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Free Machine Learning Courses from Top Universities
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Fine-tuning AI Models: Adjusting Weights and Prompting Techniques
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Adjusting the weights of an existing model, not training from scratch. When you fine-tune (with enough examples), you don’t include instructions in the prompt. See OpenAI’s fine-tuning guide here: https://
beta.openai.com/docs/guides/fi
ne-tuning
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Teaching children politeness to AI prevents behavioral problems
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A study showed that kids raised with Alexa who were allowed to treat her badly were more likely to have behavioral problems later on. Even if you don’t have to, I think we should continue to be nice to AIs so we don’t condition ourselves in ways we don’t expect
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Prompt Engineering Mitigations and Fine-Tuned Models for AI Security
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Prompt-engineering mitigations to prompt echo attacks are not robust. The only 100% reliable defense is to use a fine-tuned model, tuned without instructions in the examples. No prompt, no problems.
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Content Summarization and Sentiment Analysis in NLP
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In this @Cognilytica #AIToday #podcast episode 'Content Summarization and Analysis, Sentiment Analysis' from the AI Glossary Series, hosts @rschmelzer & @kath0134 define Content Summarization and #Analysis and #sentimentanalysis. Full episode: https://
cognilytica.com/2022/12/28/ai-
today-podcast-ai-glossary-series-content-summarization-and-analysis-sentiment-analysis/?utm_source=dlvr.it&utm_medium=twitter
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#ML #AI #nlp -
Wage Inequality Falls as Bottom Earners See Rising Wages
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“For the first time in four decades, wage inequality is falling, thanks to rising wages at the bottom”
@davidautor
@greg_ip
#economy https://
wsj.com/articles/wage-
inequality-may-be-starting-to-reverse-11672339062
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Word embeddings and latent factors in language models
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I'd argue that the janky "queen = king – man + woman" thing is definitely related. It's not doing language generation, but you're trying to query the latent factors the model has used to minimise the surface objective
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Using nlp.pipe() for faster batched predictions in spaCy
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Nice example! Here's a tip for next time as well: the nlp.pipe() function operates over a sequence of inputs, and lets the model make batched predictions, making it much faster:
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5G Innovation Transforms Digital Infrastructure and SDG Impact
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How #5G #innovation transforms #SDGs impact & #DigitalTransformation of #infrastructure See #UK #5GTrailblazers inc Prof @Dsimeo https://
bit.ly/3SWW9mq @ericsson #DataScience #womenintech @ipfconline1 #AI @DeepLearn007 #Bristol #EricssonAmbassador #CES2023 @dinisguarda -
Neural Radiance Fields (NeRF) for Unconstrained Photo Collections
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Paper: Neural Radiance Fields (NeRF) for Unconstrained Photo Collections https://
nerf-w.github.io