Categorii: Tot - personalization - modeling - integration - recommendation

realizată de Eric Nic 2 luni în urmă

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ProMom AI-empowered Capabilities Ideas

The content covers a diverse range of applications for AI and machine learning in product development and health recommendations. It includes processes such as data preparation, cleaning, and preprocessing of information sourced from Amazon.

ProMom AI-empowered
Capabilities Ideas

Product Use Cases

Search

FullText
Semantic

AI Criteria Tags

Filter + Result Page
Search + Result Page

Customers Say

Attributes/Tag generation
Summarization

Rrecommendation

Product Basket
Personalized
Popularity_based
Category Rec

Product Similarity/relevancy

DataOps

Security & Compliance: Ensuring data privacy (important for health-related apps) and compliance with regulations like HIPAA.

Monitoring and Quality Assurance: Ensure data quality, detect anomalies, and apply corrective actions.

Version Control & Collaboration: Managing different versions of data, changes in ML models, and collaboration among team members.

Data Pipeline Orchestration Managing the flow from data ingestion to storage and processing.

Data Storage / Data Lake
OpenSearch: If search and retrieval are key functions, OpenSearch (for analytics) can be used in combination with a data lake.
AWS S3: suitable for building a data lake.
Ingestion Layer
Real-time ingestion: For handling QA, user chats , calendar event updates
Batch ingestion: large data dumps like historical product data or user logs
Data Sorces
7. External, Knowledge_Base
6. Calendar Tracking: Time series data (appointments, events, etc.).
5. QA interactions (Bellysafe, Expert, ...) Text-based data.
Product

4. User clickstream data, system log, user preference

3. User Reviews

2. Product Meta , Details, Categories

1. Base data: User, Expert, ...tabular , text , geospatial

LLMs Tasks

Text Generation

Language Modeling

Plan

Litterateur Review R&D

Deployment
LLM Modeling and Benchmark
GCP VM Instance
Models and Code

BERTTopic

Data
Amazon Website
Amazon Adver API
Amazon Ready to Use
Data Gathering
Elastic
Crawling Feasibility

Subtopic

Topic Modeling

Research/Base Model with Sample Data

PEFT Methods

Selective Fine-Tunning

Structural Masking
S-Diff pruning ,S-BitFit , FAR, Bitfit, SPT
Unstructural Masking
U-Diff pruning , FishMask , Fish-Dip , AM

Reparameterized Fine-Tuning

LoRA Derivatives
Multiple LoRA

LoRAHub, MoLORA , MoA, MoLE, MixLoRA

LoRA Improvement

Laplace-LoRA , LoRA Dropout , LoRA+

Dynamic Rank

DyLoRA , AdaLoRA , SoRA , CapaBoost , AutoLoRA

Low-rank Decomposition
LoRA , Compacter KronA , VeRA , DoRA

Additive Fine-Tunning

Soft Prompt-based
Training Speedup
Soft Prompt Design

Prefix-tuning , p-tuning , Prompt-tuning , Xprompt, APrompt

Adapter-based
Multi-task Adaptation

AdapterFusion , AdaMix , AdapterSoup , MerA , Hyperformer

Adapter Design

Serial Adapter, Parallel Adapter, CoDA

Integration with Expert, Personalized Recommendations (foods rich ) , Balanced Meal Planning, and Pregnancy-Safe Consumption

Prediction and personalized notifications

- ~ 10 wdays - 2 Researcher/Data scientist

Determine the most fertile days. Recs for increase the chances of conception

e.g. In some cultures, bananas are eaten unripe or cooked, system can offer information on safe preparation methods for pregnant women.

Criteria Generation

Test
Integration, deployment, scalability
Modeling
Semi supervised
Unsupervised

Traditional

LLM

Fine-Tunning & Evaluation

Criteria Representation

Criteria Extraction

Data Preparation Product descriptions, reviews, and metadata from Amazon
Cleaning and Preprocessing
Crawling
Setting and Set up ML Modeling Environment
Research/Base Model with Sample Data (Min 10 days)

Pregnancy-safe smoothies, banana bread with whole wheat flour (better for blood sugar control), or frozen banana "nice cream"

Pre-existing allergies, intolerances, and pregnancy-induced food aversions

Essential nutrients for fetal development

- Min 4 weeks, Max 2 months - 1-2 Data Scientist - RAM 64 GB to 128 GB - 200 GB to 500 GB for model checkpoints and datasets(1 TB or more for storing fine-tuning datasets and model checkpoints) - GPU A100

Suggest foods and drinks known to alleviate nausea and morning sickness

5 wdays

Depends on Crawling Tools and quality and size of the crawled data: - Min 3 weeks, Max 3 months in case of bad data - 1 Data Analyst - Storage: ?

e.g. Craving sweets: Recommend fruit smoothies or yogurt parfaits.

Related to the menstrual cycle or general recom

e.g. ...in case of gestational diabetes suggest monitoring sugar intake and considering portion control

In case of potential food risks Offer alternative options with similar nutritional benefits

ProMom AI-empowered Capabilities Ideas

Type in the name of the project that is under review, and press Enter.

Mental Health and Emotional Support

Tracker
AI-powered chatbots

Expert

New Feats
Automatic appointment setting
Expert Recommendation

Language Preference ,communication method

User Feedback , Rating and Sentiment Analysis

User -Expert Matching(Rec Algorithms)

Text Analytics Engine

Personalized Health Recommendations

Lifestyle
Exercise

Calendar

Effortless Scheduling and Booking
Event Tracker and Trends Forecasting
Anomaly detection and Recommendation
Mood Tracking and Symptom Prediction
Fertility Window Identification
Menstrual Cycle and Ovulation Prediction

BellySafe

Engagement and Support
Nutritional Guidance and Education

Supplement Recommendations

Balanced Meal Planning (all necessary nutrients for mom and baby)

Pregnancy-Safe Consumption

Hydration Support (weather, activity level, and stage)

Caffeine and Alcohol Intake (Moderation or alternatives)

Personalized Recommendations (foods rich )

Dietary Restrictions & Aversions

Craving Management

Morning Sickness Relief

Trimester-Specific Needs

Conversational AI Current Feats Enhancement
User Feedback Loop
Nutrient Breakdown
Cultural Awareness
Alternative Suggestions
Recipe Recommendations
Risk Assessment and Health Condition Awareness

Product

New Feats
Personalized Product Recommendation
Topic Modeling and Fine-Tuning
Sentiment Analysis
Current Feats Enhancement
Text Analytics Engine