I already told you I don't want to talk about this here and now. It is not dumb but it is disrespectful to demand explanations from strangers, like I have time for this.
Well it's there in the name, they add machine learning to Postgres. They are not the only ones doing this, I am working on a similar idea and I don't think all of us are as misguided as the crypto bros of 2022. This is as much about Postgres as it is about AI. No one has yet successfully communicated what those in the know are seeing, and it is sort of hard to explain but relational databases are a good match for AI. Personally my strategy is to try to build compelling application instead of an infrastructure play, but to each its own and I wish them the best.
Stimulating different parts of the body stimulates different parts of the brain[1]. Through cross talking neurones this might influence parts of your brain to be rewired differently and relieve some over burdened circuits, just like it might happen with traumatic events, but the rigour and precision by which this can be done is still very much an open question.
Universal grammar in the way that Chomsky suggested, a sort of structure all humans must have in there brain, is not a thing. But I believe there is something like the "universality of grammar" where the human vision system or motor system can have a grammatical quality to them. In that sense that there is ambiguity in which tree structure represent the world. I've seen this in many places but I am not sure if someone has put this into (better) writing.
The big lie about the semantic web is this ridiculous notion that it is machine readable just because it has an unambiguous grammar to parser and has ontologies to disambiguate homonyms.
Sentence embeddings have been great for improving semantic search, but I am still struggling with finding relevant documents for numerical values. Questions like "what people where born in 1992" or "people with at least 4 children". One thing I can do is pre-process the data by transforming the date of birth into boomers/zoomers/millenials and the like but this does not help on the question side if people don't know what to ask
Lets break down the three clains in reverse order:
1. Are there primitive societies of hunter-gatherer that are not self aware, as in they don't pass neurological test that measure this?
2. From a evolutionary perspective what is the advantage of this sexual dimorphism and given that this advantage exists why did this advantage disappear afterwards and become present in both sexes. Are there any other traits where woman are shown to have larger divergence. I thought men where the "weak" sex in this regard.
3. If consciousness is recent then how do you explain conscious trails and self awareness in lower primates, is this also a case of convergent evolution?
Yes, in my career I've seen a OO extension of C written in XML that required a custom eclipse plugin to write. A language where you defined a function like: function foo() while (...) ... end while; if (...) ... end if; end foo, because those guys loved the C++ style of putting comments at the end of control structures. Finally there was the language you had to write in excel that was exported to CSV that in turn was used to generate XML that was parsed before compile time to generate java code with System.out.println and was finally loaded at runtime through some dynamic loading. I never had any respect for these people as engineers, I was very KrugerDunnings early on in my career but I don't think I was to entirely to blame for always knowing better.
There are a lot more middle man then that, a lot of CEO and CTO i've met had an almost active disintrest in anything technical or even practical knowledge of there product, not knowing the priorities is in there own backlog or not knowing what an init system is or does but ask you how to start a process when a computer starts. Unbelievable what people complain about in meetings without having googles that problems in MONTHS. Most people just secretly hate technology and will grasp at anything that gives them an excuse not to care.
I once tried helping a drunken homeless man that was throwing up blood at 1 in the morning when I was on my way to the office to pick up some paperwork. My phone died the moment I took it out of my pocket to call an ambulance. I spend the next 30 minutes trying to get the guy help including calling the intercom of a hospice/clinic around the corner. I ended up talking to another homeless woman who impersonated a doctor on the intercom of the hospice to get them to call an ambulance.
It is easy to avoid multiple workers processing the same task: `delete from task where id = (select id from task for update skip locked limit 1) returning *;`
This is a depressing list, I was expecting some interesting new bio engineering process or dunno quantum chemistry this or that for easier synthesise of whatever, but instead it was either marginal improvements like wasm or total BS like blockchain/cloud. AI/ML is probably the only interesting thing happening in tech at the moment, it has been getting more attention in the last year but that is because it has honestly enabled a lot of people to do things they could not do before. Personally I think that there is also a lot of things happening in computer graphics but the money has been miss allocated on creating virtual places instead of making the real world better.
There is just so much, I've thought of writing some blog post about it but there is already a lot of content out there because pg is a big community with a lot of people doing interesting things and I don't know if what I know is unique and not just parroting others peoples stuff.
But ok sure I can give you some pointers to cool stuff. Sometimes it are just architectural patterns that are easy to do like upsert statements in sql using `on conflict`, or writing a task queue on the cheap using `for update skip locked limit 1`. Replace 90% of your crud api controllers with `postgrest` and use row level security for everything, AI is not going to steal your job category theory is. From a operations and scaling perspective it pays dividend to learn about `explain analyse` but did you know they also have `stats` that can help the analyser optimise queries based on statistical relations of different columns. I've also been looking into how to "branch" a database instead if just doing a backup, it does require some ZFS tricks but that is also just pure power and not something you find with a cloud file system. There are also just a ton of extension for timeseries or vector embeddings, or write your own in Rust using `pgx`. Like I said way too much to write here, I don't use all of this in production but I just keep finding these gems while working on my own project. There is a strong OSS ecosystem with lots of teams giving there own spin on pg and that is welcomed if you have a opinion of your own and still want to learn from others. You need motivation to go this deep but in contrast to other esoteric knowledge I have mastered companies are also willing to pay for it.
I've been building a Postgresql extension in the last months for some functionality that was needed and have learned a ton about the internal workings of this database. All very scary and complicated sounding stuff but I feel privileged to be able to do this because the things you learn are just pure gold. My attitude before this was that of the ideal customer of a cloud database, someone who was scared of sql and preferred to hide behind the complexity of a ORM. Not anymore, now I write thousands of lines of sql and laugh to myself like a maniac.
Lately I've been made to understand that DevOps or Software Engineering is not for me, capability/maturity models, processes written in anything other then code, or metrics this and that just ism't me. We can argue about the meaning of words all day long but like I said this just isn't me. Some of us just prefer to say close to the metal (as in reality with all its complexity that escapes the precision of words and that is totally ok) and are deeply suspicious of any excessive abstractions. There must be others like me, so I am in search for my tribe, and I want to know what do we call ourself, maybe we don't want to call ourself anything, but where can we meet, who want to hire us, please tell me if you know, Thanks!
I live in Europe and a large part of my (extended) family works in the social sector and for all the good they do I can never shake the impression that the first to benefit from all these social programs is the people that organise them. Same thing with a lot of startup and business accelerators or professional networks they love to talk about how they are helping but I've learned that they do (almost) nothing for you and that it is better to invest your time in executing your own plan.
I was complaining about the cookies banners in 2009, but ok people tend to conflate the two but it is not fair to lash out to people saying they don't like X with a simple rebuff that the thing is actually called Y. China makes the hardware, America writes the software and the EU makes the regulation, is a very common critique of technical people in the tech sector who lack political and economical power compared to the value they create.
I've been playing around with sentence embeddings to search documents, but I wonder how useful they are as a natural language interface for a database. The way one might phrase a question might be very different content wise from how the document describes the answer. Maybe it might be possible to do some type of transform where the question is transformed into a possible answer and then turned into a embedding but I haven't found much info on that yet.
Another idea I've had is to "overfit" a generative model like GPT on a dataset but pay more attention to how url and the like are tokenised
I want to live in an alternative timeline where RDF was never adopted by wikidata but instead created something that solved its specific problems in a human friendly manner. People always point to wikidata as a succesful semantic web project but fail to imagine how much more awesome it could have been. First off, wikidata has little use for ontologies outside of its own domain because all the types are modeled as dynamic second order concepts. Meaning, people organise knowledge using web pages and those webpages are used to structure other knowledge.
A simple Sparql query for wikidate would look something like this
select *
where {
?item wdt:Qe23oieke wd:Ert923Ee3451 .
service wikibase:label { bd:serviceParam wikibase:language "en" }
}
This incomprehensible nonsense is the result of two choices:
1) It had to be language independent because you know the world is bigger than just the anglosphere.
2) It had to be "machine readable", because then the computer can work together in harmony.
Putting the cart before the horse, or in this case the machine before the man.
Enterprise architecture is a form of quiet quitting. Just print out the Bash or Yaml files or whatever you used to configure your system and show it to your team: see guys it is just users, groups, files, processes, network interfaces, ports, ip addresses, dns records and the like.
This is what we in the comedy business call making fun of someone making fun. I call myself Krugger Dunning as an obvious play on the Dunnings Krugger effect because I try to approach every topic from a point of epistemic humility and in part that means being self-aware enough to realise I might just be a total idiot. The hard work has been done by me in reflecting on my shortcoming as a person and I try to show my weaknesses openly with all of you in the hope we can find within them our common humanity, while you just issue cheap insults.
No, you are waiting in line because you want your stupid coffee the jew to be executed does not want to be executed, so no equivalence class here baby.