Becoming Dick

Becoming Dick is a 2000 comedy movie-made-for-television starring Harland Williams and directed by Bob Saget.

Becoming Dick
GenreComedy
Written byRick Gitelson
Directed byBob Saget
StarringHarland Williams
Robert Wagner
Elizabeth Berkley
William B. Davis
Woody Jeffreys
Bob Saget
Music byPeter Rodgers Melnick
Country of originUnited States
Canada
Original language(s)English
Production
Executive producer(s)Lynn Deegan
James Shavick
Producer(s)Shawn Williamson
Production location(s)Vancouver
CinematographyRon Orieux
Editor(s)Ron Yoshida
Running time120 minutes
Production company(s)BD Productions
Exclamation Productions
Shavick Entertainment
DistributorE!
Release
Picture formatColor
Original releaseAugust 31, 2000

Plot

Richard Breggs (Harland Williams) is a struggling actor living in an apartment with his girlfriend. After a conversation with a friend, Richard decides that he is too much of a "nice guy" and that the key to success is to act like a jerk. After his new obnoxious personality lands him a part in a play, Richard thinks he is on his way to being a success. He goes to sleep in his apartment and wakes up in a mansion. It is four years later, but Richard doesn't remember anything that has happened in the elapsed time, due to an accidental bump on the head that gave him amnesia. It turns out that he is now a famous TV star, known for being obnoxious, selfish, and difficult to work with. Richard (now known as Dick) realizes that while his new personality gave him success, it also caused him to lose his girlfriend and best friend. He sets about trying to right the wrongs of the past 4 years.[1]

Production

The film was shot in Vancouver, British Columbia, Canada.

gollark: The embeddings for your example sentences are the same each time you run the model, so you can just store them somewhere and run the cosine similarity thing on all of them in bulk.
gollark: Well, it doesn't look like you ever actually move the `roberta-large-mnli` model to your GPU, but I think the Sentence Transformers one is slow because you're using it wrong.
gollark: For the sentence_transformers one, are you precomputing the embeddings for the example sentences *then* just cosine-similaritying them against the new sentence? Because if not that's probably a very large bottleneck.
gollark: sentence_transformers says you should be able to do several thousand sentences a second on a V100, which I'm pretty sure is worse than your GPU. Are you actually running it on the GPU?
gollark: https://www.theverge.com/2021/10/28/22751220/facebook-portal-oculus-quest-meta-horizon-renaming

References

  1. Summary written by Jaclyn Mussehl, imdb.com


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