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Continuum

Applied Artificial Intelligence

Overview

Continuum's foundation is the application of technology.

We translate the latest academic research and technology into practical application.

This knowledge repository is an overview of the research and technology of each of the primary components of a neural language model application and the generative AI industry.

We decompose the generative AI application value chain into the following sub components:

  1. Datasets - Creation, Curation and Structuring

  2. Models - Foundation Models, Instruction Tuned Models

  3. Fine Tuning - Tokenization, Embedding, Parameter Efficient Fine Tuning, Training Processes

  4. Inference - Optimisation of model inference

  5. Knowledge - Vector databases

  6. Retrieval Augmented Generation

  7. Embedding and Recommendation Engines

  8. AI agents and AI autonomy

  9. Regulation and Ethics

  10. AI Infrastructure

Generative AI Disruption

We also use this platform to discuss the potential disruption of generative AI on various domains such as data architecture and pipelines, search and recommendation systems.

Continuum Labs is an organisation that seeks to participate in the disruption that will be caused by artificial intelligence.

We offer a suite of tools and a platform designed for the development of generative AI applications - seeking to empower organisations of all sizes to harness the disruptive potential of AI - and concurrently avoid being disrupted by AI.

Our mission is to not only provide the technical foundation for AI applications, but to generate creative ideas that can be implemented to secure competitive edge for businesses.

Our approach goes beyond offering tools; we aim to provide a perspective on how AI can create organisational value.

We see generative AI disrupting major industries - content creation, advertising, knowledge sectors, consulting, creatives and most important of all - search.

With this will come the total reorganisation of data architecture. Generative AI will become embedded in data pipelines, redirecting data flows, transforming it, and translating it into knowledge and insights to allow enhanced and more rapid decision making.

DatasetsMODELSTrainingINFERENCEVector DatabasesRetrieval Augmented GenerationAGENTSRegulation and EthicsDISRUPTIONSearchInfrastructure

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