Firefox is also the only browser that vets uBlock's code on every update to make sure the developer hasn't inserted spyware or malware into the extension.
They don't do it for every extension, but they do so for a wide selection of popular options.
> Recommended extensions differ from other extensions that are regularly reviewed by Firefox staff in that they are curated extensions that meet the highest standards of security, functionality and user experience. After receiving Recommended status, safety standards are maintained through automated checks, monitoring, and periodic technical reviews
I suspect that a lot about what we call being very intelligent is ultimately out-remembering people around us. I think of all the times in my software career when I did something that others considered very high performance, it either came down to either having more energy than others at tackling a problem they thought was more trouble than it was worth, or just bringing back random knowledge from previous jobs or self study, and being able to apply it to the problem at hand.
I don't think I've had a truly original idea in my life. Combine A + B, when it's rare for people to know A and B at the same time. So from that perspective, what LLMs are doing is basically the same thing. Sometimes I am faster than the LLM because my context might be better organized, but it typically needs just a hint from me to steer itself correctly. It claims something is a memory leak, but smelling a rat, I suggest it to double check the garbage collection statistics too, at which point it's clear it's no leak, but a tuning error, at which point the LLM is better at tuning than me, because it has more energy than I do.
Maybe there's true brilliance out there, when something doesn't come out of combining data and building hypothesis until you get really lucky. My experience is not comprehensive. But I look around me, and it sure seems I've not been lucky enough to see it. Even the shiniest people I've worked with, which most of the audience here would recognize, have never shown me that they can go past this.
It's worth realizing that, before computerized central offices, telephone wiretapping required running physical wires. Back when Rudi Giuliani was prosecuting organized time, not only did physical wires have to be run, the cops were billed for them as expensive private lines. His task force was spending about a million dollars a year with New York Telephone on wiretapping.
In one case, law enforcement didn't pay their bill, resulting in the person being wiretapped having the wiretap connection show up on their bill, blowing the case.
That resulted in the Communications Assistance to Law Enforcement Act, which mandated that central offices offer remote wiretapping. Capacity up to 1% of lines is required.
Back in the electromechanical era, the only call data that could be collected was outgoing dial pulses, using a "pen register".[1] (The one shown in Wikipedia is mine. It's a beautiful piece of antique brass telegraph technology. It records dial pulses as dashes, and has to be wound up like a clock, with a big brass key.) The Supreme Court decision allowing "pen registers" without a warrant refers to these "extremely limited" devices. That definition has been stretched and stretched by law enforcement into all non-voice data collected by telcos.
tdlr: This is a Novo Nordisk-funded study focusing on predictive biomarkers rather than real-world dementia cases. Novo Nordisk's actual dedicated clinical trials for Alzheimer's completely failed to show that semaglutide stops cognitive decline.
"A predictive biomarker is like a "check engine" light on your dashboard. It warns you that there is a risk of a future problem. In this study, the researchers only checked if the drug turned off the "check engine" light (by measuring blood proteins), rather than testing if the car was actually driving properly (by testing the patients' actual memory and brain function)."
Always do FIRST analysis on studies. Or have AI do it for you. I used Gemini to dig into this:
"Novo Nordisk funded this study, and several of the researchers are employees or minor shareholders. While corporate funding doesn't automatically mean the data is fabricated, it does mean the company is highly motivated to find and publish data that makes their blockbuster drug (semaglutide, marketed as Wegovy, Ozempic, and Rybelsus) look like a preventative treatment for a wider range of conditions, expanding its market and driving up profits."
"Funding: The study was funded by Novo Nordisk A/S.
Investigation: Researchers conducted a post hoc analysis using data from the randomized, placebo-controlled SELECT trial. They applied the Dementia SomaSignal Test (dSST)—a 25-protein risk score—to non-fasted serum samples collected at baseline and at week 104 to estimate 5-year and 20-year all-cause dementia risk in patients receiving semaglutide (2.4 mg) versus a placebo.
Results: Semaglutide significantly attenuated the progression of the dementia risk signature. Compared to the placebo group, the 5-year predicted risk increased 2.5-fold less (a 26.0% lower predicted event rate) and the 20-year risk increased 1.67-fold less (an 8.8% lower rate). Semaglutide also lowered the odds of patients moving into a higher dementia risk category by 36%.
Subjects: The analysis included 2,970 older adults aged 65 and older (mean age of ~69.7 years) who had overweight or obesity and cardiovascular disease, but no history of diabetes. The cohort consisted of 814 women (27.4%) and 2,156 men (72.6%).
Time: The study evaluated data over a 104-week (2-year) follow-up period. The analysis was published on August 8, 2026."
And then map the weakness to each respective letter if you want to dig deeper.
The word is "management", not "leadership". This comes across as a LinkedIn post filled with vague notions and weak writing.
The conclusion also completely contradicts a previous point, which is that managing an LLM is not like managing a human. So the skills are, in contradiction to that LLM-ism of a conclusion, new. The author isn't using their people management skills, they're using new LLM-management skills. They think the two are similar, but didn't bother breaking down how they're the same vs where they contrast. It's just a lazy observation expanded out to a short essay that says nothing interesting.
People have told me I was smart since I was a kid, but I can't remember for shit. I had a thought when I was fairly young that the only reason I was (maybe, sometimes) outperforming others intellectually is that I was habitually compensating for my poor memory by working things out on the fly, while others could rely more on rote memorization. Anyway, takes all kinds I guess!
In the last couple of days I wanted to try out the new definitive DeepSeek v4 releases. I gave it the repository of a semi-abandoned video compression codec and I told it to perform the usual benchmark -> profile -> verify -> research -> improve loop. I specifically chose this codec because the authors include a verifier for the bitstream to make sure you don't break stuff if you want to try your own implementation. I gave the agents access to the compiler's profiler and also Intel's VTune, which has fantastic output. In a couple of hours the LLM generated SSE and AVX implementations of the compression and decompression algorithms that almost doubled performance with a single core. Then I asked it to create a CUDA implementation using NVIDIA's NSIGHT profiler as a guide and it also started doing some good work.
Personally, I believe that LLMs should be treated like an advanced version of Prolog or linear programming: you give the constraints, you have a way of verifying correctness, and you give it a clear goal. If the LLM can verify itself and course-correct you can basically leave it on autopilot
What's funny is that extensions were supposed to be a way to let you do the things the browser didn't want you to do. Guess that was a bit too much freedom for Google to accept, so they had to make a store with a gate, and destroy the APIs so that they're useless. Then they had to make up some reasons to justify that and ram it through the pipeline despite everyone's objections, and the frog got boiled.
Now we're back to needing an actual extension system that does what extensions were supposed to do in the first place.
RISC-V is... fine. It satisfies my two requirements for an ISA as a hobby CPU designer, which are:
1. Supported in mainline LLVM and GCC.
2. I can implement it without lawyers sending me a love letter.
Everything else, I can fix in post. There are enough good ideas spread across the extensions that I can assemble a reasonably put-together, curated embedded ISA with competitive performance and code density that admits a simple implementation.
I think Dmitry's points are largely on-target, though I have filed my usual statutory complaint that every rant that includes a bitfield diagram for the RISC-V J format should accompany it with a similar diagram for the Arm T32 BL encoding.
Credit where it's due. Qwen 3.8 27B is only the second local model after Gemma 4 that managed to correctly reason through one of my private benchmarks. It took 5x as many tokens to do it and 12m30s with MTP enabled, but it did do it.
Gemma 4 reasoned through it more implicitly, while Qwen 3.8 reasoned more explicitly. Laguna and Muse Glimmer failed hard on it, though they're useful for other tasks.
The VRAM usage seems way less efficient than Gemma 4 or Glimmer though, with 32K of context taking 2.5GB of VRAM. With those, even with MTP or a DFlash model loaded, you could still fit 256k-768k of context. With Qwen 3.8 27B I can't even fit 128k if I quantize V to Q4_0. Maybe with some trial and error I can find some settings that perform well enough with a larger context window that it's still useful for longer tasks.
Lots more testing to do, though I was getting some decent results out of Muse Glimmer which was more than twice as fast and supported huge context windows, managing to solve some bugs that Gemma 4 struggled with. I can't even begin to throw that task at Qwen, because just the prompt alone would use the entire context window and then it would reason for probably that same amount.
If you've got a 32GB card, it should be a decent model even if it really is memory hungry.
EDIT: Tried a few kv cache quantization settings, but it failed with those. I designed this benchmark to be pretty brutal in the face of KLD and any reasoning quality loss, so it's not too surprising. Gemma 4's QAT held up pretty well, at least and could consistently complete it.
I often forget how browsing the web looks for most people. Can't understand why they put up with it, or do they just think that it's part and parcel of the internet to have every page look like a slot machine from hell?
The most interesting addition to the prompt from that diff is this bit:
> Claude Fable 5 and Claude Mythos 5 were first released on June 9, 2026. On June 12, 2026, Anthropic suspended access to both models to comply with U.S. Department of Commerce export controls; the Department lifted those controls on June 30, 2026, and Anthropic restored access on July 1, 2026 (Anthropic's statement: [https://www.anthropic.com/news/fable-mythos-access](https://www.anthropic.com/news/fable-mythos-access)). These events are after Claude's training-data cutoff, so Claude knows about them only from this notice. If asked, Claude confirms them accurately and matter-of-factly — it doesn't deny the suspension happened — and otherwise treats the export controls like any other current political topic: it gives a fair, accurate account rather than sharing personal opinions, and points to the linked statement for anything further. Things may have developed since this notice, so Claude checks for newer information when it can search, and otherwise suggests checking Anthropic's site.
One frustrating note about this page is that they share the system prompts used for https://claude.ai and the Claude mobile apps regular chat, but they omit the tool definitions. Those are much more interesting if you want to understand what Claude can actually do for you. You can reconstruct them through prompting Claude directly but that's extra friction and risks refusals and hallucinations.
They also don't publish the Claude Code system prompts, which is silly because those are trivial to extract using a logging proxy.
It's also "out-brute forcing them." It just never gets tired. If a mathematician picks a research direction and spends a whole week on it and it doesn't pan out, they will likely be annoyed, need a break for a while, etc. This thing just does not ever get tired or discouraged or care; it's just onto the next thing until something ends up working.
<quote>
Have you ever heard of the Joined Together States? Or bosom peril? Kidney disappointment? Fake neural organizations? Lactose bigotry? These nonsensical, and sometimes amusing, word sequences are among thousands of “tortured phrases” that sleuths have found littered throughout reputable scientific journals.
They typically result from using paraphrasing tools to evade plagiarism-detection software when stealing someone else’s text. The phrases above are real examples of bungled synonyms for the United States, breast cancer, kidney failure, artificial neural networks, and lactose intolerance, respectively.
</quote>
The problem with this analogy (actually one of many) is that most people can make do with a cabinet that is literally identical to everyone else's. IKEA is great for that.
If you want software that is literally identical to what someone else is using then you don't need AI. You need a license to that software! That is just the traditional software model.
AI gives software that is bespoke with hundreds of decisions made, hidden from you, in the background. If it's a throwaway script, that's fine (and I don't mean to undersell this - this is a huge application). If you want a larger program that is going to form part of your business process then it will need at least some level of supervision from an actual expert.
Recently I came across the /handoff skill, which I've been using a lot. I find it much better than /compact.
Basically:
- /handoff file creates a short document with the important context from your current session and maybe next steps as checklist.
- You can then start a fresh session with /continue file
- You can also hand the work from Claude to ChatGPT, or the other way around. Very useful at time of session limits.
- Plus your handoff files becomes a useful piece of project memory that you can reference later.
I find this much more useful than /compact or /clear because the context is saved in something portable instead of being tied to one session and i've seen better results doing this every 20 messages or so than running long sessions.
A gem Opus 5 gifted to me today:
"A devastating pair of findings, and the first is beautiful in a way worth naming: the anti-vacuity floor is what blinds the gate to a vacuous case."
Offtopic. I have a concern that this forum is removing stories that have negative connotation on AI.
Few days back, I posted an article[1] that was about how AI threatens natural resources for billions. This was from United Nations and it was flagged. I did not think much about it until I saw two other stories [2] & [3] today that were doing fairly good on front page but they suddenly disappeared. They are not even on 2nd or 3rd page. I have seen this happening at other times as well but did not document it. Just thought you all should know about this.
I was going to create Tell HN thread but I thought the same would happen with it too. I am pretty sure this thread is not going anywhere so I'm posting my concern here.
My Eng lead has no coding experience, 25 years of management experience, yet has driven 3 separate projects into technical bankruptcy to date.
He just accepts anything that Claude says as truth. He vibecoded over 60,000 lines of code in 3 weeks, but couldn’t get it to do what he want and made a project overrun for 3 extra months. When the pissed off stakeholders called a meeting to ask what was going on he didn’t show up and sent his junior engineer to answer questions and take the blame. Now thats leadership.
> In the real world, it does feel likely that we’re going to hit some sort of a ceiling on the number of useful bugs, and probably we’ll hit it soon.
This doesn't resonate with me. I see companies adding more sloppily written features with AI. I see more bugs in the software I use, not less. While it's plausible that software is getting both buggier and more secure, I suspect those two move in the same direction not opposite.
My guess is that we're getting better at finding _existing_ security issues with AI (and thus fixing those issues), but simultaneously adding more insecure surface areas _at a faster rate_.
> Garg acknowledges he’s “hard-nosed” and the famous Zoom layoffs severely damaged the company’s reputation — a mistake he knows will continue to haunt him.
I really hope Garg is here reading this. It’s not just a mistake that will continue to haunt him, it’s all he’s ever going to be. It’s how he was introduced in this headline. It’s how he’ll be referred to when he starts his next venture. If newspapers publish his obituary someday, it’ll be in the first few sentences explaining why anyone knows his name.
They don't do it for every extension, but they do so for a wide selection of popular options.
> Recommended extensions differ from other extensions that are regularly reviewed by Firefox staff in that they are curated extensions that meet the highest standards of security, functionality and user experience. After receiving Recommended status, safety standards are maintained through automated checks, monitoring, and periodic technical reviews
https://support.mozilla.org/en-US/kb/recommended-extensions-...