skysight-inc/HackerNews huggingface dataset:
SEEKING WORK | Europe/North America | Remote

Freelance Sr. Engineer with Kubernetes/DevOps/Golang Focus

Location: Berlin, Germany
Remote: yes
Current preferences:
Kubernetes, Golang, Kubernetes Operators, Ci/CD, Terraform, Ansible, ArgoCD, Containers and automating everything
Languages: German (Native), English (Native)
LinkedIn: https://www.linkedin.com/in/johannes-h%C3%B6lzel
Github: https://github.com/jhoelzel
Blog: https://www.hoelzel.it

Hi, I'm Johannes, a tech specialist with a focus on Kubernetes. I have been working in the industry since 2003 and have extensive experience building and managing large-scale systems using Kubernetes, with a focus on Amazon AWS, Microsoft Azure, and bare-metal deployments.

In addition to my technical skills, I also have a background in psychology which gives me unique insights on team leadership and communication. I have a proven track record of leading and creating successful international teams.

One of my specialties are bare-metal kubernetes deployment with RKE2 or K3s which are CIS compliant and use SELINUX under the hood. They can effectively be used to bring your wind to your excisting datacenters and hardware or create hybrid systems that easily connect your online and on-premise servers. My Mantra is that in then end of the day your kubernetes clusters should be able to run anywhere with minimal modifications, because that is the promise kubernetes actually offers.

I'm currently offering my services as a freelancer and would be happy to discuss potential opportunities involving Kubernetes. If you're looking for someone with seniority and experience in the field, please feel free to reach out. I have a wealth of experience with Amazon AWS, Microsoft Azure, and bare-metal Kubernetes and am confident in my abilities.

You can read some articles I wrote:

https://www.hoelzel.it

or contact me on my linkedin:

https://www.linkedin.com/in/johannes-h%C3%B6lzel

or see some of my work on Github:

https://github.com/jhoelzel
No one’s selling a retail product now, but there’s definitely going to be investors speculatively pushing money into the space
Elon Musk’s X sues anti-hate researchers
I've actually had no trouble writing slides in Markdown and then converting them into presentations with Pandoc. If you don't need a very complicated presentation, this is my preferred method.
Interesting.

In Europe (at least the UK and Germany) it seems to be the opposite. Outside of a big-city Uber is non-existent and you are relying on local taxi-firms.
I'm going to be honest, I did this evaluation several months ago and I don't remember all of the exact points. If I remember:

* I did not like that it was an alternative to a different Facebook rich text editor (draft.js)

* Very React focused (makes sense, it's a Facebook/Meta project) - even applying concepts. Here's an excerpt from their site: "If you've used React Hooks before, you can think of $ functions as being something that follows a similar pattern. These are functions that show their intent as to where they can or cannot be used."

I don't want to use React Hooks or things designed to be like React Hooks.

* Newer and less features/polished. Looking at their official project site, there's way less features already available. That means more custom code you have to write.

* No standard schema/for formatting rich content
> After this hype cycle ends, things will probably bump along slowly for a decade or so, then suddenly you’ll look up and they’ll be everywhere, and you’ll wonder “when did that happen?”

The reason this is incorrect is that “AI” isn’t one capability. It’s a huge swath of capabilities under the umbrella of “automate X”. All of them have been enabled by software and hardware improvements over the last decades. The underlying technologies aren’t that new in many cases either, it’s just the scale that’s different.

After we get bored of one huge new capability, another comes along. A year ago everyone was talking about automatic image generation. Now it’s automatic text generation. There are plenty of other things we’d like to automate. So the hype train is likely to continue for quite a while.
It's hard to find the right solution. Users complain when the UI changes, for better or for worse. Users complain when the UI doesn't change and looks 10 years old. There's no good option
That article specifically discusses water filtration plants that are handling concentrated PFAS after filtering them away from drinking water. That the small fraction of them flowing through water treatment facilities can be broken down with special handling (which that article also says will not be ready for the market for some time) does not negate the fact that in the environment / our bodies, they are extremely slow to break down. I think it's obvious even to laypeople that the label is not literally true (nothing lasts forever), but it's still an apt descriptor. Even if municipal water can filter them out and break them down, these chemicals will be literally in our bodies and environments for the rest of our lives.
In low-temperature (liquid helium) superconductors electrons start slightly sticking to each other. This makes their energy spectrum quantized (I mean, even more than usual), so to transfer any energy to electrons it has to be in a large enough chunk to kick them apart.

And cold atoms don't have enough thermal energy to do that, so there's no energy transfer between atoms and electron pairs.

In high-temperature superconductors (liquid nitrogen) something similar happens, but the exact mechanism is still unknown.
Not unless you ask. Resumes omit many things due to length constraints, and the candidate might prioritize recent work over quality work if it's too long ago.

Legacy skills are important too, but those details don't always make the cut in both the resume and job description.
Type theory has applications far beyond readable documentation. It is the basis for modern science.
He'd also name another child XLK99.
For the first example, I think that was just due to the specific problem being solved. I can tell you there are a ton of places that aren't yet "solved" yet, and that aren't trivial to solve either. One thing we haven't discussed in this conversation is the data itself, and cleaning up that data. Rad AI probably spent more money on staff cleaning up data than they did on model training. This isn't trivial- for medical grade stuff you need physician data scientists to help out, and that field has only really existed since 2018 (which was the first time the title was listed in any job listing). The reason background removal is "mature" is because it's not that hard of a problem and there's a good amount of data out there.

I also think that you're way off on the second point. I'm not saying that to be rude, because it does seem to be a popular opinion. It's just that if you read papers most people publishing aren't using giant clusters. There's a whole field of people who are finding ways to shrink models down. Once we understand the models we can also optimize them. You see this happen in all sorts of fields beyond "general intelligence"- tasks that used to take entire clusters to run can work on your cell phone now. Optimization is important not just because it opens up more people to work on things, but also because it drops down the costs that these big companies are paying.

Lets think about this in another direction. ML models are based off of how the brain is thought to work. The human brain is capable of quite a bit, but it uses very little power: about 10 watts. It is clearly better optimized than ML models are. That means there's a huge gap we still have to fit on efficiency.
LUMI as an "AI customer" has a:

- low-budget: tax payer supercomputer for tax payer phd students

- high-risk tolerance: tolerate AI cluster arriving 5 years late (Intel and Aurora), lack of AI SW stack, etc.

- High FP64 FLOPs constraint: nobody doing AI cares about FP64

Private companies whose survival depend on very expensive engineers (10x EU phd student salary) quickly generating value from AI in a very competitive market are completely different kind of "AI customers".
Terraform Cloud experiencing workspace errors
Protestant work ethic needs constant surveillance from above or else all humans do is sinning and slothing. Completely opposed to the self-employed employee model that gets stuff done out of intrinsic motivation.
It almost feels like we're back in the days of Lavoisier. Scientists staging elaborate public experiments, blowing things up to support or debunk a popular theory. Deadly rivalries, publicity stunts, each new development a matter of personal, institutional, and national hubris.
> The answer is 4. Can you believe it? It's 4. Just like the four years of unprecedented success we had in my first term.

Unironically good public speaking lmao
> jiggawatts's gripe is that the researchers seem generally incapable of effectively using the cameras they already possess (including iphones)

I’m not sure why there’s an expectation that they know how. Expertise in one subject doesn’t make you capable in others. I’m not sure if you’re ever worked with phds before, but there’s often an extreme contrast in ability and lack of ability, depending on the context.

There’s a good chance these people don’t spend much time messing with their phones.
Throughout this whole saga I've had this feeling that at the very least we can rely on China to really pursue this new development to it's logical end. It's kind of sad, but I don't think I can say the same about the US at this moment. You know for a fact China's going to JUMP on this, figure out if it works or not, and iterate.
Think your EV is so efficient that you only need to charge it once every 5000 miles.
To be fair to Nim, only Python has the huge ML ecosystem of numpy, scipy, pandas, opencv, pytorch, tensorflow, keres... Doing ML/AI style work in anything but python is really hard!

That said Nim does have the nimpy library that allows for pretty seamless interop with python. Which means you can just import PyTorch, or scipy, or opencv and use them in Nim.
A huge renaissance in desk toys, at the very least!
Kinda? You'd expect flat bands from putting a copper atom into a big insulating supercell. The population of the d band is interesting, though. I don't find it super super compelling, but it's certainly not nothing.
$100m is not a problem if a way can be found to allow millions of users to contribute idle resources to the task.

Yes, that's like saying "Just invent a practical fusion reactor"... but we're also trying to do that, and this is almost as important.
Show HN: Release Train – Continuous Releases Made Easy
Release Train will automatically create a new GitHub release every time you merge a
pull request into main or whatever release branches you set up. It's inspired by
semantic-release[1] but takes a different approach. Instead of using commit messages
it uses PR labels to determine the type of release. This makes it easier to use.
It's also a single binary so it doesn't require npm or any other package manager.

It comes in the forms of both cli and GitHub Action.

The downside of this approach is that it ties you to GitHub. It could be extended or
forked to support any platform that has something like a pull request with labels.
I'm comfortable adding that to the technical debt I will incur migrating away from
GitHub.

I would love to get notes from the hn community on this.

[1] https://github.com/semantic-release/semantic-release
https://news.ycombinator.com/item?id=36957558 answers your question.
LK-99 is already patented so even if Elon were making a ton of it, he couldn't do much in his products without licensing it from the creators.
Try a markdown editor sometime and never fiddle with formatting, fonts, font sizing, layout, etc again, at least not during the writing stage. I like Typora, obsidian, and especially ulysses
Location: Lehi, UT
Remote: Yes (7 Years)
Willing to relocate: No
Technologies: JavaScript, Python, React, Docker, PostgreSQL, RDS
Résumé/CV: See link below
Email: vibrato.carol-0g@icloud.com [Burner Email since these get scraped, works for now]

I'm a Lead Software Engineer and have 12+ years of experience. Over the years, I've gotten pretty good at JavaScript, Python, React, Docker, PostgreSQL, and RDS. I've led teams, made cool stuff, and saved companies lots money. Now, I'm looking for a new place where I can keep doing that.

Resume: https://www.knbrlo.com/ken_barlow_resume.pdf
Out of curiosity, why are you writing C99 in the year 2023?
You asked about `git fetch`. If you change your question to `git pull --tags` then yes, the answer is different.
It takes very little to try and explain a concept to someone asking for pointers — assuming of course, you know the topic at hand. Your response is as unhelpful as it gets.
> The upload performance of HTTP/2 has been significantly improved starting with Firefox 115.0, particularly on those with a higher bandwidth delay product (i.e., networks characterized by both high bandwidth and high latency).

This sounds interesting, anyone aware of the details?
> The rules are designed so that there will be absolutely no encumberance to them using your submission in any way that they want (if you win 1st, 2nd, or 3rd place). From limiting datasets to stipulating the license to a requirement of patent unencumberance and broad IP permissions.

The rules not only do that for them, but for anyone else (the direct grant of rights would be sufficient for them, asking for the most permissive license available where there is a choice establishes that for other people.) This is consistent with this being a public interest project.
Dig a 1300m shaft in the ground. Robots would be ideal for construction, as a large cistern would need to be built at the bottom.
It would be possible to make iterators more SIMD-friendly than they are today but that would come at the cost of interpreting what the user might have intended and then dropping or introducing additional side-effects (e.g. by skipping things or grabbing a few more items than needed).
Without an effects system that makes purity available on the type level libraries can't even conservatively apply those optimizations on pure lambdas because they have no way to tell the pure and impure ones apart.
The S curve only makes sense for one technology at a time. AI isn't one technology. It’s a category of technologies.
There are post-quantum-computing encryption schemes [1], thankfully.

[1]: https://en.wikipedia.org/wiki/Post-quantum_cryptography
Location: Cameroon

Remote: Yes/Hybrid

Willing to relocate: Yes

Technologies: Docker, Python (Django & Djangorest, Flask, pandas, numpy, sklearn), PHP (Symfony, CI4), Supabase, SQL (MySQL, Postgres), JavaScript (React, VueJS)

Résumé/CV: https://mistaia.github.io

Email: ismaelabbo46[at]gmail[dot]com

As a backend engineer, mostly looking internship opportunities but have also a few professional experiences.
The purity required in these types of materials is high enough that glue would interfere with the result.

But for example when refining YBCO (another famous superconductor - but one that requires liquid nitrogen cooling to demonstrate its properties), you can take YBCO and grind/blend it up into a powder and press the powder into whatever shape you want with a die cast and then re-bake the new piece.

https://www.youtube.com/watch?v=RS7gyZJg5nc
Mostly, the only formatting you don't want to put off can be taken care of with <p> and <h#> tags. Depending on the genre, style, and so forth, maybe the occasional <blockquote>.

I wouldn't want to do non-fiction though... that'd just be torment.

I don't know if it will make you more productive, but it won't make you any less.
Yes "what about"
The logic employed was:

Every Uber driver I’ve had in US and Canada are happy with driving for Uber. One guy I had the other day drives under as his second job and He says it pays his rent, his car payment and gas and his primary job goes straight to savings.

I wrote a comment using similar logic. Every child I've met working in mines was happy to be able to provide money for their family.

The logic is bad. It's poor reasoning to say, "Every person I've met doing X is happy. Therefore letting people do X is a good thing." I was pointing that out.
True, I should properly say that the publicity and a lot of SV focus went to full self-driving. Thank goodness people are actually pushing the less glamorous topics.

That said, it would be great to see more public focus on solving problems like keeping bikes and pedestrians from being run over. In my town there's a lot of talk about the issue but it's not been backed up by initiatives that actually change the numbers. (Which are bad.)
I gamified my debt repayment with a popular free online financial service that has a net worth chart that shows assets, debt, and a net worth trend. Getting those red lines below the line to go up was a huge motivator for me and even if my debt wasn't at zero, seeing it tic up over time was rewarding. slowly but surely, I did it.
That one feature is a major make or break feature imo.
Shortwave | Senior or Staff Software Engineer | ONSITE in San Francisco | $140k-$250k base + generous equity

I previously cofounded Firebase (YC S11) and sold it to Google, and most of our team is ex-Google / ex-Firebase.

Shortwave (https://www.shortwave.com/) is building a cybernetically enhanced email client. We're bringing the power of LLMs to your email to help you get things done. On top of this, we're bringing users a modern messaging UX and best-in-class productivity features. Email is an enormous market (4.5 BILLION users), and we're working to build the next unicorn productivity tool.

Imagine an AI virtual assistant with perfect knowledge of every message, attachment, receipt, newsletter, etc you've ever sent or received. Your AI assistant can answer questions about your email ("which candidates in my inbox have experience with Kotlin?") and act on your behalf ("Draft responses asking them to schedule a time with me").

We are building a world-class AI software team. We use a modern tech stack (Typescript, Kotlin, K8s, React, cutting-edge ML stack) and ship 5x+ times per day.

We want the best and are willing to pay for it. We like generalists with strong CS fundamentals, app development experience, scrappiness, speed, and grit.

Come help us build the future. Email if interested: joinourteam@shortwave.com
What does your contract/partnership agreement say...?
You will hear many explanations, but the real one is that the US leadership in hard science is fading. We are too cerebral and cyber - Asia has picked up the mantle now.
Thank you for your comment. I am the app's creator, and English is my second language. This is a work in progress, I hope that more feedback like yours will make this app better in time.

Would "Total assets" work better for you?
Collide+Power Side-Channel Attack
Converting magnetic force into electrical current (electromagnetic induction) is the principal behind of all electrical power generation. SMES (superconducting magnetic electrical storage) is essentially an inductor made using superconductors. Electrical current gets converted into magnetic force and then back into electrical current when the circuit is discharged.
We've been happy users of Tiptap at Sudowrite, and recently finished converting 1M+ documents from Quill (with Firebase) into Tiptap (with self-hosted WS Hocuspocus), running admirably @ 50 updates per second. Happy to answer questions on how it's been going.

(psst, we're also hiring!)
I wonder which airport doesn't already have flat rates...
GPT-4 has a capped number of responses, it also costs $20/month. If it's only marginally better than GPT-3.5, why would I pay for it?
Yeah, it's this.

Having worked for a number of companies implementing these measures, there's no malicious intent, they are rolling their eyes the whole time. It's just a box they need to tick. Everyone wishes it would just go away.
Intel's Fred Getting Ready to Meet the Linux Kernel
In my local Walmart, these screens would get drawn all over pretty quickly after they're put up. I'm sure there are nice Walmart where this will work, but I'll see an ad with male genitals drawn over it.
I had a hand-full of friends and coworkers who felt this way. Talking to them about it broke them into three broad categories:

Enthusiastic extroverts who needed face to face interaction to stay happy. The pandemic limited their social options and they longed for the amount of in person interactions they had when working from the office.

Easily distractable people unable to set up a distraction free environment at home who got stressed because their productivity suffered. I thought I was going to be one of these people because I had a pre-school aged child who was also stuck at home but it didn't end up being that much of a problem for me thanks to my wife being very proactive and able to juggle her school schedule to when I was available to parent. Some of my co-workers privately admitted that they couldn't focus on work when their hobbies and house-chores were so close at hand.

Those who had issues in their home environment that caused them grief and they relied on the office as an escape rather than fixing their problem. These were the people who got divorced or broke leases at the beginning of the pandemic as they were unable to live 24/7 with the people they had been able to deal with as long as they had 40+ hours of break from them every week previously.
Is Nim 1 going to receive patches going forward? Or is it a hard upgrade?
I like the support for Vector DBs and LLaMa-2. I'm curious as to whether and what influences compelled PromptTools, and how it differs from other tools in this space. For context, we've also released a prompt engineering IDE, ChainForge, which is open-source and has many of the features here, such as querying multiple models at once, prompt templating, evaluating responses with Python/JS code and LLM scorers, plotting responses, etc (https://github.com/ianarawjo/ChainForge and a playground at http://chainforge.ai).

One big problem we're seeing in this space is over-trust in LLM scorers as 'evaluators'. I've personally seen that minor tweaks to a scoring prompt can sometimes result in vastly different evaluation 'results.' Given recent debacles (https://news.ycombinator.com/item?id=36370685), I'm wondering how we can design LLMOps tools for evaluation which both support the use of LLMs as scorers, but also caution users about their results. Are you thinking similarly about this question, or seen usability testing which points to over-trust in 'auto-evaluators' as an emerging problem?
actually, people in large groups tend to estimate correct answers quite well when you average their responses
> CSS, and styling pages in general, has always been a mess. Either have a disaster trying to name all your classes, or abuse HTML by using a billion utility classes a la Tailwind.

In my book this is not a problem inherent to CSS but, well, how to name classes and stuff in your HTML. At this very moment writing CSS is just amazing and many of its "new" features are what many of us have dreamed about for years.

Still I have another unpopular (and for many of you, stupid) opinion: I'd like it if HTML, CSS and JavaScript had all the same syntax. Like QML's.
Linux 6.6's Cpupower Utility Enables New AMD P-State Features
It does make you selfish, though. You'd force people who don't want to RTO into the office because you prefer it?