I got interested into the hashgraph algorithm quite early and wrote a toy implementation in python (in fact discovering an error in the paper in the process). Unless something changed it's entirely useless for open-membership internet-scale consensus. As I remember, the processing time of a message at a node is linear in the number of nodes and same for the local storage at a node, meaning it's not very scalable. Moreover, the nodes must somehow a priori agree on the list of participants of the consensus process, again something which is not realistic for internet-wide consensus. The protocol is quite neat and not too hard to implement but it's similar in scope to paxos/raft: consensus inside an organization, where some things are a priori agreed upon.
Always infuriating to see that people always focus on the his pre-70s (hardcore math) or post-80s period (borderline mysticism ramp up). In the 70s he was most politically active and _definitely_ not delirious in any sense of the word and in fact according to Leila Schneps this is one of the few periods of his life he described as happy, the "sunday of his life" [1]. I translated the '72 CERN talk, its baffling how relevant it is, to this day [2].
Demonstrating how some languages and some compilers are bad at tasks such as writing constant-time crypto routines is fine. Concluding that all compilers and non-asm languages are bad is a non sequitur. Just because you don't want non-branching code to change into branching code doesn't mean you should have to do register allocation by hand. Write simple domain-specific compilers and languages people.
> This has nothing to do with science and is really a point about the division of labor/economics.
This is not a critic of the idea science, ie some kind of pursuit of knowledge using any reasonable means. It is a critic of the modern institution that academic science currently is. As such, yes, some critics are in fact more generally applicable than just for science (as you say, division of labor). But these are particularly visible in science and have specific consequences in this context.
For a bit more background on Grothendieck's position on science, I've recently translated Grothendieck's talk on science at CERN, which was quite hard to find at some point: https://github.com/Lapin0t/grothendieck-cern/.
Hey, thank you for your service! you should post this to the front page as its own article!
>I think that agriculture, stockbreeding, decentralized energy production, medicine of a certain kind, very different from the medicine that prevails today, will come to the fore.
>In general, people see two extreme alternatives and see no middle ground between the two. If the person I'm talking to has chosen a certain alternative and I have a vision that lies beyond the one they considers good, they'll immediately accuse me of having chosen the opposite extreme alternative, because they can't see the middle ground.
> Of the people who see your math paper, 90% will only read the title. Of those who read on, 90% will only read the abstract. Of those who go still further, 90% will read only the introduction, and then quit.
My personal experience is usually quite different. Perhaps i'm very weird but i like to think i'm nothing special. I mostly read papers when searching for something specific (referral by someone in a discussion, searching for a definition, a proof). I almost never read the introductions, at least not in my first pass. My first pass is usually scanning the outline to search which section will contain what i'm searching for and then reading that, jumping back and forth between definitions and theorems. I usually then read discussion/related work at the end, to read about what the authors think about their method, what they like or dislike in related papers.
Abstract and introduction i only read when i have done several such passes on a paper and i realize i am really interested in the thing and need to understand all the details.
I very much hate this "be catchy at the beginning" and its extremist instantiation "the quest for reader engagement". Sure you should pay attention to your prose and the story you're telling. But treating reader of a scientific paper as some busy consumer you should captivate is just disrespectful, scientifically unethical and probably just coping with current organizational problems (proliferation of papers, dilution of results, time pressure on reviewers and researchers). Scientific literature is technical, its quality should be measured by clarity and precision, ease of searching, ease of generalization, honesty about tradeoffs. Not by some engagement metric of a damned abstract.
So, marketing is inevitable and necessary, but I have a hypothesis that the current Internet is making it worse. For example, creators (I'm lumping in researchers with songwriters, actors, etc) used to focus on passing the hurdle of getting an "elite" power (record company, publisher, University) to support them. Once over that hurdle, they specialized in creating and left marketing to the elite.
The elites would pressure the creators to do things they thought were marketable, but it didn't always work because creators had some leverage in negotiation and a small number of elites actually cared about making good stuff.
Now, there are fewer gatekeepers, but instead there is an all powerful algorithm. Creators all have to do their own marketing in addition to creating, and the algorithm can't be negotiated with.
So what we wind up with is insipid YouTube thumbnails and myriad academic papers with breathless "state of the art" claims.
There are tradeoffs, but I do think it's worth noticing how effectively we've started to reward creators for marketing rather than creating.
