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tadeegan

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Agree sadly. I shy away from web3 investment strategies like participating in liquidity pools because I'm scared about reporting the taxes correctly. I'm now considering ways of anonymizing my self-custody so that I can avoid this burden. Im basically forced to act illegally to avoid this toil

I guess they realized muilti-backend keras is futile? I never liked the tf.keras apis and the docs always promosed multi backend but then I guess they were never able to deliver that without breaking keras 3 changes. And even now.... "Keras 3 includes a brand new distribution API, the keras.distribution namespace, currently implemented for the JAX backend (coming soon to the TensorFlow and PyTorch backends)". I don't believe it. They are too different to reconcile under 1 api. And even if you could, I dont really see the benefit. Torch and Flax have similar goals to Keras and are imo better.

With less rain, the plants in the area rely more on the snowmelt for water, leaving less water to make its way into the nearby streams. Decreased rain also means sunny skies, which encourages plant growth and water evaporation from the soil.

Logical next step: remove the vegetation for more human population!

Compilers have soooo many heuristics. And a lot of it looks like a chess or Go game: You have a list of 100s of AST optimization passes (possible moves) that preserve the semantics of the program but you have limited compute with which to run iterations of these passes. What order and combination of these should you use?

I think PyTorch c++ api is less mature and harder to compile into other projects. Tensorflow started with the c++ api exposed which is why the graph format is so stable and favorable to deployment in heterogeneous environments.

Tensorflow is just such a classic clusterfuck google project. V2 had huge breaking changes (reminiscent of angular) and tons of the apis are clunky and don’t work well together. There are like 3 different ways to save a model. It’s almost like a bunch of teams built features with no oversight.

I’m pretty sure tf is considered in maintenance mode within google as Brain and the tf creators themselves have moved to Jax. I do think Google learned a lot from tensorflow and am excited to see Jax pan out.

Pytorch is a pleasure to debug. I think pytorch jit could close the deployment gap.

Ive noticed that the rentals on the market, while cheaper are generally lower quality. It seems to me that many landlords are opting for airbnb, where you can find 1 fully furnished 1 bedrooms for 2k$ a month rather than lock in a rent controlled tenant at the current prices.

Testing model code tends to be very difficult unless you design your training loop with lots of abstractions and dependency injection which makes the code less explicit and difficult to understand. For example, try to look at the Tensorflow Estimator framework. Absolutely awful to use but is well tested.

The other day I said “Hay Siri, take me to Buena Vista park.” She responded “the entrance buena vista Avenue?” and I responded: “oops I actually meant corona height park” and she instantly started navigation there. I actually held a productive conversation with a computer. Magical.

J2CL attempts to solve a much different problem than GWT. It does not try to replace js or js developers.

J2CL is designed for cross platform code reuse. For example, the code powering Google Docs front end needs to be written for web, Android and iOS. J2CL does the transpilation of all document manipulation and rendering logic from Java -> JS (and accomplishes this with unprecedented js code size). The UI is still written in JS.

Java -> Android

Java -> Backend Server

Java -> J2objc -> iOS

Java -> J2CL -> JS/web.