skysight-inc/HackerNews huggingface dataset:
Stevens Capital Management LP | C++ Market Data Feeds Developer | Radnor, PA | ONSITE | www.scm-lp.com

Stevens Capital Management LP (“SCM”) is a registered investment adviser that manages a multi-billion dollar hedge fund that has been in business for 25+ years.
SCM specializes in the rigorous development and disciplined implementation of empirically based quantitative trading strategies. Our highly productive team works in a fast-paced collegial environment, utilizing extensive data sets, technology and the scientific method to devise and employ trading strategies throughout the world’s most liquid financial markets.

We are seeking highly driven, production-oriented developers who possess strong technical skills and the ability to work in a fast-paced collaborative environment.

This is an opportunity to work in a real-time environment where you can make immediate contributions. You will be part of a small team building real-time data feed handlers for the largest financial exchanges such as the NYSE, LSE, TSE, CME, BATS, ICE and NASDAQ.

Primary Responsibilities
•	Develop and implement infrastructure to support market data and trading.
•	Develop and maintain market data feeds.
•	Build and design large scale applications, with a focus on reducing latency and improving the performance of the system.

Requirements
•	High proficiency in C++ development in a Linux environment.
•	A Computer Science degree.
•	Outstanding problem solving skills.
•	Familiarity with multi-threading and networking protocols (TCP/IP, Multicast preferred).
•	Experience in a real-time environment in the Financial industry.

Please submit your resume to: recruiting@scm-lp.com
clickbait headline + reports on other sites content, please follow the guidelines: https://news.ycombinator.com/newsguidelines.html
I was talking more about the fact that they were mostly stuck doing "administrative tasks," presentations, code reviews, data migrations. Things that don't exactly contribute to the progress of the project per se.

Edit:
Actually the interns were doing the refactoring too. This project is a bit outlier however as the code base was completely new, like 3 days old when we joined.
Well, Mac has many other text editors of the similar or better quality. I think nobody feels any need to spend time porting Np++ to a new platform and then supporting it.
I still don't understand what happens after all the bitcoins have been mined.

It seems to be designed to just fail eventually and be replaced, which I cannot reconcile against the elegance of the rest of the design.

To clarify: bitcoins can go away forever. About 6 years ago and had a wallet with a couple bitcoins in it. I have lost the key to that bitcoin wallet and if I can't find it, and noone else can find it, those bitcoins should be gone forever and irreversibly, right? If it were possible to recover the key to a wallet you dont own and spend coins that are not yours none of it would work.

So, once there are no more new coins, eventually all the coins will be lost. Am I missing something?
Making computers incredibly simple to use seems to have worked out well in the case of the iPhone. Lots of common usability problems in computer UI simply went away with a much better design. It's hard to say where the mobile-phone industry would be today if that shift hadn't happened in 2007.

Perhaps the same could happen for computer programming. For example, in the 1990s, HTML introduced coding to lots of people who otherwise probably wouldn't ever have considered it. A forgiving declarative interface was a lot more appealing than learning what compilers, linkers, functions, parameters, and APIs were.
Stevens Capital Management LP | Technical Recruiter | Radnor, PA | ONSITE | www.scm-lp.com

Stevens Capital Management LP (“SCM”) is a registered investment adviser that manages a multi-billion dollar hedge fund that has been in business for 25+ years.
SCM specializes in the rigorous development and disciplined implementation of empirically based quantitative trading strategies. Our highly productive team works in a fast-paced collegial environment, utilizing extensive data sets, technology and the scientific method to devise and employ trading strategies throughout the world’s most liquid financial markets.

We're seeking a technical recruiter with extensive experience recruiting software developers to work in a fast paced, high performance computational environment. Candidates should be familiar with the requirements of highly selective, data intensive, quantitative research-driven organizations, and possess an established recruiting network.

Primary Responsibilities:

•	Design and implement tailored recruiting strategies.
•	Identify and prioritize recruiting sources and networks.
•	Work with colleagues to develop job descriptions and specifications.
•	Source and attract highly qualified candidates.
•	Conduct interviews and employ tools and methods to assess applicants' skills, experience and aptitudes.
•	Represent SCM at recruiting events and functions.

Requirements:

•	Proven experience recruiting software developers for highly selective, data intensive, technology reliant organizations.
•	Solid familiarity with the personnel and technology requirements of a high performance computational environment.
•	Established recruiting contacts in software development and the related academic communities.
•	Experience recruiting for low latency securities trading organizations is a strong plus.
•	Creative thinker who can generate innovative recruiting strategies.
•	Excellent communication and interpersonal skills.

Please submit your resume to: recruiting@scm-lp.com
Wine Into Fire: AI-Generated Poetry
Well, most fire extinguishers need to be checked every two years. So perhaps you extend the period to two years for those.
To be fair, his background is in social work and public policy; Hassabis is the technical lead, Suleyman is very much focused on strategy and societal impact.
Seems unlikely. The focus seems to be on improving AI through "vision". The idea is to make the AI learn skills the same way a human would (at least in the first years of life). Google's AlphaGo also learned from screen pixels.

So these would be human-like bots, rather than bot-like bots, like you normally have in games. The bot would simply learn by doing, until it masters the game, not by getting access to game algorithms.
Ask HN: Bootstrapper on the brink, what to do?
I have a small bootstrapped business. Have been working on it for about a year in my spare time. It started out as 5 hours a week, then 10, then 20. Right now it is demanding 30-40 hours of work per week.

The problem? I have a fulltime job. I cannot do awesome at both. Burnout is a very real possibility. My choices are:

1) Continue to fight the bootstrap fight. My calculations show that in 6 months I will reach the point where I can pay all business expenses plus my salary full time, so I can quit my dayjob. If I make it through to this other side, I have my dream. 100% of a business, and full control of my destiny.

2) Go raise a seed round. On a few 100k, I could hire a few employees + quit my day job, and really kickstart the entire thing. I could add 2-3x the features in the next year of what I could in #1 above.

3) Compromise. Somewhere between choices 1 and 2. My projections say that for 50k I could quit my day job and make the plunge (hiring no extra staff). Then in 6-9 months, I could start to hire. It would be less stressful than #1, but slower growth than #2. I have a few options for funding. I can pull it out of house equity, I can borrow from friends and family, or similar.

For a brief summary of where the project is at.. it is a b2b SAAS app. Currently bringing in $1500 per month, and has grown roughly 100% for the last 3 months ($350 -> $700 -> $1500). Not expecting quite that pace to continue, but I have a pretty big backlog of customers I cannot fully get going with my limited time.

Smart people tell me #1 is sweet. To come out on the other side of a new and growing business with no debt and a profitable business. But if a seed round is going to cost me a few % of my ownership, I am right now (in the pile of work I have in front of me) having a hard time caring about 5-30% of my company. I mean 95-70% of a lot of money is still a lot of money.
DeepMind sounds more and more like IBM Watson by the day. Both created AI engines for games (Jeopardy, Go) and are now focusing on the medical market. The two examples of actual AI applications cited in the article focus on DeepMind's healthcare efforts:

The company is working with the National Health Service (NHS) in the UK on a project around the early detection of acute kidney injuries. Critics, however, argue that the collaboration with DeepMind is wider than the company and the NHS previously disclosed. In addition, it’s also working with the Moorfields Eye Hospital on looking at how it can use the hospital’s eye scans to diagnose eye conditions better and faster. The NHS, however, mostly used its own algorithm in its project, with DeepMind focussing on the front-facing app. Suleyman argued that this is due to the fact that it’s still early days for this collaboration, which only started 12 months ago.

So in the health space they're currently doing anomaly detection and building applications for their clients. Sounds very Watson/consulting. Lots of money in healthcare due to the amount of data generated and the complexity of building regulation-compliant.

Judging from their website, they've also built an algorithm for reducing cooling energy usage in Google's data centers.

There are a ton of IoT platforms that are currently competing to connect a bunch of industrial/medical/automotive/aerospace and defense devices and servers, analyze that data with machine learning and statistical techniques, make it easy for users to build their own cloud/edge applications, and eke out every last drop of efficiency they can for their customers.

DeepMind is fortunate to have Google's brand, infrastructure, and reach. I'm just not sure what else separates them from any other "AI" (read machine learning/algorithm-building/efficiency consultancy) out there.
To me this is actually an argument against extensive moderation mozumder is suggesting.

Echo chamber is still an echo chamber even if you like the sound of the echoes.
Paper is open access and freely available [1][2]

Quoted conclusion:

> In conclusion, our results provide further evidence that nut
> consumption may reduce the risk of coronary heart
> disease, stroke, cardiovascular disease, total cancer, and all-cause
> mortality, and possibly mortality from diabetes, respiratory
> disease, and infectious disease. In 2013, an estimated
> 4.4 million deaths may be attributable to a nut
> intake below 20 grams per day in North and South
> America, Europe, Southeast Asia, and the Western Pacific.
> These findings support dietary recommendations
> to increase nut consumption to reduce chronic disease
> risk and mortality.

[1] https://bmcmedicine.biomedcentral.com/articles/10.1186/s1291...

[2] [PDF] https://bmcmedicine.biomedcentral.com/track/pdf/10.1186/s129...
Chernobyl could produce 4GW of power before the accident. Solar currently costs about $3/watt, so the equivalent solar installation would cost $12 billion, and that's ignoring the part where solar generates less in bad weather and nothing at night.

Traditional nuclear power plants are very expensive, but that's because they're huge.
Entire article became moot once I saw a link to Cryptsy under reputable exchanges. Are you fucking serious? Author needs to update his resources.
Have kids. Validate their feelings. Set boundaries. Enforce boundaries. Talk with your kids. Teach them. Don't try to change them. Embrace them.

Spanking and timeouts are not required for this.
Getting the game state data means deciding a-priori what features the AI should learn on. The whole point of the deep learning paradigm is to allow a machine to learn such features that enable good prediction, visualization, generation (aka. hallucination), etc.

Instead, researchers have provided the raw feed input data to these agents with the hope that the learned features could be interpreted as game state data by humans.
> Apart from implementation details of hardware platforms and runtimes

The platform described to share all this knowledge and code is beyond what humanity can build today. The manifesto described that we share "All cells exist in a single, globally shared hierarchy". The trust problem has many forms, from trusted medical info on Wikipedia, Facebook fake news filtering, to open Github code with hidden backdoors.

See a list of 100+ projects that are struggling with trust and full decentralisation:
https://github.com/redecentralize/alternative-internet
Why use Maven when there is Gradle?
Seems like the kind of stuff you get at by combining sklearn's official docs with some material from one of the moocs (like udacity's machine learning class, coursera's etc.) + some wikipedia. This is my default style of learning: picking a "track" (whatever mooc or a cool side project idea) + lots of small specific resources.

I'm really curious why would you recommend and actual book?

It has all the chances to get outdated in a few months, while the separate resources will get updated for sure. yeah, there's some googling effort, but still...
I never liked the way Maven built projects - it just seemed like overkill for simple things. I tended to use hand-written Ant builds backed by Ivy for dependencies. Then again, I also build odd outputs, like self-executing jars.
Anyone can add to the title (2014)?
I'm the CTO of www.collaborizm.com it helps you find collaborators for your projects, would love to have your side project on there.
> Google's AlphaGo also learned from screen pixels.

Source? That literally seems to make zero sense to me. Go can be represented in a super-simple state. Why make it spend millions of cycles learning to categorize pixels into that state you already have?
Nobody likes that answer. Personal accountability sucks.
Court Allows IRS to Order Coinbase to Give Up Their Customers' Identities
While not an expert (and actually something of a critic):

I think the idea is that new bitcoins will be mined at a rate that will outstrip those lost. A LOT of the early coins were lost because they basically had no value. That was when mining was easy. Now, bitcoins have value and people are less likely to lose it. And mining is now harder.

Similarly, we migrated from people keeping their wallets in a text file (money in a mattress) toward lots of sites like coinbase that basically give this Totally Free And Unregulated currency a system of banks. That further decreases the likelihood of money disappearing, especially if said banks start offering interest in exchange for being allowed to do loans. That resolves issues of people like me having some in a wallet that they are unlikely to ever collect/convert to fiat (not worth the hassle).

So while bitcoin is likely to fail for MANY reasons, I don't think lost currency will be it (unless it is more stuff like that Japanese bitcoin bank that just went dark).
Kids often has a reason for doing things, including not cooperating. Where he trying to get attention? emulating? You can't reason with kids out of those.

Trying to scare kids into compliance is rarely a effective method, and has some very nasty side effects. If long term approaches can't be used, child proof gas knobs exist.
Lawyers cost money to fill the same long-ass forms that you can fill up yourself!
I think the term GAI/AGI isn't meaningless. It's just imprecise. But the phrase has value since there is no better term for "human-level cognitive ability".

I'm pretty sure Siri/Alexa/GoogleNow don't use rules. Like all modern Q&A systems like IBM Watson, they use a variety of statistical word match/associations and phrase/sentence response templates. Like Watson, the algorithm identifies the most probable word match to fill the void in your query and then inserts it into the most appropriate answer template. Yes, it's a bit hit or miss (like Watson answering "Toronto" for the US city with an airport named after a WWII hero). But if Apple/Google/Amazon adds some simple sequential disambiguation and refinement (clarification Q&A), I suspect this approach should answer most casual questions quite nicely.

IMHO, calling it "AI" means that the problem is not amenable to a closed form solution, so some form of iterative search and refinement is required. In venerable GOFAI parlance, AI problems are inherently 'scruffy'. Once the problem can be solved efficiently, it becomes 'neat' and it's no longer considered to be AI.

IMHO, most of today's progress in AI is scruffy (probabilistic word matches and deep learning), since they're driven not by formal internally-curated information but by smart search against presumed-relevant external referents, requiring secondary refinement -- a process that is largely inefficient and open-ended and error-prone, and will remain so indefinitely, I think, since we're not trying to improve the quality of the referent data, which is the weakest link in the cognitive chain.
Yep, no need. Lots of better alternatives out there.
>One of the first things you learn in Computer Science is that not all problems can be solved with a computer.

Oh ... could you elaborate? I think my cut-rate, community college degree skipped that part :) it seems like a useful thing to know!
Given that Jupyter works on a server / browser model, it should be possible to customize the browser without bothering the server. For instance, I imagine a plug-in that spiffs up the editing blocks within one of the major browsers. That way, you preserve compatibility across all browsers, but provide an option for those who want their preferred editing features.

Admittedly, I don't use a code editor, perhaps because I'm just too old, and got used to living without one. I remember when being able to edit a program in full screen mode was a big deal. But I certainly wouldn't turn down better editing for Jupyter.
How Bad Are Zillow “Zestimates”?
Agree, except with the 'nearly infinite' qualifier. We have some large data sets now and we can draw a cat. We don't know if we can build anything interesting with those data sets yet.
How to find local coffee shops in a strange city
Most (all? I can't remember exactly) of it doesn't use Scikit-learn. You actually implement the algorithms yourself and see what happens under the hood
If you can't show enough money in your bank account at the time of interview (we had bank statements for the last 3 days only), you have to talk about your straightforward plan about how to get a job ASAP. In my experience your plan has to answer the following questions:

What is your marketable skillset?

Where is this skillset needed (name at least 5 different metropolitan areas and their job market outlook)?

What are potential employers in this area?

What are your next steps to reach out and do some networking in your field?

What will you do to cover your cost of living before you get a full-time job? (part-time retailer jobs etc, or maybe something you had work experience while still in college)

How will you get the first references from US employers so you can hunt for your next job?

You might not be able to talk about all that, because your interview partner decides what to ask. It is a good idea to have those answers, and to try to get these topics into the interview when it is your time to speak. Be confident about your future as a highly skilled immigrant.

But talk about that very politely and friendly, even if you know more about your potential job. Treat your interview partner (the US consul) as an employer. You have to convince him you are a good catch for the country.

There will be a difference once you have your greencard and a SSN, because now a company can hire you without visa sponsorship. But you will need US references, because HR wants to call people you worked with. So get to know local people, maybe start as an intern, maybe work in retail, work in a non-profit, do whatever it takes to get a reference by your supervisor. You can do short term apartment leases in each metro area to go to meetups and have interviews with local companies. And you can do interview training and work on your resume with this non profit company: https://www.upwardlyglobal.org/ (You need some work experience in your local country to be eligible)

Please do not make things up and lie. You will get caught. Your interview partner is trained to find out if there is something wrong with your story. But you should show up prepared, have a plan, maybe back it up with some printouts, for example your action steps, the websites of Upwardlyglobal, temp staffing agencies in your desired areas, job listings in your field etc.

The more your prepare and rehearse what you are going to say, the less stress you will have at the interview. In the end it might be easier than you think , but if you don't have enough money to start in the US, you don't meet all the requirements for the DV greencard. Simple as that. So do your best to look like a professional and a goal getter.

All the best. It's a great country and worth the effort.
Finding local coffee shops can sometimes be challenging. Google Maps tends to show the national chains, and it's tedious to filter through the Starbucks, Caribou, Peet's noise.

Now there's a better way. Pass The Buck finds nearby local coffee shops while filtering out the big guys.
Its a wonderful tool! If you could shed some light on the stack used in the editor.
https://news.ycombinator.com/item?id=13077468
I'm on my second J1 Visa, it's pretty straightforward:

- proving to be a student

- proving that the job fits with the studies

- proving that the job is gonna be done in good conditions

- proving to have enough money to live there

- etc.
But the app is required for configuration, not for actually using your wifi, right? Perhaps I'm wrong.. The overlap for needing to configure your network and the internet connection being down is probably very small, although not non-existant.
> J-1 after it expires (1.5 years)

1.5 years might be for your case. For research scholars you can extend it for up to 5 years.

> But transitioning from a J-1 to a H1-B doesn't require waiting that much. I was out of the country only for 1 month or so.

The current processing time for an H1-B visa is eight months. You also aren't required to leave the country.

I'd be careful taking your experience and extrapolating it to all situations. People here may be mislead by some of the information you provided.
Sharks kill people also every year, but this fact do not makes Chernobil more safe.
They read the Mail and Express because their counterparts are biased and devoted to pushing narratives, and have little interest in informing anyone when it's inconvenient to their worldview.
AFAIK the health stuff at DeepMind is just one part, the research division is the main bit. Not like IBM Watson consultancy-pretending-to-be-AI-research.

> I'm just not sure what else separates them from any other "AI" (read machine learning/algorithm-building/efficiency consultancy) out there.

probably the amount of pure research they produce: https://deepmind.com/research/publications/
One could be charitable and allow the use of the word hemorrhage as a metaphor for iron-catalyzed lysomal rupture.
> It was very common everywhere until about 10-20 years ago.

I keep hearing this mentioned as why "kids these days" are so stupid/weak/emotional/etc, without any proof.

I'm curious if there is any (popular) research in these areas that I can show otherwise (or not!).
You are probably right, it was some time ago, but did they also not wanted other things that paper publications are required, like storing copy in some archive?

Anyway, accreditation would make it even more troublesome and still would not solve the root issue and even if we focus on scenario OP described: FB ranking the news by trust, there are still many loopholes here. Like publishing true news with a spin or simply spamming worthless articles "Random Celebrity said good things about President Candidate" - just that alone would still do the trick.