I think with waste products there is more of a last-mile (first-mile?) collection issue. Regardless we're definitely seeing some processed bio-oil waste coming in to the diesel lab for analysis in the recent year or two.
Looks to me like someone who is prospering based on coconut plantations would be the beneficiary from tapping a new market from a jet fuel process, and it probably could be made into a cleaner fuel than the waste-based bio-fuel.
Is Jet Fuel really the best use of coconut oil? I'd imagine it's far better as a lubricant or ingredient in things more directly adjacent to human rather than mechanical use.
sorry for the throwaways but the math is off by an order of magnitude because I fucked it up in my head while commenting, by exactly that much lol 2000~ not 20000~ whoops
These claims by WH site are at least debatable/unsubstanciated:
- "The virus possesses a biological characteristic that is not found in nature."
Furin cleavage sites are common in other types of coronaviruses (like MERS).
- "Data shows all cases stem from a single introduction into humans."
The collected samples suggest there were at least two separate spillover events (Lineage A and Lineage B) at the Huanan Market.
- "If there was evidence of a natural origin it would have already surfaced."
For many viruses we have never found the exact animal/human jump variant or the in-between carriers.
As said before, the physics for chemistry is 100 years old (Schrödinger/Dirac), but the N-body Hamiltonian is an exponential beast. Scaling to just 1mg (~10¹⁹ particles) hits the "Exponential Wall."
The app on your Mac today isn't a rewrite of the legendary Mac OS 7.2.1 Graphing Calculator, but an acquired app based on Curvus Pro introduced in OSX Tiger.
The first one has a legendary backstory.
2 devs snuck into Apple after their project was canceled:
https://www.pacifict.com/Story/
“We looked at each other, took a deep breath, and launched the application. The monitor burst into flames. We calmly carried it outside to avoid setting off smoke detectors, plugged in another monitor, and tried again.”
This highlights what I think is missing within a lot of tech companies today. I don’t know too many people who are so passionate about what they’re doing that they would sneak into their former employer’s office buildings and then find employees willing to work together with them to finish a project that simply had to get done. That alone makes me a bit sad.
The disagreement in timelines usually comes from differences in the used definition of AGI.
Many who predict a 2026–2028 arrival define it as: 'the ability to perform any purely cognitive task a human can do.'
If we stick strictly to that 'cognitive-only' metric, we are arguably very close.
When you explore a problem, use Python and lists/sets/dictionaries/JSON. Wait with types and specific data structures till you have understanding.
Speed of development over speed of execution.
When you know what and how to build commit to good data structures. Do the types, structs, classes, Trie, CRDTs, XML, Protobuf, Parquet and whatnot where apropriate. Instrument your program.
The efficiency of the final product counts.
