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Monte Carlo Simulation

There is nothing much interesting about Monaco aside from Monte Carlo (the famous high-end gambling place, which I deliberately skipped for obvious reasons), the race that was unfortunately off-season during my visit, and the fleeting ritzy and luxurious vibe of this country as heard from the grapevine. So really, I am struggling with something to write at this moment. Anyways, on the train, there was one person who asked me questions about the cameras I clumsily dropped while fixing my things. I found the questions hard to answer as I honestly do not care enough to know such details. So, right then and there I made a conscious effort to once and for all check and looknfor answers, to be able to have a confident response when such questions pop up again in the future. 


Basically, I have my Huawei P30 phone, dedicated for Instagram stories and quick Facebook posts. For a self-confessed Android apologist, I am quite pleased with the quality of photos and videos this phone gives, though might not be as excellent compared to its contemporaries. Secondly, I have the Sony α6000 mirrorless camera I bought in 2019 at a much lower price through a Black Friday sale, equipped with a free Sony 55-210mm OSS lens, offering precision. Lastly, I acquired this GoPro Black 10 as a Christmas steal, surpassing expectations much like the surprise outcomes of Monte Carlo iterations. For me, GoPro’s size is a game changer, doing all the dirty tricks, single-handedly putting my Sony cam to a redundancy situation; considering the following shots, and this vid.

 


So, the moral of the story? Continuously learn new things, no matter how small or big. They always count as a step toward some iterative refinement, just like how it goes in Monte Carlo simulations.








This post first appeared on Olvr's Trvls, please read the originial post: here

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Monte Carlo Simulation

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