travis 1y ago • 100%
Thanks for sharing! These seem to focus on LLMs/transformers, but since they use MLPs I should be able to find a way to adapt them for my use!
travis 1y ago • 100%
Sort of - the models are able to predict numerical property values given a large amount of data to observe during training. In other words, given the scope of known data, we can extrapolate predictions for new data. The predictive capabilities of the model are only as reliable as the data used to train it, and unfortunately in our case we only have hundreds of samples per property, as opposed to other ML tasks with millions of samples. This highlights how much time it actually takes to find, synthesize, and experimentally test molecules!
Unfortunately neural networks, especially traditional multi-layered feed-forward networks, are often seen as a "black box" approach to regression and classification, where we don't really understand how a network learns or why its weights are tuned the way they are. Analysis methods have come a long way, but ambiguity still exists.
What we have done, however, is find the statistical significance of specific molecular substructures as they relate to combustion properties. For example, when we trained our models to predict sooting propensity (amount of pollution formed during combustion), we noticed that various algorithms such as random forest regression were putting a heck of a lot more weight into a molecular variable measuring path length (length of carbon chains, number of higher order bonds); from this, we were able to conclude that long-chain hydrocarbons with a higher number of double or triple bonds form more soot, and an idea of what mechanistic pathways we should stay away from when producing bio-oil.
As for fuel-grade molecules, we've found that furanic compounds and compounds with cyclohexane substructures generally have equal operating efficiency (cetane number), equal energy density (lower heating value, MJ/kg), operate well in various environments (optimal flash, boiling, and cloud points, deg. C), all while producing much less soot (yield sooting index) compared to diesel fuel. The next step is finding a cheap way to mass produce the stuff!
Recently we've started down the rabbit hole of fungus-derived bio-oils, terpenes (yes, those terpenes!) derived from fungus may be useful for use as soot-reducing fuel additives.
travis 1y ago • 100%
TL;DR, I throw a bunch of molecules at a pile of linear algebra, and hope predicted values line up with known experimental values; then I use the pile of linear algebra on novel molecules.
There's a bit more to it than that, like how to represent molecules in a computer-readable format, generating additional input variables (molecular characteristics), input variable down-selection and/or dimensionality reduction, the specific ML models we use (feed-forward MLPs and graph convolution nets), and how to interpret results as they relate back to combustion.
From a broad perspective, our work is just a small part of a larger push from the Department of Energy to find economically-viable alternative liquid fuels. ML speeds up the process of screening candidate molecules, for example those found in bio-oil resulting from pyrolizing and catalytically-upgrading lignocellulosic biomass or other renewable sources. Our colleagues don't have to synthesize large samples of many molecules just to test their properties and determine how they will behave in existing engines (a very costly and time-consuming process), instead we predict the properties and behaviors to highlight viable candidates so our colleagues can focus on analyzing those.
These papers (1, 2, 3) best outline the procedures and motivations for this work. PM me if you can't get access and I'll send you them!
travis 1y ago • 100%
Postdoc in engineering research - we’re using machine learning to predict chemical properties relevant to combustion, speeding up the discovery of cleaner liquid fuels as we transition away from fossil fuels!
Hi everyone, I'm pleasantly surprised and very thankful for the traction [Plemmy](https://github.com/tjkessler/plemmy) has received in a few short weeks since its initial release! The primary goal of Plemmy is simple: offer access to the [LemmyHttp API](https://join-lemmy.org/api/classes/LemmyHttp.html) in Python, allowing users to interact with any Lemmy instance using Python. Plemmy's `LemmyHttp` object does just this, returning Python `request.Response` objects resulting from Lemmy API calls. All LemmyHttp functions have been implemented! With release 0.3.0, Plemmy now offers a way to parse `request.Response` objects, extracting all information and placing them in easy-to-use Python objects. The design of these functions/objects closely mirrors the objects and data types defined in the [lemmy-js-client](https://join-lemmy.org/api/modules.html). These additions should make interacting with Lemmy in Python easier than ever. Check out Plemmy's [repository](https://github.com/tjkessler/plemmy) for example usage (more documentation to come!). Thanks for the continued support, Travis
Hi everyone, I'm pleasantly surprised and very thankful for the traction [Plemmy](https://github.com/tjkessler/plemmy) has received in a few short weeks since its initial release! The primary goal of Plemmy is simple: offer access to the [LemmyHttp API](https://join-lemmy.org/api/classes/LemmyHttp.html) in Python, allowing users to interact with any Lemmy instance using Python. Plemmy's `LemmyHttp` object does just this, returning Python `request.Response` objects resulting from Lemmy API calls. All LemmyHttp functions have been implemented! With release 0.3.0, Plemmy now offers a way to parse `request.Response` objects, extracting all information and placing them in easy-to-use Python objects. The design of these functions/objects closely mirrors the objects and data types defined in the [lemmy-js-client](https://join-lemmy.org/api/modules.html). These additions should make interacting with Lemmy in Python easier than ever. Check out Plemmy's [repository](https://github.com/tjkessler/plemmy) for example usage (more documentation to come!). Thanks for the continued support, Travis
Hi everyone, I'm pleasantly surprised and very thankful for the traction [Plemmy](https://github.com/tjkessler/plemmy) has received in a few short weeks since its initial release! The primary goal of Plemmy is simple: offer access to the [LemmyHttp API](https://join-lemmy.org/api/classes/LemmyHttp.html) in Python, allowing users to interact with any Lemmy instance using Python. Plemmy's `LemmyHttp` object does just this, returning Python `request.Response` objects resulting from Lemmy API calls. All LemmyHttp functions have been implemented! With release 0.3.0, Plemmy now offers a way to parse `request.Response` objects, extracting all information and placing them in easy-to-use Python objects. The design of these functions/objects closely mirrors the objects and data types defined in the [lemmy-js-client](https://join-lemmy.org/api/modules.html). These additions should make interacting with Lemmy in Python easier than ever. Check out Plemmy's [repository](https://github.com/tjkessler/plemmy) for example usage (more documentation to come!). Thanks for the continued support, Travis
Hi everyone, I'm pleasantly surprised and very thankful for the traction [Plemmy](https://github.com/tjkessler/plemmy) has received in a few short weeks since its initial release! The primary goal of Plemmy is simple: offer access to the [LemmyHttp API](https://join-lemmy.org/api/classes/LemmyHttp.html) in Python, allowing users to interact with any Lemmy instance using Python. Plemmy's `LemmyHttp` object does just this, returning Python `request.Response` objects resulting from Lemmy API calls. All LemmyHttp functions have been implemented! With release 0.3.0, Plemmy now offers a way to parse `request.Response` objects, extracting all information and placing them in easy-to-use Python objects. The design of these functions/objects closely mirrors the objects and data types defined in the [lemmy-js-client](https://join-lemmy.org/api/modules.html). These additions should make interacting with Lemmy in Python easier than ever. Check out Plemmy's [repository](https://github.com/tjkessler/plemmy) for example usage (more documentation to come!). Thanks for the continued support, Travis
travis 1y ago • 100%
I use a few used Dell Optiplex 7050 Micros, they’re great for the price (and have a small footprint too!)
Edit: for storage I have a HP MicroServer Gen. 10 plus
travis 1y ago • 100%
Self-hosting lemmy.blue!
travis 1y ago • 100%
YouTube TV and Spotify. There’s a workaround for everything else!
travis 1y ago • 100%
I'm not sure there's a way to interact with other Lemmy instances at the moment - clearly we can using the UI, but I think the API doesn't have the functionality yet. As soon as this and other features are added I'll aim for a quick implementation!
travis 1y ago • 100%
I like the idea of a Reddit-Lemmy cross-poster! It should make transitioning to Lemmy a bit easier for those used to seeing more Reddit-like content.
travis 1y ago • 100%
From what I've seen, Pythorhead is focusing on "higher-level" functions, while Plemmy is focusing on LemmyHttp API parity and returning request responses. Who knows, maybe we'll implement some more complex functionality in the future!
travis 1y ago • 100%
I'm not sure, I don't think there's a direct way to do this at the moment. Maybe there's a way using the get_community and get_person_details functions?
travis 1y ago • 0%
I believe rate limits (messages, images, sign-ups etc.) can be defined for a site 1.) on creation using the create_site function and 2.) editing a site using the edit_site function.
Hi everyone, I’d like to share a project I’ve been working on recently, Plemmy! Plemmy allows you to interact with any Lemmy instance using Python and the [LemmyHttp API](https://join-lemmy.org/api/classes/LemmyHttp.html). Currently all LemmyHttp functions (POST, PUT, GET) have been implemented. Feel free to provide feedback or contribute in any way!
Hi everyone, I’d like to share a project I’ve been working on recently, Plemmy! Plemmy allows you to interact with any Lemmy instance using Python and the [LemmyHttp API](https://join-lemmy.org/api/classes/LemmyHttp.html). Currently all LemmyHttp functions (POST, PUT, GET) have been implemented. Feel free to provide feedback or contribute in any way!
Howdy, I'd like to share a project I've been working on recently, Plemmy! Plemmy allows you to interact with any Lemmy instance using Python and the [LemmyHttp API](https://join-lemmy.org/api/classes/LemmyHttp.html). Currently *all* LemmyHttp functions (POST, PUT, GET) have been implemented. Feel free to provide feedback or contribute in any way!
Hello everyone! I'm here to share a project I've been working on, Plemmy. Plemmy is a Python package for accessing the Lemmy API, specifically through [LemmyHttp](https://join-lemmy.org/api/classes/LemmyHttp.html). Feel free to offer advice and contribute! Edit: version 0.2.0 released, all LemmyHttp operations are supported! (Most methods still need testing)
travis 1y ago • 100%
Very cool, I'll do some digging myself!
travis 1y ago • 100%
Interesting - it would be even more interesting if they provided some metrics as to how much time is being saved compared to RSS.
travis 1y ago • 100%
What's worse:
Meanwhile Kim Dotcom, the founder of Megaupload, is continuing to fight the U.S. charges and threat of extradition. He has said he expects his former colleagues to testify against him as part of the deal they struck.
travis 1y ago • 100%
Ortmann was sentenced to 2 years and 7 months while van der Kolk was sentenced to 2 years and 6 months. Each had faced a maximum sentence of 10 years in prison but argued they should be allowed to serve their sentences in home detention.
Does the punishment fit the "crime"?
travis 1y ago • 100%
Joined! PhD with applied ML experience, looking forward to contributing.
travis 1y ago • 100%
He’s gonna run Twitter into the ground like you would your favorite car
travis 1y ago • 100%
Fantastic! An Apollo-like app will make switching so much easier for so many people
travis 1y ago • 100%
+1 for running TrueNAS in a VM, I’ve got one running in Proxmox. Make sure to enable hardware passthrough so TrueNAS has direct access to your drives!