skysight-inc/HackerNews huggingface dataset:
Costco was selling MB Air M2 8 GB for $699! Incredible deal.

I’ve been using the exact model for about a year and I rarely find limitations for my typical office type work. The only time I’ve managed to thermally throttle it has been with some super suboptimal Excel Macros.
Wow, that's horrible. And you might even have to stay at a 4 star instead of a 5 star resort in Bali when you take a vacation during your severance, job market is tough.

Even worse, you might have to miss one contribution to your FATfire investment account to deal with the extra risk. Compounded, that missed contribution might mean you'll have to retire at 46 instead of 45.

How dare these companies treat these people this way. They took the massive risk of working for an already-successful company at $250K/yr with a $200K stock package, and now fat cat Drew Houston dares to leave them with just an abnormally large severance after they are no longer needed.
I don't want to interact with people who lie. I don't want to interact with people who say lying is a good thing. Apple is saying lying is a good thing ("genius") in some of these ads.
There is a hosted offering https://wazuh.com/cloud

I run an in-house deployment using the Docker conf they supply. It requires a couple of hours per month and mainly a lot of disparate skills.

The real thing that takes time is the installation and configuration of the rules and agents. That’s something that you have to do for any SIEM really, irrespective of open source / paid: you have to understand your nominal feed and that takes time.
Our use case is atypical, based on what others seem to require. While we serve multiple requests in parallel, our workloads are not 'chat'.
Chimpanzee Grooming Human Face and Legs [video]
2024 Dora Report
Great news. The pro is kinda of heavy for my liking so the Air is the way to go
> I have to admit though that the automatic is way faster than me at changing gears, which helps keeping a constant acceleration and avoid head bobbing.

That's because a DSG gearbox has two clutches. It is basically a traditional gearbox with one clutch connected to the odd gears and one to the even gears. The system selects the next gear according to the revs of the engine and does all the physical shifting in advance. The actual gear change is then only disengaging one clutch while engaging the other one. You can overlap this so the engine continously delivers torque to the wheels. Thus, no head bobbing.
Same for me. The only reason to replace it, is that my M1 pro’s SSD or battery will go bad or if I accidentally drop the machine and something breaks.
> enter a sort of maintenance mode

There exists such a mode: it's called dividend distribution. But currently DBX and many other tech companies aren't paying any dividends to stock holders. So if it's not growing and not paying dividends, what is the company doing?
I bought a framework back in 2020 or so and really wish I just waited a little longer and spent a few hundred bucks more on the M1.

It's fine, but the issue is linux sleep/hibernate - battery drain. To use the laptop after a few days, I have to plug it in and wait for it to charge a little bit because the battery dies. I have to shut it down (not just close the screen) before flying or my backpack becomes a heater and the laptop dies. To use a macbook that's been closed for months I just open it and it works. I'll pay double for that experience. If I want a computer that needs to be plugged in to work I have a desktop for that already. The battery life is not good either.

Maybe it's better now if I take the time to research what to upgrade, but I don't have the time to tinker with hardware/linux config like I did a few years ago.
Thank you for this article, many of us American's see it too!
Even monolithic training runs take sources more disparate than any human has the capacity to consume.

Also, given the lack of imagination everyone has with naming places, I had to check:

https://en.wikipedia.org/wiki/Moscow_(disambiguation)
A lot of my work can be easily done with a Celeron - it's editing source, compiling very little, running tests on Python code, running small Docker containers and so on. Could it be faster? Of course! Do I need it to be faster? Not really.

I am due to update my Mac mini because my current one can't run Sonoma, but, apart from that, it's a lovely little box with more than enough power for me.
There seems to be an upgrade path for cutting steel with a slower spindle and extra steel plates for added stiffness. There are other DIY CNCs that are designed for steel and use concrete for stiffness which are probably more appropriate - but they do cost more so it really depends on your needs.

What I think will really change things are the 3-in-1 fiber laser sources that can be used for welding, cutting, and cleaning. Building a CNC gantry that can use the cutter means large pieces can be cut from stock plate, assembled like a 3D puzzle, and very quickly welded together. While much more expensive than a Milo it is be a totally different category for capability. Plus a handheld laser welding, cutting, cleaning are very useful tools in their own right. I think laser welding is soaking up most of the supply at the moment but I also think it's just a matter of time before people figure out how to hook up the cutter to a CNC gantry like many already do with hand held plasma torches.
Neon Authorize: Simplifying row-level security for Postgres
It seems you need the M4 Max with the 40-core GPU to go over 36GB.

The M4 Pro with 14‑core CPU & 20‑core GPU can do 48GB.

If you're looking for ~>36-48GB memory, here's the options:

$2,800 = 48GB, Apple M4 Pro chip with 14‑core CPU, 20‑core GPU

$3,200 = 36GB, Apple M4 Max chip with 14‑core CPU, 32‑core GPU

$3,600 = 48GB, Apple M4 Max chip with 16‑core CPU, 40‑core GPU

So the M4 Pro could get you a lot of memory, but less GPU cores. Not sure how much those GPU cores factor in to performance, I only really hear complaints about the memory limits... Something to consider if looking to buy in this range of memory.

Of course, a lot of people here probably consider it not a big deal to throw an extra 3 grand on hardware, but I'm a hobbyist in academia when it comes to AI, I don't big 6-figure salaries :-)
Desktops are two channels of 64 bits, or with DDR5 now four (sub)channels of 32 bits; either way, mainstream desktop platforms have had a total bus width of 128 bits for decades. 8x64 bit channels is only available from server platforms. (Some high-end GPUs have used 512-bit bus widths, and Apple's Max level of processors, but those are with memory types where the individual channels are typically 16 bits.)
> There is some model of truthfulness encoded in our heads, and we don't draw all of that from our direct experience. For instance, I have never been to Connecticut or Moscow, but I still think that it is false that the capital of Connecticut is Moscow.

Isn't this just conveniently glossing over the fact that you weren't taught that. It's not a "model of truthfulness", you were taught facts about geography and you learned them.
Agree. If people want to delude themselves that async is useful, that's fine. But don't inflict it on the rest of us by viral propagation throughout the dependency ecosystem.
Agent based is not really a big burden, most monitoring systems work like this (Prometheus). Companys use Ansible etc.
Some libraries use callbacks for e.g. host certificate verification so the consuming application can manage its own whitelists.
Laptops in general are just better than they used to be, with modern CPUs and NVMe disks. I feel exactly the same seeing new mobile AMD chips too, I'm pretty sure I'll be happy with my Ryzen 7040-based laptop for at least a few years.

Apple's M1 came at a really interesting point. Intel was still dominating the laptop game for Windows laptops, but generational improvements felt pretty lame. A whole lot of money for mediocre performance gains, high heat output and not very impressive battery. The laptop ecosystem changed rapidly as not only the Apple M1 arrived, but also AMD started to gain real prominence in the laptop market after hitting pretty big in the desktop and data center CPU market. (Addendum: and FWIW, Intel has also gotten a fair bit better at mobile too in the meantime. Their recent mobile chipsets have shown good efficiency improvements.)

If Qualcomm's Windows on ARM efforts live past the ARM lawsuit, I imagine a couple generations from now they could also have a fairly compelling product. In my eyes, there has never been a better time to buy a laptop.

(Obligatory: I do have an M2 laptop in my possession from work. The hardware is very nice, it beats the battery life on my AMD laptop even if the AMD laptop chews through some compute a bit faster. That said, I love the AMD laptop because it runs Linux really well. I've tried Asahi on an M1 Mac Mini, it is very cool but not something I'd consider daily driving soon.)
Sadly OSSEC is largely abandoned. Back in the day it was very good for a lightweight and effective security system for those that didn't want to install full-blown antivirus on everything. I wish they would donate the project to Linux Foundation or CNCF, but it seems destined for decline.
It's actually true: Propylene glycol is harmless.

Although some use Ethylene glycol, don't drink that.
> Would any top grad nowadays go to Jane Street over OpenAI or Anthropic?

You’re measuring which part of the economy pays math majors best. If I had to trace the centre of gravity of my top former colleagues, it was banks and hedge funds (never Jane); Uber; some leakage to crypto, they never recovered; now AI.
A glass of the concentrate is where it starts to get worrisome.

The LD50 is somewhere in the 5000 mg/kg range; that's around 250 grams for a 50kg person. For concentrated glyphosate, you're in that ballpark with around a liter of concentrate, depending on the exact dilution.
https://www.youtube.com/watch?v=u48vYSLvKNQ

same vibe: https://www.youtube.com/watch?v=hiKuxfcSrEU
Try embedded rust: Get an RP2040 board and fool around with that. It'll make a lot more sense to you if the parts you don't understand are encapsulation types like RC, Box, and Arc because those aren't really used in embedded rust!

Lifetimes are still used but not nearly as much.
An Overlooked Path to a Financial Fresh Start
Guess that’s why most of their comparisons are with the older Intel Macs.
I am replacing a Dell laptop because the case is cracking, not because it's too slow (it isn't lightning fast, of course, but it sure is fast enough for casual use).
I read all that marketing stuff and my brain just sees APU. I guess at some level, that’s just marketing stuff too, but it’s not a new idea.
I figured but erred on the side of "maybe not a joke" :D
FWIW I’ve never heard of these tools until today
Why would Youtube, which makes money off ads, allow a web browser that blocks ads to access Youtube when they could just refuse to serve their user agent?
It enhanced my conversation as when both people do not know something you are looking at and or discussing you can now find the answer quickly via glasses on your face.

We all use Google to find knowledge/answers but most are not pulling out our phones during conversations cause that's rude. Yet it's not rude to get the answer from your glasses you are wearing on your face and still present in the conversation your having as well people will think wow that's cool (per my experience).
The first piece of code is perfect in Java:

int t = (val_11b << (32 - 11)) >> (32 - 11).
I have an m3 ultra. I don’t think I need to upgrade. I also find it amusing they’re comparing the m4 to the m1 and i7 processors.
ill give that a shot, thanks! im pretty sure it's just a dead battery though - after i charge it for 5-10 min it shows the percentage at like 3-5% which is enough for several more hours and then i just plug it in overnight
Even if that were true (and I'd challenge that assumption[0]), there's no dichotomy here.

Software quality, for the most part, is a cost center, and as such will always be minimal bearable.

As the civil engineering saying goes, any fool can make a bridge that stands, it takes an engineer to build a bridge that barely stands.

And anyway, all of those concerns are orthogonal to the tooling used, in this case LLMs.

[0] things we now take for granted, such as automated testing, safer languages, ci/cd, etc; makes for far better software than when we used to roll our own crypto in C.
That some people losing their jobs have it better than others has nothing to do with the hypocrisy of a CEO claiming to take full responsibility while suffering zero consequences.
- AR is very promising for both work and play, but is worthless shit if you have to hold a device to use it. Instantly 100x better if you've got hypothetical near-future non-terrible AR glasses on most of the day.

- Half of what people use the Web for is looking up trivia that would have been too high-cost to look up before, to bother with (most of the other half is posting on social media about it). Glasses further lower the cost of looking up many categories of trivia, making even more trivial pieces of knowledge cheap enough to look up. On a revealed-preference basis, this seems to be something people really like and find irritating when denied—nobody used to feel an itch when they couldn't find an answer to some fleeting trivial question that entered their mind. Once exposed to the Web, and even more so when smartphones were introduced and the Web became something you carried everywhere, they do, and it'll be the same for answering questions about stuff they're looking at, once used to glasses.

- The use case of capturing otherwise-missed (getting out the phone is too slow) fleeting once-ever moments is going to be very compelling for people.
This is the machine I'm waiting for. Hopefully early 2025
> Yeah, I feel like Apple has done the opposite of planned obsolescence with the M chips.

They always have. If you want an objective measure of planned obsolescence, look at the resale value. Apple products hold their resale value better than pretty much every competitor because they stay useful for far longer.
Yes, other M.2 SSDs have comparable performance when swapping, and other operating systems compress memory, too — though I believe not as much as MacOS.

Although machines with Apple Silicon swap flawlessly, I worry about degrading the SSD, which is non-replaceable. So ultimately I pay for more RAM and not need swapping at all.
Yep. That's roughly 20% per generation improvement which ain't half-bad these days, but the really huge cliff was going from Intel to the M1 generation.

M1 series machines are going to be fine for years to come.
Yup, I'm a developer who still primarily works on a 2018 Intel Mac. Apple's messaging felt very targeted towards me. Looking forward to getting the M4 Max as soon as possible!
Some details on the Stripe solution at https://stripe.com/blog/how-we-built-it-smart-retries
Apple equipment always last a long time and retain value on the second-hand market.
Type A people who become CEOs don't dream of sitting around on yachts.

Some might be driven by money, but at a certain level it probably switches to a sense of responsibility, but also, it's intoxicating to be at the top where you don't really have to work in the same way, but get to direct what happens. People enjoy power. People enjoy the secrets of what happens at the top. People enjoy the recognition (within their peer group). etc...
The parent of their comment seems to be confused by how the EPA and IARC are not related, so I don't think they do have a point. Prior to my comment, the comment you responded to originally posed the question of whether the EPA could ban red meat due to it being on IARCs list, before being stealth edited.
In general for local LLMs, the more memory the better. You will be able to fit larger models in RAM. The faster CPU will give you more tokens/second, but if you are just chatting with a human in the loop, most recent M series macs will be able to generate tokens faster than you can read them.
wiki has the answer, ballpark is around twice as long, and they're using this new design for an upcoming probe
Strongly disagree. At the level of io_uring (syscalls/syscall orchestration), it is expected that available tools are prone to mis-use, and that libraries/higher layers will provide abstractions around them to mitigate that risk.

This isn't like the Rust-vs-C argument, where the claim is that you should prefer the option of two equivalently-capable solutions in a space that doesn't allow mis-use.

This is more like assembly language, or the fact that memory inside kernel rings is flat and vulnerable: those are low-level tools to facilitate low-level goals with a high risk of mis-use, and the appropriate mitigation for that risk is to build higher-level tools that intercept/prevent that mis-use.
Interesting! That exercise is what I expected the Angius and Primiero paper to be.
> There can’t be any information about “truthfulness” encoded in an LLM, because there isn’t a notion of “truthfulness” for a program which has only ever been fed tokens and can only ever regurgitate their statistical correlations.

I think there are two issues here:

1. The "truthfulness" of the underlying data set, and
2. The faithfulness of the LLM to pass along that truthfulness. Lack of passing along the truthfulness is, I think, the definition of the hallucination.

To your point, if the data set if flawed or factually wrong, the model will always produce the wrong result. But I don't think that's a hallucination.
I haven't checked (I make maybe 10 calls per second at most). Intuitively, they should be similar.
I think spec-wise the Air is good enough for almost everyone who isn't doing video production or running local LLMs, I just wish it had the much nicer screen that the Pro has. But I suppose they have to segregate the product lines somehow.
Try it out in the demo https://cloud.google.com/text-to-speech/?hl=en and in the API https://cloud.google.com/text-to-speech/docs/create-dialogue...
As far as I can tell, you can't actually buy a 55" 8K TV anywhere.
We kinda do have LLMs in a swarm configuration though. Currently LLMs training data, which includes all of the non RAG facts they know, come from the swarm that is humans. As LLM outputs seep into the internet, older generations effectively start communicating with newer generations.

This last bit is not a great thing though, as LLMs don't have the direct experience needed to correct factual errors about the external world. Unfortunately we care about the external world, and want them to make accurate statements about it.

It would be possible for LLMs to see inconsistencies across or within sources, and try to resolve those. If perfect, then this would result in a self-consistent description of some world, it just wouldn't necessarily be ours.
I'm absolutely sure than LLMs have an internal representation of "truthfulness" because "truthfulness" is a token.
hey gotta do something on the toilet
> if the accept completes before the SQE for the cancellation is submitted, the FD will still be leaked.

If the accept completes before the cancel SQE is submitted, the cancel operation will fail and the runtime will have a chance to poll the CQE in place and close the fd.
> If the program was trained on a thousand data points saying that the capital of Connecticut is Moscow, the model would encode this “truthfulness” information about that fact, despite it being false.

This isn't true.

You're conflating whether a model (that hasn't been fine tuned) would complete "the capital of Connecticut is ___" with "Moscow", and whether that model contains a bit labeling that fact as "false". (It's not actually stored as a bit, but you get the idea.)

Some sentences that a model learns could be classified as "trivia", and the model learns this category by sentences like "Who needs to know that octopuses have three hearts, that's just trivia". Other sentences a model learns could be classified as "false", and the model learns this category by sentences like "2 + 2 isn't 5". Whether a sentence is "false" isn't particularly important to the model, any more than whether it's "trivia", but it will learn those categories.

There's a pattern to "false" sentences. For example, even if there's no training data directly saying that "the capital of Connecticut is Moscow" is false, there are a lot of other sentences like "Moscow is in Russia" and "Moscow is really far from CT" and "people in Moscow speak Russian", that all together follow the statistical pattern of "false" sentences, so a model could categorize "Moscow is the capital of Connecticut" as "false" even if it's never directly told so.
This guy invented flame graphs (among other things) so... I'm gonna allow it.

https://en.wikipedia.org/wiki/Brendan_Gregg
UN Spc Rapporteur report on situation of human rights in Palestinian territories [pdf]
Can anyone comment on the viability of using an external SSD rather than upgrading storage? Specifically for data analysis (e.g. storing/analysing parquet files using Python/duckdb, or video editing using divinci resolve).

Also, any recommendations for suitable ssds, ideally not too expensive? Thank you!
Glyphosate is not toxic. But the stuff in the bottle is mixed with adjuvants and surfactants - and those are toxic.

So you have to distinguish which thing is being studied if you want to research this product.
Yep. last time I got laid off, I got paid through that day. nothing else.
Most retailers have had the older models on closeout for a few weeks now. Best Buy, Amazon and Costco have had the M3 models for a few hundred off depending on models.
For testing mixing function quality I recommend you check out SMHasher3 by Frank Wojcik: https://gitlab.com/fwojcik/smhasher3
Not unique to AI, honestly.

If I try to watch a technical review on a smartphone, they’ll still talk about camera megapixels, screen size/brightness, corners, etc. No one talks about scroll sensitivity and jankiness, [bad] position of buttons on screen and on the frame, sensor nuances, how it feels in a pocket, can it work as a display, notification sounds and sound level separation, etc.

All marketing, including third-party based, focuses on absolutely basic features for abstract people who do nothing and have no problems to solve apart from taking pics of themselves and other two-digit iq activities. I guess it’s only logical for this image to walk into a skate park and ask their glasses about what these guys are doing.
Disenshittify the Web one small step at a time
It always seemed common sense to me that once a piece of software became stable and profitable you would need a much smaller engineering staff than when it was being built. The opposite seems to happens and orgs 10X their engineer headcount once they start making money.

It makes sense to keep some high performers and a few redundancies to stabilize/modernize it and make small improvements, but it feels like tech got really bloated with these massive corps who were trying to burn as much as they could to keep all the VC money flowing. Take like Uber having a team that built and maintained a chat app just for internal use, and every single big org having a bunch of teams responsible for various "some_dumb_name" that is the "custom X for 'Y'" where smaller teams just use the OS solutions to those problems.
I'm curious why they decided to go this route, but glad to see it. Perhaps ~4 efficiency cores is simply just enough for the average MBP user's standard compute?

In January, after researching, I bought an apple restored MBP with an M2 Max over an M3 Pro/Max machine because of the performance/efficiency core ratio. I do a lot of music production in DAWs, and many, even Apple's Logic Pro don't really make use of efficiency cores. I'm curious about what restraints have led to this.. but perhaps this also factors into Apple's choice to increase the ratio of performance/efficiency cores.
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