Kudos to Google for moving this along! A few weeks, the HN community picked up [0, 1] on a presentation [2] about the Tint shading language, a WebGPU shading language prototype. It's great to see them formalize their prototype into a draft spec.
Thank you to those who are working hard on bringing WebGPU to the masses!
Qt's licensing for commercial products is something like $500/month/developer. For a small team of 6 developers, that's $36k in licensing a year. Unfortunately, you're not allowed to take existing Qt code and "port" it over to the commercial license -- you're required to start from scratch IIRC.
If you're affected by this and would love to work on a dedicated team developing spacecraft orbit simulation software, my company is hiring. Please send me an e-mail at [email protected].
Would you be interested in working on high-fidelity satellite orbit simulation software? Our software architecture is primarily C++ and C#, but we're starting to explore some new technologies for our front-end, i.e., Electron, WebAssembly, React.
Take a look at our posting in the Who Is Hiring thread!
a.i. solutions | Washington, D.C. | C++ Software Engineer | U.S. Citizenship
Would you love to be a part of the new space industry?
Do you like solving challenging problems with algorithms and data structures?
Do you enjoy designing and developing sophisticated software architectures?
Read on!
We’re a team of software engineers, aerospace engineers, physicists, mathematicians, and data scientists building FreeFlyer, one of the top platforms for satellite orbital modeling and trajectory design. Our software is used by NASA and other space agencies and private companies for satellite mission planning and mission control. FreeFlyer has been used for spacecraft missions of all types, including the International Space Station, communications satellites, science missions, and several planned missions to the Moon and beyond.
We are looking for someone to join our team who is excited to dive in and make an impact. By joining the team, you will have the opportunity to:
+ Solve interesting problems that are centered around high fidelity computational modeling, data structures, algorithms, data visualization, and performance.
+ Contribute to improving our software architecture and help us build a better product.
+ Learn from subject matter experts about everything that goes into sending a satellite into orbit.
If this sounds interesting to you, we would love to hear from you! You can reach out to us over email or connect with us via the DC Tech Slack community with any questions.
They were able to recover the failed backup gyroscope by executing a series of attitude maneuvers while switching between operational modes on the gyro.
They literally shook the spacecraft and turned the gyro off-and-on.
Sometimes you gotta bang on something to get it to work!
I would love to buy a beer for the mission operations team member who came up with that idea!
The bit that stands out to me is an e-mail he received from a female engineer:
> While the idealist in me would love to aim for a world where sex was treated more equally and openly, the unfortunate reality of tech is that it has been a haven for misogynistic men and the environment is heavily male dominated. While in an ideal world the name SexMachine would be something that both genders could joke about, the reality is that the tech community is not ready or capable of that today.
Neat! I've been looking around for a comprehensive guide in how to write a custom React renderer for an upcoming project of mine. It's unfortunate that Facebook hasn't had the time to document the process, often leaving folks to have to poke around at how other libraries do it. I'm starting to really appreciate how React can be used to incremental render complex state configurations to mediums other than the DOM.
OP: thanks for taking the time to write this series! It'll definitely help me out with some work I'm interested in doing.
Hello! Airbnb is looking for a front-end engineer to join its growing Service Excellence team in Portland, Oregon. We are building world-class tools for our global team of Customer Experience and Trust and Safety agents to ensure our guests and hosts have a great experience on Airbnb, 24/7, and 365 days a year.
Working closely with designers, we implement the user interface of our web app. We build libraries and abstractions to make our lives easier, such as DLS, our front-end toolkit. We make the most of modern tools like React, ES6, and Redux, and even our next-generation mobile apps are built with JavaScript on React Native.
It details a creative process for developing concepts and testing them. Given that the book outlines a 5-day process that is tailored for product development teams, you might get a lot out of it for personal projects.
Oregon Health & Science University | Scientific Programmer | Portland, OR | ONSITE | Full Time | Relocation available
We are seeking a skilled scientific programmer to develop genomic, imaging, and clinical analysis applications on a distributed data / workflow management and analytics platform currently under development. This position will work in a team oriented software development environment, following best practices such as code sharing through GitHub and development of structured software APIs. A successful candidate will contribute to the international development of standardized APIs and data schemas, and develop implementations compatible with such APIs, ensuring that the system is interoperable within the emerging community ecosystem of software tools.
Responsibilities
+ Develop custom analytics and data management applications to facilitate one or more of the following: large-scale genomic data analysis; machine learning methods to infer genotype-to-phenotype predictive models; analysis of quantitative imaging data.
+ Work with the platform development team to implement scalable cloud-enabled workflows to disseminate analytical advances to the research community.
+ Establish and maintain standards for structured software & systems engineering, including requirements, design, code, test, quality, configuration & release management and project management.
+ Provide documentation and user support allowing computational researchers across campus to access and re-use analysis tools.
+ Maintain well-curated, highly structured, transparent omics, imaging, or clinical data resources.
+ Develop tools to integrate commonly used open source bioinformatics software applications.
+ Participate in leading international efforts aimed at establishing best practices and standards for genomic data representation and analysis.
This is pretty much the main idea behind another paper that Eamonn wrote [0]. The idea is that you can normalize and discretize timeseries data into a lecicographical representation, then perform all sorts of interests analyses on it. For example, searching for common subsequences can be done via regular expressions.
Neat! I did some similar analysis of conducting topic modeling around tweets during the Boston Marathon bombing a couple of years back. It was pretty cool to see how topics were neatly ordered over time.
> Spatial statistics aren't the same as regular statistics
I've always been frustrated with the gap between statistics and spatial statistics. For example, some of the methodologies with conducting hot-spot analysis is somewhat misleading, especially to uninformed geospatial analysts. For example, Esri [0] implements this first by conducting geospatial aggregation, then calculating z-scores based on Gaussian assumptions, then generates a corresponding "p-value" to extract "statistically significant areas" that are coined "hot spots". At that point, an analyst typically color-codes those p-values showing regions with low p-values as "extreme" areas of interest. I'm really curious if there's any empirical or anecdotal research that validates this methodology.
There are some attempts to try and normalize sampled data. Location Quotient [1] (and Standardized Location Quotient), for example, compares a local measure to a global measure. However, this too has Gaussian assumptions and doesn't properly account for variance in the data.
I would definitely love to see a hierarchical Bayesian spatial model that takes into account a geospatial prior (such as the overall density of tweets) allowing you to solve for the posterior of cluster centers. Has anyone seen this done before?
For those cases where I have to dip into R for specific functionality, I'll use Rpy2. Pandas has great support for translating Pandas data frames to R data frames!
Also check out Vowpal Wabbit [0]. Although this is a tool that provides several online versions of classification, regression, etc, there's an online LDA module included as well. It takes advantage of the "hashing trick", meaning that you can build an LDA model with a fixed memory footprint. I've had a lot of success using this tool.
Thank you to those who are working hard on bringing WebGPU to the masses!
[0]: https://news.ycombinator.com/item?id=22316777 [1]: https://news.ycombinator.com/item?id=22351285 [2]: https://docs.google.com/presentation/d/1qHhFq0GJtY_59rNjpiHU...