Lightnews — Scholar-powered news

Jed Brown @jedbrown.org · 16h

Thanks for explaining. That's an interesting workflow. In addition to submission tooling, it seems like it would take some reviewer training and and stretches the usual GitHub/GitLab review tooling, especially cross-cutting comments that might reorganize an ordinary PR.

Reposted by Jed Brown

Tressie McMillan Cottom @tressiemcphd.bsky.social · 20h

When they keep emailing you that the VIP tickets for a band you’ve never heard of are going fast

Robert Kelchen @robertkelchen.com · 21h

After getting zero firm commitments to this point from the first nine invitees, the Trump administration is extending its proposed compact to all colleges. Expect some red-state publics to say yes.

Trump Offers All Colleges Preferential Funding Plan Rejected by MIT

The Trump administration is inviting all US colleges to participate in a compact — initially rejected by the Massachusetts Institute of Technology — that would grant preferential federal funding in re...

www.bloomberg.com

6 110 510

Reposted by Jed Brown

This skeet will self destruct @pardoguerra.bsky.social · 17h

This is a sign of immense weakness. It’s like a mobster asking others if they’d be interested in a shakedown because their first targets didn’t cooperate.

Robert Kelchen @robertkelchen.com · 21h

After getting zero firm commitments to this point from the first nine invitees, the Trump administration is extending its proposed compact to all colleges. Expect some red-state publics to say yes.

Trump Offers All Colleges Preferential Funding Plan Rejected by MIT

The Trump administration is inviting all US colleges to participate in a compact — initially rejected by the Massachusetts Institute of Technology — that would grant preferential federal funding in re...

www.bloomberg.com

9 130 540

Jed Brown @jedbrown.org · 22h

The value of smaller-granularity commits will obviously depend on the project, its goals, and the people working on it. When bisecting after squash-merge, you land on the whole PR-as-commit instead of a separate refactor-with-no-functional-change-intended or minimal functional-change-with-test.

1

Jed Brown @jedbrown.org · 22h

Thanks for the example. I see here [40/n] involves 26 commits that were squash-merged, and PRs like [23.5/n] were inserted. This is an impressive sequence of coordinated PRs (and spr seems cool), but I think the squash-merge/coarser-granularity critique applies. github.com/oxidecompute...

[40/n] blueprint planner logic + sled agent code to honor mupdate overrides by sunshowers · Pull Request #8456 · oxidecomputer/omicron

Implement the blueprint planner logic for mupdate overrides, as well as Sled Agent logic for honoring them. These two changes are clubbed into one atomic commit because system correctness depends o...

github.com

2

Jed Brown @jedbrown.org · 23h

What does that look like? Does CI run on each of the 41 commits or only on the head? Is it squash-merged at the end or do all 41 commits stay intact (presumably after a no-conflict rebase)? Maybe this is answered in the spr docs, but the "Comprehensive documentation" is 404.

1

Jed Brown @jedbrown.org · 23h

With rebase-and-ff-merge, the intermediate commits never get tested and can be broken even if the final state works, which is a mess if you are bisecting. Squash-merge is reliable, but coarser grained.

It is frustrating that GitHub goes hard on update culture/sync with upstream without intent.

2 1 1

Jed Brown @jedbrown.org · 1d

Why are people eager to merge from upstream? (A lot of ink has been spilled on this, e.g., Linus in 2008: yarchive.net/comp/linux/g... .) The issue I see is that linearizing via rebase/fast-forward is unreliable and lacks parallelism, but squashing is terrible for bisection and commit messages.

1

Jed Brown @jedbrown.org · 1d

I read this as mainly an argument against merging from upstream rather than against all merges. Merge-based workflows expose parallelism and facilitate atomicity. Rebases internalize the updating cost (modulo reliability with respect to intermediate commits) while merging from upstream externalizes.

1 1

Jed Brown @jedbrown.org · 2d

Everything is moving so fast, we need to accept papers generated by LLMs based on "reviews" generated by LLMs. But don't worry, it's all Rigorous and Responsible.

Deeply unserious.
aaai.org/aaai-launche...

Cutting-Edge Methods with Rigorous Safeguards

The pilot employs state-of-the-art methodologies in the responsible deployment of LLM technology, including:

Multi-step reasoning processes at inference time
Web search capabilities as tools in the reasoning chain
Rigorous checks for proper data source attribution
Comprehensive monitoring and evaluation of LLM contributions

2 7

Jed Brown @jedbrown.org · 2d

Also, there is no company advertising all-human bad scholarly practice as the future of scholarship and jobs. Educators can do a better job at teaching critical scholarship skills, but at no point has manual bad scholarship been taught or promoted. It was human nature, cutting corners, without pride

1

Jed Brown @jedbrown.org · 2d

It does mimic (somewhat common) bad scholarly practice to an extent, however, a person just reading an abstract is still epistemically better. People actually interpret meaning and can notice adjacent claims that may or may not be consistent with their understanding (prompting more thought/reading).

1 1

Jed Brown @jedbrown.org · 2d

We also have to recognize the context of "inevitability" discourse and outrageous claims. The METR study, being a statement against interest and pretty good *relative* to other citable studies, is useful to start a more sober conversation and reconsider our null hypotheses.

2 3

Jed Brown @jedbrown.org · 2d

Some of the studies are expensive, federal funding agencies have a lot of FOMO, and academic incentives are not great for that kind of work. Meanwhile, industry can shut off their own such studies at the drop of a hat (or stop publishing them).

2 2

Jed Brown @jedbrown.org · 2d

It's a societal vulnerability that significant amounts of "AI" critique is coming from industry and industry-friendly sources (Apple on illusion of reasoning, Microsoft on medical benchmark brittleness, Meta on delimiter brittleness, METR, etc.). They're notable as statements against interest.

2 8

Reposted by Jed Brown

Olivia Guest · Ολίβια Γκεστ @olivia.science · 4d

important on LLMs for academics:

1️⃣ LLMs are usefully seen as lossy content-addressable systems

2️⃣ we can't automatically detect plagiarism

3️⃣ LLMs automate plagiarism & paper mills

4️⃣ we must protect literature from pollution

5️⃣ LLM use is a CoI

6️⃣ prompts do not cause output in authorial sense

5 Ghostwriter in the Machine
A unique selling point of these systems is conversing and writing in a human-like way. This is imminently understandable, although wrong-headed, when one realises these are systems that
essentially function as lossy2
content-addressable memory: when
input is given, the output generated by the model is text that
stochastically matches the input text. The reason text at the output looks novel is because by design the AI product performs
an automated version of what is known as mosaic or patchwork
plagiarism (Baždarić, 2013) — due to the nature of input masking and next token prediction, the output essentially uses similar words in similar orders to what it has been exposed to. This
makes the automated flagging of plagiarism unlikely, which is
also true when students or colleagues perform this type of copypaste and then thesaurus trick, and true when so-called AI plagiarism detectors falsely claim to detect AI-produced text (Edwards, 2023a). This aspect of LLM-based AI products can be
seen as an automation of plagiarism and especially of the research paper mill (Guest, 2025; Guest, Suarez, et al., 2025; van
Rooij, 2022): the “churn[ing] out [of] fake or poor-quality journal papers” (Sanderson, 2024; Committee on Publication Ethics,

Either way, even if
the courts decide in the favour of companies, we should not allow
these companies with vested interests to write our papers (Fisher
et al., 2025), or to filter what we include in our papers. Because
it is not the case that we only operate based on legal precedents,
but also on our own ethical values and scientific integrity codes
(ALLEA, 2023; KNAW et al., 2018), and we have a direct duty to
protect, as with previous crises and in general, the literature from
pollution. In other words, the same issues as in previous sections
play out here, where essentially now every paper produced using
chatbot output must declare a conflict of interest, since the output text can be biased in subtle or direct ways by the company
who owns the bot (see Table 2).
Seen in the right light — AI products understood as contentaddressable systems — we see that framing the user, the academic
in this case, as the creator of the bot’s output is misplaced. The
input does not cause the output in an authorial sense, much like
input to a library search engine does not cause relevant articles
and books to be written (Guest, 2025). The respective authors
wrote those, not the search query!

1 67 170

Reposted by Jed Brown

Sherrilyn Ifill @sifill.bsky.social · 3d

We have the timidity of countless corporate and university GCs to thank for the fact DEI is treated as though it were illegal.

Anna Gifty @itsafronomics.bsky.social · 3d

lol gentle reminder that DEI is not illegal. Supporting marginalized groups is not illegal. Anyone reneging on support is making a CHOICE to do so.

25 490 1.7K

Reposted by Jed Brown

Iris van Rooij 💭 @irisvanrooij.bsky.social · 3d

“Deloitte “misused AI and used it very inappropriately: misquoted a judge, used references that are non-existent,” Pocock told Australian Broadcasting Corp. “I mean, the kinds of things that a first-year university student would be in deep trouble for.””

👀

fortune.com/2025/10/07/d...

Deloitte was caught using AI in $290,000 report to help the Australian government crack down on welfare after a researcher flagged hallucinations | Fortune

The updates “in no way impact” the report’s findings and recommendations, the Big Four firm said.

fortune.com

6 60 140

Reposted by Jed Brown

michael veale @michae.lv · 3d

Does your university have a contract with Grammarly? Write to the decision-maker asking if they think the university should be paying for a tool that is fast integrating features that can only be used for academic misconduct and cognitive offloading and request they drop the contract.

Jed Brown @jedbrown.org · Aug 18

It is not "attribution and sourcing" to generate post-hoc citations that have not been read and did not inform the student's writing. Those should be regarded as fraudulent: artifacts testifying to human actions and thought that did not occur.
www.theverge.com/news/760508/...

For help with attribution and sourcing, Grammarly is releasing a citation finder agent that automatically generates correctly formatted citations backing up claims in a piece of writing, and an expert review agent that provides personalized, topic-specific feedback.

Screenshot from Grammarly's demo of inserting a post-hoc citation.
https://www.grammarly.com/ai-agents/citation-finder

3 78 160

Jed Brown @jedbrown.org · 3d

To be clear, the original crime is lying about the diligence and cognitive process that are claimed to underly the report. A fake citation is secondary, and most significant as circumstantial evidence of the first.

There is now an industry around obfuscating the evidence.

Jed Brown @jedbrown.org · Aug 18

It is not "attribution and sourcing" to generate post-hoc citations that have not been read and did not inform the student's writing. Those should be regarded as fraudulent: artifacts testifying to human actions and thought that did not occur.
www.theverge.com/news/760508/...

5 13

Jed Brown @jedbrown.org · 3d

Imagine being able to get caught doing fraud and simply clean up the evidence, avoid reputational harm, keep most of the money, and continue to influence government in a way that most honest actors could only dream of.

“The updates made in no way impact or affect the substantive content, findings and recommendations in the report,” Deloitte wrote.

1 7 16

Jed Brown @jedbrown.org · 4d

One can interpret this brittleness as (a) an embarrassing property to be concealed by training/prompting, or (b) failure of the model to validate (benchmark score doesn't assess what is implied), and either restrict the application space or go back to the drawing board. Science demands the latter.

Figure 1 One can manipulate rankings to put any model in the lead by varying the single delimiter character. On the left, we
show the delimiter used to separate examples in common evals with few-shot examples such as mmlu. On the right,
we show model rankings based on mmlu performance as the example delimiter varies with each column corresponding
to a different ranking.

2

Reposted by Jed Brown

Dr Abeba Birhane @abeba.bsky.social · 4d

we wrote this over 5 yrs ago

dl.acm.org/doi/abs/10.1...

1 17 65

Jed Brown @jedbrown.org · 5d

He hasn't been subtle about it.
blacksky.community/profile/did:...

Christopher Mathias @letsgomathias.bsky.social · 5d

Jack collaborated with neo-Nazi twins to make a documentary. He was a fan of white supremacist Richard Spencer. He has tweeted 1488, the alphanumeric code for Heil Hitler. He wrote an unreadable anti-antifa book. Last year he wrote a book abt the left called “Unhumans.” That he’s now speaking here…

Prem Thakker ツ @premthakker.bsky.social · 5d

From Donald Trump's Roundtable on Antifa just now —
"Antifa has been around in various iterations for almost 100 years in some instances, going back to the Weimar Republic in Germany."
— special guest Jack Posobiec

5

Jed Brown @jedbrown.org · 5d

Just like the segregationists who filled community swimming pools with concrete.

Asked what percentage of children she imagines should be in public schools going forward, Justice, who is now with The Heritage Foundation’s political advocacy arm, told ProPublica: “I hope zero. I hope to get to zero.”

1 1