skysight-inc/HackerNews huggingface dataset:
Not as snugly.

"a method for systematically changing attitudes or altering beliefs," fits very well. "originated in totalitarian countries" not so much, and "especially through the use of torture, drugs, or psychological-stress techniques" very little, although it's an "especially", so not a required feature.

The "originated in totalitarian countries" is a bit odd requirement for my taste. Of course, if one wants to use that definition, then by definition even "a method for systematically changing attitudes or altering beliefs the use of torture, drugs, or psychological-stress techniques" is not brainwashing if it doesn't originate from a country that is defined as totalitarian with some definition.
I do something similar, except at one shop where the WTFs outnumbered everything sane by a wide margin.
I put my opinions on the conflict right on LinkedIn. I'd much rather filter out employers like Google and Meta. There's a million ways to make money, I'd pick the one that doesn't put any blood on my hands. Some people require more courage to move than others; we all have different environments. I'm just glad I'm not in the US and not neck deep in such a mess. We've been wondering if we should just use Chinese tech, but their hands are clean either. I guess we'll make our own one day.
It is also frustrating that there are differences between US American, Canadian, British and Australian cups. And the pure irony that „Because actual drinking cups may differ greatly from the size of this unit, standard measuring cups may be used, with a metric cup being 250 millilitres.“
Meta (iirc Zuck in some interview) has stated before that monetizing the models directly isn't part of their plan, they intend to profit from platforms that are built around them, e.g. targeting ads better by having a model look at people's messenger history. It's in their interest to have the community do free work to improve their architecture.

Mistral is monetizing them directly, they sell API access.
> I got paid way more because of it.

I can believe it, but that doesn't really tell us anything and I suspect you are being cagy here on purpose.

The bulk of the cost of college isn't the out of pocket expense, it is the opportunity cost. Your time focused on college is time you are not doing something else. Thanks to the properties of compound interest, your time is most valuable when you are young. By a huge margin. So any time not spent making money when you are young can become financially devastating rather quickly.

So, yes, obviously you needed to be paid way more just to begin to break even. You wouldn't be able to afford to take the job otherwise. But to break even isn't worth it from an economic point of view – especially given the high risk involved; you could have just as easily ended up unable to find a job. Sure, maybe you gained something out of the experience as a hobby, and there is certainly something to be said about that, but is really beyond the topic at hand.

I mean, if you went to college when you were in your 50s, then okay. In that case, being paid way more has the potential to start to trump the cost of time lost, but when going to college in your 50s you are, again, not exactly in tune with the topic at hand.
And with SPARK/Ada it will. When I was learning it that was actually a very common thing that it caught in my code (various forms of over/underflow errors). In practice most of them would not occur, but a few could have under real-world use-cases.
Geohot? I know enough people at OpenAI to know 4 people's reaction at the time he started claiming 1T based on timing latency in the ChatGPT webui per token.

In general, not someone you wanna be citing with lengthy platitudes, he's an influencer who speaks engineer, he's burned out of every community he's been in, acrimonously.
I think the concept of a 'WTF notebook' is great, and I think writing down one's thoughts in general is a good idea. I also think that it helps formulate thoughts and communicate them in a more thoughtful not-in-the-heat-of-the-moment way.

However,

> For two weeks, that's all I do. I just write it down. I don't tell the team everything that I think they're doing wrong. I don't show up at retro with all the stuff I think they need to change. I just watch, and listen, and I write down everything that seems deeply weird.

> [...]

> Before I started keeping this kind of list, I brought up problem I saw immediately, as soon as I noticed it. The reputation I got was, "Nat's always complaining about things. Nat thinks we're never doing things right." People stopped listening to me. I was personally frustrated, and professionally ineffective.

Not bringing up things that you think could be improved in a retro.. that's pretty silly. If you are getting a reputation of 'always complaining', and coming across as 'telling people they are doing things wrong', etc. then you are just bad/unprofessional at communication.

Communicate things as 'I was thinking maybe we could do <X> better if <Y>, what do you think?' and make it a genuine discussion with people, rather than 'WTF <x>?' - especially when it is someone else's work and you want to remain on good terms with them.

You don't have to wait 2 weeks, compile a secret list and then bring it to your manager - though. You can communicate things that you think can be improved in a polite/respectful manner as they occur. Being on a team is about working together. If you cannot safely do that when communicating effectively, then you are with a terrible team/company.
No it’s just people don’t want to lose weight. If they lived with me and allowed me to control their diet and exercise routine, they would be in shape. It’s a matter of will and they don’t have the will to be normal weight, if not physically fit.
I downloaded llama3:8b-instruct-q4_0 in ollama and said "hi" and it answered with 10 screen long rant. This is an exerpt.

> You're welcome! It was a pleasure chatting with you. Bye for now!assistant

> Bye for now!assistant

> Bye!assistant
I disagree. In most subjects, recapitulating the historical development of a thing helps motivate modern developments. Eg

1. Start with bag of words. Represent words as all zero except one index that is not zero. Then a document is the sum (or average) of all the words in the document. We now have a method of embedding a variable length piece of text into a fixed size vector and we start to see how "similar" is approximately "close", though clearly there are some issues. We're somewhere at the start of nlp now.

2. One big issue is that there are a lot of common noisy words (like "good", "think", "said", etc.) that can make the embedding more similar than we feel they should be. So now we develop strategies for reducing the impact of those words one our vector. Remember how we just summed up the individual word vectors in 1? Now we'll scale each word vector by its frequency so that the more frequent the word in our corpus, the smaller we'll make the corresponding word vector. That brings us to tf-idf embeddings.

3. Another big issue is that our representation of words don't capture word similarity at all. The sentences "I hate when it rains" and "I dislike when it rains" should be more similar than "I hate when it rains" and "I like when it rains", but in our embeddings from (2) the similarity of the two pairs is going to be similar. So now we revisit our method of constructing word vectors and start to explore ways to "smear" words out. This is where things like word2vec and glove pop up as methods of creating distributed representation of words. Now we can represent documents by summing/averaging/tf-idfing our word vectors the same as we did in 2.

4. Now we notice there is an issue where words can have multiple meanings depending on their surrounding context. Think of things like irony, metaphor, humor, etc. Consider "She rolled her eyes and said, 'Don't you love it here?"'" and "She rolled the dough and said, 'Don't you love it here?'". Odds our, the similarity per (3) is going to be pretty similar, despite the fact that its clear these are wildly different meanings. The issue is that our model in (3) just uses a static operation for combining our words, and because of that we aren't capturing the fact that "Don't you love it here" shouldn't mean the same thing in the first and second sentences. So now we start to consider ways in which we can combine our word vectors differently and let the context affect the way in which we combine them.

5. And that brings us to now where we have a lot more compute than we did before and access to way bigger corpora so we can do some really interesting things, but its all still the basic steps of breaking down text into its constituent parts, representing those numerically, and then defining a method to combine various parts to produce a final representation for a document. The above steps greatly help by showing the motivation for each change and understanding why we do the things we do today.
deepseek-coder-instruct 6.7B still looks like is better than llama 3 8B on HumanEval [0], and deepseek-coder-instruct 33B still within reach to run on 32 GB Macbook M2 Max - Lamma 3 70B on the other hand will be hard to run locally unless you really have 128GB ram or more. But we will see in the following days how it performs in real life.

[0] https://github.com/deepseek-ai/deepseek-coder?tab=readme-ov-...
Tears of the Kingdom's biggest problem was the lack of a good story or dungeons, which was never solved
Well, exactly, and that's why IMO they'll end up pulling out the EU. There's barely any money in non-targeted ads.
This, this, this (plus zoning laws based off this).

I drive through a neighborhood in Baltimore County, Maryland where a number of the houses have these black and white signs, "Save the suburbs!" "No new light rail!"

The USA has a lot of unaddressed trauma around "others" and urban living. Plus a car infrastructure it heavily relies on to the detriment of all other modes of transportation. And stores that take up an enormous amount of square footage with cheap goods… and… and…

(edited for coherence)
My todo list item to install driver cams has gone for way too long, I need to bump it up in priority.

Hope you’re doing better.
Hi Udayan - nice to see another shot at electrowetting microfluidics in this space.

1. How does your technology or product offering distinguish itself from prior attempts like NeoPrep (née Advanced Liquid Logic) from Illumina or Voltrax from ONT?

2. How "hackable" is the offering for power users to implement custom protocols on the instrument and consumables?
We're on a good employer plan, and weight loss meds are all out of pocket.
+1. I just read this on your recommendation and can also recommend it.
Bipartisan ire flares in response to Chinese Embassy's quiet TikTok lobbying
Im just saying that this was not a reality for 99.99999% of humans to ever live.
Maybe it’s related to how we (government, industry) used to routinely make great instructional videos and other learning materials, but are now largely terrible at it.

I suspect it’s all connected to the rise of a professional management class, rather than promotion through the ranks, and management by people who’ve done the work. Nobody who’s in a position to demand better or to make sure the right people are in the right roles, actually knows WTF they’re doing outside of a spreadsheet and PowerPoint.
Railway launches $5k startup program
>City design and zoning

More than any one factor, this is one of the biggest, if not thee biggest one. Get people out of cares and walking around to do daily things like going to work, or shopping for groceries etc. and you naturally get more movement (and interaction) in your day. This compounds over time and encourages other movement.

Of course food matters (you can't exercise away a bad diet after all) but we actively encourage stationary activities by not having public spaces that are designed for movement and activity on foot / bicycle / other physically active options
>But Hunter wasn’t just a reporter, objectively chronicling conditions in China. As he told the assembled senators, he was also an anticommunist activist who served as a propagandist for the OSS, or Office of Strategic Services—something that was considered normal and patriotic at the time. His reporting blurred the line between fact and political mythology.

Err...: http://jmc.stanford.edu/commentary/progress/venona.html

I get that expecting truly quality research work from Technology Review is an eggs-in-moonshine level fantasy, but it'd be nice to employ literally one editor who has read literally any of MIT's greatest researchers with all the ivy league cash they spend on fancy robots or buildings or whatever else.
I can't wait for the 400b to be released. GPT-4 is too expensive and the fact that we can distribute the workload between different companies (one company trains it, another creates a performant API) means we will get a much cheaper product.
Yeah, though a way to connect fewer data pins to each chip doesn't particularly have to be clamshell, it just requires a little bit of flexibility in the design.
I'm fine with forcing upgrades this way - however, from an operations standpoint, it is an absolute nightmare.

For one, depending on your situation/CRD's/automation, doing these upgrades in-place can be next to impossible. Updating an EKS minor version can only be done one version at a time - e.g., if you want to go from 1.24 -> 1.28, you need to do 1.25, then 1.26, then 1.27, then 1.28. So teams without a lot of resources are probably in a tough spot depending on how far they are behind here. Often, it's far more efficient to build an entirely new cluster from scratch and then cut over - which seems ridiculous.

Why are upgrading EKS versions such a pain? Well, if you're using any cluster add-ons, for one, all those need to be upgraded to the correct versions, and the compatibility matrix there can be rough. Stuff often breaks at this stage. Care needs to be taken around PV's, the CNI, and god help you if you have some helm charts or CRD's that rely on some deprecated EKS API - even if the upstream repository has a fix for it, you will often find this yak-shaving nightmare of fixing all the stuff that breaks on upgrading that, and then whatever downstream services THAT service breaks - etc.

What is the solution? I don't know. I'm not a kubernetes architect, but I work with it a lot. I understand there are security patches and improvements constantly, but the release cycle, at least from an infrastructure/operations perspective, IME places considerable strain on teams, to the point where I have literally seen a role in a company whose primary responsibility was upgrading EKS cluster versions.

I have a sneaking suspicion this is to try to encourage people to migrate to more expensive managed container orchestration services.
I can relate to some of what this author is saying about a Realtors. I bought a house last year and it was the first house I bought in many decades. Dealing with various Realtors was an annoying experience. Instead of acting like my agent and a fiduciary for me they acted like a used car salesman. Within a couple of those interactions they were gone I had nothing more to do with them because that's not what I wanted. I was looking at various places around the country for the right house and I knew my criteria. I was looking for boots on the ground essentially to look at places and give me accurate feedback as if I was looking at it. I didn't need someone to sell me on a place I just needed them to tell me about it.

I did end up using a realtor and I found a very good one. He was exceedingly helpful he looked at a dozen or more properties for me and gave me the exact feedback that I wanted as if I was there. Not trying to sell me of whether it was good or bad just feeding me information about the property things that he saw the neighborhood and other things that weren't easy for me to know just from looking at the pictures. Nearly every property was one that I sent to him because I saw the pictures and I was interested. He was very interested in learning my needs and finding my fit rather than finding something to sell to me just to get a commission. The house I ended up buying when he went and looked at it I got a call within an hour and the first things out of his mouth was you are going to want to buy this house. When I flew into inspect it personally he was absolutely right because he took the time to get to know me and what I wanted it.

I absolutely understand that is not the normal experience and I had to go through a number of Realtors to get to one that could give me that level of experience. Unfortunately it seems all too easy to get a real estate license and to throw yourself out there to make easy commissions in a booming market.
Microsoft refused to allow police to use some of their facial recognition technology because of this, and it was before BLM.
https://archive.ph/GfQrf
You absolutely can since it has a size advantage either way. MoE means the expert model performs better BECAUSE of the overall model size.
WotC President Cynthia Williams stepping down
All I Need to Know about Physics I had to Dig Up by Myself
This is the credo of a physicist but I think most of it can be applied to almost any profession. A somewhat longer version appeared in Physics Today which you can find here
https://pubs.aip.org/physicstoday/article-abstract/46/5/63/4...

Does anyone have anything to add to this?
Well seeing that if AWS went bankrupt and couldn’t afford their servers, I assure you that the federal government would step in seeing how many government services are hosted both in the commercial, GovCloud and “secret” (an official type) regions not to mention how many financial companies are hosted there.

And every cloud provider has their own set of proprietary services that you are going to need to both design around and have staff trained for and constantly be testing for.

No “running K8s and open source software” is not the answer. You still need to integrate with thier IAM solution, how they manage their VMs other supporting infrastructure and often if you are large enough, you will have redundant physical connections to their data centers.

Also “using Terraform” is not the answer. A TF configuration is not portable at all across vendors.
CheatEngine exists on modern systems and can still do a lot of this, though modern game engines are less friendly to the simple "scan for the health variable and set it to 1000" workflow of yesteryear. However, newer versions of cheat engine include C#/monogame decompilers that let you screw around with some unity games
We've got an API out here: https://replicate.com/blog/run-llama-3-with-an-api

You can also chat with it here: https://llama3.replicate.dev/
I've found that writing randomized unit tests for each small part of a system finds this sort of stuff immediately.

In this case, a test that just generated 1,000,000 random strings and passed them to punycode would probably have found the problem (maybe not in the first run, but after a week or two in continuous integration).

I try to structure the tests so they can run with dumb random input or with coverage-guided input from a fuzzer. The former usually finds >90% of the bugs the fuzzer would, and does so 100x faster, so it's better than fuzzing during development, but worse during nightly testing.

One other advantage for dumb random input is that it works with distributed systems and things written in multiple languages (where coverage information isn't readily available).
Run Meta Llama 3 with an API
It still has nothing to do with the maturity of the field.

How many astronauts could design a rocket that could get to space? I believe the answer is zero, irrespective of maturity.
The risks are unknown at an individual level but at a population level are quantifiable and fairly stable. In any case the companies are turning profits in the billions of dollars which means Americans are overpaying for worse outcomes.

> Canadians constantly complain about their system

Everyone complains. That’s part of democracy. Americans complain about our health care system too.

What matters is outcomes, and Canadians live longer than Americans. The fact of the matter is the US government can’t figure out how to get healthcare to people, so instead sells them excuses and propaganda for why not fixing the problem is actually acceptable.
I'm struggling to see how this relates to TFA. It sounds like you're talking about organizing your personal TODOs, whereas the article is about how to acclimate and communicate within a team.
I actually can't wrap my head around this number, even though I have been working on and off with deep learning for a few years. The biggest models we've ever deployed on production still have less than 1B parameters, and the latency is already pretty hard to manage during rush hours. I have no idea how they deploy (multiple?) 1.8T models that serve tens of millions of users a day.
This makes sense though...customers are pushing to have chips made outside of Taiwan to protect their supply chain, why not make them pay for that when it's clearly more expensive to do so.

Many companies have already cleared out of China as much as possible (Dell made it clear they wanted all supply out of China by 2024)...Taiwan is the next logical step.

You will start to see the term NCNT (No China, No Taiwan) used more and more...it's already part of many companies internal strategy and corporate planning. Similarly China has a "China for China" policy...where they want everything sold in China to be 100% made in China.
Search for Netflix’s reinvent talks on YouTube
Thanks, really appreciate your thoughtful and genuine responses in this thread.
Deep Archive has retrieval times up to 12 hours, so for on-prem/colo that is then competing with buying a few tape robots (you can get a single tape archive that handles >1 exabyte, but you'll of course want redundancy without having to have staff shuffling tape in an archive that will run into the thousands). You can buy management software that tries to replicate a glacier-like experience for things like SpectraLogic tape libraries but they may not be the cheapest option.

It ends up becoming a very different beast than the storage classes w/fast enough retrieval guarantees to need disk, in any case.
Ship of Theseus problem, lol
Exposed: SEOs Stealing Millions from Reddit
Paul Graham on Bloom Tech
With enough experience one usually can start to differentiate the actual hoo-why-oh-why WTFs from the oh-there's-subtle-complexity-here WTFs. The first are straight up failures, the second usually resolve themselves after steeping oneself in the environment. Still handy to note them down, regardless.
The storage medium for sunlight are carbohydrates Ü
This is something most people don't realize is an aspect of Red Hat's value. Extended Lifecycle Support (ELS) + Extended Update Support (EUS) are available _just in case_ you really can't figure out how to migrate off of those Red Hat Enterprise Linux 6 systems running on x86 (32 bit). https://access.redhat.com/support/policy/updates/errata
I enjoy cheeky letters and even moreso, I really enjoy cheeky responses to said letters.

The staffer who replied probably enjoyed writing it.
I recall there was a website tracking the ideological bias of LLMs, but I can’t find it now. But it was showing where all the LLMs rank on a political graph with four quadrants. I think we need something like that, ranking these LLMs on aspects like censorship.

Example: https://www.technologyreview.com/2023/08/07/1077324/ai-langu...

But I think some other site was doing this ‘live’ and adding more models as they appeared.