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mikegrr

I asked ChatCBT "atc phraseology for departing airplanes"

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This is some of what it came up with. Seems like AI can easily be used for ATC. I just asked a basic question and got detailed instructions... I'm not sure if this has been discussed before but here goes.

  • Initial Contact with Ground Control:

    • Pilot: "Ground, [Aircraft Callsign], [Aircraft Type], at [Current Location], with [ATIS Information], ready to taxi."
    • Ground Control: " [Aircraft Callsign], taxi to [Runway Number] via [Taxiways], [Additional Instructions if Necessary]."
  • Taxi Instructions:

    • Ground Control will provide taxi instructions to the runway, which may include specific taxiway routes and hold short instructions for other runways or intersections.
  • Holding Short of Runway:

    • Pilot: "Tower, [Aircraft Callsign], holding short of [Runway Number]."
    • Tower: "[Aircraft Callsign], hold short of [Runway Number], landing [Aircraft Type] on final."
  • Takeoff Clearance:

    • Tower: "[Aircraft Callsign], [Wind Information], [Cleared for Takeoff], [Runway Number]."
    • Pilot: "Cleared for takeoff, [Runway Number], [Aircraft Callsign]."
  • After Takeoff Instructions:

    • Tower may provide instructions for a specific departure procedure, heading, or altitude to follow after takeoff.
  • Departure Frequency:

    • Tower: "Contact [Departure Control Frequency] on [Squawk Code]."
    • Pilot: "Contact [Departure Control Frequency] on [Squawk Code], [Aircraft Callsign]."
  • Initial Departure Communication with Departure Control:

    • Pilot: "Departure, [Aircraft Callsign], [Altitude], climbing [Direction]."
    • Departure Control: "[Aircraft Callsign], radar contact, climb and maintain [Assigned Altitude]."

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Well AI is way off lol


flight sim addict, airplane owner, CFI

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48 minutes ago, sd_flyer said:

Well AI is way off lol

Yep lol


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I do wonder what ChatGPT would come up with... 😎

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The Large Language Model (LLM) AI's would just need to be "trained"....i.e. exposed to an enormous chunk of contextualized data (ATC conversations, preferably with tags for good and bad outcomes), and you'd get much more accurate answers.

LLM's make the whole machine learning part easier (as I understand it), because you don't necessarily have to program in every single rule. Just feed it good data, and it kinda figures it out   <<<That's an oversimplification.

DB

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