The White House is rolling back emission restrictions. From Trump Administration Hardens Its Attack on Climate Science by B. Thibodeaux, 2019, https://static01.nyt.com/images/2019/05/24/us/politics/00dc-cli-trump1/merlin_151256502_8b48e75c-4479-4e89-a186-ae5f913c1c7b-jumbo.jpg
Donald Trump
Donald Trump is the 45th president with many less than positive traits. As the most powerful man in the most influential country in the world, his views and opinions have a large impact on how the world is shaped. Therefore, it does not help that he lacks common sense on many facets of the world, and his denial of scientific assessment of the climate change is one of many examples. In fact, he claims the term climate change is at least misleading if not a conspiracy theory (Davenport & Landler, 2019).
Events
Based on the news article by Davenport and Landler, the president elect has played hardline against the pro-environmentalist. For example, not only has he infamously retreated from the crucial Paris Accord, he recently has refused to acknowledge climate change by refusing to sign a document that uses the word “Climate Change” (Davenport & Landler, 2019). Under his guidance, the United States Geological Survey has recently recreated their information by unrealistically limiting the data to shorter time frame to mask away some of the likely and unfavorable conclusions (Davenport & Landler, 2019).
Remarks
For this author, Donald Trump is an easy man to dislike. Throughout this research, I was left with only one question for the man: is he truly an unintelligent man who simply became the most powerful man on Earth through luck, or is he simply a short-sighted man with low moral compass? While I am not well versed in the study of history, I would wager that would be the central theme of this era in the history books.
References
Davenport, C., & Landler, M. (2019, May 27). Trump Administration Hardens Its Attack on Climate Science. The New York Times. Retrieved June 23, 2019, from https://www.nytimes.com/2019/05/27/us/politics/trump-climate-science.html
AI for Earth In the Microsoft blog called “Researchers turn to AI in a bid to improve weather forecasts” by Roach, the author highlights some of the company's contribution to the research that benefits mankind. Through the AI for Earth initiative, the company funds various challenging research projects that studies Earth. The blog also highlights the social activities, such as hackathons, that illustrates some of the current trends of using machine learning to solve difficult problems. References Roach, J. (2019, May 20). Researchers turn to AI in a bid to improve weather forecasts. Retrieved May 26, 2019, from https://blogs.microsoft.com/ai/ai-subseasonal-weather-forecast/
Personalization The Faceapp is a controversial phone app that manipulates a person’s picture to show how the person would look many years from now (Koetsier, 2019). Controversies aside, it is an interesting app that has sparked an explosive interest from the general population by showing them a personal and likely future of its user. In many ways, Schmidt and his colleagues had a very similar idea in their effort to gain public interest on climate change: show a personal and likely future of its user (Schmidt, et al., 2019). Instead of face, the team used house, and instead of just few years of aging, the team showed the future after 50 years with likely climate change and the related natural disaster in mind (Schmidt, et al., 2019). Figure 1: "Before" and "After" Pictures. From Visualizing the consequences of climate change using cycle-consistent adversarial networks by V. Schmidt, et al., 2019 Conclusion This is a refreshing effort by scientists to nud...
About In this 2018 paper, “Predicting weather forecast uncertainty with machine learning” by professor Scher and professor Messori, shows an early effort to test the feasibility of the technology as a potential replacement to the popular ensemble weather model approach. The ensemble weather model approach, as the name suggest, is similar to having a panel of experts instead of just one expert; the approach produces information that is a composite of different information generated by multiple models given the same input data. Each model caters to different specialization and has their own strength and weaknesses, and by combining information from each model, the approach attempts to generate more accurate information. As such, while it increases the accuracy and precision, it became computationally very expensive to perform in a timely manner. The researchers’ goal was to provide a competitive solution to the computationally expensive ensemble weather model approach by using machine ...
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