It doesn’t know the time — it’s not in the prompt it’s given. It’s hallucinating an arbitrary time the same way it would any other detail in a fictional example.
MACHINE LEARNING
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Deep Learning Papers Called Autoregressive Sampling Dreaming
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Many deep learning papers (at the preprint http://
arxiv.org stage) used to call autoregressive sampling, “dreaming” -
Banks Digital Transformation: AI, FinTech Partnerships, Data Skills
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Part3 Session Pick: How can #banks continue #DigitalTransformation in a downturn? Superb points Janet Jones @MSFTBusinessUK #FTBanking #Ad #AI #ML Anchor on omnichannel #experience Explore #FinTech partnerships for #innovation
Support #data literacy & #developer skills -
Learn Data Science: Essential Resources and Tutorials
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Try these: https://
x.com/DataChaz/statu
s/1536030599923830786
… https://
x.com/DataChaz/statu
s/1542223758433439746
… https://
x.com/DataChaz/statu
s/1193905658950823936
… https://
kaggle.com/learn -
Model with 8192 token context, double others, no RLHF tuning
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It also has a context window of 8192 tokens, which is 2x any of the instruction-following models available in the API. Also the model is internally labelled “text-davinci-002-render”, which would seem to imply it doesn’t include RLHF tuning (unique to 003).
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Fine-tuning process and 8192 token context window
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It’s clearly a very different fine-tuning process, which they talk about in some detail in the announcement. Also the context window is 8192 tokens, double any of the text models available through the API.
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AIOps: Real-time IT Issue Detection via Analytics and Machine Learning
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#AIOps uses analytics and #machinelearning in order to analyze #bigdata from various #IT operation tools and devices. As a result, it is able to automatically spot and more importantly react to issues in real-time.
Via @ingliguori #MLOps #DigitalTransformation #DevOps #IoT #IIoT -
Large financial firms adoption of deep learning since 2016
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Some large hedge funds, investment banks, and financial firms started getting into deep learning around 2016 (though probably not into Deep RL). That probably paid off well!
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Deep RL for Real Robots: Limited Success in 2016
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Deep RL for real robots didn’t really work so well back in 2016.