Breaking Smart

Thank you for posting this article, which led me down to the Breakingsmart post titled "Against Waldenponding" https://breakingsmart.substack.com/p/against-waldenponding I highly recommend reading both.

Boyd's famous OODA loop (observe-orient-decide-act) is probably the most misunderstood and misused diagram of practical significance in decision making. It is to decision-making what the five elements (earth/fire/water/wind/ether) model from alchemy is to modern chemistry. Or what Freud's id-ego-superego model is to neuroscience ... Though the terms and concepts of the OODA loop are intuitive and coherent at least at a first pass, there is fundamentally no way to use them entirely safely without making gross errors. Just as there is no way to do modern chemistry using alchemical concepts without making gross errors. Or trying to do neurosurgery based on an id-ego-superego map of the brain without making gross errors. https://breakingsmart.substack.com/p/the-use-and-misuse-of-the-ooda-lo…

FWIW, back in 2017 Venkatesh Rao looked at the distractions going on in the world and criticised 'deep work' in the process: https://breakingsmart.substack.com/p/life-in-the-time-of-choleric "17/ In more sanguine times, this is easy in theory. You just log off from Facebook and Twitter, and put your head down and do what people like Cal Newport call “deep work.” 18/ I personally don’t believe in the idea of unplugging for "productivity" even in sanguine times, but in choleric times, it is a recipe for doing tone-deaf projects nobody cares about. 19/ Unless you work in pure mathematics or physics (and perhaps even then), your work is capable of creating meaning only if it is responsive to, and consciously situated in, its social milieu."

how about semi-colon shaped https://breakingsmart.substack.com/p/semicolon-shaped-people

Hi, I put together a newsletter called Interesting Things that curates 40+ interesting stories and links every week about tech with a splash of business and science. Looking through the past few editions, there has been an average of one AI/deep-learning/neural-network related article per week: Issue #001 Shedding light on fairness in AI with a new data set — Facebook publishes a dataset of of 45,186 human face-to-face videos with an emphasis on fairness and diversity across age, gender, skin tone, & ambient lighting. — https://ai.facebook.com/blog/shedding-light-on-fairness-in-ai-with-a-n… Issue #002 Geometric foundations of Deep Learning — An attempt to unify a broad class of ML problems from the perspectives of symmetry and invariance. — https://towardsdatascience.com/geometric-foundations-of-deep-learning-… Latest Neural Nets Solve World’s Hardest Equations Faster Than Ever Before — New approaches to solve entire families of partial differential equations and make it easier to model complicated systems. — https://www.quantamagazine.org/new-neural-networks-solve-hardest-equat… Issue #004 Superhistory, Not Superintelligence — Simpler algorithms and more data do better than more complex algorithms with less data. What are the implications? — https://breakingsmart.substack.com/p/superhistory-not-superintelligenc… Reimagining Databases for Vector Embeddings — How is a vector database different from a conventional…