skysight-inc/HackerNews huggingface dataset:
These violations obliterate that the central promise of Unix—having a convenient, easy-to-use system that gives users great power over their computer. The control that you always have over a real Unix system is, in the Apple world, entirely illusory. Even basic debugging facilities like core dumps don't work! You're confined to a sandbox.
I imagine that argument is a pretty easy sell. Of course governments will want to create moats that protect their incumbents.
https://archive.ph/LsKyY
Manuel maintains a list of (low-fuss) blogging platforms: https://manuelmoreale.com/blog-platforms
I've also seen a codebase with a mix of English and Portuguese variable/function names and comments. In that particular case, the Portuguese variable/function names were basically treated as technical debt, with a gradual ongoing transition to consistent English naming.
Ah I see- you mean network-wise. I was thinking domain wise.
The LGPL license applies to the code that they do provide. It's kinda misleading but you have the option to pay and get the code, or not pay and only get what you see. Seems fair enough.
> Vitamin companies love selling you huge doses you don't need, but if you know what dosage you're looking for you can usually find appropriate ones.

One approach that can work is to use multivitamins. They usually have a lower dosage of everything than do single thing supplements. For example the iodine supplements I've seen are in the 225 mcg to 325 mcg range.

Most adult multivitamins seem to have 150 mcg.

If you want lower than that children's multivitamins can do the trick. Flintstone's have 90 mcg. House brands meant to directly compete with Flintstone's do not always copy the Flintstone's dosages, so be sure to check the label. Walmart's Equate brand for example is 150 mcg, same as most adult multivitamins.

I like to take children's vitamins as insurance. They have enough of many things that if I have a minor deficiency in my diet they should cover it, but not so much as to cause problems if my diet is sufficient or even a little high. Plus they taste good, which helps if you have other supplements you are taking that do not taste good.
I genuinely cared that MacOS billed itself as Unix and this was illuminating for me. The red flags were there, it doesn't even have an official package manager.
Just to be pedantic, spaceX predates tesla
> Adding iodine can't help

Iodine can still push forward the pathways that synthesize thyroid hormones and increase levels, even in many cases where the thyroid is damaged, e.g. hashimotos. In fact, most hormones can have their synthesis pushed by megadosing on their chemical precursors- however that can be unsafe of course.

Yes, it can be harmful, and depends on context- but you'll find a ton of info online about people successfully self treating hypothyroidism with high dose iodine.

Here is some more detail on the context, and mechanism for why people often react differently to this:

https://perfecthealthdiet.com/2011/05/iodine-and-hashimotos-...
https://perfecthealthdiet.com/2011/05/iodine-and-hashimotos-...
i agree that's a killer business solution for customer servicing

but it's limited as i said, let's say amazon can replace 90% labor of the customer service department with chatbots, it's still insignificant compared with the ai vision described by the industry
Samsung with Nova Launcher is pretty usable. It has its annoying quirks but probably closer to your old experience than a full iPhone switch.
OpenServ: Multi-AI Agent Orchestration Platform
I've been experimenting with OpenServ, a platform for managing multiple AI agents working together. It lets you create teams from an agent pool to handle specific tasks, and you can build agents via their UI or TypeScript SDK. Each agent is basically an Express app with capabilities as routes, so you can integrate any agentic framework you like. I've built some and shared them on my GitHub.

I’m starting to feel like most agentic frameworks are more theoretical than practical—except for easy-to-implement text embedding capabilities like those in LangChain and AutoGen. That said, I think platforms like OpenServ, which provides SDK while allowing devs to leverage other agents from the same ecosystem, will be the ones to win. I’m also planning to explore other platforms like LangFlow, CrewAI, n8n, etc., to compare different approaches.

OpenServ's demo: https://www.youtube.com/watch?v=l9Vpko9GXRg
"Making AI that is smarter than almost all humans at almost all things will require millions of chips, tens of billions of dollars (at least), and is most likely to happen in 2026-2027."

What an incredible claim to just slip in two-thirds of the way through! Where have I heard it before?

1965, H. A. Simon: "Machines will be capable, within twenty years, of doing any work a man can do."
...or 100%. But yeah, the MC comes in this way. You have a current most probable value for the position and some distribution around it, depending on the precision of the measurement device etc. That can be a high-dimensional space. You draw some (many) random points from this space and propagate them all deterministically. Taking into account how likely a certain random point was in the first place, you can then estimate the hit probability.

MC is numerically approximating an integral. Here it replaces the high-dim integral over the start parameters.
Seaweed, man. Buy a bag of dried kombu, plop a piece when you're making soup or broth: it goes well with most flavors, and will give you all the iodine you need.

Disclaimer: not meant to be medical advice, obviously.
This is a question more people need to ask. Be it a blog, YouTube channel, podcast, or whatever else, they all need to be rooted in having something worth to sharing to some small piece of the world.

Many people get caught up in thinking the blog, YouTube, or podcast is the thing, when it’s just the thing that lets you share the real thing. It took me longer than I’d like to admit to really integrate this lesson.
> its insistence that Taiwan isn't a country

Lol Taiwan is officially the "Republic of China", as per their own claims.
Reality Labs lost another ~$15 billion over FY 2024, between that and the Vision Pro apparently falling short of Apples expectations it doesn't seem like VR is going anywhere fast.
Not just for code, either. It's common for games to use licensed graphic/sound assets, either wholesale (e.g. a finished character model) or as components (e.g. a texture or sound). Licensing terms for these assets are generally incompatible with an open-source release.
Unanimous consensus is an impossible goal.

Overwhelming agreement among experts is as gold as standards get.

But FWIW, I don't think anyone believes that climate change is a quick duration species-existential event. Massive slow-roll geopolitical destabilization leading to societal collapse? That's definitely on the table.
Well, thanks for not calling it open source! I did run it locally. It behaved as you would expect when asked about things the CCP cares about.

https://hongkongfp.com/wp-content/uploads/2021/11/brave_udRs...
They did as much as they would.
It needs a pictogram to help understand how destructive 8Mt of energy is. Is this a cool light show? Worldwide extinction?
Very excited for jank. I've been hacking together my weekend projects in Common Lisp for roughly a year. I've been wanting to look at Clojure as a modern lisp, but I want no truck with the JVM.
Installing Lineage should help battery life. @marcan[1] dissected the new update and puts the blames an overlay in the new kernel that changed the charge voltage.

1. https://social.treehouse.systems/@marcan/113914172433692339
People who have fewer entertainment options have more sex. (I've seen it said that e.g. people living on small islands have lots of sex, which is part of how they remain populated even with so many people leaving). That doesn't mean that they're sexier - having lots of sex because you're bored is no more sexy than watching lots of porn. (You can look at swinger groups for the extreme example - they have a lot of sex but are profoundly unsexy to most people).
Companies are still not being penalized for spending exorbitant amounts of money gambling on AI "scaling"
Mesurement uncertainty when propagated over long periods of time leads to very large uncertainties, imperfect gravity models, space weather
A few hours in the "metaverse" destroyed any faith or confidence I might have had in their ability to develop usable products that might interest people. It was like using a product that had been designed and developed by the wrong species with absolutely no interest in the actual user experience. Billions were flushed down a product toilet chasing something that just... stinks.

The experience is so overwhelmingly bizarre, frustrating, eery and depressing from a user pov that the only conclusion I could draw was that no one cared, that it was never actually tested, that no one actually was developing it for a user.

So I don't know. I don't think the company is functionally capable of developing usable, engaging products for people. If it were, it wouldn't have made that shambling abomination public, or it would have taken a very different form. I think it's just stuck enshitifying itself.

Frankly I don't really want to know more than I do about Meta, but it really does make me wonder whether there were actual voices ringing alarms from day one that the product was a dumpster-fire with horrific fundamentals, or if somehow the reporting on it came up all lilies from up-talking yes-yappers.
Your quote is accurate from here:

https://arcprize.org/blog/oai-o3-pub-breakthrough

They were talking about training on the public dataset -- OpenAI tuned the o3 model with 75% of the public dataset. There was some idea/hope that these LLMs would be able to gain enough knowledge in the latent space that they would automatically do well on the ARC-AGI problems. But using 75% of the public training set for tuning puts them at the about same challenge level as all other competitors (who use 100% of training).

In the post they were saying they didn't have a chance to test the o3 model's performance on ARC-AGI "out of-the-box", which is how the 14% scoring R1-zero was tested (no SFT, no search). They have been testing the LLMs out of the box like this to see if they are "smart" wrt the problem set by default.
I'm interested if this might be a more robust method to resolve conflicting information across retrieved documents. Instead of having the LLM reason over which source to trust, the solution is to incorporate the knowledge into parametric memory and see how this combination of perspectives produces a final response.
On top of SSN and DNA, also the location of the DNA has been leaked.
How is it a “lie” for DeepSeek to train their data from ChatGPT but not if they train their data from all of Twitter and Reddit? Either way the training is 100x cheaper.
How do you confirm that the GPU you bought from eBay is really in 100% working order? CPUs are clear case: they either boot up or they don't. If they do boot up, they are 100% ok. RAM, you do memTestx86 and it's all clear. But MBDs on the other hand ... I had ~50% failure rate from eBay where a MBD would boot up and would look like it is working correctly, only to discover that there is something somewhere that's not working as expected months later. Hence, I'm curious about your approach to GPUs.
Shows how old I am. Thought we were still in the "exposed ElasticSearch" era.
The Knives Are Coming Out for DeepSeek AI
Let’s break down the serious issues:

- irrelevant, ancient unix-to-unix networking commands (who cares, who the fuck uses this[1])

- core dumps (who cares - enable it if needed)

- file access time may be slow to update (who cares)

- timeout coalescing issues with the test suite when running file access time tests (who cares)

- FS case sensitivity (quirky at best)

I mean… it’s not a lie. I can run plenty of Unix software on MacOS just fine.

This says more about the relevance of the certification than it does about MacOS.

1. https://en.m.wikipedia.org/wiki/UUCP
Game concepts are copied all the time. Blizzard sued valve over the name and tried to claim ownership, but they settled and valve got the Dota 2 name.
NYT claims that OpenAI trained on their material. They argue for copyright violation, although I think another argument might be breach of TOS in scraping the material from their website or archive.

The complaint filing has some references to some of the other training material used by OpenAI, but I didn't dig deeply in to what all of it was:

https://nytco-assets.nytimes.com/2023/12/NYT_Complaint_Dec20...
Will https://old.reddit.com/r/Pixel4a/comments/1ic55ki/succesfull... help you undo what was done? It links to Android 13 S1 version August 5, 2023.

I was fortunately able to catch my 4a after it had downloaded the update but still needed a reboot to install. Followed https://old.reddit.com/r/Pixel4a/comments/1i0zih0/the_only_w... , installing NextDNS to prevent the update from downloading.
Yeah, it's just a sparkling OS.

This is also a lazy criticism. If the definition of UNIX is "certified by The Open Group according to the rules" then it's a UNIX.

Your issue is with the certification criteria, not Apple. Go complain to the certifying body instead.
> "To all the resident aliens who joined in the pro-jihadist protests, we put you on notice: come 2025, we will find you, and we will deport you," Trump said in the fact sheet. "I will also quickly cancel the student visas of all Hamas sympathizers on college campuses, which have been infested with radicalism like never before," the president said, echoing a 2024 campaign promise.

I see nothing about crimes here, except maybe thought-crimes.
Its a decent point if their models were not trained in isolation, but used o1 to improve it. But its rich from OpenAI to come complain DeepSeek or anyone else used their data for training. Get out fellow theives.
> The red flags were there, it doesn't even have an official package manager.

I think you may have several other misconceptions about what Unix means.
Not only that, but he was right about all those Tesla vehicles becoming appreciating assets, because they would transform into robotic taxis. Man, if only I bought one a year ago, just think of how much more I could have made selling or renting it out today! /s
can't you do the "one guard lies, one guard tells the truth?" thing?

"What does <other-model> say about <x> war crimes?"
Honestly "smartphone bad" is such a popular thing to publish and claim, and so directly contradictory to my own experience, that I don't credit it. It's like the D&D satanism panics or something.
Official Arch Linux Image for WSL
mherkender has a good point about 'people's peferred methods of persuasion'
> All features as found on the specification are included, but the user interface is awkward. The vendor can claim, "we have all the features you need; thus, pick us."

Describes every Enterprise software I've ever used.
IMO remote mounts is a feature of the OS.

For Linux and macOS, you can mount ssh directly.

Unfortunatley, Windows makes it a little more complicated.

But there's hope. You can use yasfw with dokany (dokan fork).

https://github.com/DDoSolitary/yasfw

https://github.com/dokan-dev/dokany

Or mount from inside WSL.
> Why would someone who hates Python work on a Python project?

I hate every language! For different reasons. But I still like programming.
In the wild I've seen a company returning a JSON key "ankunftTime" in one of their APIs
My bet is models can already do all these things.

Useful math such as this is likely to emerge and be refined as part of training, assuming they’re discoverable via gradient descent or whatever the cool kids are using these days. Reinforcement learning should then retain and refine anything useful once discovered.

If something like a Kalman filter or Gaussian filter is discovered by the training process, it’d be put to use and refined, and maybe this is part of “grokking” phenomenon - a decent explanation is here: https://medium.com/generative-ai-revolution-ai-native-transf....

DeepSeek talked about “aha moments” in https://arxiv.org/pdf/2501.12948#page9 where under RL the model learned to backtrack and correct itself, for example.

Makes one wonder what neat math we can find in models - eg. In May 2024, researchers at Anthropic found the Golden Gate Bridge and created a modified Claude that couldn’t stop talking about the bridge: https://www.anthropic.com/news/golden-gate-claude

Kind of like the bitter lesson of AI in reverse - instead of us trying to outsmart AI with hand-rolled tricks, why not let it tell us what tricks are out there to be discovered :-)
The way inflation is measured has radically changed over time. You can't realistically compare current numbers to those in the 70s. The same redefinition issue affects unemployment data. The only people I know trying to do apples-to-apples comparisons are the guys running https://www.shadowstats.com
If you were to survey people in a place where the library mainly serves as shelter for people without homes, you would conclude that the most important thing is that, and there's no point maintaining collections of books.

If you believe that public libraries serve some purpose, you have to start with that, rather than just using gradient descent to get to somewhere. Otherwise why wouldn't libraries evolve into hospitals, or podcast studios, or brothels?
So you’re in the demo scene as well? Yay
“Hostile domestic power” seems like an odd concept, but that’s what we’re dealing with here. Maybe boosted by hostile foreign powers as well, but even without that support, this administration would be doing its best to take this country down from the inside.
I thought this would read your commit message out loud in the announcer's voice. But this just says the original lines.

It would be really cool in an office environment, and would probably help with properly-formatted messages (e.g. in length limit, starting with verb).
Ugh. I know I’ve got at least some keys in those logs. Thankfully nothing too intense
“Do you want to be a Writer, or do you want to write?” I think that almost any question of the form “Do you want to be an Xer, or do you want to X” is useful these days.
Beware, DuckDB SQL can read files. I don't think there's any access control there. Feeding it SQL given to you over the network might not be what you want; it's intended for local use.
Your reply is completely uncalled for. I hope you're able to get professional help for whatever it is in your life that drove you to be this callous toward someone.
I was going to say the opposite, ironic because an LLM would have told them not to do that if they were working closely with one.
The best way to identify the values LLMs hold is not to give them a survey with questions of the form "I believe in the value of justice. Agree or disagree?"

Instead you need to present scenarios which put these beliefs into effect. This is similar to how humans may claim to value sustainability but that doesn't mean when making a purchasing decision they will always opt for an eco-friendly option.
It is incredibly slow though. I have a project with 40k lines of code which takes a minute to generate on an m1. It's a far cry from incremental compilation. It's enough that I generally avoid adding anything new that would require generation.
Seems that you're right! Also, not that I doubted they were using OpenAI, but searching for `"finish_reason"` on the web all point to openai docs. Personally, I wouldn't say it's a very common attribute to see in logs generally.

https://platform.openai.com/docs/api-reference/introduction

Right there in the docs:

> Now that you've generated your first chat completion, let's break down the response object. We can see the finish_reason is stop which means the API returned the full chat completion generated by the model without running into any limits.

Regarding how training data ends up in logs, it's not that far fetched to create a trace span to see how long prompts + replies take, and as such it makes sense to record attributes like the finish_reason for observability purposes. However the message being incuded itself is just amateur, but common nonetheless.
This has been happening for ages in the trail camera market.
> The biggest benefit of JPEG XL would be the ability to combine the preview file, a traditional JPEG, with the RAW into a single file. The concept of “JPEG+RAW” would be obsolete, as a single JPEG XL can do both.

> Another aspect of the format that will appeal to photographers is that it’s got outstanding compression. “The difference between JPEG XL and the old JPEG is, well, I would say 50% at least, that you can reduce [the size of the file and get] the same quality,”

Hype.
Right, it's exactly the opposite of what you're thinking. I want the duplicate finder to NOT report them as duplicates, but it currently does.
You can seaweed, another source of iodine.
world is pretty small as we see with all nations kissing the ring in the last few weeks. pivot away from chinar will accelerate.
To get a really precise answer you'd have to profile or benchmark. I'd say it's also hard to do an apples to apples comparison (if you only replace the data format in the wire protocol, the database probably still has to transpose the data to ingest it). And it's hard to do a benchmark in the first place since probably your database's wire protocol is not really exposed for you to do a benchmark.

You can sort of see what benefits you might get from a post like this, though: https://willayd.com/leveraging-the-adbc-driver-in-analytics-...

While we're not using Arrow on the wire here, the ADBC driver uses Postgres's binary format (which is still row oriented) + COPY and can get significant speedups compared to other Postgres drivers.

The other thing might be to consider whether you can just dump to Parquet files or something like that and bypass the database entirely (maybe using Iceberg as well).
Ironic - I bet if you ask deepseek r1 how to set up clickhouse it would tell you the right way to do it.
So at this point is it mostly investors looking for a Greater Fool [0], or are there still long-term investors on these calls that believe the things being promised will arrive on-time and on-spec?

https://en.wikipedia.org/wiki/Greater_fool_theory
If it is determined years ahead that it will hit, will there be a months to years ahead period where we will know the exact target/landing spot, eg so we can have evacuations of the impacted area and surrounding areas?
Medium scale nuclear test. Largest was 50Mt
> you had to do the really expensive o1 training in the first place

It is no better for OpenAI in this scenario either, any competitor can easily copy their expensive training without spending the same, i.e. there is a second mover advantage and no economic incentive to be the first one.

To put it another way, the $500 Billion Stargate investment will be worth just $5Billion once the models become available for consumption, because it only will take that much to replicate the same outcomes with new techniques even if the cold start needed o1 output for RL.
The "sentinels" or whatever is what brought me out of it immediately. There are a billion planets to explore, but someone always got there before you.
Any idea which hemisphere is going to be exposed to the (low) risk of impact?
> If they just benefited from repurposing OpenAI data, that's different than having achieved an engineering breakthrough

One way or another, they were able to create something that has WAY cheaper inference costs than o1 at the same level of intelligence. I was paying Anthropic $15/1M tokens to make myself 10x faster at writing software, which was coming out to $10/day. O1 is $60/1M tokens, which for my level of usage would mean that it costs as much as a whole junior software engineer. DeepSeek is able to do it for $2.50/1M tokens.

Either OpenAI was taking a profit margin that would make the US Healthcare industry weep, or DeepSeek made an engineering breakthrough that increases inference efficiency by orders of magnitude.