Pardis

Pardis (Persian: پردیس‎) is a city in Pardis County, Tehran Province, Iran. It is a suburb located 17 kilometers northeast of Tehran. The city is home to 73,363 people as of 2016 according to the Census Bureau.[1] Pardis is a planned city that at the end of its construction should reach a population of 600,000.

For other uses, see Pardis (disambiguation).
Pardis

پرديس
City
Pardis
Coordinates: 35°44′16″N 51°48′56″E
Country Iran
ProvinceTehran
CountyPardis
DistrictBumehen
Area
 • Total276.3 km2 (106.7 sq mi)
Elevation
1,800 m (5,900 ft)
Population
 (2016 Census)
 • Total73,363 [1]
Time zoneUTC+3:30 (IRST)
 • Summer (DST)UTC+4:30 (IRDT)
Pardis County Historical population
YearPop.±%
200625,360—    
201137,257+46.9%
201673,363+96.9%
amar.org.ir
Pardis Mehr Housing press conference.

Technology Park

Adjacent to a Telecommunication Company of Iran Satellite Earth Station, is Pardis Technology Park. Land has been allocated for the establishment of business related to technology.

Pars Online, an Iranian ISP, has established the first private Data center in Iran, at Pardis Technology Park.

gollark: As if that's possible.
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

References
  1. "Statistical Center of Iran > Home". www.amar.org.ir.


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