One of the most important measures of productivity should be the time and attention that you use for doing what really matters to you. Become more productive by doing more of what really matters to you.
AI
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Learning Real World Machine Learning Recommended Resource
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Awesome! Recommended to anyone interested in learning how real world ML works!
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Ethics of Tech Innovation Financing and Righteousness
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I for one believe only the righteous should be allow to finance tech innovation.
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MIT Dataset Enables Precise Semantic Image Captions for Accessibility
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Training ML models w/MIT’s new dataset empowers them to create precise, semantically dense captions, while illustrating data trends & intricate patterns. It could help improve accessibility for those w/visual disabilities: https://
bit.ly/3D6VwQZ -
Likelihood Versus Probability: Key Differences in Data Science
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What is the Difference Between Likelihood and Probability?: Likelihood and probability are interrelated and often confused terms finding common usage in data science and business. Both probabilities are associated with probabilities but differ in… https://
analyticsvidhya.com/blog/2023/06/l
ikelihood-vs-probability/?utm_source=dlvr.it&utm_medium=twitter
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Cultivating Curiosity in Medicine: Beyond Efficiency to Patient Care
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"Exercising curiosity at the bedside — which is not
always incompatible with efficiency— is how we cultivate relationships with our patients, how
we diagnose disease, and most important, how we advance the art of medicine." https://
nejm.org/doi/full/10.10
56/NEJMp2304992?query=WB&cid=NEJMWeekendBriefing,July22,2023DM2273275_NEJM_Subscriber&bid=1689454157
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Best practices for evaluating LLM-driven applications
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The best way to evaluate LLM-driven apps, by yours truly at @V7Labs
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Self-Attention Mechanism in Large Language Models Explained
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Understanding and Coding the Self-Attention Mechanism of Large Language Models From Scratch https://
bit.ly/3YL821l #AI #DeepLearning #MachineLearning #DataScience -
Aging Actively: Long-Term Engagement in Science and Academia
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In this age of short attention, no one plans what we would do if we lived beyond 100. But at @Caltech surrounded by amazing role models of all ages, I feel energized and positive about growing old and doing things I love with students and colleagues.
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Why DeepMind Never Released AlphaGo to the Public
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I wonder this is the reason why DeepMind has never released AlphaGo (or any of its variants), and has never let the general public play against it. So that no one will be able to find holes in it, and show that, just like other AIs, AlphaGo can easily be defeated or jail broken.