skysight-inc/HackerNews huggingface dataset:
No my problem with Twitter is that the quality of the discourse is poor and getting worse every day.

Which is a direct result of Musk deciding to prioritise blue check comments over others. If you're having to pay to have people listen to you then that means you typically don't have something worth saying.

And we see this manifest in many ways e.g. pages of laughing emojis in response to a tweet.
> I don't know when the change was made, but conditional moves are fast and efficient on the last several generations of AMD and Intel processors. Usually, you are trading 1 or 2 extra cycles of latency against the chance of a ~15 cycle mispredicted branch penalty. If your branch cannot be predicted correctly ~85% of the time, this can be a significant win.

https://news.ycombinator.com/item?id=10749195
That’s standard. Me and others in my PhD cohort have had experiences where we saw so many minor inaccuracies in the copy we only fixed things that were flat out wrong, otherwise we’d have rewritten the whole article. It’s the result of a combination of non-experts having a 30 minute conversation with you then writing based off their notes a week later and the fact that their job is to hype up research so that it gets more attention from a broader audience. Everyone I knew said they wouldn’t let that happen to them when the press office called, but rewriting someone’s whole article because you feel like they missed nuances is hard to take a strong stance on, especially as an early career researcher.
How so? Would we have travel bans to prevent emissions of travelling?
This was more or less a series of side quests in Cyberpunk.
Yes? That’s the point. Who cares about an outdated concept that has no digital analog? All the artists have moved on already #midjourney.
Another way to parse Markdown, HTML, or docx files would be pandoc [1]:

pandoc --to json file.docx

or in Python:

import json
from sh import pandoc
doc = json.loads( pandoc("file.docx", to="json").stdout )

Example output (reformatted slightly to reduce number of lines:

{'pandoc-api-version': [1, 22, 2],
'meta': {'title': {'t': 'MetaInlines',
'c': [{'t': 'Str', 'c': 'The'}, {'t': 'Space'}, {'t': 'Str', 'c': 'Title'}]}},
'blocks': [{'t': 'Header',
'c': [1,
['first-chapter', [], []],
[{'t': 'Str', 'c': 'First'}, {'t': 'Space'}, {'t': 'Str', 'c': 'Chapter'}]]},
{'t': 'Para',
'c': [{'t': 'Str', 'c': 'I'}, {'t': 'Space'}, {'t': 'Str', 'c': 'like'}, {'t': 'Space'},
{'t': 'Emph', 'c': [{'t': 'Str', 'c': 'cursive'}]}, {'t': 'Space'}, {'t': 'Str', 'c': 'or'},
{'t': 'Space'}, {'t': 'Strong', 'c': [{'t': 'Str', 'c': 'bold'}]}, {'t': 'Space'},
{'t': 'Str', 'c': 'text.'}]},
{'t': 'Para',
'c': [{'t': 'Str', 'c': 'Here'}, {'t': 'Space'}, {'t': 'Str', 'c': 'is'}, {'t': 'Space'},
{'t': 'Str', 'c': 'a'}, {'t': 'Space'}, {'t': 'Link',
'c': [['', [], []], [{'t': 'Str', 'c': 'link'}], ['https://ix.de/', '']]},
{'t': 'Str', 'c': '.'}]},
{'t': 'BulletList',
'c': [[{'t': 'Para', 'c': [{'t': 'Str', 'c': 'Item'}, {'t': 'Space'}, 't': 'Str', 'c': '1'}]}],
[{'t': 'Para', 'c': [{'t': 'Str', 'c': 'Item'}, {'t': 'Space'}, {'t': 'Str', 'c': '2'}]}]]}]}

[1] https://pandoc.org/
MongoDB compass
Where is generative design in drug discovery today?
If it had been "easy", China would have been able to do it. For them it is a existential that at nation level. Just money ain't enough to beat decade(s) of effort.
Your are joking, right? A niche market like gaming? lol
Oh but one downside I found is that there is no model selector and only gpt 3.5 16k is allowed, which is strange.
What if you could train an LLM on the body of source code for AWS (or whatever you choose as your SaaS) and so it would actually know deeply, exactly, intimately exactly how AWS works, and how to do anything and everything in it? Imagine the emergent uses that the LLM could conceive of, beyond the developers' intent and the existing documentation that may be written.

With the bonus effect that you could retrain the LLM as often as you like, as new software is released, and it could always be aware of the latest features (and even the bugs and vulnerabilities.)
AFAIK the "most powerful" TPU that you can get is CRL-G18U-P3DF, and that is only capable of running quantized tensorflow lite models. Not sure how that is supposed to compete with those 700W TDP superchips.
Different quantizations can give you a big speedup if you've had "depressingly slow" issues. Even the slowest ones (that fit in RAM) will run at basically interactive speed, not instant, but also not "email speed". I have a laptop with a 2018 CPU and I'm working with them just fine.

Text generation style instead of chat style is another avenue that makes the feedback time not so annoying for a developer.

at 100ms/token, it's faster than most people type, I think. That's what you might get on an old laptop with a 7B model.

There's a useful leaderboard here to help you pick a model: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderb...

It really depends on your task, lots and lots of natural language type tasks give great results, the models seem to have extensive knowledge of many fields. So for some kinds of Q&A bot (technical or not), for copy blurbs, for fiction, game NPCs, etc, the models (especially 13B and up) can be breathtaking, even moreso considering they run on bottom-dollar consumer hardware (I paid $250 for the laptop I'm developing on).

There are of course some things that neither the local LLMs nor GPT4 can do, like create useful OpenSCAD models :)

Things keep getting better, newer quantization methods give you more smarts in the same amount of RAM at basically the same speed -- the models are getting better, there are more permissively licensed ones now.
Correct, zig currently does not do any of its own optimizations. It won't necessarily have identical results to clang because it'll generate equivalent but not identical IR and the optimizer passes may happen to do something different as a result, but it's not going to be consistently different.
I've thought about implementing this before (in a systemd alternative), but there are some good reasons to reboot. The kernel does leak, and only rebooting user space is a force multiplier for certain types of attacks where userspace is limited to an action a finite number of times per boot.

One recent article that comes to mind is this (though incrementing the counter here doesn't need a reboot to get hit):
https://googleprojectzero.blogspot.com/2023/01/exploiting-nu...

The other thing is that not rebooting the kernel removes the pressure on the kernel developers to reboot quickly. If people depend on it less, that can regress. systemd is big enough to affect that.
Do you get sparsity issues though? Say with a million tokens, what does attention between token 123887 “the” and token 4 “ing” even mean? You probably want less density of connections? Genuine question.
It looks like there are no provisions for double or treble damages. Look no farther for the reason airlines deny automatically.
Can you elaborate? I have no personal experience as I don’t travel enough, but I heard the reimbursement process is pretty straightforward?
There was this one bit in KQ4, I think near the end, where I got stuck for weeks.

A bunch of step stones going across a swamp, if I recall correctly, which needed to be navigated in order to get to the next screen.

I repeatedly tried stuff like "jump on stone", "jump across", "swim".

"YOU CAN'T DO THAT HERE"

It took weeks to figure out that all I needed to do was type "jump" without any additional text. Oh, the good old days.
Triple damages, that reminds me of something … if you happen to live in Massachusetts you might be able to send them a Chapter 93A letter (which entitles you to triple damages if they don't attempt to settle in good faith)
> I'm guessing not, but I'm having a hard time understanding why.

Second law of thermodynamics.
PC gamers with GPUs is probably much smaller than the console gaming market. And Nvidia did not entirely own that market either.
OpenAI Removes the “Chat with Code” Plugin from Store
It just dawned on me that linking to Twitter is now impossible on the open web. Unless you have an account, a person can not see the linked material.

This is a huge loss for the world, and makes me a bit angry.

Edit: I had falsely assumed that because GP missed out on the JITing etc. described in the linked tweet, that Twitter was still inaccessible to the open web. However, trying again now, Twitter is again viewable without an account. So Twitter's communication about needing an account to view it was lacking, but so was my diligence.
>A big reason that Nvidia keeps winning is that AMD doesn’t bother to compete.

AMD definitely wants to compete. Why wouldn't they want a piece of a trillion dollar market?

The problem is that AMD was almost bankrupt, had poor leadership until Lisa Su, and they were just trying to survive making console chips for Sony and Microsoft until Zen2.
You've angered every modern web app.

They're all configured to return 200.
The implication of Kholsa's tweet is spending one's working life at McKinsey. You're talking about alumni, people who no longer work at McKinsey. A bit of a stretch there ...

My reading of the counter post is that McKinsey had something to do with the fact that those alumni founded or help found or provided venture capital to startups. Maybe it did, maybe it didn't. A bit of false equivalence there.
Are these just mockups? This is a wonderful idea.
ChatGPT can't provide primary resources, and given its training material, can't put primary resources it has been given into a valid historical context. History as a discipline is safe.

What you're thinking of as history is just a collection of facts. And it'll lie about those.
It's been well documented by now that the number of parameters does not necessarily translate to a better model. My guess is that OpenAI has learned a thing or two from the endless papers published daily that your "instance" of the model is not what it seems. They likely have a workflow that picks the best model suitable for your prompt. Some people may get a 13B permutation because it is "good enough" to produce a common answer to a common prompt. Why waste precious compute resources on a prompt that is common? Would it not be feasible to collect the data of the top worldwide prompts and produce a small model that can answer those? Why would OpenAI spend precious compute time on the typical user's "write a short story of...".

I would guesstimate that the great majority of prompts are trash. People playing with a toy and amusing themselves. The platform sends those to the trash models.

For the other tiny percentage that produces a prompt the size of a paragraph, using the techniques published by OpenAI themselves, they likely get the higher tier models. This is also why I believe many are recently complaining about the quality of the outputs. When your chat history is filled with "have waifu pretend to be my girlfriend" then whatever memory the model is maintaining will be poisoned by the quality of your past prompts.

Garbage in, garbage out. I am certain that the #1 priority for OpenAI/Microsoft is lowering the cost of each prompt while satisfying the majority.

The majority is not in HN.
> are they using some subset of the language?

They're using a derived language called Hack.

> Does the compiled code use a garbage collector? Or reference counting?

Not sure but it's open source so I'm sure you can dig up the answers one way or another: https://github.com/facebook/hhvm
Yes indeed, I was just being a bit cheeky given GP's other discussion of the definition of 'opinion' :)
If there were millions or even thousands using 4chan the board would be moving so fast as soon as you found a thread to post in it would have been trimmed from the board. And 4chan is THE most popular image board.

I hate to be the bringer of bad news bud, but their isnt as many people online as you think there are.
This may be the difference between arbitration and court. My guess is the arbitration company doesn’t care if their biggest client is always lying or not but a judge might just ruin your attorney’s week if you give them lies to present in court.
https://jacobaldridge.com/articles/

I’ve not been especially active the past few years. Now doing something at least weekly, but via email and intermittently uploading to my blog.
I agree with that. What's good for the goose is good for the gander.
How many predictions of "catastrophic climate change" have actually come true in the past few decades? Some of us have lived long enough to realise the truth.
Zombie Twitter Has Arrived
I feel like I'm not smart enough to figure this out so I'll just ask. You are very against a scan of your face by the people who you just handed a photo id to because...
I think ChatGPT and LLM models in general are more suited for "What is xyz" or "How is xyz done" family of questions. Basically a smart search engine.

Beyond that it will simply have the output/personality of a person with rote-memory.
https://mpost.io/phi-1-a-compact-language-model-outpaces-gpt...

a 1billion parameter model beats 175billion parameter GPT3.5

OpenAI wants us all to drink the kool-aid.
https://skillenai.com/blog/

Writing about all things data science.

But the main purpose of my site is to scrape RSS feeds of data science blogs and serve them as an email digest (kind of like Google News alerts for data science tutorials).
https://skillenai.com/subscribe/ to subscribe.

I'm loving this thread of personal blogs, I may need to scrape it and add a bunch to my list...
:s/major/minor
Joplin as a FOSS app is really a good initiative and I keep trying it from time to time. However having used smartphones for more than a decade now (and being a mobile developer) I have realised that, whatever would be the reason for an Electron app (there might be valid ones like resource, time, target audience etc), an electron app just doesn't cut it. So I doubt I can use an electron app on mobile. Problem is it shows :(
I use an unscientific rule of thumb that 10-100x scaling is about the most to plan for except for exceptional cases. Anything beyond that ends up with overcomplicated bloat for a "tomorrow" problem.

Being able to handle spikes and iterate quickly is probably more important.
I did this move (then switched back) by learning from a PM I know, doing a lot of reading, then finding a PM role that wanted a strong technical background (in my case in ML at the time). Microsoft also had for a bit back then a habit of hiring ex-software devs to PM roles. Many people applying for PM roles are non or less technical so you get a leg up there to make up for other gaps. If you show some ability to take on PM-ish tasks occasionally, can learn fast, and are a double threat with software dev, you’ll find something.

Word of advice though, make sure it’s a role you’re willing to do for more then just because you think you’ll be in charge in some way (CEO of the product). That simply isn’t a real role and PMs in many companies have a wide range of competency so you can get stuck in a low quality group with a lot of MBA types where you aren’t really learning to build and ship but instead how to have meetings or keep your higher ups happy. Every company (and many times every org) has different PM expectations. I also really missed being on the development side (though I ended up mostly in engineering leadership and now running a startup so a stint in PM did help broaden my perspective).

This is also a role that became bloated in numbers so many companies aren’t hiring them (and seem to be cutting down on them to make a better ratio) so you’ll be competing with folks with PM experience for fewer roles.
24GB is still less considering the amount of bloatwares these Chinese brands put in their garbage phones and the number of crappy apps run in the background 24*7
The only thing we do know about “intelligence” is that more compute = better performance on tasks we use to evaluate increasing generalization on tasks.

So map out the computing power and hardware requirements of an average adult human with IQ 100 and no disabilities and that should tell you what you need.

It’s probably 3x harder than just a brain.
Last November he tweeted about the people he'd fired, sarcastically saying "I would like to apologize for firing these geniuses. Clearly their immense talent will no doubt be of great use elsewhere."

Can't make this shit up.
C doesn't even originally have true/false, I think you may be conflating the two concepts that "any nonzero int is truthy" and "boolean expressions evaluate to ints". The standard mandates that boolean expressions like equality always evaluate to 0/1.
Location: Lima, Peru (UTC -5) open to work on US timezones
Remote: Yes
Willing to relocate: Depends on Location
Technologies: java, rest-assured, selenium, cypress, jmeter, docker
Résumé/CV: https://www.linkedin.com/in/renzhonrabines/
Email: renzho_307@yahoo.es

Senior QA Engineer (Manual and Automation) with 8+ years of experience, I have a knack for finding bugs and automating tests. I also enjoy measuring the application performance. I'm looking for a new challenge where I can apply my skills and learn new ones. I have experience working with Credit Sesame, a leading fintech company, as my last client.
Until every fucking wanker who reads this article adds profanity to their shitty code expecting their bullshit to be better.
Capital One does too. I’ve used Zelle through Capital One’s website for years, and have never had the mobile app installed.
This reminds me of the episode of South Park where Jimmy is able to tell if a news article is an advertisement or the news.
Joplin and nextcloud/WebDAV was horrible. Horrible. I can’t go back, trilium is way more extendable
We received €600 each for a flight out of OAK where the plane was late, followed by really late, followed by completely cancelled and rebooked for the next day. Ended up leaving 25 hours later than planned and losing a day from the vacation, but it was a nice payout given that the seats were only $200 to start with.
I recommend you read the FAQ for the implications.
And as homework for the reader, consider the banlist is a bloom filter
Which jurisdiction was this lawsuit filed?
> a determining factor in whether somebody will use a service

Threads is currently not available in Europe because its privacy policy isn't compliant with EU law, that's literally what the article is about. We're not talking about individual choice here, or absolutists behind Tor. I don't understand what your post has to do with the topic. Clearly we have with privacy legislation at least accomplished that Meta must follow the rules or not operate here.

You're right that individual users agreeing with TOS's is meaningless, but we've been beyond that for years.
they are popular because insurance, law, and regulations. it's hard to measure a corps security posture in a way that can apply to everyone and every thing. read them, know them, and if you are required to, meet them. but don't think for a second having all the boxes ticked gets you secure.

in fact I would suggest cis controls over nist and iso for pretty much everyone, but nothing beats knowing your environment inside and out, and striving for 100% visibility.
Trilium
Being compliant within any of those frameworks does not make an organization secure. It's a good place to start, and will make the auditors happy, but assuming that (compliance equals secure) is a huge mistake.
A great amount of modern systems is copying data from A to B to C. The construct of frontends and backends implies it, or middleware, or proxies, or distributed storage, or blockchains. Even in the most complex systems, latency is one of the easiest core metrics to measure, and is always a priority. It is always lower latency to prefetch the inter-system pipelines, or to use optimistic concurrency and to preprocess data before it has been authenticated.

Chunked streaming can make the difference smaller, but even that "small" difference is beyond what is relevant to say ... filling an L1 cache, or waiting a round-trip. Some of the cases of "read before auth" I've seen have been on very small messages, but in contexts where the incentives are even further driven up, like trading or bidding protocols. It just left me thinking that we should enforce AEAD mathematically. Many practitioners often assume it already is enforced!
Just to reiterate on this point: Pretty much every Vulkan game on Windows forgoes using Vulkan Swapchains in favor of presenting from compute and using native DXGI Swapchains. If you are shipping a production quality game or application, you really want to use the platforms native APIs to get the full capabilities.
Arti 1.1.6 is released: Now you can connect* to Onion Services
Well, that would keep him in the news...
pankajpipada.com
What do you think is the connection between Australian bushfires and climate change?

Did Australia not drastically cut back and stop the amount of back burning that Australia used to traditionally do in order to prevent larger bushfires? You only have to ask anyone who has lived for a while in an at risk area to discover first hand that these activities had been curtailed and stopped for quite a few years.
It's just the bunny slopes or foothills of extremist signalling, having to demonstrate that you're the sort of person who doesn't get upset at the things that cause other people grief and despair (which of course you take every opportunity to exaggerate) with the presumable but unspoken conclusion that you're the AntiSnowflake gifted with exceptional reserves of mental fortitude or maturity. Like bullshiting, these positions don't care whether the arguments they are contradicting are right or wrong, they only care that it in opposing them they can project an image of cool unconcern.

This is what being an internet tough guy has sunk to in the age of twitter.
All fair points. However, I was taking issue specifically with the claim that the "Gaming industry is mostly using DirectX or Gnm/PSSL".

It would be hard to quantify exactly how much of it is using OpenGL, as a percentage.

However, for a very rough upper bound I quickly looked up these:

* Mobile gaming apparently makes 52% of the entire gaming market in 2023

* Android is 78% of mobile gaming

That could mean OpenGL makes up to 40% of the entire gaming market just from Android.

Although I have no idea what percentage of Android games use OpenGL and wouldn't know how to look that up. I also don't know how accurate those percentages are. I got them from brief Google queries and got both the 52% and 78% figures from the featured snippet.

But even if that 40% is much too high, we still need to add switch and PC games and I would find a figure of 30% of the gaming industry using openGL to be believable. That would put OpenGL as the largest API which I didn't expect, even as a possibility.
And here I am halfway through Michael Crichton's novel "Prey" ...
Nvidia knows that the profit margins at mid-tier GPUs are tiny - so they're pushing people to buy the 4070, 4080, and 4090.

Wafer prices have increased drastically in the last decade - to the point that midrange cards are no longer midrange priced.

It simply isn't really profitable to make real midrange cards anymore.

In addition, discrete GPUs market is a declining market and has been for 15 years or so. Therefore, in any declining market, the low-end and mid-range products will get squeezed and the high end will get pushed. The remaining buyers of discrete GPUs are willing to pay higher prices. Those who don't will buy a laptop with an Nvidia GPU already in it or some sort of SoC (like Apple Silicon/AMD APUs/Intel APUs).
Why does OpenAI demand your phone number, and a particular KIND of phone number at that? For example they won't accept VOIP numbers. I'm not about to give them my real phone number.

It's a deal-breaker for many.
They’re literally protesting right now in the streets in France, so I don’t know what you’re talking about.

No country is a saint, but you should stop with the whataboutism.