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2030 = No Water = No Food = No Green Energy
Today they are 96%. Just 4% of land vertebrates by weight are wild.
We have to grow more food in 30 years than we did in the last 3,000 years.
If you are 15 years old, emission went up 30% in your lifetime - Global Carbon Project 2018
If you are 30 years old emissions went up 50% in your lifetime - Global Carbon Project 2018
The world totally failed 4 major global climate initiatives in 30 years - Government of Canada
It took 30 years for solar and wind to reach 4% of world energy - BP Statistical Review 2019
In 2019 renewable energy is 4% of world energy – Wall Street Journal 2019
Renewable energy will be 15% of world energy by 2040 – BP 2019
Global energy use will grow 1% / yr until 2040 due to economic and population growth - CNBC 2019
Renewable energy may be 20% of global energy by 2040 at most.1573591637655.png) - CNBC 2019
At this rate will take 400 years for 100% renewable energy - MIT 2018
Warming must stop at 1.5 °C or life on earth will collapse – Nature 2019
By 2030 human emissions will be 38% higher than needed to stay below 1.5 °C - UN 2019
By 2030 fossil fuel emissions will be 150% higher than needed to stay below 1.5 °C - Production 2019
By 2030 emissions must go down 55% to stay under 1.5 °C - Science Magazine 2019
2030 - 2050 = 1.5 °C on earth - Reuters 2018
The "New Energy Economy": An Exercise in Magical Thinking - Manhatten Project 2019
Why Renewable Energy Can’t Save the Planet- Quillette 2019
U.S. Electrical Grid on the Edge of Failure - Scientific American 2013
The extreme vulnerability of power grids - Nature Physics 2013
America's infrastructure is decaying - Business Insider 2019
America's Electrical Grid Is Falling Apart - Whowhatwhy.org 2017
The Challenges and Requirements for a New Power Grid - Lexington 2016
As the United States economy and society have become more reliant on the uninterrupted flow of electricity, the power grid upon which it depends for that supply has experienced deteriorating reliability. The grid loses power 285% more often today than in 1984.Revenge of the Power Grid - Atlantic 2019
Why It's So Hard to Restart Venezuela's Power Grid - Wired 2019
Re-energizing a dead grid, a process known as a black start, is challenging under any circumstances —a problem exacerbated by aging infrastructure.What would happen in an apocalyptic blackout? - BBC 2019
Growing demand on our electricity supplies from rising populations and new technologies like electric cars will face increasing instability as we shift to more renewable, but intermittent energy sources like wind and solar power.Blackouts: a sociology of electrical power failure - Core UK undated
Electric vehicles could stall due to mineral shortages - Petroleum Economist 2019
US, Canada and Australia join forces to tackle metal shortage risk - Financial Times 2019
Tesla expects global shortage of electric vehicle battery minerals - Reuters 2019
Shift to renewable energy could have biodiversity cost - Monga Bay 2019
We Don't Mine Enough Rare Earth Metals to Replace Fossil Fuels With Renewable Energy - Motherboard 2018
Top supply shocks humanity isn’t prepared for - Russia Today 2019
Forests should never be used to serve our electricity needs - The Hill 2019
Insects could die out in worst extinction since the dinosaurs
OZONE NOT RECOVERING
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Mass extinction is preceding runaway hothouse chaos. Within this century our oceans will become super saturated with carbon and destroy most of the plankton on earth. In other words, earth won't be fine without us.
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[P] TensorFlow 2.0 Implementation of Yolo V3 Object Detection Network
Hey reddit ml, I am sharing my implementation of YoloV3 in TensorFlow 2.0 alphasubmitted by zzh8829 to MachineLearning
There is a lot of buzz around TensorFlow 2.0 with tons of blog posts and tutorial. But I haven't found a complete example that uses all the latest features and best practices brought by TF2. This project is created with the goal of being clean, efficient and complete with zero legacy debts.
Some of the key features include:
The YoloV3 implementation is mostly referenced from the origin paper, original darknet with inspirations from many existing code written in PyTorch, Keras and TF1 (I credited them at the end of the README). I tried to fixed all the inconsistency, incompleteness and minor errors existing in other repos here. The project works with both YoloV3 and YoloV3-Tiny and is compatible with pre-trained darknet weights.
Example of detection output:
This project has been quite a great learning experience for me. After working with TF1 and then Keras and then PyTorch, coming back to TensorFlow 2.0 feels very refreshing and enjoyable. TF2 will definitely rise and shine in the coming months following the official GA release.