dis

AI slop turned Facebook into an anaerobic lagoon of botshit, the laziest, grossest engagement bait, much of it from rise-and-grind spammers who consume get rich quick "courses" and churn out a torrent of "shrimp Jesus" and fake chainsaw sculptures: 404media.co/email/1cdf7620… 16/

@johnlashlee @zlflynn Batch processing data where it is stored is probably a more cost effective approach in most cases but some problem spaces are too complex to pre-compute and are best solved at runtime. Also building runtime services with plumber is pretty good fun :)

A fun R package: plumber. Can quickly spin up an API to make analyses, etc, runnable via GET's and POST's. You just add these special comments like in doxygen and then it calls R functions at those end points. Very fun and easy to use.

@predict_addict Financial gradient descent? arxiv.org/abs/1704.04289….

Why do failed companies like bayesianism? Asking for a friend. #bayesianism

@Swayam_Nath_ I suspect you're just not getting good stuff. Check which side of the cold war the intellectual tradition is on.

All these Dry and Obvious social science paper will suck the life out of me. Gurll at this point my only home is in literary studies, philosophy and crazy history works (microhistory, Subaltern Studies and so on).

@martin_eve In the UK corruption generally seems to take place in public, in accordance with the law, without much recognition and in the near absence of the widespread moral scandal it so richly deserves.

They should get some consultants in to do an inquiry into this

@pressfuturist I don't think work as personal as a thesis can ever be perfected or even completed to satisfaction so it can never be finished. The only thing you can do is finalise it to be abandoned so that the great relief of working on something else can happen. Good luck!

Swimming against a very strong current today on this thesis, knowing that it has to be submitted tomorrow; that I haven't left myself enough time to complete it as I want to; and trying very hard not to let this knowledge drain my strength and stop me from swimming to the finish.

A small, portable vector database powered by SQLite for on-device RAG? 🤯 sqlite-vec is a new vector search SQLite extension written entirely in C with no dependencies, MIT/Apache-2.0 dual licensed.   sqlite-vec queries: - 1 million 128-dimensional vectors in just 17ms - 500,000 with 960-dimensional vectors in 41ms sqlite-vec supports: 💾 Matryoshka embedding slicing 💡 Binary quantization reduces storage by 32x with minimal accuracy loss 🤏🏻 L2, cosine and Hamming distance calculations 🧮 Retrieval against Python List and NP Arrays 🛠️ SDKs for Python, Javascript, Go, Rust, Wasm and more 🧠 local direct embedding with “sqlite-lembed” for gguf models and @ggerganov Llama.CPP ☁️ remote embedding with “sqlite-rembed” for @OpenAI compatible APIs

@xgabegottliebx In the aggrandised socio-historical-linguistic sense one would have to make it impossible to write in some important way as everyone had written before. Maybe you have written a particularly decisive paper?

@xgabegottliebx One could almost think about deconstruction as a transcendental argument in reverse.

Embarrassing, but I don't think I've ever deconstructed anything. I've deduced and posited some shit, even counterposited, synthesized, and described some things. Interpreted and intuited a few things. Deduced and genetically constructioed stuff, too. Never deconstructed, though.

@xgabegottliebx If we deflate (and risk psychologising) the term something like deconstruction must occur whenever we change our mind.

@xgabegottliebx Instead of apprehending the general necessary preconditions of a fact; a general necessity is revealed as an impossible assumption in the confrontation of the fact.

The paper we have been waiting for essentially shows that #timeseries #llms do not work in forecasting. Back in 2022, paper “Are Transformers Effective for Time Series Forecasting?“ challenged the appearing narrative that transformers are useful for forecasting. By removing transformer elements the authors showed the performance went up ⬆️ And now people did the same with time series LLMs. The papers demonstrated: - removing the LLM component or replacing it with a basic attention layer does not degrade the forecasting results—in most cases the results even improved! - in fact removing even removing the language model entirely, yields comparable or better performance! - these simpler methods after removal of LLM component reduce training and inference time by up to three orders of magnitude while maintaining comparable performance! - the sequence modeling capabilities of LLMs do not transfer to time series. By shuffling input time series the authors find no appreciable change in performance. What this says is that LLMs can’t deal with critical features of time series, the time order is key and if LLMs performance doesn’t change when shuffling data it basically means it doesn’t model time series. These finding are as damming to time series LLMs as the “Are Transformers Effective for Time Series Forecasting?” was for transformers. #timeseries #forecasting

Don't worry, all politics is human geography and all human geography is history and all history is phenomenology.

@matthewclifford @HenryEOliver This is some ignorant shit. GP in your pocket? Please. Medical advice is high risk under the EU AI Act and SHOULD BE because guessing about medical advice will kill people and that's what AI means - guessing. I would not take advice on what over regulation means from this man.

Nice piece by the excellent @HenryEOliver on def/acc and AI👇

@soychotic RStudio is the asylum that raised me

Stand back advertisers - someone just said something sensible about #AI on Twitter!

This interesting thread swerves into eugenics at the end - the explanatory variable here is going to be culture not genes.

@kareem_carr You can fit an LM via OLS or gradient descent. The resulting model weights and summary statistics can be equivalent but the closed solution is not ML and the latter is. Despite all the hype and bullshit there is a shift in methodology there; though the future mightn't notice.

“we saved billions of dollars by using ai to find patterns in our data” finding patterns in structured data is just regular statistics. you did statistics.