Chunky Orbits and Stepped Realities: Make Noise Explores MultiMod’s Shaping Power

The heart of the demonstration lies in the staircase and ramp shapes, which fundamentally alter how the MultiMod processes incoming signals. The staircase shape, in particular, is highlighted as an alternative to the classic ramp—offering a stepped, rather than smooth, progression through the input material. Instead of a continuous sweep, the playback jumps at discrete intervals, creating a choppy, quantised rendition of whatever is fed into the module.

By patching in a cycling function from Maths, the video makes these differences audible. Fast spread settings yield a tightly stepped output, while slowing things down exaggerates the length of each step, eventually abstracting the input beyond recognition. The spread control further allows for channel differentiation, resulting in a patch that’s as visually jagged as it is sonically. It’s a clear illustration of how MultiMod’s shapes can transform even the simplest modulation source into something far more intricate.

With the basics established, the video leans into the metaphor of sound as food—likening the MultiMod’s discontinuous shapes to making coleslaw or a smoothie. This isn’t just whimsy; it’s a practical way to think about how the module chops and mixes input signals. By adjusting time, spread, and shape, users can determine just how rough or smooth their sonic concoction becomes.

The demonstration shows that by tweaking these parameters, one can move between highly stepped, almost granular modulations and smoother, more blended results. The interplay between the module’s controls invites experimentation, rewarding those who aren’t afraid to push the MultiMod into less predictable territory. It’s a reminder that modular synthesis is as much about process as it is about outcome.

Randomisation is introduced as a key ingredient in MultiMod’s palette. Switching to step random, the module assigns each channel a random position in its orbit at its own clock rate, breaking away from direct representation of the input shape. However, the input’s contour still influences the probability distribution—logarithmic functions bias the output high, exponential ones bias it low, and linear shapes yield even spread.

The video goes further, demonstrating how attenuating and offsetting the input can constrain the range of random outputs, enabling targeted randomness. Feeding in a gate stream transforms the MultiMod into a probabilistic gate generator, with pulse width and duty cycle controlling the likelihood of output events. Modulating these parameters in real time, or clocking the module for regularity, opens up a world of evolving, unpredictable rhythms—ideal for those who crave a bit of chaos in their patches.

The final section spotlights the Ramp Let’s shape, which randomly selects a starting point before moving forward through the input, producing a flock of miniature, offset curves. The presenter hints at the depth of creative potential here—suggesting that Ramp Let’s deserves its own dedicated exploration. Viewers are invited to share their own patch ideas in the comments, reinforcing the open-ended, community-driven ethos that Make Noise is known for.