boltzmannbrain

Pasteur Labs (https://pasteurlabs.ai) | Full-time | REMOTE (worldwide) | DevOps / MLOps / full-stack / platform / MLEng

At Pasteur Labs, we develop computing technologies that enable scientific and industrial challenges to be approached in new ways: that is, a first of its kind AI-native, developer-first platform for modeling & simulation (M&S). Our product aim is to enable in-silico playgrounds for human-machine teams experimenting and building in industrial R&D, energy security, & advanced manufacturing arenas. As a public-benefit for-profit startup, our mission is Nobel-Turing [1] technologies to advance science and society for all humankind. With venture funding and Fortune500 customers (+dozens more on the waitlist), we’re looking for ambitious, intellectually curious software engineers that can consistently contribute in non-trivial, impressive ways as we ship and scale our flagship product platform — some call it “live intelligent digital twins” and others say “cyberphysical testbeds for AGI”, while most view Pasteur Labs product catalogue as “Databricks for industrial R&D”.

--> https://pasteurlabs.ai/careers/ <-- While we don’t list requirements for degrees or years-experience, everyone needs to demonstrate high-caliber engineering and problem-solving; we’re dedicated to scientific rigor and robust engineering for complex and dynamic environments, so prove to us that you not only fit in but that you can make us better. In particular, we are seeking experienced DevOps / MLOps teammates that can build from day 1 with Go, Python, containerization, and our multiple cloud setups (Azure, Google (GCP), Oracle Cloud (OCI)), and on-prem infrastructure for mixed GPU & CPU workloads — if you've done this before with CAE simulation systems and scientific datasets, reach out and say so!

Our team is largely made of industry-hardened research-software engineering experts [2], whom thrive in interdisciplinary and fast-paced teams—from NASA to Nvidia, Deepmind to Oracle, CERN to Cerebras, SpaceX to Autodesk, the Navy, Air Force, and on. With HQ in Brooklyn NY [3], and satellite offices opening in Copenhagen + London + Vancouver in 2025, we are an internationally distributed team running remote full-time — from San Francisco to Sao Paulo to Stockholm and everywhere in-between. The full team gathers multiple times per year for 1-week Pasteur Labs “onsites”—recently in Miami, Amsterdam, Cambridge, and more.

If what we’re doing speaks to you, please get in touch! Send your CV/resume and other supporting info/demos/etc to us at [email protected]

[1] https://arxiv.org/pdf/2112.03235.pdf

[2] https://us-rse.org/about/what-is-an-rse/

[3] http://newlab.com

On "science that is greater than the sum of its parts", the post hits on key ingredients:

+ understanding of problems from multiple perspectives and across multiple dimensions;

+ pragmatic engineering for high-quality execution;

+ touching the real world, doing it at scale;

+ demonstration and iteration, always;

that can together enable "execution-driven science." In practice, much of that R&D progress is posted at https://pasteur4d.ai/research and other offshoots of https://arxiv.org/pdf/2112.03235

Pasteur Labs – https://pasteurlabs.ai | Full-time | REMOTE (worldwide) | Sr+ Engineers (in Applied Simulation, Data Engineering, Product Dev, HCI Dev, 3D Game/Physics Engines): https://simulation.science/careers

At Pasteur Labs, we develop computing technologies that enable scientific and industrial challenges to be approached in new ways: that is, a first of its kind AI-native, developer-first platform for modeling & simulation (M&S). Our product aim is to enable in-silico playgrounds for human-machine teams experimenting and building in industrial R&D, energy security, & advanced manufacturing arenas. As a public-benefit for-profit startup, our mission is Nobel-Turing [1] technologies to advance science and society for all humankind.

The pursuit calls for industry hardened and intellectually curious builders who thrive in interdisciplinary territories that are often less-traveled. The team brings deep, diverse expertise from Deepmind, Cerebras, Vicarious, SpaceX, NASA, CERN, Sandia, Nvidia, Autodesk, and more. With fresh venture funding and Fortune500 customers (+dozens more on the waitlist), we're looking for ambitious, intellectually curious software engineers that can consistently contribute in non-trivial, impressive ways as we ship and scale our flagship product platform — some call it "live intelligent digital twins" and others say "cyberphysical testbeds for AGI", while most view Pasteur Labs product catalogue as "Unity for industrial R&D."

With HQ in Brooklyn NY [2], we are an internationally distributed team running remote full-time — from San Diego to Stockholm and everywhere in-between. The full team gathers 2x per year for Pasteur Labs "onsites", alternating sites such as Montreal, Amsterdam, Austin, London, NYC etc.

-> https://simulation.science/careers

While we don't list requirements for degrees or years-experience, everyone needs to demonstrate high-caliber engineering and problem-solving in multiple domains; we're dedicated to scientific rigor and robust engineering for complex and dynamic environments, so prove to us that you not only fit in but that you can make us better.

If what we’re doing speaks to you, please get in touch! Send your CV/resume and other supporting info/demos/etc to us at [email protected]

[1] https://arxiv.org/pdf/2112.03235.pdf

[2] http://newlab.com

"Machine-Guided Discovery of a Real-World Rogue Wave Model" published in PNAS [1], out of Pasteur Labs and colleagues [2].

[1] https://www.pnas.org/doi/abs/10.1073/pnas.2306275120

[2] https://simulation.science/

PASTEUR LABS (https://pasteurlabs.ai) | Full-time | REMOTE (worldwide) | Sr+ Engineers (for MLOps, Data Engineering, 3D Game/Physics Engines)

At Pasteur Labs [1], we develop computing technologies that enable scientific and industrial challenges to be approached in new ways: that is, a first of its kind AI-native, developer-first platform of in-silico playgrounds for human-machine teams experimenting and building in industrial R&D, energy security, & adv/additive manufacturing arenas. As a public-benefit for-profit startup, our mission is Nobel-Turing [2] technologies to advance science and society for all humankind.

The pursuit calls for industry hardened and intellectually curious builders who thrive in interdisciplinary territories that are often less-traveled. The team brings deep, diverse expertise from Deepmind, Cerebras, Vicarious, SpaceX, NASA, CERN, Sandia, Nvidia, Autodesk, and more. With fresh venture funding and Fortune500 customers (+100 more on the waitlist), we’re looking for ambitious, intellectually curious software engineers that can consistently contribute in non-trivial, impressive ways as we ship and scale our flagship product platform — some call it “live intelligent digital twins” and others say “cyberphysical testbeds for AGI”, while most view Pasteur Labs product catalogue as “Unity for industrial R&D.”

We’re looking for Engineers at or above Senior level expertise in one or more of MLOps, Data Engineering, 3D Game/Physics Engines.

With HQ in Brooklyn NY [3], we are an internationally distributed team the runs remote full-time — from San Diego to Stockholm and everywhere in-between. The full team gathers 2x per year for Pasteur Labs “onsites”, alternating sites such as Montreal, Amsterdam, Texas, London, NYC etc.

While we don't list requirements for degrees or years-experience, everyone needs to demonstrate high-caliber engineering and problem-solving in multiple domains; we're dedicated to scientific rigor and robust engineering for complex and dynamic environments, so prove to us that you not only fit in but that you can make us better.

If what we’re doing speaks to you, please get in touch! Send your CV/resume and other supporting info/demos/etc to us at [email protected]

[1] https://pasteurlabs.ai/

[2] https://arxiv.org/pdf/2112.03235.pdf

[3] http://newlab.com

SEEKING FREELANCER (remote)

Looking for website dev and animation, to make something similar to https://www.aqlab.io

Contact [email protected] with subject 'HN website dev', and please provide examples of similar work you've done.

Data scientists are too comfortable with R, while software engineers won't touch it with a ten foot pole. So to move forward in the career you allude to, definitely use Python in your current role as much as possible, and push yourself with engineering-like tasks/skills (e.g. volunteer to work on that CI/CD pipeline, don't just use numpy but understand how it writes to memory, etc.).

Finalists here: https://computerhistory.org/mcgovern-finalists-2021/

Yes, even for a general-audience neuroscience book this is sparse on details and has embarrassingly few references. That being said, Numenta has dedicated significant effort to publishing more details in the past 5-6 years:

https://numenta.com/neuroscience-research/research-publicati...

Still there is much to be desired in the ways of mathematical and empirical grounding.

Great writeup. The definition here is a bit different and more general.

What are the alternatives that didn't win out?

This post should (1) reflect the 2018 posting date, and (2) the main hosting site: https://hdsr.mitpress.mit.edu/pub/wot7mkc1/release/9

"OpenAI LP is a for profit Delaware Limited Partnership managed by its General Partner, a single-member Delaware LLC controlled by OpenAI Inc (the nonprofit)'s Board of Directors."

Could someone explain this, and why specifically LP and LLC are the corporate entities?

Take a deep breath, temper your expectations.

If you're going to fear for the future, there are far grander, realistic, and imminent risks to be concerned with.

Empty vessels make the loudest noise, aka the Dunning-Kruger effect [1].

[1] http://theurbanengine.com/blog//the-dunning-kruger-effect

+1 "Never merge with GitHub... I don’t feel that I have the proper control"

Agreed these will vary greatly org to org, and are bound to be biased, yet having a collection of these lists will help myself and others distill what is needed for a specific org.

So ideally there will be many many lists / recommendations / best practices (with the org's specific situation / requirements) such that I and others can formulate our specific blueprint and start building.

> "walkthroughs", best practices, etc should be based on logical conclusions coming out of project scope and goals.

Would love to see real examples of this thought process... i.e. of the form "we have these requirements, so we chose this and that, etc."

Startup Owner's Manual is great. However I'm looking for a much more technical to-do list... i.e., here is the best practice for dev-ops, here is the best practice for security, here is the best practice for data lakes, etc. Understandably these will vary greatly org to org, and are bound to be biased, yet having a collection of these lists will help myself and others distill what is needed for a specific org.

This is very useful, thanks!

And to answer your question on background and aims: I'm a machine learning engineer focusing on probabilistic graphical models (i.e. not deep learning) and would like to better understand how dedicated compute could (or could not) improve computational efficiency.