MurphyA/hacker-news huggingface dataset:
by mmh0000 | 2026-01-08 20:37:05+00:00
See also:

https://www.fastmail.help/hc/en-us/articles/1500000279881-Se...

Android does not support CalDAV or CardDAV, which are used to sync calendars and contacts. However, a workaround is installing a CalDAV or CardDAV sync adapter.

We have tested and recommend DAVx⁵, which is approximately $5. Once you have added your account in DAVx⁵, you can set up calendars or contacts in the app of your choice, and the changes will sync with Fastmail.
by jorl17 | 2026-01-08 20:37:11+00:00
I used to think that, too, but I don't think it's the case.

Many people slowly open up to an LLM as if they were meeting someone. Sure, they might open up faster or share some morally questionable things earlier on, but there are some things that they hide even from the LLM (like one hides thoughts from oneself, only to then open up to a friend). To know that an LLM knows everything about you will certainly alienate many people, especially because who I am today is very different from who I was five years ago, or two weeks ago when I was mad and acted irrationally.

Google has loads of information, but it knows very little of how I actually think. Of what I feel. Of the memories I cherish. It may know what I should buy, or my interests in general. It may know where I live, my age, my friends, the kind of writing I had ten years ago and have now, and many many other things which are definitely interesting and useful, but don't really amount to knowing me. When people around me say "ChatGPT knows them", this is not what they are talking about at all. (And, in part, it's also because they are making some of it up, sure)

We know a lot about famous people, historical figures. We know their biographies, their struggles, their life story. But they would surely not get the feeling that we "know them" or that we "get them", because that's something they would have to forge together with us, by priming us the right way, or by providing us with their raw, unfiltered thoughts in a dialogue. To truly know someone is to forge a bond with them — to me, no one is known alone, we are all known to each other. I don't think google (or apple, or whomever) can do that without it being born out of a two-way street (user and LLM)[1]. Especially if we then take into account the aforementioned issue that we evolve, our beliefs change, how we feel about the past changes, and others.

[1] But — and I guess sort of contradicting myself — Google could certainly try to grab all my data and forge that conversation and connection. Prompt me with questions about things, and so on. Like a therapist who has suddenly come into possession of all our diaries and whom we slowly, but surely, open up to. Google could definitely intelligently go from the information to the feeling of connection.
by PaulDavisThe1st | 2026-01-08 20:37:21+00:00
The line I quoted from you concerned people who don't consider that renters should be involved in local decision making. I'm asking you what difference it makes what they consider, when they are not actually able to enact any barriers to participating in local decision making? I mean, sure, they make think that renters should stay out of the planning meetings, but if they do not stop them, what difference does it make what they think? Renters vote too ....
Show HN: Remotedays – Cross-border remote work compliance for EU companies
by alwinaugustin | 2026-01-08 20:37:48+00:00
Remotedays helps companies maintain compliance with EU cross-border remote work regulations. When employees work remotely across borders (France, Belgium, Germany, Luxembourg), exceeding specific thresholds triggers social security and tax liability shifts for both employees and employers.

Thresholds:

France/Belgium: 34 days/year
Germany: 183 days/year

Most companies track this manually or not at all, creating audit and penalty risk.

Key Features

For Employees:

One-click daily declarations via automated email prompts with real-time threshold tracking

For HR/Compliance:

Real-time compliance dashboard with alerts across the entire workforce

Complete audit trail for regulatory inspections

Links

Live: https://remotedays.app

Demo: https://demo.remotedays.app

Built with security and GDPR compliance as core requirements. Currently seeking feedback and open to customization or developing similar compliance solutions for specific organizational needs.

Questions and feedback welcome.
by drnick1 | 2026-01-08 20:38:51+00:00
> If you're talking about not being able to install third party apps, aurora store doesn't require an account and works fine on stock android. Most other basic functionality works fine too, eg. camera, calls, browsing, maps.

The Play Store is not the only issue with stock Android devices. Google dependencies run with high privileges and the device is constantly communicating with Google servers for one reason or another. You do not own a Google device for all intents an purposes. The main contribution of Graphene here is that it strips out the proprietary blobs and optionally provides an environment to run Google's libraries with unprivileged access.
by ori_b | 2026-01-08 20:38:53+00:00
> Ideally the alert would only happen if the comment seemed important but it would readily discard short or nonsensical input

No, ideally I would be able to predict and understand how my UI behaves, and train muscle memory.

If closing a tab would mean losing valuable data, the ideal UI would allow me to undo it, not try to guess if I cared.
by roadbuster | 2026-01-08 20:39:03+00:00
This is a well-written, well-researched piece, but some of the narratives are off the mark. For example:

> Phase 1 (Courtship, 2010-2014): TSMC needed Apple for legitimacy

TSMC was already the world's largest pure-play foundry long before Apple walked through the door, controlling more than 50% of market revenue. Although vertically-integrated microprocessor businesses had better-performing processes (Intel, AMD/IBM with PD-SOI), TSMC was head of the pack in the foundry world (competitors: UMC, Chartered, SMIC, etc).

> What if Apple chose Intel in 2014?

How would they have done that? Intel didn't even offer a foundry service at that time, and it would have taken years for Intel to adapt to a foundry model (one which publishes a "process design kit" for use by industry-standard EDA software to design and simulate circuits).
by bpt3 | 2026-01-08 20:39:17+00:00
Yes, I've been following current events for the last few decades, including the last year. We weren't "completely fucked" in 1990-1991, 2000-2001, 2008, or 2020, (or any of the other cataclysmic events that occurred long before my lifetime) so why would slowing down from the hottest labor market in a generation mean we are "completely fucked" now?

And what on earth does "we are in a race to steal and horde all the data before people catch on" even mean? Who is the "we" who are stealing and hoarding (which is the correct spelling FYI) compared to the "people" who would catch on that it's happening (and presumably care)? What data is being stolen, how, and from whom? Why is hoarding data a problem? Why would any of this matter in the first place if we're "completely fucked" anyway?

Could it be that people like you and the parent poster lack perspective (and potentially some self-awareness) and are prone to overreacting?
by CamperBob2 | 2026-01-08 20:39:26+00:00
Worse, I believe the rack-scale systems have to phone home to Nvidia to continue working. This may actually be mandatory by law now, in order to enforce export regs.

Between that and power consumption/heat generation, it is going to be pretty challenging to run these at home. Never say never, but it will require some hacking.

(Don't downvote, explain why I'm wrong so others can learn something.)
by 9rx | 2026-01-08 20:39:52+00:00
> Wouldn't you just hit undo?

Because:

1. Undo is usually treated as an application-level concern, meaning that once the application has exited there is no specific undo, as it is normally though of, function available. The 'desktop environment' integration necessary for this isn't commonly found.

2. Even if the application is still running, it only helps if the browser has implemented it. You mention Chrome has it, which is good, but Chrome is pretty lousy about just about everything else, so... Pick your poison, I guess.

3. This was already mentioned as the better user experience anyway, so it is not exactly clear what you are trying to add. Did you randomly stop reading in the middle?
by agosta | 2026-01-08 20:39:57+00:00
The business is this: Tailwind is free. Everyone uses it. People visit their docs and eventually buy some of the things they actually sell (like books, support, etc).

With LLMs, almost nobody visits their docs anymore just like folks barely visit Stackoverflow anymore (SOs traffic is down +80%). Fewer people see things they may want to buy from team Tailwind so they make less money so they implode. Plus LLMs just directly compete with their support offering.
by WoWSaaS | 2026-01-08 20:40:02+00:00
Hi HN,

I’m Afraz, an independent builder working on Vect AI.

One problem I kept running into with AI-generated content was that it often looked correct, polished, and on-brand — yet failed once it reached real users. This wasn’t a grammar or tone issue. It was a resonance problem.

Most tools help generate content, but they don’t answer a harder question upfront:
Will this actually land with the intended audience?

To solve this, I built the Resonance Engine inside Vect AI.

Instead of publishing content and measuring engagement later, the Resonance Engine evaluates drafts before they ship by simulating a defined target audience and surfacing clarity, relevance, persuasion, and emotional alignment gaps early.

At a high level:

Brand context and audience profile are defined once

Draft content is evaluated against that audience, not generic writing rules

Feedback highlights what feels unclear, generic, or misaligned

The goal is to expose weak assumptions before real users see the content

This has been most useful when:

Content sounds polished but lacks a strong hook

Messaging fits the brand but not the audience’s real concerns

AI-generated copy feels technically right but emotionally flat

I’m not trying to replace human judgment. The aim is to reduce blind spots earlier in the workflow, when decisions are still cheap.

For transparency, all public pages can be inspected here:
https://www.google.com/search?q=site:vect.pro

You can try the Resonance Engine directly here (deep link into the tool):
https://vect.pro/#/signup?continue=%2Fapp%2Ftools%3Ftool%3DR...

I’ve also documented the broader system and reasoning behind Vect AI here:
https://blog.vect.pro/vect-ai-bible-guide

Curious how others here think about testing resonance before publishing, audience simulation as a signal, and where AI feedback becomes noise instead of insight. Happy to answer questions or discuss edge cases.
by Rooster61 | 2026-01-08 20:40:37+00:00
I happened to take a look at your HN profile and realized you don't post much, which leads me to believe this is REALLY bothering you.

I can relate. My grandfather, who had been a math teacher and actually got me into computing way back in the beige toaster Macintosh days, religiously checked his email and practiced his Spanish on Rosetta Stone for decades. I had to update from Win 7 to 10 for the desktop I built for him, and that was a big struggle for him. That would probably be many times harder now considering the sad shape of Windows. It was heartbreaking watching him struggle with one of the few simple joys he had left towards the end of his life.

I'm very sorry you're having to deal with that and your anger is warranted.
by hnuser123456 | 2026-01-08 20:40:40+00:00
Non-MS manufacturers get offers from e.g. McAfee to pre-install a nagware version of their software for a kickback. I have an ASUS ROG laptop, and even if I run a full Windows Reset, I get a prompt to install McAfee during OOBE setup, right after being prompted to subscribe to office/copilot/365/onedrive/game pass/etc.
by heisgone | 2026-01-08 20:41:11+00:00
The biggest challenge is that it's a very slow process and most people don't have the patience for it. I have been practicing Vipassana for 14 years, including all day long body awareness (so, not only on cushion, but basically integrating Vipassana to normal activities like work) and it's took close to a decade to be satisfied by the results. That being said, permanent relaxation of muscle is really what you gain from it. There have been period with faster developpement but there are up liits to progress. Notably, the release of muscle release all sort of chemicals in the blood streams, which would make my body smell during intense practice and if we progress too fast, we get bizarre side effects. For instance, relaxation of some of my muscles meant that other muscles in my legs had to be "trained" when walking, or I would be in pain for a while, etc, etc.
by bitwize | 2026-01-08 20:41:29+00:00
At my current work much of our software stack is based on GOFAI techniques. Except no one calls them AI anymore, they call it a "rules engine". Rules engines, like LLMs, used to be sold standalone and promoted as miracle workers in and of themselves. We called them "expert systems" then; this term has largely faded from use.

This AI summer is really kind of a replay of the last AI summer. In a recent story about expert systems seen here on Hackernews, there was even a description of Gary Kildall from The Computer Chronicles expressing skepticism about AI that parallels modern-day AI skepticism. LLMs and CNNs will, as you describe, settle into certain applications where they'll be profoundly useful, become embedded in other software as techniques rather than an application in and of themselves... and then we won't call them AI. Winter is coming.
by fragmede | 2026-01-08 20:41:39+00:00
I mean, if you take out the guard rails, here's codex in 46 lines of bash:

#!/usr/bin/env bash
set -euo pipefail

# Fail fast if OPENAI_API_KEY is unset or empty
: "${OPENAI_API_KEY:?set OPENAI_API_KEY}"
MODEL="${MODEL:-gpt-5.2-chat-latest}"

extract_text_joined() {
# Collect all text fields from the Responses API output and join them
jq -r '[.output[]?.content[]? | select(has("text")) | .text] | join("")'
}

apply_writes() {
local plan="$1"
echo "$plan" | jq -c '.files[]' | while read -r f; do
local path content
path="$(echo "$f" | jq -r '.path')"
content="$(echo "$f" | jq -r '.content')"
mkdir -p "$(dirname "$path")"
printf "%s" "$content" > "$path"
echo "wrote $path"
done
}
while true; do
printf "> "
read -r USER_INPUT || exit 0
[[ -z "$USER_INPUT" ]] && continue
# File list relative to cwd
TREE="$(find . -type f -maxdepth 6 -print | sed 's|^\./||')"
USER_JSON="$(jq -n --arg task "$USER_INPUT" --arg tree "$TREE" \
'{task:$task, workspace_tree:$tree,
rules:[
"Return ONLY JSON matching the schema.",
"Write files wholesale: full final content for each file.",
"If no file changes are needed, return files:[]"
] }')"
RESP="$(
curl -s https://api.openai.com/v1/responses \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d "$(jq -n --arg model "$MODEL" --argjson user "$USER_JSON" '{model:$model,input:[{role:"system",content:"You output only JSON file-write plans."},{role:"user",content:$user}],text:{format:{type:"json_schema",name:"file_writes",schema:{type:"object",additionalProperties:false,properties:{files:{type:"array",items:{type:"object",additionalProperties:false,properties:{path:{type:"string"},content:{type:"string"}},required:["path","content"]}}},required:["files"]}}}')"
)"
PLAN="$(printf "%s" "$RESP" | extract_text_joined)"
apply_writes "$PLAN"
done
by haolez | 2026-01-08 20:41:55+00:00
It is a bet on two things:

1. the enshitification of smart devices would continue progressing and, at some point, our product would just be better and enough reason to migrate
2. a single, catastrophic privacy event would change the public perception on the importance of privacy and trusting your own devices, which would change the value perception of dumb appliances

Any one of those two would suffice to make the business viable, in my opinion.
by nyrikki | 2026-01-08 20:42:18+00:00
> In the documentation, IBM warns that setting auto-approve for commands constitutes a 'high risk' that can 'potentially execute harmful operations' - with the recommendation that users leverage whitelists and avoid wildcards

Users have been trained to do this, as shifting the burden to the user with no way to enforce bounds or even sensible defaults.

E.G. I can guarantee that people will whitelist bwrap, crun, docker, expecting to gain advantage from isolation, while the caller can override all of those protections with arguments.

The reality is that we have trained the public to allow local code execution on their devices to save a few cents on a hamburger, we can’t have it both ways.

Unless you are going to teach everyone that they need to make sure address family 40, openat2(), etc.. are unsafe, users have no way to win right now.

The use case has to either explicitly harden or shift blame.

With Opendesktop, OCI, systemd, and kernel all making locally optimal decisions, the reality is that ephemeral VMs is the only ‘safe’ way to run untrusted code today.

Sandboxes can be better but containers on a workstation (without a machine VM) are purely theatre.
by benrazdev | 2026-01-08 20:43:30+00:00
Technically, with generics, you could get a Result that is almost as good as Rust, but it is unidiomatic and awkward to write:

type Result[T, E any] struct {
Val T
Err E
IsErr bool
}

type Payload string

type ProgError struct {
Prog string
Code int
Reason string
}

func DoStuff(x int) Result[Payload, ProgError] {
if x > 8 {
return Result[Payload, ProgError]{Err: ProgError{Prog: "ls", code: 1, "no directory"}}
}
return Result[Payload, ProgError]{Val: "hello"}
}
by nyellin | 2026-01-08 20:45:13+00:00
There's a bit more to it!

For example, the agent in the post will demonstrate 'early stopping' where it finishes before the task is really done. You'd think you can solve this with reasoning models, but it doesn't actually work on SOTA models.

To fix 'early stopping' you need extra features in the agent harness. Claude Code does this with TODOs that are injected back into every prompt to remind the LLM what tasks remain open. (If you're curious somewhere in the public repo for HolmesGPT we have benchamrks with all the experiments we ran to solve this - from hypothesis tracking to other exotic approaches - but TODOs always performed best.)

Still, good article. Agents really are just tools in a loop. It's not rocket science.
by jacquesm | 2026-01-08 20:45:24+00:00
Definitely not just talking about Trump. The failure is institutional, the whole thing is just incredible watching from the outside in, you've never had a more 'clear and present danger' to the USA and to the world order and all of the institutions that are supposed to protect against that are failing one after the other.

This is how you go from stability to world wars. A couple of rich guys got together and decided they were going to redraw all of the maps and toss the rulebook overboard, and it is for the most part going their way. People are being executed and the useful idiots are falling over each other to defend it.

If you had told me in 1999 that this would happen by 2026 I would have happily declared you mad, but here we are.
by hazrmard | 2026-01-08 20:45:33+00:00
This reflects my experience. Yet, I feel that getting reliability out of LLM calls with a while-loop harness is elusive.

For example

- how can I reliably have a decision block to end the loop (or keep it running)?

- how can I reliably call tools with the right schema?

- how can I reliably summarize context / excise noise from the conversation?

Perhaps, as the models get better, they'll approach some threshold where my worries just go away. However, I can't quantify that threshold myself and that leaves a cloud of uncertainty hanging over any agentic loops I build.

Perhaps I should accept that it's a feature and not a bug? :)
by Certhas | 2026-01-08 20:46:45+00:00
I find it hard to parse the middle of your post. Are you saying Wigner's article, which is what all the "unreasonable effectiveness" titles reference, is silly?

If that is what you are saying I suggest that you actually go back and read it. Or at least the Wiki article:

https://en.wikipedia.org/wiki/The_Unreasonable_Effectiveness...

By means of contrast: I think it's clear that mathematics is, for example, not unreasonably effective in psychology. It's necessary and useful and effective at doing what it does, but not surprisingly so. Yet in the natural sciences it often has been. This is not a statement about mathematics but about the world.

(As Wittgenstein put it some decades earlier: "So too the fact that it can be described by Newtonian mechanics asserts nothing about the world; but this asserts something, namely, that it can be described in that particular way in which as a matter of fact it is described. The fact, too, that it can be described more simply by one system of mechanics than by another says something about the world.")
by jackfranklyn | 2026-01-08 20:46:51+00:00
The benchmark point is interesting but I think it undersells what the complexity buys you in practice. Yes, a minimal loop can score similarly on standardised tasks - but real development work has this annoying property of requiring you to hold context across many files, remember what you already tried, and recover gracefully when a path doesn't work out.

The TODO injection nyellin mentions is a good example. It's not sophisticated ML - it's bookkeeping. But without it, the agent will confidently declare victory three steps into a ten-step task. Same with subagents - they're not magic, they're just a way to keep working memory from getting polluted when you need to go investigate something.

The 200-line version captures the loop. The production version captures the paperwork around the loop. That paperwork is boring but turns out to be load-bearing.
by shigawire | 2026-01-08 20:48:04+00:00
>Personally, I think Iran is ignored more because Palestine is sucking all the air out of the room than anything else, especially with all the graphic videos/photos.

>Sudan on the other hand... there's really no excuse for ignoring that.

Palestine has the focus because America tax dollars most directly fuel the conflict and it is the most one-sided.

Iran is an internal conflict and Sudan is a civil war - neither of which are as directly funded by the US. Also neither has a perceived clear solution. In the case of Israel, the US should have significant leverage that it does not have in those other conflicts.
by staticshock | 2026-01-08 20:48:17+00:00
It is likewise unreasonable to look down on any kind of world model from the past. Remember that you, in 2026, are benefitting from millions of aggregate improvements to a world model that you've absorbed passively through participation in society, and not through original thought. You have a different vantage point on many things as a result of the shoulders of giants you get to stand on.
by jay_kyburz | 2026-01-08 20:48:51+00:00
We have a home pod, we use it a lot for simple things like timers when cooking or playing a particular kind of music. They are simple and dumb, but they have become part of our lives. It's just a hands free way to doing simple things we might do on the phone.

We are looking forward to being able to ask Siri to pipe some speech through to an AI
by heavyset_go | 2026-01-08 20:48:51+00:00
Yes, the idea before the whole shove LLMs into everything era was that small, dedicated models for different tasks would be integrated into both the OS and applications.

If you're using a recent phone with a camera, it's likely using ML models that may or may not be using AI accelerators/NPUs on the device itself. The small models are there, though.

Same thing with translation, subtitles, etc. All small local models doing specialized tasks well.