tbabej

The author of Poetry has an open Github sponsors account [0]. If you're using Poetry, or rely on it in the commercial context, I'd suggest investing into reliability and sustainability of your build tools :)

In my startup, I started to make sure that we allocate a small monthly budget to distribute between our open source dependencies, Poetry being one of them. It's always shocking to find how little support the projects are getting - the author of Poetry currently has 11 sponsors (with majority of those being individuals).

[0] https://github.com/sponsors/sdispater

I did look into it, but its focus on animations gave me the perhaps unfair impression that the more mundane text UI elements (i.e. forms, etc.) would be a second-class citizen.

Looked like a really great library to build a text adventure game with though!

It's great to see some more competitors on the TUI front of the Python ecosystem! I recently tried multiple existing frameworks and was not particularly happy with the state.

Here are the main contenders for libraries that provide higher-level API than urwid/ncurses:

* Picotui, https://github.com/pfalcon/picotui

* Npyscreen, https://github.com/npcole/npyscreen

* py_cui, https://github.com/jwlodek/py_cui

Both Picotui and Npyscreen are relatively unmaintained / considered feature-full. py_cui seems to be in the best shape.

Fingers crossed for this project making it through, building on top of Rich gives it quite a bit of headstart. You can also sponsor @willmcgugan on Github [0].

[0]: https://github.com/sponsors/willmcgugan

You can join a company whose success would be arguably a net benefit for the society. Facing a similar mindset, that is the reason I started https://proteinqure.com/ couple of years back.

Needless to say, we're always on a lookout for good people to join us. My contact info is in the profile, if you want to chat.

ProteinQure - https://proteinqure.com/ | Computational drug design | Senior SW engineer | Toronto (onsite, currently remote)

At ProteinQure, we are building a computational platform for the design of protein therapeutics. We work on treatments for cancer, diabetes, among others, and partner with industry leaders in drug discovery (i.e. AstraZeneca) to generate novel therapeutics outside of the conventional chemical space.

We are hiring a Senior software engineer, our stack is mostly written in Python. Your job would be split between helping us develop our internal platform for drug discovery, and directly participating in drug discovery projects alongside computational biologists, machine learning experts and wetlab scientists.

I'd be happy to casually chat with interested candidates, email me at tomas at <company domain> or reach out to me through other means listed in my profile (keybase, irc, twitter).

This paper basically explores a hypothetical scenario where scaling quantum memory ends up being cheaper than scaling computational qubits. The title (or abstract) unfortunately does not mention the quantum memory requirements at n=2048 explicitly.

For factoring 2048 RSA integers, the technique proposed in the paper would require ~430 million memory qubits (see the table at top of page 16).

In my experience, there is quite a bit of untapped potential for applying engineering/cs/ml lessons in less traditional domains - not despite, but precisely because the other scientific disciplines are embracing and leveraging computation more.

I'm happy to elaborate on a more private channel, email/twitter is in the profile.

Source: Cofounded a startup in comp.bio space ~3.5 years ago, been busy supercharging our scientists and increasing pace of innovation and haven't really ran out of ideas yet.

If I remember correctly, the user in question kept exported plain-text backups of the conversations on the phone. The encryption of the app itself was not breached.

I have glued on top the classic cheap heat sink [1], which came with the Pi. Once that was determined to be unsuficient, I slotted the aluminium foil (folded to achieve sufficient thickness to stay in place) between the teeth.

[1] https://www.buyapi.ca/product/aluminum-heatsink-for-raspberr...

No, its malleable aluminium foil (I took it from the kitchen), that holds between the teeth of the original sinks merely by pressure of being jammed in.

For what it's worth, I resolved my Pi4 overheating issue by expanding the surface area of the heat sink with some folded aluminium foil [1].

Not the prettiest solution, but works just fine. The Pi4s on the picture are running at ~100% CPU utilization of all cores for months (using mlucas) now without any overheating events.

[1] https://postimg.cc/CzNzMb6B

This paper provides an approach for a simplified representation of a problem, so called lattice protein folding, for a very small protein.

In particular, they find a 2D lattice fold of a 6-amino acid sequence (PSVKMA). 2D lattice fold means that every amino acid must occupy discrete Euclidean coordinates (i.e. (0,2) or (2,1)), which allows you to convert the search into optimization problem.

Couple of years later (using more tricks and newer D-Wave machine), we pushed the limit to 10 amino acids on the planar grid, and generalized the approach to 3D grids as well (where we were able to obtain a lattice fold of 8 amino acid sequence) [1]. This is actually still well below what your laptop can search with some effort.

On the other hand, AlphaFold2 predicts coordinates of the C-alpha atoms in the continuous space, so the predicted structure would actually be an potential direct substitute for experimental structure (similar to, i.e. a structure obtained using homology modelling).

[1] https://arxiv.org/abs/1811.00713

Removal of repositories like youtube-dl seems to have been happening for a while though, here are couple of examples:

Removal of Udemy-dl (2015,2017): https://github.com/github/dmca/blob/master/2015/2015-08-12-U... https://github.com/github/dmca/blob/master/2017/2017-11-13-U...

Removal of linuxacademy-dl (2018): https://github.com/github/dmca/blob/master/2018/2018-09-24-l...

Removal of Instagram-API (2020): https://github.com/github/dmca/blob/master/2020/01/2020-01-2...

The removal of youtube-dl is a loss to the open source community. I hope this does not set a precedence going forward and that authors re-establish themselves (and the bug tracker, which had immense amount of information).

At the same time, this lead me to browse the Github's DMCA repo, which has some real gems. For example, this DMCA takedown of repo with copied course assignment of a different student and did not comply with the Apache 2.0 Licence [1].

[1] https://github.com/github/dmca/blob/master/2020/10/2020-10-2...

Happy to hear you find it useful!

Given the title, that would be quite funny, as RH IdM is actually written in Python and also open source :) [0]

[0] https://github.com/freeipa/freeipa

Quick plug for folks that are coming from the SWE background, and would love to get more hands-on experience (thus learn by doing!), the effort behind Quantum open source foundation might be of interest [0].

We have compiled learning resources [2], organize workshops and hackathons (i.e. we are behind the Quantum track at FOSDEM [3]) and even offer mentorships [4] for people that have some QC knowledge and are interested in entering the field of quantum SW development.

Originally the effort started as surveying the current state of open source software in QC [1], but shortly afterwards we realized that the field could benefit (similar as AI has), among other things, from more people with SWE background joining and helping the ecosystem grow, making the individual pieces of the QC stack more robust and interoperable, but also completely building parts that are currently missing.

In that spirit, more recently we are trying to organize efforts to help the open source quantum ecosystem by building various projects where people with good SWE background could be very helpful.

Write me a short info about you at `tomas at qosf.org` with "[HN]" prefix if interested to volunteer some of your time!

We're hoping to add couple of people into the team, and looking for people with a different backgrounds (Python is the language of the science world in QC, but we have use for everything ranging from devops, frontend to backend skillsets).

[0] https://qosf.org

[1] https://journals.plos.org/plosone/article?id=10.1371/journal...

[2] https://qosf.org/learn_quantum/

[3] https://fosdem.org/2020/schedule/track/quantum_computing/

[4] https://qosf.org/qc_mentorship/

The author has a point. When going to upvote the article, I caught myself subconsciously running the risk analysis of HN DB getting hacked and the upvote data getting publicly exposed.

Data indeed is not reliable, growing up in that area, I can say Slovakia and Czech Republic have similar demographics and employment rates, while occupy very different places in the linked data source.

Here is a more reliable source from worldbank, claiming ~60% labor participation rate [1].

[1] https://data.worldbank.org/indicator/SL.TLF.CACT.NE.ZS?locat...

Happy to see this development! There was an earlier attempt at universal static linter by the coala project [1], however, in the recent years the project was not keeping up with the underlying tools changing [2].

It's lovely somebody's picking up the torch here!

[1] https://github.com/coala/coala

[2] https://github.com/coala/coala/graphs/contributors

While (likely) not using directly deep learning, I found the following talk [1] by Emily Shea on her code dictation setup (based on Talon Voice) both insightful and impressive.

EDIT: Actual demo with coding starts at 18.00: https://youtu.be/YKuRkGkf5HU?t=1076

[1] https://www.youtube.com/watch?v=YKuRkGkf5HU

Middle button to zoom. It is worth it to have a closer look at those walls with millenia-old artwork.

Have a look at interpret.ml, which also links to their github org: https://github.com/interpretml

What I would recommend is buying an off-the-shelf retractable lanyard [1] and putting a Yubikey on it. I do so myself, and it has a number of advantages:

* You cannot leave your computer alone with Yubikey plugged in (especially useful when combined with modifying your PAM stack to lock the screen when yubikey is plugged out [2])

* Plugging Yubikey on a keychain which is bulky is cumbersome

* Yubikey on your neck can be a great conversation opener :)

[1] https://www.amazon.com/Updated-CarryLuxe-Lanyard-Polyester-R...

[2] https://tbabej.com/Yubikey-secure-session-setup/

ProteinQure - https://proteinqure.com/ | Computational drug design | Various engineering roles | Toronto (onsite)

At ProteinQure, we are building a computational platform for the design of protein therapeutics. Our mission is to help to create a world where drugs are engineered, not just discovered. We work on treatments for cancer, diabetes, among others, and partner with industry leaders in drug discovery to generate novel therapeutics outside of the conventional chemical space.

Our technology combines computational biophysical models with statistical and machine learning approaches to enable us to search across vast spaces of protein therapeutics. We build and deploy these computational modules using a scalable cloud computing infrastructure and complement their predictions with results from wet lab experiments. We utilize advanced computing architectures based on high-performance GPUs, TPUs and investigate novel methodologies in biophysical modelling.

We are a seed-stage company and have just recently raised our $4M USD seed round by some of the top Silicon Valley and Canadian investors. We are rapidly expanding our 9-person multidisciplinary team and hiring across a range of engineering roles: Backend, Infrastructure / DevOps, ML scientists, statisticians and computational biologists.

This an opportunity to be an early technical employee at a deep tech company and grow into leadership roles as we scale. Biology background is not needed for the engineering roles.

For more details about the roles and the company, check out our job descriptions: https://jobs.lever.co/proteinqure

I am one of the founders, feel free to reach out to me directly: tomas@proteinqure.com

ProteinQure - https://proteinqure.com/ | Computational drug design | Various engineering roles | Toronto (onsite)

At ProteinQure, we are building a computational platform for design of protein therapeutics. Our mission is to help to create a world where drugs are engineered, not discovered. We work on treatments for cancer, diabetes, asthma, and cardiovascular diseases, among others, and partner with industry leaders in drug discovery to generate novel therapeutics outside of the conventional chemical space.

Our technology combines computational biophysical models with statistical and machine learning approaches to enable us to search across vast spaces of protein therapeutics. We build and deploy these computational modules using a scalable cloud computing infrastructure and complement their predictions with results from wet lab experiments. We utilize advanced computing architectures based on high-performance GPUs, TPUs and investigate novel methodologies in biophysical modelling.

We are a seed-stage company and have just recently raised our $4M USD seed round by some of the top Silicon Valley and Canadian investors. We are rapidly expanding our 8-person multidisciplinary team and hiring across a range of engineering roles: Frontend, Backend, Infrastructure / Devops, ML engineers, statisticians and computer scientists.

For more details about the roles and the company, check out our job descriptions: https://proteinqure.com/hiring.html

At ProteinQure [1], we were part of this incubator in the 2017-2018 batch. Happy to answer any questions!

[1] http://proteinqure.com/

It's important to note here that the current gate-based quantum processors also suffer from the connectivity problems. It's not just annealers suffering.

In those architectures, the limited connectivity enforces usage of SWAP gates, which increases the circuit depth.

Circuit depth, with imperfect qubits and gates, is currently the limiting factor - we don't have practical error-correction for the chips of today's size. Hence one can only perform a certain number of operations before his computation decoheres and becomes useless.

We don't do poster sessions, but we have a dedicated slot for lightning talks in one of the two days. Shoot us an email at info@qosf.org and we'll see if it's a good fit.

Hi! Maybe this is a misunderstanding due to FOSDEM lingo - call for participation is not an registration/invite, it is the equivalent of call for papers (that is, talk submissions).

FOSDEM [1] is open to all (there is no registration or fees) - and several thousands of people come every year.

[1] https://fosdem.org/2019/