a_tartaruga

https://www.reddit.com/r/DIYbio/ and other places focused on this sort of thing are full of ideas. In my limited experience the ratio of problems/ideas to people working on them is very high.

Since you linked that nice biology article I'm guessing you already know about "The Machinery of Life," that book seems like it would be good. The Kurzgesagt Immune System book is probably even better as it's intentionally written at an accessible level.

Organic Chemistry as a Second Language is maybe my favorite introductory text of all time though it might be a little dry if you aren't already interested.

It has its own political bend but I would recommend "A People's History of the United States." There's a lot of quality graphic novels out there that are interesting in a different way than textbooks that can teach a lot of history. I'm thinking of Persepolis as an example.

> I don't think the whole Blockchain web3 thing is really doing that

I would argue most of whatever fraction of web3 projects are in good faith are trying to do exactly this. One reason to miss this is that most of the digital goods/services offered in web3 are financial in an economy that really only needs 0.01% the current level of finance in terms of its real value. There are some non financial projects which for the past year have branded themselves as "DePin" (full disclosure this is the area I work in).

> It's almost like you need something that makes use of it in a properly decentralised way. Meaning an app protocol?

The history of open markets for hard digital goods (not finance) is maybe longer than you think. If you read Brahm Cohen talk about his work at Mojo nation in the late 90s you'll see that early attempts at this left people discouraged about user demand, which is maybe what you are getting at with "app protocol". The comments of this old Unenumerated post have more ex-Mojo nation people arguing against similar ideas: https://unenumerated.blogspot.com/2007/06/nanobarter.html

The situation is potentially different today with demand for more control over our digital lives and less trust in spy corps bubbling under the surface of what regular people want. One charismatic example is Blue Sky which is built on a data model ready to go for decentralized storage markets (though not using any afaik). All of the discussion around open models and AI safety also look vaguely like opportunities.

IMO a lot of future success depends on the cost curves of fundamental cryptographic primitives especially snarks (which actually look promising) and also on the potential for disruption with radically new primitives: non excruciating FHE, VDFs that actually work etc

Both internet and web are themselves examples of what you are talking about. Maybe you're too young to have lived through it but for entertainment everyone used to watch TV decided by a few corporations.

You'll hear little positive about them on hacker news but there are many projects attempting to turn centralized services into market based p2p open services. Not clear if any will seriously work out, bitcoin is probably the only thing that is really working. But not clear others won't work out.

The many examples of functionalities fulfilled by decentralized structures in nature indicate that this is more complicated. The endocrine system and immune system in your body are beyond current human technology capability and are decentralized. But they also exist alongside a centralized nervous system.

Idk if this email is a scam but Fluence is a legit project.

Sipser is one of the best textbooks of all time from any field

This class was so fun. I remember a lot of people did find it difficult too.

Baba is you is similarly a good introduction to the mindset needed to write exploits.

It's not esoteric to biologists but genetic engineering. Everything is written in assembly and the execution environment is non deterministic and 3 dimensional.

The Genesis of Technoscientific Revolutions by Narayanamurti and Tsao is worth reading for a better understanding of how research works and how to nurture it. It has a very clear explanation of how engineering and technology mirror science and how both work together.

Funny enough sewerAI is legit and predates the chatgpt moment

This isn't specified well enough to get detailed criticism. I don't know what you're hashing exactly but I think it includes purchase time. Depending on resolution of {Time of purchase of lottery} it might be very easy to manipulate.

It is probably the most hopeful thing I've ever read and more or less believed. Internalizing parts of it has made almost everything easier to think about. I love the idea that flowers are objectively beautifully.

The answer is yes and it's the only way. You need to develop fluency to understand "Math B". It's only ungraspable right now because you haven't had enough of the right kind of practice. The right kind of practice is 1) well motivated for your curiosity 2) achievable.

General overview of biotech industry look at Stat magazine and subscribe if you can afford it. Listen to their weekly "Readout Loud" podcast.

For actual projects if you live in USA: Seattle, NYC, SF, Baltimore then visit community bio labs there. People are generally friendly and there are easy ways to get involved through either group meetups or classes.

If you don't it's much harder since DIY bio is still so early. If you are near a local university there might be some opportunities to work with others. Watch Thought Emporium videos to see what is possible with a home lab in principle though probably not in practice unless you are full time and wealthy.

For background reading - on lab techniques this book is good: https://www.wiley.com/en-us/Gene+Cloning+and+DNA+Analysis:+A... - basic body of knowledge of genomics: https://www.taylorfrancis.com/books/mono/10.1201/97804290217...

Start by learning quantum mechanics for dogs: https://www.goodreads.com/en/book/show/8243716

Then go here: https://qubit.guide/index

What you are pointing out is real and I think unavoidable. Math is just denser than most other things. A few high level things I've come up with while self studying for the past few months

- Focus on what is achievable. Learning difficult things is like building a tall pile of sand at the beach. You need a very wide base of experience to be able to climb high. Don't expect to learn algebraic geometry without mastery of abstract algebra etc. Reading research papers before working through relevant textbooks is a lot harder.

- Use quality resources. Some books are really good for self study at a less advanced level (Abbot, Sipser, Pinter) while others are bad or need more maturity. Research papers from earlier on in fields and further back in time feel more approachable.

- Try harder to get help from people. I have found reddit's r/math biweekly Quick Questions threads to be helpful for specific, advanced questions. Reach out to colleagues and acquaintances. There are people out there who love this stuff.

- There's no substitute for going back to school and taking an actual class with office hours and someone who will look over your work every week and correct your errors, it probably speeds things up 10x

Ousterhout had a tradition like this on Fridays in CS 140. Looking up his name and scars seems to be what you are talking about https://gist.github.com/gtallen1187/27a585fcf36d6e657db2.

Yes. Also networks that perform simple versions of useful work exist today. I work on a network which uses zk proofs to check storage of user input data and pays out blockchain consensus rewards accordingly.