AI/ML Enhance & Predict Taste Profiles
We see AI/ML can understand what people like to drink and even know how to make it taste better … amazing!
“We have demonstrated that, by feeding an algorithm with data consisting of people’s flavour impressions, the algorithm can make more accurate predictions of what kind of wine we individually prefer,” says Thoranna Bender, a graduate student at DTU who conducted the study under the auspices of the Pioneer Centre for AI at the University of Copenhagen.
From Summery: Incorporating human tastes into artificial intelligence makes it easier for wine buyers thirsting for the right wine. Researchers have shown that AI can accurately predict individual wine preferences. The researchers expect that nourishing machines with human sensory experiences will continue to grow.
Better Tasting Beer
Researchers in Belgium have developed a system that uses machine learning to predict how to tweak a beer’s chemical profile to enhance its flavor. This system could be particularly useful for improving the taste of alcohol-free beers. The researchers created chemical cocktails of important flavor-enhancing compounds and spiked commercial beers with them. In tests with a trained tasting panel, these additions significantly improved the overall appreciation of a Belgian blonde and an alcohol-free beer.
This lays the foundation of your project.
Reimagining the Fountain Soda Experience
A User-Centric Approach with Sustainability and Personalization
Abstract: The traditional fountain soda dispenser offers a convenient yet uninspired experience. This research proposes a novel system that leverages existing smartphone technology and minor modifications to existing dispensing machines. The user interacts through a dedicated smartphone app, enabling contactless payment, personalized drink creation with precise control over syrup, carbonation, and water ratios, and social sharing of favorite formulations. The dispenser, equipped with Bluetooth connectivity and internal mixing valves, fulfills the user’s customized recipe. This user-centric approach emphasizes sustainability through refillable containers and reduces waste by eliminating disposable cups. Additionally, the system facilitates personalization and fosters a sense of community through recipe sharing.
Keywords: Fountain Soda Dispenser, Smartphone Integration, NFC (Near Field Communication), Bluetooth, Refillable Container, Personalization, Sustainability
Introduction:
The fountain soda experience has remained largely unchanged for decades, offering a convenient yet limited option for beverage consumption. While these dispensers provide a quick and familiar method for acquiring a sugary drink, they present significant drawbacks. Firstly, the reliance on disposable cups generates substantial waste, contributing to environmental concerns. Secondly, the standard selection of pre-mixed syrups offers little to no opportunity for customization. Here we propose a novel approach that addresses these limitations by leveraging the ubiquitous nature of smartphones and integrating user-centric features.
We use AI/ML to generate the perfect drink
AI-Powered Recommendations — Leveraging Food Preferences
Strategic Questioning: The AI/ML model can ask a series of carefully chosen questions about the user’s food preferences. These questions should be:
- Simple and Clear: Easy for users to understand and answer quickly.
- Targeted: Focused on identifying key taste preferences that translate well to soda flavors.
- Variety Focused: Cover a range of taste categories to build a comprehensive picture.
Example Questions:
- Do you prefer sweet, salty, savory, or spicy foods?
- When it comes to fruits, do you gravitate towards citrus flavors (like oranges and grapefruits) or berries (like strawberries and raspberries)?
- Do you enjoy creamy desserts or prefer lighter, fruitier options?
- When choosing snacks, do you reach for something salty like chips or popcorn, or something sweet like candy or cookies?
Building the Taste Profile
Mapping Food Preferences to Soda Flavors
The AI/ML model can analyze the user’s responses and map them to relevant soda flavor profiles. For example, a user who prefers sweet and fruity foods might be more likely to enjoy berry-flavored sodas, while someone who enjoys salty snacks might favor citrusy or cola-based flavors.
Refining the Model
As users interact with the system more frequently, the AI/ML model can be continuously refined. By analyzing past purchase data and feedback on AI-suggested recipes, the model can learn individual preferences and become more accurate in its predictions.
Limitations and Considerations:
- Complexity of Taste: Taste is a complex experience influenced by factors beyond basic preferences. While AI/ML can provide a good starting point, it’s important to acknowledge its limitations.
- User Transparency: Users should be informed about how their food preferences are being used to suggest soda flavors. Transparency builds trust and allows users to feel comfortable with the AI-powered recommendations.
- Openness to Exploration: While the AI can offer suggestions, users should always have the freedom to explore different flavors and create their own unique soda combinations.
By incorporating AI/ML and strategically designed questions about food preferences, the system can paint a more comprehensive picture of a user’s taste profile, leading to more accurate soda recommendations and enhancing the overall user experience.
Pushing this further …
Integrating AI/ML for Personalized Movie-Themed Soda Creation
The proposed system for a reimagined fountain soda dispenser can be further enhanced by incorporating Artificial Intelligence (AI) and Machine Learning (ML) to personalize the drink creation experience based on user preferences and movie context. Here’s how:
AI/ML-powered User Taste Profile:
- Simple Pre-Purchase Questions: Upon launching the app, users can answer a few simple questions about their general soda preferences (e.g., preferred level of sweetness, preferred flavors like citrus or berry). This data becomes the foundation of their user profile.
- Movie Genre and Rating Integration: The app can access information about the movie the user plans to watch (genre, rating, etc.) through APIs or by scanning the movie ticket.
- AI/ML Analysis: Combining user profile data with movie genre information, the AI/ML algorithm can analyze historical user behavior and identify trends. For instance, users who prefer comedies might typically choose sweeter sodas, while those watching thrillers might favor bolder, more acidic flavors.
Generating the Perfect Movie Soda:
- AI-Suggested Base Recipe: Based on the user profile and movie genre, the AI can recommend a starting point for the user’s personalized soda. For example, for a comedy, the AI might suggest a fruity soda base with a higher sweetness level, while for a thriller, a citrusy soda with a touch of bitterness could be recommended.
- User Fine-Tuning: The user retains full control and can customize the AI’s suggestion by adjusting syrup ratios, carbonation level, and even adding flavor shots (as described previously).
- Machine Learning Feedback Loop: User choices regarding the AI’s initial suggestion are fed back into the ML model, continuously refining its recommendations for future purchases. This ongoing learning process ensures the AI adapts to individual preferences and evolving tastes. Iteration could incorporate AI to analyze user preferences and recommend new recipes based on past selections and anonymized data on popular flavor combinations. This would add a layer of personalization and potentially introduce users to new favorites.
Examples of Movie-Themed Soda Recommendations:
- Comedy: A light and bubbly soda with a mix of fruity syrups (e.g., cherry, orange) and a higher carbonation level for a refreshing feel.
- Thriller: A citrus-forward soda with a hint of bitterness (e.g., grapefruit, lime) and a lower carbonation level for a more intense flavor experience.
- Action/Adventure: A bold and energetic soda with a mix of tropical fruit syrups (e.g., mango, pineapple) and a moderate level of carbonation for a dynamic flavor profile.
- Horror: A dark and mysterious soda with unique flavor combinations that pique curiosity and might surprise the palate. Here are some examples:
— Blood Orange & Black Cherry: This crimson colored soda blends the citrusy tartness of blood orange with the sweetness and depth of black cherry, creating a complex and slightly eerie taste sensation.
— Watermelon & Licorice: This unexpected pairing offers a sweet watermelon base contrasted by the dark, salty licorice for a flavor that’s both intriguing and unsettling, much like a good horror twist.
— Cream Soda & Dirt ⛰️: This unconventional mix combines the familiar sweetness of cream soda with a hint of earthy, vegetal flavors, creating a taste that’s oddly familiar yet unsettling, reminiscent of a monster lurking beneath the surface.
The system could learn what works for each type as more data is gathered.
Benefits of AI/ML Integration
- Enhanced Personalization: AI-powered recommendations cater to individual preferences and movie context, creating a truly unique soda experience tailored to the user’s mood and the movie genre.
- Increased Customer Satisfaction: Users are more likely to be satisfied with a soda that aligns with their taste profile and complements the movie experience.
- Data-Driven Innovation: By analyzing user choices, the AI/ML system can identify popular flavor combinations, potentially informing the development of new syrups or flavor profiles tailored to specific movie genres.
By integrating AI/ML for user taste profiling and movie-themed soda creation, the proposed system takes personalization to a whole new level, creating a truly interactive and engaging experience for moviegoers.
- Real-Time Ingredient Information: The app could integrate with a database that provides real-time information on the nutritional content and source of each syrup and flavoring ingredient. This would allow users to make informed choices based on dietary restrictions, allergies, or personal preferences.
Enhanced User Experience
- Interactive Recipe Exploration: The app could feature a section for browsing and discovering popular user-created recipes. This could be gamified by allowing users to “like” and rate recipes, creating a sense of community and encouraging exploration of new flavor combinations.
- AI-Powered Recommendations: A future iteration could incorporate AI to analyze user preferences and recommend new recipes based on past selections and anonymized data on popular flavor combinations. This would add a layer of personalization and potentially introduce users to new favorites.
Advanced Software/System
The proposed system hinges on three key components working in concert to provide a seamless and personalized experience:
Smartphone App
The dedicated app serves as the central hub for user interaction with the system. It offers a range of functionalities beyond simply placing an order. These include:
- Account Management: Users can create and manage their accounts, allowing for features like tracking past purchases, storing preferred drink recipes, and accumulating rewards.
- Dispenser Locator: The app integrates geolocation services to help users locate nearby dispensers equipped with the necessary technology.
- Personalized Drink Creation: This core functionality allows users to create custom recipes by specifying the exact ratios of syrup, carbonation, and water for their desired beverage. This level of customization caters to individual preferences and dietary needs.
- Cloud Storage for User-Created Recipes: Users can save their personalized recipes in the cloud, allowing them to easily access and reorder their favorite creations across different dispensers.
- Social Sharing of Drink Formulations: The app facilitates a social element by enabling users to share their favorite drink recipes with friends. This allows for discovery of new flavor combinations and fosters a sense of community among users. They can try their favorite celebrities and/or famous chef flavors.
- Potential Integration with Health and Fitness Apps: Future iterations of the app could explore integration with health and fitness apps. This would allow users to leverage their health data to receive personalized suggestions for adding vitamins or minerals to their beverages, promoting a more holistic approach to hydration.
Refillable Container
To address sustainability concerns and incentivize reusable options, the system employs eco-friendly, BPA-free refillable containers. Each container is equipped with a unique NFC (Near Field Communication) tag. This embedded tag allows for seamless identification by the dispenser and facilitates secure communication with the smartphone app.
Fountain Soda Dispenser
The existing design of the fountain soda dispenser undergoes minimal modifications for integration with the proposed system. These modifications include:
- Integrated NFC Reader: An NFC reader is installed on the dispenser to identify the user’s container via the embedded NFC tag. This establishes a secure connection and retrieves user data from the app.
- Bluetooth Connectivity: The dispenser is equipped with Bluetooth connectivity to facilitate two-way communication with the smartphone app. This allows for the transmission of the user’s customized recipe and ensures precise execution by the dispenser.
- Internal Mixing Valves with Servo Motors: Traditional dispensing mechanisms are replaced with internal mixing valves controlled by servo motors. This enables precise control over the amount of syrup, carbonation, and water dispensed, ensuring the user’s customized recipe is accurately fulfilled.
- Large Digital Display: The dispenser retains a large digital display for menu navigation, showcasing available syrup options and potential functionalities offered by the app.
Benefits:
The proposed system offers a multitude of benefits for both users and the environment:
- Reduced Waste: By eliminating the need for disposable cups, the system significantly reduces waste generated by traditional fountain soda dispensers. This contributes to a more sustainable approach to beverage consumption.
- Convenience: Contactless payment and the ability to create and reorder personalized drinks enhance the user experience and streamline the purchasing process.
- Sustainability: Refillable containers and eco-friendly materials promote environmental responsibility by reducing reliance on single-use plastics.
- Rewards: A potential “Movie Dollars” program could incentivize participation by rewarding users for frequent purchases and refills.
- Personalization: The system caters to individual preferences by allowing users to create and save custom drink recipes, offering a level of control not available with traditional dispensers.
Additional Considerations:
- Hygiene and Maintenance: The design of the refillable container and dispenser should prioritize hygiene and ease of cleaning to ensure user safety and prevent the spread of germs.
- Environmental Impact Assessment: A life-cycle assessment could be conducted to evaluate the overall environmental impact of the system, considering factors like material sourcing, energy consumption during operation, and the reusability of the refillable containers.
Conclusion
The proposed system for a reimagined fountain soda experience presents a compelling alternative to the traditional model. By leveraging existing smartphone technology and requiring only minor modifications to existing dispensers, this user-centric approach offers a multitude of benefits.
Sustainability: The system significantly reduces environmental impact by eliminating disposable cups and promoting the use of refillable containers. Eco-friendly materials further contribute to a more sustainable approach to beverage consumption.
Personalization: Gone are the days of limited flavor options. This system empowers users to create and save custom drink recipes, catering to individual preferences and dietary needs. AI/ML integration further enhances personalization by analyzing food preferences and movie context to suggest flavors that complement the user’s experience.
Convenience: Contactless payment and the ability to reorder favorite recipes streamline the purchasing process. Users can easily locate dispensers equipped with the necessary technology, eliminating the need to search for specific beverage options.
Community and Innovation: The social sharing feature fosters a sense of community by allowing users to share their favorite drink creations. User interaction with the system also provides valuable data that can inform future iterations. This data could be used to develop new syrups, flavor profiles, or reward programs, ensuring the system continues to evolve and meet user preferences.
A Step Forward:
This research proposes a realistic and achievable approach to revolutionize the fountain soda experience. By focusing on user preferences, sustainability, and readily available technology, the system offers a win-win for both consumers and beverage companies. Further research could explore additional functionalities, such as integration with health and fitness apps for a more holistic approach to hydration, or the development of additional flavoring options and customization features. The future of fountain soda dispensers is bright, with the potential to be not only convenient but also personalized, sustainable, and engaging.
We are always looking for ideas to get people back into movie theaters.
Movie Match — [Android & ML]
Watch great movies with great people.
AI inference engine learns what movies you like and finds a nice group for you to join.
Introducing Mobile Movie Group that tackles the struggle of finding people to watch movies with. The app uses your preferences to recommend movies and then connects you with groups going to see the same chosen movie. You can browse movie options, swipe through selections to indicate your interests, and ultimately join a group for a specific showing. The app even facilitates post-movie discussions by revealing the meeting spot of your group. With Mobile Movie Group, finding movie companions and enjoying the cinema together becomes a breeze.
Demo Video:
AMC Theaters
This could be a good idea for AMC Theaters:
The Challenge:
Traditional fountain soda dispensers offer a limited selection and generate significant waste through disposable cups. This one-size-fits-all approach fails to cater to individual preferences and creates an environmental burden.
Our Solution:
We propose a system that integrates seamlessly with your existing infrastructure and offers a multitude of benefits:
- Personalized Experience: Using a dedicated smartphone app, users can create custom soda recipes with precise control over syrup, carbonation, and water ratios. AI/ML can further personalize recommendations based on food preferences and the movie genre.
- Sustainable Approach: Refillable containers eliminate the need for disposable cups, significantly reducing waste. Eco-friendly materials further contribute to a greener footprint.
- Convenience and Efficiency: Contactless payment and the ability to reorder favorite recipes streamline the purchasing process. Users can easily locate dispensers equipped with the technology through the app.
- Enhanced Engagement: Social sharing features within the app foster a sense of community, allowing users to discover new flavor combinations and share their favorites.
Benefits for AMC Theaters:
- Increased Customer Satisfaction: A personalized and engaging soda experience can lead to happier customers and potentially encourage repeat visits.
- Sustainability Leadership: Demonstrate your commitment to environmental responsibility by adopting a system that reduces waste.
- Data-Driven Innovation: User data can inform future decisions about flavor offerings and promotions.
A Perfect Match:
This proposal aligns perfectly with AMC’s focus on enhancing the moviegoing experience. By offering a personalized, sustainable, and interactive soda solution, you can create a unique selling proposition and attract a wider audience.
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