Innovation Exchange challenge: Artificial Intelligence and Machine Learning

The UK Secret Intelligence Service (SIS) are exploring how Artificial Intelligence (AI) and Machine Learning (ML) can enhance efficiency and capability.

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The challenge holder has a range of commercial arrangements (including flexibility around IP).

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In order to take advantage of a thriving science and technology ecosystem, and the opportunities this presents for national security, the UK Secret Intelligence Service (SIS), also known as MI6, are looking for creative, interesting and novel solutions to some current technology challenges.

SIS are, like many other organisations, exploring how Artificial Intelligence (AI) and Machine Learning (ML) can enhance our efficiency and capability. Examples of this are analysing visual information to determine intent from a person of interest, pattern recognition from financial records, identifying and countering cyber-attacks, large scale simulation or digital twinning, and large language models.

To use diverse AI and ML technology most efficiently, SIS intends to underpin and streamline the onboarding and development of new algorithms by building a robust and cross utility AI and ML IT enterprise architecture.

In particular, conversational AI (incluing bots, recommenders, and interactive avatars) could sift data more quickly, and allow us to translate, summarise and analyse information efficiently. Such an ‘avatar’ (animation would be a helpful addition) could usefully interact via a conversational AI to highlight key facts, providing real-time responses that are context aware and use domain-specific vocabulary. The intent is to flag data requiring further human-led attention. For audit trail purposes we require all generated content to be watermarked/labelled as machine generated.

SIS are looking to work with industry and academia for:

  • Access to existing AI frameworks and pre-trained models to jump start diverse AI solutions
  • Access to existing Generative AI domain models, pre-post processing and prediction, that we can bind to our own (image, audio, video and conversational AI).
  • A synthetic media generator and catalogue to add to our own digital assets, supported by a microservice API framework; an open, standards based multi-source plug-and-play architecture, so components can be reused as part of generative AI workflow, and combined as part of a multi-modal media modality pipeline.

The challenge holder is keen to hear from a range of sole traders, small and medium size businesses (start-ups, SMEs) and academia.


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