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What if China no longer needs Hollywood?
www.cnn.com/2021/01/28/media/china-box-office-coronavirus/index.html
“In 2020, China overtook the United States to become the top movie market in the world. The country, perennially the second-largest movie market, brought in $3.1 billion at the box office in 2020, according to Comscore (SCOR) โ nearly $1 billion more than the United States did last year.
“If China doesn’t need US movies, Hollywood studios will have to dramatically reduce their spending on big budget blockbusters,” Aynne Kokas, the author of “Hollywood Made in China,” told CNN Business. “The current budgets are unsustainable without access to the China market. That could fundamentally change the model of the US film industry.”
“Regardless of what happens with Covid, we have at a minimum entered a world where the Chinese and US box offices are equally important,”
So where do Hollywood and China go from here? That question, like so many in the film industry right now, has no easy answer. Yet whatever the future of the film industry is, it’s likely to be one where Hollywood and China remain the two major pillars holding up the global box office.
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Andreas Horn – Want cutting edge AI?
๐ง๐ต๐ฒ ๐ฏ๐๐ถ๐น๐ฑ๐ถ๐ป๐ด ๐ฏ๐น๐ผ๐ฐ๐ธ๐ ๐ผ๐ณ ๐๐ ๐ฎ๐ป๐ฑ ๐ฒ๐๐๐ฒ๐ป๐๐ถ๐ฎ๐น ๐ฝ๐ฟ๐ผ๐ฐ๐ฒ๐๐๐ฒ๐:
– Collect: Data from sensors, logs, and user input.
– Move/Store: Build infrastructure, pipelines, and reliable data flow.
– Explore/Transform: Clean, prep, and detect anomalies to make the data usable.
– Aggregate/Label: Add analytics, metrics, and labels to create training data.
– Learn/Optimize: Experiment, test, and train AI models.๐ง๐ต๐ฒ ๐น๐ฎ๐๐ฒ๐ฟ๐ ๐ผ๐ณ ๐ฑ๐ฎ๐๐ฎ ๐ฎ๐ป๐ฑ ๐ต๐ผ๐ ๐๐ต๐ฒ๐ ๐ฏ๐ฒ๐ฐ๐ผ๐บ๐ฒ ๐ถ๐ป๐๐ฒ๐น๐น๐ถ๐ด๐ฒ๐ป๐:
– Instrumentation and logging: Sensors, logs, and external data capture the raw inputs.
– Data flow and storage: Pipelines and infrastructure ensure smooth movement and reliable storage.
– Exploration and transformation: Data is cleaned, prepped, and anomalies are detected.
– Aggregation and labeling: Analytics, metrics, and labels create structured, usable datasets.
– Experimenting/AI/ML: Models are trained and optimized using the prepared data.
– AI insights and actions: Advanced AI generates predictions, insights, and decisions at the top.๐ช๐ต๐ผ ๐บ๐ฎ๐ธ๐ฒ๐ ๐ถ๐ ๐ต๐ฎ๐ฝ๐ฝ๐ฒ๐ป ๐ฎ๐ป๐ฑ ๐ธ๐ฒ๐ ๐ฟ๐ผ๐น๐ฒ๐:
– Data Infrastructure Engineers: Build the foundation โ collect, move, and store data.
– Data Engineers: Prep and transform the data into usable formats.
– Data Analysts & Scientists: Aggregate, label, and generate insights.
– Machine Learning Engineers: Optimize and deploy AI models.๐ง๐ต๐ฒ ๐บ๐ฎ๐ด๐ถ๐ฐ ๐ผ๐ณ ๐๐ ๐ถ๐ ๐ถ๐ป ๐ต๐ผ๐ ๐๐ต๐ฒ๐๐ฒ ๐น๐ฎ๐๐ฒ๐ฟ๐ ๐ฎ๐ป๐ฑ ๐ฟ๐ผ๐น๐ฒ๐ ๐๐ผ๐ฟ๐ธ ๐๐ผ๐ด๐ฒ๐๐ต๐ฒ๐ฟ. ๐ง๐ต๐ฒ ๐๐๐ฟ๐ผ๐ป๐ด๐ฒ๐ฟ ๐๐ผ๐๐ฟ ๐ณ๐ผ๐๐ป๐ฑ๐ฎ๐๐ถ๐ผ๐ป, ๐๐ต๐ฒ ๐๐บ๐ฎ๐ฟ๐๐ฒ๐ฟ ๐๐ผ๐๐ฟ ๐๐.
