Opus 4.8 formulated the hypotheses in advance, conducting data cleaning, did research on references, conducted analyses, did robustness checks, and put out the whole paper in LaTEX style. GPT-5.5 found one issue with a hallucinated result, and had other constructive feedback.
@emollick
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AI agents wrote and reviewed an academic paper
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I had Opus 4.8 in Claude Code write a sophisticated, if minor, academic paper from a archive of hundreds of de-identified research files from years ago I had to use GPT-5.5 Pro as a reviewer, it spotted one major error & some minor points. Opus corrected https://
embeddedness-gradient.netlify.app -
Paper: Differences Between AI and Human Narrative Styles
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There is a lot being written about the stylistic tells of AI writing (em-dashes, etc.) but this paper looks at AI narrative tells Fascinating differences between AI & human narrative, and asking AI to write in different styles doesn't do much to change it https://
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Lem and Adams’ Fictional AIs Predicted Modern AI Themes
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Lem & Douglas Adams got AI right Presciently Golem XIV (from 1981) has an illustration of the jagged frontier as explained by an AI, Golem (GENERAL OPERATOR, LONG-RANGE, ETHICALLY STABILIZED, MULTIMODELING), discussing itself and a smarter AI (Honest Annie) compared to people
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Recurring Themes in AI-Written Fiction
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When they write fiction, AIs are obsessed by things that take or give memories, contracts with sentient inanimate objects, sets of secretive rules that govern conduct & which no one can acknowledge out loud… All very on-the-nose. I suspect a lot is hyperstition at this point.
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Google’s Omni multimodal model and blending potential
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Google has the only true Omni model, but the elements aren't hooked up. It appears it can take in & output audio, images. video, songs, text, code, etc. But right now each type of output is separate. When you can access the model directly, blending modes, a lot becomes possible.
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Organizations overspending on AI token budgets highlights cost-management gap
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I have heard from quite a few large organizations that blew through their entire token budget in the first couple months of the year. There aren't even good processes for thinking through how token costs will change over time.
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Companies wrestling with token usage and model choices
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Most companies only have very crude understanding of token usage right now, so they veer from focusing on adoption (“everyone should use as many tokens as possible”) to cost control (“can we just use local models?”) depending on the moment and manager. This is all very new.
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Debate over Token Allocation as AI Becomes Essential for Coding
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The fact that tokens went from something no one even put in a budget line a year ago to an absolute requirement for coding now is the cause of handwringing, not that AI is not turning out to be useful No one knows who should get tokens, how much they should get & how to control
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What to Keep Human and What to Hand Over to AI
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I wrote a new post on what we need to keep human and what to hand over to AI, with forays into experiments in education, consulting, and the the latest controversy over literary prizes.