February 2026

Hello everyone, I am looking for critical feedback on an idea that could look somewhat redundant but has the potential to clarify how modelling context and observed data interact in probabilistic inference. In many scientific models, inference is formally expressed as conditioning on observed data, yet in practice the interpretation of observations also depends on contextual information such as modelling assumptions, calibration parameters, and prior knowledge. This paper introduces a simple notation for representing that contextual inference step […]

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Mistral AI lands a partnership with Accenture, the consultant that has also recently announced partnerships with rivals OpenAI and Anthropic.

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Large language models are trained primarily on human-generated data and feedback, yet they exhibit persistent errors arising from annotation noise, subjective preferences, and the limited expressive bandwidth of natural language. We argue that these limitations reflect structural properties of the supervision channel rather than model scale or optimization. We develop a unified theory showing that whenever the human supervision channel is not sufficient for a latent evaluation target, it acts as an information-reducing channel that induces a strictly […]

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This post is partly a belated response to Joshua Achiam, currently OpenAI’s Head of Mission Alignment: If we adopt safety best practices that are common in other professional engineering fields, we’ll get there … I consider myself one of the x-risk people, though I agree that most of them would reject my view on how to prevent it. I think the wholesale rejection of safety best practices from other fields is one of the dumbest mistakes that a […]

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It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the “progress as usual” way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since – the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it […]

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The camera-ready versions have been sent in October! I keep looking at https://papers.nips.cc, and they don’t “publish” it. Does anyone have any idea why this is taking so long this year?? submitted by /u/TheFaithlessness708 [link] [comments]

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Machine learning techniques are now routinely encountered in research laboratories across the globe. Impressive progress has been made through ML and AI techniques with regards to large data set processing. This progress has increased the ability of the experimenter to digest data and make novel predictions regarding phenomena of interest. However, machine learning predictors generated from data sets taken from the natural sciences are often treated as black boxes which are used broadly and generally without detailed consideration […]

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