Definitions:
- Generative AI: AI models that can generate new, synthetic but realistic data. Generative AI uses techniques such as generative adversarial networks (GANs) and variational autoencoders (VAEs) to create data that mimics real-world data. This is particularly useful in fields such as art, music, and design, where the creation of novel content is valuable. Generative AI can also be used to augment training data for machine learning models.
- Google Cloud Platform (GCP): A suite of cloud computing services offered by Google. GCP provides a wide range of services, including computing, data storage, data analytics, and machine learning. It is designed to help businesses build, deploy, and scale applications, websites, and services on Google's infrastructure. GCP is known for its robust data analytics and machine learning capabilities, including services like BigQuery, TensorFlow, and AI Platform.
- Graph Databases: Databases that use graph structures for semantic queries with nodes, edges, and properties to represent and store data. Graph databases are optimised for handling complex relationships between data elements, making them ideal for applications such as social networks, recommendation systems, and fraud detection. They provide efficient querying and traversal of interconnected data, allowing for more intuitive and flexible data modelling.
- Growth Hacking: Strategies and techniques focused solely on growth. Growth hacking involves using creative, data-driven, and low-cost strategies to rapidly grow a business. This approach often combines elements of marketing, product development, and data analysis to identify and exploit opportunities for growth. Growth hacking is particularly popular in startups and tech companies, where rapid expansion is crucial for success.
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