skysight-inc/HackerNews huggingface dataset:
>Association Between Time-Restricted Eating and All-Cause and Cause-Specific Mortality

https://www.abstractsonline.com/pp8/#!/20343/presentation/37...

Abstract

Introduction: Time-restricted eating (TRE) has gained popularity as a dietary intervention that limits daily food consumption to a 4- to 12-hour window. Most short-term randomized controlled trials reported that TRE improved cardiometabolic risk profiles. However, whether TRE is associated with long-term hard endpoints remains unknown.

Hypothesis: We assessed the hypothesis that TRE is associated with a reduced risk of all-cause and cause-specific mortality.

Methods: Participants aged at least 20 years who completed two valid 24-hour dietary recalls and reported usual intake in both recalls were included from the National Health and Nutrition Examination Survey in 2003-2018. Mortality status as of December 2019 was obtained through linkage to the National Death Index. An eating occasion required consuming more than 5 kcal of foods or beverages. Eating duration between the last and first eating occasion was calculated for each day. The average duration of two recall days defined typical eating duration which was then categorized as <8, 8-<10, 10-<12, 12-16 (reference group; mean duration in US adults), and >16 hours. Multivariable Cox proportional hazards models were employed to estimate the association of eating duration with all-cause and cause-specific mortality in the overall sample and among adults with cardiovascular disease or cancer. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were derived.

Results: Among 20,078 adults included, the weighted mean (SE) age was 48.5 (0.3) years, 50.0% were men, and 73.3% were non-Hispanic White. During a median follow-up of 8.0 years (IQR, 4.2-11.8), 2797 all-cause deaths occurred, including 840 cardiovascular deaths and 643 cancer deaths. Compared with eating duration of 12-16 hours, eating duration <8 hours was significantly associated with an increased risk of cardiovascular mortality (HR, 1.96 [95% CI, 1.23-3.13]); this association was also observed in adults with cardiovascular disease (HR, 2.06 [95% CI, 1.12-3.81]) and adults with cancer (HR, 2.72 [95% CI, 1.28-5.80]). Other eating durations were not associated with cardiovascular mortality, except for eating duration of 8-<10 hours in people with cardiovascular disease (HR, 1.64 [95% CI, 1.02-2.63]). No significant associations were found between eating duration and all-cause or cancer mortality in the overall sample and diseased subsamples, except that eating duration >16 hours was associated with a lower risk of cancer mortality in people with cancer (HR, 0.46; [95% CI, 0.22-0.95]).

Conclusions: In US adults, TRE with eating duration <8 hours was significantly associated with a higher risk of cardiovascular mortality in the general population as well as in people with cardiovascular disease or cancer. These findings do not support long-term use of 16:8 TRE for preventing cardiovascular death.
> this is the standard way to get really rich

The standard way for a young 15yo to get rich, is to be passed on wealth by their parents. But starting a company can probably work, occasionally enough that we can use it as a smoke screen.
It’s great that he recognizes that most people aren’t to be trusted either. Most people outside the field are talking about “safety” as though humans never lie or make up bullshit, whereas in reality I trust GPT4 much more than I’d trust an average human, just not 100%. Literally people keep hyperventilating about “fake news” generation even though their entire news consumption already consists solely of pre approved narratives, many of which are fake, by omission or otherwise.

I can’t wait for the day when ultra long context LLMs are able to point out omissions and factual contradictions in human produced fake news for any given event
Highly recommended to watch the entire video and also check out the other stuff by Angela Collier (formerly acollierastro).

Also funny that Avi takes string theory as an example of mainstream science. Some scientists are not sure it's science at all because it was never based on anything but assumptions.
sure. email in bio.
Yup wikipedia agrees, temperature is inversely proportional to mass. Surface gravity as well.

https://en.wikipedia.org/wiki/Hawking_radiation#Black_hole_e...

https://en.wikipedia.org/wiki/Surface_gravity#Schwarzschild_...
> Swipe up from the bottom of your iPhone. Oops, you're suddenly doing 3D transformations.

So don't do that exact effect? This is a pretty weak objection.

> there's just no such thing as a 2D GPU these days, it makes no sense

This might be stronger but I'm not an expert on pixel pushing.
Wow! I've worked with SMS sending gateway and cofounders cannot avoid temptation to use stored procedures for logic (we use Postgres, and logic in Perl). Because of this, last years installations limited by HDD performance, but fortunately, after crisis of 2008, we don't need much scaling.
I mean I think the biggest problem with the LLM community is that a sizable portion of not a majority of it consists of the exact same opportunistic "ground floor" people as just jumped off of cryptocurrency as the "thing they refuse to shut up about" which is all well and good when it's an exciting new thing that might change the world, but gets notably more insufferable when it's obviously just the newest route that person sees to getting greater amounts of money and/or social media clout, and they clearly do not know anything about it beyond it's potential to do those things. The colloquial term for that, I think, being "grifter." And to be clear, LLMs are not unique in their ability to draw in those types of insufferable people: see the aforementioned comment about crypto, it was the last big one, and before that probably dropshipping. But I digress.

And I bring all that up to say: no, the vast majority of people, I don't think expect the computer to come to life and tell them it loves them. I think the vast majority, in fact, don't know a fucking thing about LLMs beyond maybe the rote copy/pasted code it takes to bring one into existence, or if we're being honest, more likely, the websites to put their credit card information into to gain access to one for their use, and that shift in base assumptions I think explains why they speak so incoherently: they do not understand it in any depth, and thereofre, they might think the computer will come to life, because they don't know much about computers in general and to a layman, what an LLM does can indeed look like a vague imitation of life.

Like, I mean this in the nicest way possible though just by virtue of what I'm going to say, it is going to sound mean, but: tons of the really big pro-AI hype people just, clearly, bluntly, full disclosure, do not know shit about LLM. Quite a large slice of that pie also don't know shit about technology in general, or seemingly, much of anything beyond a business degree? But irrespective of that, to the wider world who aren't in this and don't participate in the groups at hand... those are your representatives, by default. The attention economy has produced them and you have my most sincere sympathies for that.
> I remain mystified why anyone thinks it’s a good idea to discuss complex issues of theoretical physics in the Twitter format, flooded with all sorts of random stupidity.

Communicating science to the general public on public forums is extremely important, and probably should be considered a job requirement for all scientists. Several reasons:

1. Obviously it may affect how the public perceives science and its social and economic value, and thus how we vote, which can affect public funding for basic research necessary for advancing science.

2. More importantly, the antidote to chaos is reason and knowledge. We live in an era of increasing emotionalism, irrationality, and a flood of sophisticated disinformation strategically exploiting and amplifying those two to sew general chaos. Science communication on public forums gives the public an alternate perspective to consider. Without that alternative perspective, the battle is already lost.

These things are necessary even if it requires suffering being flooded with all sorts of random stupidity.
These things always happen at intersections. There are lots of smart people with ideas. The magic happens at the intersection of ideas, time (what technology is available) and luck. Apple Newton was too early. Apple iPhone was just right. Doom 3D was just at the right time when commodity hardware could do what the amazing software needed it to do.
And how is this better or easier than just setting up the port forwarding on the router?
I think there's a connection here to the old adage that "small companies make it possible, big companies make it inexpensive".

The purpose of VC can be viewed as trying to take a company from nonexistent to big while skipping the small stage, but small is where the action really is.
I find him more relatable than most musicians, journalists and actors.
How does what you're describing differ from polymorphism, or from doing OOP in loosely typed languages like javascript?
UK schools are funded from central government: https://educationhub.blog.gov.uk/2024/03/19/school-funding-e...

Local councils do collect a "council tax", but it's basically a fig leaf to disguise a poll tax by just enough that people don't outright riot: https://en.wikipedia.org/wiki/Poll_tax_riots

And in practice, council tax is only about 55% of local council's funding, the rest coming from central government. And the councils do sometimes go (effectively, but not literally) bankrupt: https://www.bbc.com/news/uk-politics-66878229
Why assume this is sensible? Aerodynamics can help discover general principles that apply to both birds and planes or whatever else. I don't see how this holds for LLMs and brains. The similarity between LLMs and brains is superficial.

Besides, with human beings, we have a host of philosophical problems that undermine the neuroscientific presumption that a mechanistic and closed view of the brain can account for mental activity entirely, like the problem of intentionality.
I've also always questioned this. I have purchased about 60 sets in the past 4 years. I have a friend who has purchased well over 100 (he runs a Lego YouTube channel - he spends > $6,000 a year on Lego by his estimation).

I have never had a missing piece. There have been two times when I thought I was missing a piece and then found it stuck in a bag or hidden under another piece. I've never had to write to Lego to get a replacement (which I've heard they are really easy to work with if it does happen).

Out of curiosity, I just texted my friend to get another sample from him and he said it happened to him one time, but also admitted his kids might have been to blame.

So when people claim that every other set they buy has missing pieces, I always feel like I am either the luckiest person to ever live, or maybe the pieces are there and certain people are just more likely to misplace or lose them in the building process.
I wish I could say the same. The extra little guys is to be expected. I am talking about key pieces to the puzzle.
Yes, one and the same (he appears on the homepage you linked)
And cleaning a house isn't one task. It's a whole slew of different tasks which, given some basic instructions, my housekeeper can handle easily without supervision. And there's quite a bit of common sense required.
The history of the FBI shows many despicable acts and actors. I'm not sure it's worth the price.
> a machine was built that writes like a human

But the real hero here is not the LLM, but the training set. It took ages to collect all the knowledge, ideas and methods we put in books. It cost a lot of human effort to provide the data. Without the data we would have nothing. Without GPT we could use RWKV, Mamba, S4, etc and still get similar results. It's the data not the model.

> the intuition that language is central to thought predates LLMs

Language carries AI and humans. The same distribution of language can be the software running in our brains and in LLMs. I think humans act like conditional language models with multi modality and actions. We use language to plan and solve our problem, work together and learn (a lot) from others.

Language itself is an evolutionary system and a self replicator. Its speed is much faster than biology. We've been on the language exponential for millennia, but just now hit the critical mass for LLMs to be possible.

It's not so important that GPT-4 is a 2T weights model, what matters is that it was trained on 13T tokens of human experience and it now "writes like a human". Does that mean humans also learn the same skills GPT-4 has learned from its training set mostly by language as well?
+1, Did post the exact query in Nexusraven discord asking for an example or quick start with ollama yesterday. Before that, tried to hack their NexusRaven pip client which uses TGI inference endpoint and non-langchain.py from their evaluation repo which uses TGI pipeline. Both failed.
$110 AUD per year is insanely expensive!
> Why are we asking tech CEOs about societal racism and politics

Technically he's still a tech CEO but practically it seems like he spends much more of his time and attention on societal racism and politics
Has string theory ever led to important testable predictions? I’m very out of the loop on theoretical physics.
a) Come on, be kind

b) I don't have to think about doing systems administration on the very resource-limited stripped-down OpenWRT device

c) It's probably marginally more secure
> I have a hard time believing it's nothing more than a cost cutting measure.

It's a "keep bricks interchangeable" measure. Every LEGO set designer gets a budget of a few new piece suggestions per year. This includes color and paint schemes.

From a Verge article on how a new set happens: https://www.theverge.com/c/23991049/lego-ideas-polaroid-ones...

> And those teams came up with one simple idea to stem the tide of complexity: “frames.”

> Want a part in a different color? That costs designers a frame. A new piece? Spend some frames. Bring back an old out-of-print piece? That’s a frame, too. Every year, design leads like Scott are given a limited number of frames that they can spend on their entire portfolio for physical pieces that aren’t readily at hand. “If I have five products or 10 products coming out, I need to allocate where those frames go,” says Scott.
Agree on pure IC ones. Hybrid ones, like the one on the Prius, while still technically a CVT, are nothing like the jatco crap Nissan and others had been putting on IC cars. They are quite reliable.
(Though, to be clear, I do like the idea of doing it purely in Python!)
Yeah $110AUD/year is more than twice what I'd expect to pay.
i've always assumed that language was required to give your brain the abstractions needed to reference things in the past compared to your current perception (aka now), like an index. if you think about your earliest memories, they almost certainly came after language. i'd be interested to know if any of the documented 'wild child' cases (infants 'raised by wolves') ever delved into what the children remembered before, after being taught language as an adolescent.
At a rough glance, that does appear to be the case.
You might find this useful https://www.vitalchoice.com/blog/fish-art/#:~:text=In%201557....
Digitizing all the books in he world was an is an essential component of modern AI, a full two decades later.

I don't know what point you are trying to make.

Googles mission was always to know everything for everyone.
Some people live in places with rolling blackouts and the UPS doesn't last long enough, so easier to shutdown cleanly and power off the UPS so you're not constantly cycling the battery for no good reason.
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Our AI gives you insights on potential ad performance, helping you make better decisions without the guesswork. You can keep all your favorite ads in one spot and make collections that you or your team can go back to. It's straightforward – we keep an eye on the quality so you can focus on making your projects better.
> Can't all of the above be said about Microsoft SQL Server as well?

No.

MS SQL doesn't just keep working, needs real hardware to run, doesn't handle noSql work anywhere as well, and has many small bugs that pop-up here or there. Besides, it's a quite visible expense - that would be ok if it gained you anything.

And just as impacting but on a different dimension, it requires much more query optimization, and its language is just awful when compared to Postgres (even though it's probably the next best thing out there).
The financial crisis from 2007-2008 would not have been prevented if banks had more liquidity. Debt insurance help, but that just moves the problem to the insurer.

Subprime mortgages, toxic assets, and excessive risk-taking is about trust and risk. When the government becomes the debt insurance, then that risk get managed through stricter banking regulations. Liquidity do not make a bad debt less bad. At best it can hide the problem as the bank tanks the loss, but that only works as long the bank is profitable.

An other interesting example was the Icelandic financial crisis, where the Sovereign debt defaulted on loans from UK and Netherlands. This caused diplomatic problems, including threats of cutting of the Icelandic banks from the global banking network. The value of the Icelandic currency sharply dropped in relation to other currencies, and the Central Bank of Iceland became unable to act as a lender of last resort. The solution in the end was a international bailout support program, including securing more debt from other nations to pay existing debt. This renewed trust in the sovereign debt, but also the trust in the currency and the government.
I think they're on track at a metaphorical level to follow the same consideration of racial diversity shown to their indigenous people, i.e. mass burying in unmarked graves instead of attempting to address the disparity. I guess it's better that it's not literal this time.
US Air Force conducts final test of Lockheed's hypersonic missile
I got my dual clutch in 2010 and have barely felt guilty about not driving stick since then. Particularly because in Volkswagen's rendition of DCT, the car will react to riding the brake by using engine braking. There are certain hill shapes where it doesn't really work, but it works nearly perfectly on shallow inclines. Light tap at the top and it will hold speed the entire way down.

People will often point out that you can use the override but I feel like that misses the point. There's what a person can do, and what they will do, and when we are talking about something like global fuel economy and carbon emissions, 'will do' is the only metric that actually matters. And hybrid electrics and DCTs fare better in the 'will do' category.
There was bare PCB prototype running on my desk that was in the way. I started cleaning my desk to work on something less frustrating and it got knocked off by accident. The logger went haywire immediately. That was the hint I needed.
I talked to Pi for one New York minute and it came up with the good ole “Ahhh the X Y of Z” LLM-ism. So much for an unique conversational tone.
For the 8080 emulator, you need the c_basic.bin (renamed to just "C") and c_bios.bin to be in the same directory as the executable, as per the article. I tried this and it dumps me into a BASIC shell. So cool!
There's a site that got banned from all the captcha services and switched to a homegrown proof of work system. You can tie the PoW difficulty to the level of DDoS as well so the impact is minimal when not under attack.
Can you explain this for the folks who are interested in, but don’t understand, your reference?
I think you changed more than he did.
Of course the question assumes that you do have a main language. I know that many people program in more than one language, as needed, or for fun. If so, feel free to answer the question for some or all of the languages you use.
I wish more people knew how the power-split devices in modern hybrids worked. The 'eCVT' and similar terminology they often get just doesn't do it justice. They're a beautiful design, and entirely different than 'CVTs' as most people know them.

Some of these designs are mind-blowingly simple. My favorite is Honda's E-drive: https://www.youtube.com/watch?v=QLUIExAnNcE
Nice — definitely try Causal out! We have a 'scenarios' feature that lets you easily spin up "discrete" scenarios, and then you can use the Monte Carlo stuff to see continuous ranges of outcomes.
Couldn't reminder apps implement "nagging" such that dismissed notifications are re-notified until some action is taken?

Agreed, this is Apple taking advantage of private APIs in much the same way that got Microsoft in so much hot water in the late 90s/early 00s.
The challenge here is not simply being in the right startup but having the right combination of startup founders (& contributors) for that particular idea at that particular time. Now, it's not like there's only one great fit for each role, but it's far from rolling a d100 too.
https://en.wikipedia.org/wiki/Karaoke_machine

https://en.wikipedia.org/wiki/Shigeichi_Negishi
Am I missing the point or is this not how everyone was doing RAG before?

I've had my much greater success doing the RAG process on a fine tuned model.
While thats true they did fund Airbnb which is 100B. So while they haven't funded anyone that big yet, they have come 1/10 of the way.
As a huge fan of the Apollo program for decades, and the Artemis program now, it pained me to upvote your comment. But you are 100% correct on every point you mention.
I would recommend to stay away from AI… everyone and their dog are into the topic right now so you’ll probably face fierce competition in finding a job when the current hype is over.

We’re always looking for good students in anything related to systems if this is your thing - OS, distributed systems, compilers, virtualisation, hardware design/codesign, system level security and all sorts of embedded systems topics. Most of the students here in Germany choose to go to industry after graduating (which pays quite a bit better than universities right now in these areas), so we have quite some trouble to find good PhD students…
Fair point @jiehong, but I think modern cross-platform frameworks and libraries have made significant strides in abstracting away those complexities.

Most of them provide abstraction layers that handle low-level input events, including keyboard input, with a consistent API across platforms. They also adhere to established standards like ISO/IEC 9995 for keyboard layouts and XKB for X Window Systems.

Additionally, platforms often provide dedicated input method libraries (e.g., IBus on Linux, TSF on Windows) that these frameworks can leverage to handle different keyboard layouts and input methods seamlessly.

Not to mention the focus on localization and internationalization (L10n and I18n) in modern software development practices, which includes support for different locales, character encodings, and input methods out of the box.

While there may be some edge cases or platform-specific quirks to consider, the challenges of handling different keyboard layouts are generally well-understood and addressed by the frameworks and their active communities.
That's what he said. "Resourcefulness". Money is a resource as much as brainpower or grit or creativity.
Show HN: LLMdantic: Structured Output Is All You Need