Exclusive | The Sudden Fall of OpenAI’s Most Hyped Product Since ChatGPT - WSJ
Exclusive | The Sudden Fall of OpenAI’s Most Hyped Product Since ChatGPT WSJ
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How to Switch Industries Without Starting Over
You have spent years building expertise in one industry. You know the terminology, the workflows, the unwritten rules. And now you want out. Maybe your industry is shrinking. Maybe you have hit a ceiling. Maybe you just woke up one morning and realized you cannot do this for another twenty years. Whatever the reason, you are staring at the same terrifying question every industry switcher faces: do I have to start over? The short answer: no. Not even close. The longer answer is more nuanced, and it is what this entire guide is about. Because switching industries is not about abandoning everything you have built. It is about translating what you already know into a language your new industry understands. The Numbers Behind Industry Switching Industry switching is not the risky career move it
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![[D] Hash table aspects of ReLU neural networks](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-earth-satellite-QfbitDhCB2KjTsjtXRYcf9.webp)
[D] Hash table aspects of ReLU neural networks
If you collect the ReLU decisions into a diagonal matrix with 0 or 1 entries then a ReLU layer is DWx, where W is the weight matrix and x the input. What then is Wₙ₊₁Dₙ where Wₙ₊₁ is the matrix of weights for the next layer? It can be seen as a (locality sensitive) hash table lookup of a linear mapping (effective matrix). It can also be seen as an associative memory in itself with Dₙ as the key. There is a discussion here: https://discourse.numenta.org/t/gated-linear-associative-memory/12300 The viewpoints are not fully integrated yet and there are notation problems. Nevertheless the concepts are very simple and you could hope that people can follow along without difficulty, despite the arguments being in such a preliminary state. submitted by /u/oatmealcraving [link] [comments]
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