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GigFast Lite by ArteraDSP (Released)

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Comments

  • SchmotownSchmotown

    Even though these are big, loud amps being captured, using the “A” channel produces some beautiful clean and near-clean tones. No doubt @flo will produce another excellent demo.

    I am so impressed by this app, especially after the update. Great work from the @ArteraDSP team!

  • ltf3ltf3

    Question for ArteraDSP re: GF amp Gain

    I understand that these neural amp 'captures' are snapshots of an amp at a particular setting. How then does the GF App's "Gain" control function? If, for example the A Channel was captured with the physical amp at Gain=5, does reducing the GF App's Gain to Gain=2 actually drive the amp model less? Seems like it couldn't ... but it does seem to clean up the sound. How?

    It seems to me the GF App tone controls / volume etc would be as if a guitar/amp/processing/cabinet/mic were run through a desk and EQ's/processed there... just adjusting the sound of the whole composite 'rig' .

    Thanks for any illumination

  • espiegel123espiegel123

    @ltf3 said:
    Question for ArteraDSP re: GF amp Gain

    I understand that these neural amp 'captures' are snapshots of an amp at a particular setting. How then does the GF App's "Gain" control function? If, for example the A Channel was captured with the physical amp at Gain=5, does reducing the GF App's Gain to Gain=2 actually drive the amp model less? Seems like it couldn't ... but it does seem to clean up the sound. How?

    It seems to me the GF App tone controls / volume etc would be as if a guitar/amp/processing/cabinet/mic were run through a desk and EQ's/processed there... just adjusting the sound of the whole composite 'rig' .

    Thanks for any illumination

    Gigfast Lite’s built in models are parametric “captures” not just captures of an amp at one setting. Essentially, a parametric capture is done by performing many captures at different settings and the knobs essentially morph between the captures. So each built-in model is like having many captures and as you change the gain it changes the capture being used.

    When you load a NAM model though, you are using a static capture.

  • ArteraDSPArteraDSP

    @espiegel123 said:

    @ltf3 said:
    Question for ArteraDSP re: GF amp Gain

    I understand that these neural amp 'captures' are snapshots of an amp at a particular setting. How then does the GF App's "Gain" control function? If, for example the A Channel was captured with the physical amp at Gain=5, does reducing the GF App's Gain to Gain=2 actually drive the amp model less? Seems like it couldn't ... but it does seem to clean up the sound. How?

    It seems to me the GF App tone controls / volume etc would be as if a guitar/amp/processing/cabinet/mic were run through a desk and EQ's/processed there... just adjusting the sound of the whole composite 'rig' .

    Thanks for any illumination

    Gigfast Lite’s built in models are parametric “captures” not just captures of an amp at one setting. Essentially, a parametric capture is done by performing many captures at different settings and the knobs essentially morph between the captures. So each built-in model is like having many captures and as you change the gain it changes the capture being used.

    When you load a NAM model though, you are using a static capture.

    You are partly correct but, we are not changing captures based on the knob positions, instead we train the network with all settings at once thus resulting our parametric models. We are not the only company doing that for sure but using the NAM as the core gave us a pleasing advantage.

  • ArteraDSPArteraDSP

    Another GigFast Lite V2 video from our team!
    No post processing applied, stock amp, stock cab.

  • ltf3ltf3

    You are partly correct but, we are not changing captures based on the knob positions, instead we train the network with all settings at once

    Thanks for the description ... but what does "all settings at once" mean .... other than how most people describe my playing!

    Does it mean that instead of capturing a particular set up of amp knobs, multiple times, training for each set up then morphing between them... you somehow capture every knob setting combination, and feed that to the trainer all in one go? So then the knobs in GF are 'linked' to the loaded model ?( not for generic .nam files obviously ).

    Clearly I only know the basics of Neural Amp Modeling but I'm interested. Not trying to steal your magic! ;-)

  • ArteraDSPArteraDSP

    @ltf3 said:

    You are partly correct but, we are not changing captures based on the knob positions, instead we train the network with all settings at once

    Thanks for the description ... but what does "all settings at once" mean .... other than how most people describe my playing!

    Does it mean that instead of capturing a particular set up of amp knobs, multiple times, training for each set up then morphing between them... you somehow capture every knob setting combination, and feed that to the trainer all in one go? So then the knobs in GF are 'linked' to the loaded model ?( not for generic .nam files obviously ).

    Clearly I only know the basics of Neural Amp Modeling but I'm interested. Not trying to steal your magic! ;-)

    We somehow capture big data set with knob setting combinations, and feed that to the trainer all in one go. The knobs in GF are 'linked' to the loaded single file for each channel.

  • ArteraDSPArteraDSP

    An in-depth review of GigFast Lite, highlighting the wide range of tonal possibilities and the dynamic response of our Parametric Modeled Amps. (Video is in Turkish, but captions are available.)

  • ArteraDSPArteraDSP

    Emotional soloing with Gigfast Lite V2. It is not all about high gain. Gigfast Lite can handle ambient low gain tones with ease. For the purpose of this demonstration Fırat Öz jammed on to a youtube backing track. Dialed in a quick tone using our MJM-800 amp and MJM Dual 57 cabinet with the stereo delay inside the app. No post processing. Gigfast Lite V2 is available in appstore. Don’t forget to use #gigfastlite #arteradsp hashtags, tag us, add as collaborator in your videos.

  • ArteraDSPArteraDSP

    With the introduction of GigFast Lite Version 2, we're thrilled to create a dedicated space to connect with our users.
    As NAMM 2025 approaches, we're gearing up for some exciting announcements that we also wanted to share directly with you and get your valuable feedback about how things finalize.
    Thanks for incredible support so far!

    https://www.facebook.com/share/g/17TUUQ5DD8/

  • ArteraDSPArteraDSP

    Hello everyone. We have a black Friday sales going on until 02 December. You can save 25% for lifetime access to GigFast Lite!!! Come join the tribe!!!

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