As a company specializing in software development, we recognize the significant impact our work can have on the dissemination and consumption of information on the internet. When FactMata enlisted Geniusee's assistance to refine their AI system for identifying false claims, our team identified it as a chance to contribute positively to the distribution of truthful information.
Leveraging our proficiency in machine learning, natural language processing, and data analytics, we collaborated closely with FactMata. Our contributions included developing web scrapers, enhancing data pipelines, and improving the overall efficiency of the project.
Key Challenges:
Acquiring extensive datasets for model training.
Managing data from diverse information sources.
Creating a user-friendly online dashboard.
Tackling data quality concerns.
Enhancing data with external third-party sources.
Project Tech Stack
AWS Athena, AWS S3, AWS RDS, Kubeflow, Airflow, AWS Lambda
Results:
Enhanced scalability achieved, enabling consistent handling of increased data volumes.
Lowered cost per record through a transition to serverless architecture.
Established numerous integrations with external content platforms.
Boosted AI technology performance by adopting NLP transformers.
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