Hun Hunshi Hunshilal

Hun Hunshi Hunshilal (English Title: Love in the Time of Malaria) is a 1992 Indian Gujarati-language musical political satire film directed by Sanjiv Shah.[1][2]

Hun Hunshi Hunshilal
Directed bySanjiv Shah
Produced bySanjiv Shah
Written byParesh Naik
Starring
Music byRajat Dholakia
CinematographyNavroze Contractor
Production
company
Karnar Productions
Release date
1992
Running time
120 minutes
CountryIndia
LanguageGujarati

Plot

In the kingdom of Khojpuri, King Bhadrabhoop II (Mohan Gokhale), is annoyed by mosquitoes (representative of middle and lower class).

In a small village, Doongri, Hunshi is born to a doctor. After growing up, he adopts more respectable moniker, Hunshilal (Dilip Joshi). Hunshilal moves to Khojpuri to work at Queen's Lab, a laboratory which aims to eradicate mosquitoes problem once and for all. At the lab, Hunshilal falls in love with the fellow scientist, Parveen (Renuka Shahane).

Cast

Soundtrack

The film had 45 songs. The composer Rajat Dholakia composed them in two days.[3]

gollark: Fearsome.
gollark: I might have to release apioforms from the beecloud.
gollark: It must comfort you to think so.
gollark: > There is burgeoning interest in designing AI-basedsystems to assist humans in designing computing systems,including tools that automatically generate computer code.The most notable of these comes in the form of the first self-described ‘AI pair programmer’, GitHub Copilot, a languagemodel trained over open-source GitHub code. However, codeoften contains bugs—and so, given the vast quantity of unvettedcode that Copilot has processed, it is certain that the languagemodel will have learned from exploitable, buggy code. Thisraises concerns on the security of Copilot’s code contributions.In this work, we systematically investigate the prevalence andconditions that can cause GitHub Copilot to recommend insecurecode. To perform this analysis we prompt Copilot to generatecode in scenarios relevant to high-risk CWEs (e.g. those fromMITRE’s “Top 25” list). We explore Copilot’s performance onthree distinct code generation axes—examining how it performsgiven diversity of weaknesses, diversity of prompts, and diversityof domains. In total, we produce 89 different scenarios forCopilot to complete, producing 1,692 programs. Of these, wefound approximately 40 % to be vulnerable.Index Terms—Cybersecurity, AI, code generation, CWE
gollark: https://arxiv.org/pdf/2108.09293.pdf

References


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