SILICON SPECIES
BEERS
SP3KTRAL IPA
ABV: 6.0%
STYLE: IPA
SPECIES OF FOCUS: Gh0st
DESCRIPTION: IPA hopped w Calypso, Mosaic, Strata, Motueka & Mandarina Bavaria. Recipe created by model Gh0st.
ISL4NDBERRY
ABV: 6.2%
STYLE: Fruited Sour.
SPECIES OF FOCUS: Darw1n
DESCRIPTION: Sour ale brewed with strawberries, lime flavor, pineapple, lactose, vanilla, and natural flavors.
SILICON SPECIES
The hypothetical and theoretical "Silicon” species creating beer recipes via AI and machine learning.
Model Name: Darw1n
Algorithms:
■ Genetic Algorithm
In the genetic algorithm, parent algorithms "mate", and give birth to new offspring until the generation cycle is complete. Each offspring is given an accuracy score, and the highest scoring offspring "survives", as the rest of the population is then "killed off". This surviving offspring then continues on to initiate the next generation cycle, and is paired up with more algorithms to repeat the cycle.
Guardrails:
Darw1n has guardrails implemented to provide optimization for fruited sours only. It is also the most time consuming and compute intensive model, running anywhere between 4 hours to 48 hours to complete training.
Model Name: Gh0st
Primary Algorithms:
■ Boosted Trees Regressor
■ Extra Trees Regressor
■ Random Forest Regressor
■ OMP (Orthogonal Matching Pursuit)
■ DNN (Deep Neural Network)
■ TNN (Transformer)
Gh0st primarily utilizes an ensemble of algorithms to optimize beer recipe outputs. The ensemble approach allows combining multiple algorithms together to enhance overall performance.
Gh0st is very liquid-like and amorphous, as these algorithms (and others not mentioned above) can be added or removed from the ensemble as needed, even reducing it down to a single algorithm.
Training the ensemble or individual algorithms is typically very fast, completing in seconds to minutes on the provided data. This allows rapidly iterating and enhancing the model as more training data becomes available.
Guardrails:
Tight guardrails focus the training and output beer recipes to be on IPAs, DIPAs, and TIPAs only.
Model Name: Beh3moth
Primary Algorithms:
■ All
The Beh3moth model is aptly named, as it harnesses the power of our entire data warehouse dedicated to beer recipes. There are no limitations on its input or output—meaning, its sole objective is to craft the optimum beer flavor profile, irrespective of traditional style guidelines. This approach means Beh3moth might brew anything from a delicate low ABV lager to a groundbreaking beer style we've never encountered.
Distinguishing it from our other models, Beh3moth consistently amalgamates multiple algorithms, occasionally even utilizing every algorithm at our disposal. It stands as our most avant-garde and exploratory model.
Guardrails:
As hinted at before, Beh3moth has absolutely no guardrails in place to have it specialize in any beer style in particular, and is trained on all recipe data. Training time varies spectacularly, ranging from a couple seconds to 48 hours.
Model Name: Chri5 P
Primary Algorithms:
■ Boosted Trees Regressor
■ Extra Trees Regressor
■ TNN (Transformer)
Chri5 P operates with a selective data intake, the strictest guidelines, and boasts one of the quickest training durations. Typically, its training employs a singular algorithm, reflective of the simplified and focused nature of its data.
Yet, appearances can be deceptive. By concentrating exclusively on lagers, Chri5 P emerges as a specialist, rigorously adhering to the meticulous standards that define an exceptional lager.
Guardrails:
Chri5 P features among the models with the strictest guardrails, and its rapid training often concludes in mere seconds. Chri5 P is bound to creating recipes for lagers only.
Model Name: Fluffb4ll
Primary Algorithms:
■ Boosted Trees Regressor
■ TNN (Transformer)
Fluffb4ll stands out distinctly. While our smoothie beers usually maintain a consistent base—with variations primarily in ABV—Fluffb4ll's training zeroes in on flavor pairings. Employing just a singular algorithm, it seeks the optimal blend of adjuncts to craft innovative recipes.
This specialization grants Fluffb4ll exceptional versatility. Beyond enhancing the flavor profiles of smoothie beers, it extends its expertise to a spectrum of beverages, culinary creations, and more.
Guardrails:
Fluffb4ll adheres to rigorous standards and boasts impressively rapid training, often completing in just seconds to minutes. Its primary function is to craft unique flavor combinations.
Model Name: NAt3
Algorithms:
■ Varies dramatically, and depends on buddy model
NAt3 is an AI assistant focused solely on crafting low-alcohol beers with ABV below 3%. It partners with other models to produce specific beer styles within this alcohol limit. For example, to make a low-ABV IPA, NAt3 might collaborate with Gh0st, the IPA specialist. Its singular focus on low ABV production allows NAt3 to perfect this niche. So while NAt3 does not create recipes independently, its role is essential for brewing light, flavorful craft beers.
Guardrails:
NAt3 has very tight guardrails in place to ensure target ABV, and relies on its buddy model for the additional guardrails.
Model Name: ØCTANE
Algorithms:
■ Light GBM Regressor
■ Histogram-based Gradient Boosting Regressor
Guardrails: Hard seltzer only.