read 8 tweets

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