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Lectures on Quantitative Economics Using JAX

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This PR updates `njit` to `jit` now that `numba>=0.59` is installed https://github.com/QuantEcon/meta/issues/112

This PR makes use of the `Tesla T4` instance now available on `GitHub Actions` as a beta instance

The code to be converted to JAX is here: https://github.com/QuantEcon/book-dp1/blob/main/source_code_py/markov_js.py https://github.com/QuantEcon/book-dp1/blob/main/source_code_py/markov_js_with_sep.py These can be combined into one lecture, with the second set of code as an exercise. Background is in...

In this lecture, when we do the timings, we do not use `block_until_ready` and we don't run twice to eliminate compile time. https://jax.quantecon.org/opt_savings_1.html I think this is probably true in...

Right now, in the final figure, OPI is beating HPI for some values of m in the final figure of opt_savings_2 and opt_invest. Can HPI beat OPI if we loosen...

@mmcky Can you please search for this line: In line with immutability, JAX does not support inplace operations: It looks like JAX is sorting in place now. Could you please...

Add a new Jax lecture ``ifp_advanced_jax`` based on https://python.quantecon.org/ifp_advanced.html The code is ready, and the details need to be filled in (TBD in a new PR).