Audio Damage AD042 Axon 2 v2.1.1 WiN / OSX / LiNUX
Audio Damage AD042 Axon 2 v2.1.1 WiN / OSX / LiNUX | 20 Mb
Axon 2 is a drum synth driven by artificial intelligence. (Well, "intelligence" might be a strong word. Artificial something-or-other.) An experimental instrument, Axon uses a modified artificial neural network as a sequencer, and features seven FM-based percussion voices, that are really a single 18-operator FM voice.
Changelog
V2.1.1
New:
>>> Pitch knob replaced with larger display and increment/decrement buttons; this is much easier to use, especially on touch screens.
>>> Multiple outs are back! In addition to the main stereo outs, each Neuron has its own stereo output, labeled "Neuron 00" through "Neuron 06." Unlike Axon 1, the mixer in Axon affects these outputs. In testing, we found this to be the more desirable behavior.
>>> A demo version (not that you care if you're reading this) and a Linux x64 (Ubuntu 18+) version have been added to the deployment.
Fixes And Changes:
>>> The MIDI output has been re-written to suck less. The main thing you'll notice is that the output notes follow the pitch for the attendent neuron. So if, say, Neuron 02 is set to a pitch of C3, the MIDI note that neuron outputs will be 36 (C3).
>>> Axon 2 was rebuilt with all current SDKs. A result of this is that the 32-bit versions have been removed from the deployment, and the required systems have been changed to Windows 8.1 or greater, macOS 10.11 or greater, iOS/iPadOS 11 or greater, and Ubuntu 18 or greater.
>>> The macOS preset location has been changed to ~/Music. Axon 2.1.0 will create a new folder with new factory presets in this location the first time it is instanced. If you have user presets, you can just manually move them from the old location (/Library/Application Support/Audio Damage/Axon 2/Presets/User) to the new one. Once you have done this, you can delete the old Axon2 folder in Application Support. We attempted to do this automatically with the Quanta installer, and, well, you all know how that turned out for Catalina users, so we've decided to be less aggressive this time.
>>> Many optimizations, refactorings, and general shennannigans.