the PhD requirement is either for actual research positions or a gatekeeping function to help companies narrow down their massive candidate pools

I really enjoyed the concepts in "Artificial Intelligence, a Modern Approach" which really grounds a first-principles foundation of automated reasoning. Warning: The first 80% of the book doesn't have any sexy new deep learning approaches, but I still think it is very valuable to see the history.

+1, I'm a few chapters in and its highly instructive. Gives me a deeper appreciation for the modern deep learning regime. Also, as we enter the agent supercycle, I think many of the basic algorithms for search, planning, etc. will make comeback a in a huge way.

With lots of talk lately about California's river water management, I thought it would be neat to share these photos of the Colorado River Delta, where 100% of the water is diverted to human use and none of it to the sea.

We have very nearby and valuable evidence to demonstrate the impact of short-sighted freshwater release policies.

> LA and California as a whole have some of the highest taxes in the nation

The City of LA has a lower per capita tax revenue than most large Texan and southern cities, largely due to property tax caps.

> anti-tech superiority complex which is counterproductive

I didn't have a phone until significantly after my peers, so I used our family computer, Instagram's undocumented API, and a variety of SMS forwarding solutions to keep in touch with my friends, which I think definitely sparked my interest in hacking and a career in software.

I developed a superiority complex, but it was more anti-conformity and pro-hacking than anything.

This complex is deserved.

Enthusiastic article for sure. Lots of the hype in this piece suggests that effective semantic search for populating limited context windows of LLMs will be big business.

My thoughts:

1. Will context windows grow enough so that we can afford to be lazy and drop entire knowledge bases into our queries?

2. Will the actual models of LLMs be able to more reliably capture data in a semi-structured way, perhaps bypassing the "data moat" that the author claims?

A major innovation in search solutions is eagerly anticipated.

I used GDB to debug contributions to the ION Delay-Tolerant-Networking stack, which is composed of dozens of processes. After some practice it became super easy to attach GDB instances to several running processes and watch the C structs be passed between them.

One of my dreams is to help build an international tech manufacturing R&D zone across Tijuana and San Diego, complete with commuter trains that use the existing ROW.

It's about 1MHz. Signals can propagate pretty far due to ionospheric interactions, which could be a positive or negative effect depending on your intentions.