Creative Monster




During the winter of 2018, I spent four days in Lisbon working with the Muse.Ai team to explore logo concepts and develop identity ideas.

Important influences in this creative process included AI functionality, data visualization, biological processes, pastel de Nata and synesthesia.

The following collection of reference material and refined variations convey and explain the unique concepts developed during this period.





To tackle this challenge, I researched and drew inspiration from a variety of sources, including neural networks, computer algorithms, classic visual illusions, sci-fi tropes, Pastel de nata, data visualisation and even the physics of light itself.

Screen Shot 2018-01-08 at 13.50.30.png



Beginning with linear variants, six notable concepts preceded the final three final Muse.Ai logo treatments. Developed in tandem, these early explorations occasionally overlap themes, providing early steps toward mature ideas.

A constant theme in early iterations is light itself. The definitive heart of all photography and video, light and the colour spectrum feature heavily in most of my Muse.Ai logo work.








In an effort to simplify and stylize the monogram, I combined coloured equilateral triangles into a recognizable M shape. I then involved light properties by creating a third triangle within the overlap, using animation to simulate light spectrum combinations.





Building upon the Triangle monogram, I began adding linear elements and shapes into the M letterform, and chose a red, green and blue palette to convey the legacy of RGB light diodes.





Further elaboration upon the smooth, patterned M iteration from the previous section uncovered a likeness to sound itself, visually interpreted as sinusoidal waves.

A crucial element of video, I tried to develop this concept into an appropriate logo, combining it with input / output symbology, binary colour themes, circles and squares.





Perhaps the weakest of the initial explorations, this concept is a tangent of the Wave idea, solidified and cropped to form an abstract M interpretation.

I tried including the other letters of the company name with a matching treatment to augment the M, but the idea remains strongest as a monogram.





Returning to the exploration of light and its role in video, I tested spotlight effects in a simple animation. I then tried combining the style of classic 8-bit graphic pixellation with coloured spotlight dynamics to merge technology and light, first experimenting with abstract forms, forming an M, and then the word MUSE. 





Seeking to better combine the core elements of the MUSE.Ai service, I developed iterations that combined the established iconography of search, memory and video. 

Eventually I devised this linear combination of all three, comprised of a magnifying glass, a stylized human head and a playback icon, respectively.




From this four-day design process, three main logo concepts prevailed, each based on the combination of binary nodes and the vizualisation of a neural net. 

After receiving constructive feedback from the MUSE.Ai team, these selections seemed to most effectively resonate with the product, company and intent of the online video index AI service itself.





A linear interpretation of a binary tree as an M, this treatment evolved from a simple monogram into definitive ‘rigid’ and ‘organic’ variants.





The Rigid variety display nodes that share equal diameter, distance and weight relative to one another on an established triangular grid. Without connective lines, these nodes (solid or outlined) form a hard, semi-abstract representation, just barely maintaining the necessary aesthetic to form a recognisable M. When lit in sequence, the nodes create an intriguing animation, especially when connective data strings are shown.







Organic versions adhere to the same underlying grid alignment, but vary in all other aspects, creating a far more playful and slightly chaotic interpretation of the Rigid binary nodes. Again stretching the limits of the letterform, the Organic variations also embody themes of movement and brightness, as though firing independently or within a series* (as demonstrated in the animated .gif’s).


*It is worth noting that this family is the designer’s favourite and personal choice for the Muse.Ai logo.





A combination of the primary letter, binary data transfer nodes/strings and input / output influences, the Linear M logo variants are simplified interpretations that focus on a simple, clear monogram. 

Rounded edges, linear movement and the subtle inclusion of a classic ‘play’ icon help establish this variant as a strong visual logo that works at almost any size and use case, and is also effective as an animation.





While working on the Binary Node concepts, I began exploring serious typographic treatments for the “MUSE.AI” company name. Beginning with character simplification, I experimented with the replacement of the E middle crossbar with a circle, sized to match both the . and the dot of the i. 

The influence of the Binary Node concept spawned the idea of interaction between these elements, forming nodes of their own amongst a new imaginary data stream, spanning first between the three circles (and, in one iteration, to all points of each letterform!). 


As with most logo variants, the simplest iterations remain the most powerful... the triangular perhaps the clearest and strongest of all. An advantage of this full-length logo concept is that it also legibly includes the entire company name, not simply a monogram or a symbol. It would also work as either a static image, as visual signage, or as an animation. Furthermore, it might be possible to combine the Linear M concept with this one to allow for both a simple and a full version of this clever concept.