Way of the Geophysicist https://the-geophysicist.com Machine Learning Research and Education in Geoscience Fri, 03 Jan 2020 13:24:30 +0000 en-US hourly 1 https://wordpress.org/?v=5.3.2 https://the-geophysicist.com/wp-content/uploads/2015/09/cropped-favicon-32x32.png Way of the Geophysicist https://the-geophysicist.com 32 32 2020 Fast Approaching! – Friday Faves https://the-geophysicist.com/2020-fast-approaching-friday-faves?utm_source=rss&utm_medium=rss&utm_campaign=2020-fast-approaching-friday-faves https://the-geophysicist.com/2020-fast-approaching-friday-faves#respond Fri, 03 Jan 2020 13:24:25 +0000 https://the-geophysicist.com/?p=2525

Aaaand it’s gone. It’s starting out with one of my new projects and then a very nice wrap up of some cutting edge AI developments. Some Self Promotion! I started a Youtube series on learning machine learning for scientists. This is the first video in the series: Henry AI Labs’ Rewind A very insightful video […]

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Aaaand it’s gone. It’s starting out with one of my new projects and then a very nice wrap up of some cutting edge AI developments.

Some Self Promotion!

I started a Youtube series on learning machine learning for scientists. This is the first video in the series:

Henry AI Labs’ Rewind

A very insightful video on a lot of super-interesting insights into the developments of AI and machine learning during the last year.

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Machine Learning for Science – A Youtube Series https://the-geophysicist.com/machine-learning-for-science-a-youtube-series?utm_source=rss&utm_medium=rss&utm_campaign=machine-learning-for-science-a-youtube-series https://the-geophysicist.com/machine-learning-for-science-a-youtube-series#respond Mon, 30 Dec 2019 13:07:44 +0000 https://the-geophysicist.com/?p=2515

I’m starting a new project, where I take concepts from machine learning for science and do a short and focused deep dive into that topic. Why? I think modern data science and machine learning techniques, as well as, experiment design and systems thinking can benefit a wide range of scientists. I appreciate professors uploading their […]

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I’m starting a new project, where I take concepts from machine learning for science and do a short and focused deep dive into that topic.

Why? I think modern data science and machine learning techniques, as well as, experiment design and systems thinking can benefit a wide range of scientists. I appreciate professors uploading their lectures to Youtube, but I am missing laser-focused deep dives into a singular topic to understand the said concept better. So I’m doing just that!

🤓 The topics I want to dive into include:

  • Artificial intelligence
  • Machine learning
  • Deep learning
  • Optimization
  • Data science
  • Statistics concepts

Possibly, once I get through the basics, I can also place modern developments into context. Hope you’ll be along for the course! Maybe bring a friend or colleague! I promise the videos will get better over time too, I’m learning as well after all.

Subscribe for the coming updates: http://bit.ly/YTgeo

📽️ Youtube: https://www.youtube.com/channel/UCn_c_QdG1qQ2nCBo2MLdktQ
🎁 Community: https://www.patreon.com/thegeophysicist

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Something for a Long Trip or Unwind during the Holidays – Friday Faves https://the-geophysicist.com/something-for-a-long-trip-or-unwind-during-the-holidays-friday-faves?utm_source=rss&utm_medium=rss&utm_campaign=something-for-a-long-trip-or-unwind-during-the-holidays-friday-faves https://the-geophysicist.com/something-for-a-long-trip-or-unwind-during-the-holidays-friday-faves#comments Fri, 20 Dec 2019 15:33:47 +0000 https://the-geophysicist.com/?p=2502

It’s the holiday season, so let’s keep this Friday Fave short, with a fave that keeps on giving. Who’s Hannah Fry? Hannah Fry is a mathematician that uses math to model human behaviour. She’s also extremely good at communicating complex math concepts in several youtube videos and Podcast episodes. This is her lecture at the […]

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It’s the holiday season, so let’s keep this Friday Fave short, with a fave that keeps on giving.

Who’s Hannah Fry?

Hannah Fry is a mathematician that uses math to model human behaviour. She’s also extremely good at communicating complex math concepts in several youtube videos and Podcast episodes. This is her lecture at the Royal Institution:

Should computers run the world? – Hannah Fry at the Royal Institution

Who’s Deep Mind?

DeepMind has set the lofty goal of solving the Artificial General Intelligence problem, collaborated with Hannah Fry to have her guide you through the diverse people in the Deepmind labs in London. In case you’d enjoy having a mode of escape during the holidays or are setting out for a longer trip to head to the family, I can highly recommend this series of extremely well-produced insights into the inner workings of this research start-up.

Look who’s on that screen at NeurIPS 2019

The DeepMind Podcast

Here’s the trailer to get an initial idea of what you’re in for:

Deepmind Podcast Trailer © DeepMind

Search for “Deepmind: The Podcast” in your podcatcher. Alternatively, head on over to your favourite source:

It feels to me like Professor Fry is bringing a healthy portion of rigour and skepticism to this branded podcast, making it very enjoyable. Even, or especially, as someone working with machine learning systems. In case you enjoyed this, you will probably enjoy the upcoming Christmas lecture 2019.

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Seismic I/O, Open Source, and Deep Double Descent – Friday Faves https://the-geophysicist.com/seismic-i-o-open-source-and-deep-double-descent-friday-faves?utm_source=rss&utm_medium=rss&utm_campaign=seismic-i-o-open-source-and-deep-double-descent-friday-faves Fri, 13 Dec 2019 15:05:00 +0000 https://the-geophysicist.com/?p=2476

This week in our Friday Faves, we have a new Python package for seismic compression and input/output, a conversation on the merits and caveats of open source and the confirmation that more data sometimes hurts machine learning models. Seismic Compression and I/O Equinor anounced the Python version of a compression algorithm for seismic data that […]

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This week in our Friday Faves, we have a new Python package for seismic compression and input/output, a conversation on the merits and caveats of open source and the confirmation that more data sometimes hurts machine learning models.

Seismic Compression and I/O

https://twitter.com/grajohnt/status/1204423998773309441

Equinor anounced the Python version of a compression algorithm for seismic data that supposedly speeds up i/o for seismic cubes by 8 times at a fixed bitrate. This should be particularly interesting for online learning of seismic data in machine learning and i/o intensive tasks such as seismic processing and inversion.

Find it on PyPI: https://pypi.org/project/seismic-zfp/

Why Open Source?

I am an avid listener of the Don’t Panic Geocast, a podcast about geoscience with great guests, interesting topics and the favourite segment fun-paper Friday. As I’m slow to catch up, I recently listened to the episode about Open Source. Why do we open source things? What is the business model? How does a highly profitable company like Apple rely on open source and contribute to it?

Find Episode 122 here: http://www.dontpanicgeocast.com/?p=477

Deep Double Descent

fig_modeldd

The double descent phenomenon has been known for a bit of time. It is the oddity of classical statistics and machine learning predictability not following the expected bias-variance trade-off. Open AI have confirmed this effect for very deep networks in accordance with the original research. Challenging the classic notion that “more data is always better”.

https://openai.com/blog/deep-double-descent/

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Fake AI and ML Tipps – Friday Faves https://the-geophysicist.com/fake-ai-and-ml-tipps-friday-faves?utm_source=rss&utm_medium=rss&utm_campaign=fake-ai-and-ml-tipps-friday-faves Fri, 29 Nov 2019 14:05:11 +0000 https://the-geophysicist.com/?p=2468

This week in the Friday Faves, we’re looking at some AI snake oil and a tip for training better models. A bit shorter, as I’m updating my website and my CV after handing in my PhD thesis. AI Snake Oil So if you want to call something that solves a problem somewhat and has an […]

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This week in the Friday Faves, we’re looking at some AI snake oil and a tip for training better models. A bit shorter, as I’m updating my website and my CV after handing in my PhD thesis.

AI Snake Oil

First slide of the AI Snake Oil talk by Arvind Narayanan

So if you want to call something that solves a problem somewhat and has an if statement, you can call it AI. But maybe don’t do it on things that basically amount to “sorting humans”. Sure people always tried to do it, but phrenology was bad, eugenics was bad, and 20% on an assessment on the big five is a random number generator (which possibly outputs nicer numbers for some people than others).

https://www.cs.princeton.edu/~arvindn/talks/MIT-STS-AI-snakeoil.pdf

Stop the Augmentation

If you’re training your model, you may want to consider stopping the augmentation for the last couple of epochs to improve the final performance.

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A human artificial neural network, BeatSaber, and proper Time Series Prediction – Friday Faves https://the-geophysicist.com/a-human-artificial-neural-network-beatsaber-and-proper-time-series-prediction-friday-faves?utm_source=rss&utm_medium=rss&utm_campaign=a-human-artificial-neural-network-beatsaber-and-proper-time-series-prediction-friday-faves Fri, 22 Nov 2019 10:37:00 +0000 https://the-geophysicist.com/?p=2459

Excuse the break, but I had my thesis to finish, but that is the topic for another post. In this Friday Faves, we have a solid mix of a human neural network, playing BeatSaber without VR headsets using machine learning, and a new scikit for time series learning. The Stilwell Brain The series Mind Field […]

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Excuse the break, but I had my thesis to finish, but that is the topic for another post. In this Friday Faves, we have a solid mix of a human neural network, playing BeatSaber without VR headsets using machine learning, and a new scikit for time series learning.

The Stilwell Brain

The series Mind Field by Michael Stevens, the figure behind the very successful Youtube channel Vsauce, created a compelling series into consciousness and exploring the human mind. This series was a Youtube Premium series for some time, but has been made available to everyone recently. Episode 3 in Season 3 (yes there are seasons) explores neural networks for digit recognition. The twist? Every Neuron is a human on a football pitch. While it’s a symbolic approach instead of a machine learning approach, I feel it’s extremely interesting to see.

The Stilwell Brain – Mind Field E3S3

If you’re interested in the book mentioned by Chris Eliasmith from the University of Waterloo here called “How to build a brain”.

BeatSaber without VR

Tensorflow has been used for Pose Estimation all over the place, with incredible results. BeatSaber is an extremely popular game for VR, where you slice flying cubes with lightsabers to the beat of the music. VR can be really expensive, so why not use Tensorflow and a projector to bootstrap BeatSaber with pose estimation?

https://github.com/charliegerard/beat-pose

BeatPose in Tensorflow Demo (GNUU GPL 3.0)

Scikit-Time

The SciKits are a family of Python libraries that build on the SciPy universe to build specific implementations for scientific fields. Scikit-Learn probably being the most famous. The amazing Alan Turing Institute now made Scikit Time available for Time Series prediction and modelling.

Couldn’t find a tweet, so check out all the other amazing things The Turing Institute does.

This should meet all your tagging, classification, and regression needs. Also, remember to cite the library if you use it to better recognize the need for Research Software Engineering to be recognized as a valuable endeavour.

@misc{sktime,
      author = {Markus Löning and Anthony Bagnall and Sajaysurya Ganesh and Viktor Kazakov
      and Jason Lines and Franz J. Király},
      title = {sktime: A Unified Interface for Machine Learning with Time Series},
      year = {2019},
      eprint = {arXiv:1909.07872},
}

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Interactive Viz² and Differentiable Machine Learning – Friday Faves https://the-geophysicist.com/interactive-viz%c2%b2-and-differentiable-machine-learning-friday-faves?utm_source=rss&utm_medium=rss&utm_campaign=interactive-viz%25c2%25b2-and-differentiable-machine-learning-friday-faves Fri, 01 Nov 2019 15:53:05 +0000 https://the-geophysicist.com/?p=2444

This Friday we’ll have a look at two interactive data viewers and a differentiable ML. Nd Array Viewer Napari is an interactive Nd array Viewer with support for fast inspection and analysis of multidimensional data. Definitely something to pop out in a Jupyter notebook and take a look at the processed data. The Blog Post […]

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This Friday we’ll have a look at two interactive data viewers and a differentiable ML.

Nd Array Viewer

Napari is an interactive Nd array Viewer with support for fast inspection and analysis of multidimensional data. Definitely something to pop out in a Jupyter notebook and take a look at the processed data.

The Blog Post with even more features is here: https://ilovesymposia.com/2019/10/24/introducing-napari-a-fast-n-dimensional-image-viewer-in-python/

Find the Github repo here: https://github.com/napari/napari
or jump in and

pip install napari

Physics-based Machine Learning Framework

DiffTaichi provides a framework for physics simulation in a differential way. Whether you’d like to tack your simulator on to a CNN to generate samples on the fly, or spice up your GAN-game, this is probably a tool, you’ll want in your toolkit. I have been quoted before that “Physics-based ML is just figuring out how to make your stuff differentiable”.

It’s part of the TaiChi language: https://github.com/yuanming-hu/taichi in the examples – difftaichi.

Check out the cute moving bots and impressive liquid models here:

Exploratory Data Analysis

Apparently SandDance was a thing before, but it’s open-source now and you can integrate it into VSCode.

SandDance by Microsoft

Read the blog here: https://cloudblogs.microsoft.com/opensource/2019/10/10/microsoft-open-sources-sanddance-visual-data-exploration-tool/

Get the VSCode extension here, and make sense of your CSV: https://marketplace.visualstudio.com/items?itemName=msrvida.vscode-sanddance

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Dear EAGE we have to talk! https://the-geophysicist.com/dear-eage-we-have-to-talk?utm_source=rss&utm_medium=rss&utm_campaign=dear-eage-we-have-to-talk Wed, 30 Oct 2019 13:00:06 +0000 https://the-geophysicist.com/?p=2436

Dear EAGE, you’re my professional society. We have history! Already during my Bachelor’s, I published an extended abstract with you. But you’ve changed. We need to talk about this. Please don’t mistake me for having illusions. As you know, I run this website and some others, I know the costs of doing business online. I’ve […]

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Dear EAGE,

you’re my professional society. We have history! Already during my Bachelor’s, I published an extended abstract with you. But you’ve changed. We need to talk about this.

Please don’t mistake me for having illusions. As you know, I run this website and some others, I know the costs of doing business online. I’ve run jobs on Amazon AWS, deployed on GCP and tinkered with the Azure cloud. Tech isn’t cheap at scale. Please don’t mistake me for not understanding what redundancy, on-demand, or all the other fancy enterprise-grade words are. I get, why under the hood you’ve switched to using EventsAir, maintaining an internal solution is a monstrous job.

On top, while I know volunteering on committees is essential, you maintain over 90 employees, possibly hitting a hundred soon. That is the reason why I got involved with committees and boards. You may remember even interviewing me on “Why I got involved” for a video project that is supposed to attract more young people into the society. And we both know that the industry at large, geoscience education, and the EAGE has a problem with attracting fresh minds more than ever.

Why then do you decide to implement a discriminative pricing structure agains early career researchers?

The New Price

So what’s the issue?
Let me give you the stage first, it is copied from your website.

In summary, all members of EAGE will retain a level of access, based on their recognition level. Even first year Green Members will be able to access the most recent two calendar years, and from the second year, upon becoming a Bronze Member, the most recent four calendar years will already be available, with our Platinum Members being able to access 19 calendar years of the archive. As you grow as a member, you will gain a deeper access to the archive, however should you need immediate access to the full archive for a year, a small contribution to support the new platform is asked, depending on your Membership Recognition level as per the table below. 

EAGE EarthDoc Update (courtesy EAGE)

To get the full view, I’d like to discuss the following screengrab too:

EAGE Membership benefit (courtesy EAGE)

The main explanation for this change in pricing structure is changing to an updated EarthDoc platform, which will have nifty features and better user experience, possibly making EarthDoc competitive with the updated SEG platform and professional publishing platforms like Elsevier.

What’s the Problem

These changes sound amazing when I read the EarthDoc Update, the initial email and the email you sent me after discovering my LinkedIn post and Twitter post. I’m sure the announcement by the president in First Break will sound amazing too. I really do, those are well-crafted texts.

Didn’t make it hard to discover, I play fair, I tagged the EAGE in all posts.

The problem is that these texts hide the reality behind these changes. The direct consequence of these pricing changes. And mind me, none of these awesome inventions and improvements mean anything, if you’re limiting access to them based on membership years*. (That asterisk will become important later.) This pricing structure is discriminating against Early Career Scientists.

New students, with fewer funding, get less access and pay more to gain access.

This is not a membership reward.

Please visit the softwareunderground.org and my LinkedIn Post, where some esteemed members of the community make great points about “sunk cost” and penalization, it’s also where I initially learned about this.

What’s the Other Problem?

Unfortunately, there’s more. Quick personal anecdote: I’m a sucker for tiers, awards and recognition levels. I’m a gamer, what can I say. Furing the last EAGE Annual I was a bit weirded out, my first year of EAGE was in 2011, my membership should’ve been silver right? I should’ve gotten a pin, right? I didn’t.

The membership system is more complicated. Which is not clear from the EarthDoc Update website. You have to click through to the Membership Recognition Program site.

Membership recognition levels (courtesy EAGE)

This system penalizes breaks or rewards streaks. My break while I did not have funding during my Master’s knocked me down to Bronze instead of Silver.

I understand that you want to incentivize continued membership. Did you notice, that Silver starts right after you finish your studies, IF you joined in your first Bachelor year (laughable idea). Did you also notice that the Hardship program starts at silver?

It’s funny how this adds up. I finished my Master’s in the downturn. Do you believe that me, no experience, not finding a job, barely making rent would prioritize my EAGE membership? No, that’s right. So there goes my streak AND my access to prior publications.

Let’s revisit the statement from before

New students, with fewer funding, get less access and pay more to gain access and do not get access to support after finishing their studies, which diminuishes the access further.

I’m quite young, mostly healthy, and childless. So let me just allude to the implications of this policy to people that want to build a family and take time off. “No honey you keep the EAGE membership, you can’t break your streak. I’ll stay home and take care of the kid and never return to science.” (Let’s not talk about the survey about childcare that only members that already registered for the event without childcare could answer). Or mind you people that get sick for a prolonged time.
The return to EAGE is therefore penalized.

So we have a bias against Early Career Scientists, and people that do not put their job first in everything, even health and family. But is there more?

Is it Anti-Science?

I’m a geoscientist in machine learning. I read trends. I wrote for the website IFLS and others. I love it when OpenAI makes a new fancy video with a robot doing some incredible thing. But science journalism is plagued with the “Shiny New Object”-syndrome. That’s why we hear “chocolate saves you from cancer” and “wine makes you live longer”, they’re reading a single new study on it and write an article on it. (There’s good journalism, don’t get me wrong. But everyone has seen this type.)

Considering the EAGE has a huge number of FWI sessions every year. Do you think students should just read the last 2 years of shiny applications of FWI to a proprietary dataset? Or should they be able to read the fundamentals and break-throughs?

For my thesis, I’ve read over 300 papers and extended abstracts on applications of machine learning in geoscience alone. I have them in a spreadsheet. I don’t know how many 4D seismic papers I’ve read in addition. Imagine, I would be limited to 4 years, or pay.

I’d love to read the method sections at the coming EAGE Annual Conference “Machine Learning in Geoscience has a rich history within the two years.*”

If I have seen further it is by standing on the shoulders of Giants.

Isaac Newton

Dear EAGE, we both know, who will pay extra for access to publications. We both know who will pay most for you being able to say “we have not increased our membership fees in years”.

It will come from the pockets of Early Career Scientists, whos fee you have just at least doubled and made harder to reimburse if that was ever an option.

The Alternatives

Let’s be clear here. With a bit of foresight, this could have been avoided. If you thought that the solution you bought X years ago would run forever, I have questions about that. There should have been a fund to update the site. As a scientific and engineering organization you have seen geoscience change from paper-based interpretation rooms to automatic seismic interpretation; From CDP to FWI. But instead of blaming, let’s talk about membership fees and money.

First Break

Look, I know we talked about this before. You’re sending me the First Break dead tree copy every time. Just like every post box is filled with the glossy paper no one reads. If I want an article, I’ll look it up. Who has the time?

We both know you don’t give an opt-out because advertisers pay good money for that sort of distribution. But I’d love to know if the advertisers pay enough for the ever-increasing printing and shipping costs, especially internationally.

Is my membership paying for that?

International Pricing

Why does every other organization recognize the different values of a Euro, but the EAGE does not?

Having an unequal pricing structure that does not automatically account for GDP or similar international inequality measures aggravates the effect on low-income countries. Maybe it’s time to rework that?

Even if you disagree on this, I don’t think we have to make this inequality worse by piling hidden costs on top, if they want to unlock a 3-year old article.

General Price Increase

Maybe be up-front about the blunder and don’t try to hide it in hidden discriminatory costs. Open honest communication that the technical debt of EarthDoc was becoming a significant Euro amount, would be more appropriate, no?

Why charge the scientists of the organization more, for the articles WE provide you with?

Let’s explore this further

I’m currently in Denmark. Definitely a high-GDP country. My Ph.D. is well-funded and I can reimburse most costs. 50€ is definitely way less than my weekly shopping. There’s funding for publishing and conferences even. You know who would not care about an international pricing schema that makes it cost an appropriate amount? Me in Denmark. I lived in Malaysia before, where I mostly ate out. 50 Euros would get me accommodation for a couple of days and nice food eating out every meal. When I was a student in Hamburg, Germany, I could definitely not reimburse the EAGE cost.

Money, support and reimbursements are very different from place to place. The places that need it care. The places that don’t need it can afford it.

With 19,000+ members, a 10 Euro increase would be ~200k. Is the software you’re getting much more expensive than that?

Ok another thought experiments, based on SEG pricing (but lower). Let’s say you keep the price for low-GDP steady and double the price for high-GDP. Assuming half the members are in the low tier and half in the high tier that’d be a nice half million euros. So maybe you wouldn’t even have to double it. Also maybe more than half of your members are high-GDP to be realistic.

I’m sure other folks have other ideas that are much better than my quick write-up.

Conclusion

You’ve taken a system that was meant to reward people and turned it against you newer members with less pull in the society.

You’re locking publications further down when alternatives like Diamond Open Access Journal Volcanica make publishing and reading free. Do you think your model has a future?

Do you think these changes make for a future-oriented society that is inclusive and strong in members with a reputation for good science?

I don’t. And I will rather break my streak than be complicit in a policy change like this.

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I like oxygen – Explaining #teamtrees https://the-geophysicist.com/i-like-oxygen-teamtrees?utm_source=rss&utm_medium=rss&utm_campaign=i-like-oxygen-teamtrees Sat, 26 Oct 2019 12:39:29 +0000 https://the-geophysicist.com/?p=2419

I woke up to my Youtube subscriptions exploding with the hashtag #teamtrees. What is Team Trees? The youtube phenomenon MrBeast recently reached 20 million subscribers, which lead to an idea going viral. People spammed MrBeast to plant 20 million trees to celebrate. So he assembled some friends. Now. During the climate strike, I’ve heard my […]

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I woke up to my Youtube subscriptions exploding with the hashtag #teamtrees. What is Team Trees?

The youtube phenomenon MrBeast recently reached 20 million subscribers, which lead to an idea going viral. People spammed MrBeast to plant 20 million trees to celebrate. So he assembled some friends.

https://twitter.com/YouTube/status/1187806031520268288

Now. During the climate strike, I’ve heard my fair share of people criticizing the younger generation, that they’re all talk. Fundraising 20 million dollars and partnering with the well-respected Arbor Day Foundation, is no small feat. Getting together some huge (non-controversial) Youtubers together including MKBHD, Linus Tech Tips, Captain Disillusion, and Mark Rober.

That is 1 tree for 1$.

But How?

I am always intrigued if Mark Rober posts a new video. Usually, his videos built some ridiculous but educational toy. This time it’s a little different and he explains, how Drone Seed automates planting trees in rough terrain using huge drones while planting smart.

Mark Robers video on planting 20 million trees using drones

And it quickly took off:

Over 550,000$ in an hour?

But Why?

Why do we even need trees?
Well, they make oxygen, but Stephanie Samma of Real Science explains it best in the following video.

Doing My Part

I decided to give as much as I can, which is not much. Please consider giving a Dollar or 1000, it matters. This is a chance to come together and reverse some of the damage humans have done to the planet.

Some action is really stupid. We’ve seen “unplug your phone charger to save the planet”. We’ve seen controversial straw bans. And the Extinction Rebellion is a great way to get into a shouting match with relatives.

I think, we can all come together on trees.

If you go over 50$, you get the cool dark green badge. Unfortunately, I don’t have a 1000$ to spare. The shiny blue-green badge is clearly the greatest.

My small contribution.

Donate!

Then enjoy some more tree facts, for how well you’ve done!

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Going Meta, Geovizualizations and the PyTorch Dev Con – Friday Faves https://the-geophysicist.com/going-meta-geovizualizations-and-the-pytorch-dev-con-friday-faves?utm_source=rss&utm_medium=rss&utm_campaign=going-meta-geovizualizations-and-the-pytorch-dev-con-friday-faves Fri, 25 Oct 2019 09:47:08 +0000 https://the-geophysicist.com/?p=2412

In this week’s Friday Faves we have some very cool animations for geoscience outreach, some meta reinforcement learning and this year’s PyTorch Dev Con. Amazing Geoscience Outreach Animations These geoscience acquisition animations are everything the small comics never where. Alexandre Normandeau is a research scientist in Canada and obviously has a knack for visualization, visit […]

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In this week’s Friday Faves we have some very cool animations for geoscience outreach, some meta reinforcement learning and this year’s PyTorch Dev Con.

Amazing Geoscience Outreach Animations

These geoscience acquisition animations are everything the small comics never where. Alexandre Normandeau is a research scientist in Canada and obviously has a knack for visualization, visit his website to find more. Anton Grønne Kühl initially posted them on slack and even had a chat with Alexandre about attaching a permissive license to these animations!

Sub-Bottom Profiling – CC-BY Alexandre Normandeau

Going Full Meta Learning

With state-of-the-art claims, you can often get a model that works on a specific dataset, but not on others. Multi-task reinforcement learning bears the promise of creating more robust agents. Whereas meta reinforcement learning bears the promise of learning to learn, then learning new tasks faster and better. This new benchmark promises to facilitate this research.

Check out the paper: https://arxiv.org/pdf/1910.10897.pdf
And their nice website: https://meta-world.github.io/

Pytorch Dev Con 2019

Pytorch, the open-source deep learning framework developed at Facebook has recently come to v1.3. The Dev Con was full of nuggets of wisdom.

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