How it is Made? Amazing Star Wars Visual Affects Video
We all watch movies and decide it is good or bad just in second. And 2015’s best film was Star Wars. I personally was hoping for a better story from the writers, conversations were really weak, the only characters that We like were Ray and BB-88.
We all watch movies and decide it is good or bad just in second. And 2015’s best film was Star Wars. I personally was hoping for a better story from the writers, conversations were really weak, the only characters that We like were Ray and BB-88. Many people on IMDB just give the lowest points in their reviews, one of the highest one I have ever seen in IMDB. This low point reviews effects of high expectation, people gone crazy just for the trailers before the movie releases. And many didn’t accept a movie that looks like and old one.
READ ALSO: 14 Percent of The Disney World Closed for Building the New Star Wars Land
But we didn’t see any bad reviews about visual effects from the film. I just wanted to watch because I really liked what J.J. Abrams did for Star Trek movies ( thank god there were no lens flares ). The team made a great movie; it is obvious they spend countless ours for the effects. We just see some images for seconds, and they spend days for that couple of seconds. I can’t say the story was so good, and not all the character were my favorite, but the effect deserves Respect.!!
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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