Author Archives: pappp

Article note: They trained it on shitty florid academic writing, so it vomits out shitty florid academic writing. That style is already basically a caricature of itself, propagated by mimicry, so the same "This is probably horseshit" indicators that worked for human authors work for LLM spew.

Enlarge / If your right hand starts typing "delve," you may, in fact, be an LLM. (credit: Getty Images)

Thus far, even AI companies have had trouble coming up with tools that can reliably detect when a piece of writing was generated using a large language model. Now, a group of researchers has established a novel method for estimating LLM usage across a large set of scientific writing by measuring which "excess words" started showing up much more frequently during the LLM era (i.e., 2023 and 2024). The results "suggest that at least 10% of 2024 abstracts were processed with LLMs," according to the researchers.

In a pre-print paper posted earlier this month, four researchers from Germany's University of Tubingen and Northwestern University said they were inspired by studies that measured the impact of the COVID-19 pandemic by looking at excess deaths compared to the recent past. By taking a similar look at "excess word usage" after LLM writing tools became widely available in late 2022, the researchers found that "the appearance of LLMs led to an abrupt increase in the frequency of certain style words" that was "unprecedented in both quality and quantity."

Delving in

To measure these vocabulary changes, the researchers analyzed 14 million paper abstracts published on PubMed between 2010 and 2024, tracking the relative frequency of each word as it appeared across each year. They then compared the expected frequency of those words (based on the pre-2023 trendline) to the actual frequency of those words in abstracts from 2023 and 2024, when LLMs were in widespread use.

Article note: Heh, the patches that added the built in block-on-repeated-attempt features into the logging path were also quietly patching a (very complicated to trigger) RCE related to signal handlers and logging because a few glibc functions hit by a signal in the timeout path aren't async safe.

Article note: Apple rejects anything that contains the string "itms-services" so including handler libraries that have it in the list of possible services trigger rejection. They don't document this fact so someone had to reverse engineer it. The corporate controlled coercive content consumption jails that computers have turned into are so fucking disappointing, especially from the company that used to talk about "Wings for the Mind."

Article note: Maximum greasy.

Article note: I've seen recent evidence that public chatterbots can beat the _median_ student at "pick all that apply" questions in computer engineering, in the sense that bots can swing a C and the students did their best to absorb nothing from the class. The real deal is you _can not_ treat summative assessments that aren't regularly revised and taken in a controlled environment as reliable; the stakes and culture are such that a large fraction of students will "optimize" (cheat) to the best of their ability. Which sucks for instructors who have to deal with editing and scheduling and grading old-school exams, and students with test anxiety and such, but less than getting out-competed by a swarm of know-nothing bros whose test taking strategy only requires "Ctrl" "c" and "v."

Article note: Heh, it's a cute little form-factor, and the actual computer is a neat exercise in minimalism. Its "ALU" is a 2 input NOR gate that it bit-serial recirculates. About 20 ICs none of which are designs from after the 80s.

Article note: It isn't really matrix-math-free, it's just matrices of ternaries. That said, I'm a fan of small-range systems for sloppy approximators, (-1,0,1) ternaries map well to LLMs, and not using huge, expensive, power-hungry monstrosities for dumb bullshit is a win for everyone.

Enlarge (credit: Getty Images)

Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations that are currently accelerated by GPU chips. The findings, detailed in a recent preprint paper from researchers at the University of California Santa Cruz, UC Davis, LuxiTech, and Soochow University, could have deep implications for the environmental impact and operational costs of AI systems.

Matrix multiplication (often abbreviated to "MatMul") is at the center of most neural network computational tasks today, and GPUs are particularly good at executing the math quickly because they can perform large numbers of multiplication operations in parallel. That ability momentarily made Nvidia the most valuable company in the world last week; the company currently holds an estimated 98 percent market share for data center GPUs, which are commonly used to power AI systems like ChatGPT and Google Gemini.

In the new paper, titled "Scalable MatMul-free Language Modeling," the researchers describe creating a custom 2.7 billion parameter model without using MatMul that features similar performance to conventional large language models (LLMs). They also demonstrate running a 1.3 billion parameter model at 23.8 tokens per second on a GPU that was accelerated by a custom-programmed FPGA chip that uses about 13 watts of power (not counting the GPU's power draw). The implication is that a more efficient FPGA "paves the way for the development of more efficient and hardware-friendly architectures," they write.

Article note: It's an absurd $15,000 OAM module with 192GB of RAM on it... but it's also benching out around twice as fast as an Nvidia H100 (and drastically better in some circumstances), which is a $25,000 OAM module. ...if your software will run on AMD's toolchain(s), it's clearly a wildly preferable part, but the question is how many workloads is that reliably true of after all the pooch screwings they've made on the software front.

Article note: Yesssss. The AI Hype is dangerously out of hand, and this is signs of correction.