#TinyML

Issue 15 - Tiny ML and Augmented AI

  • Focus on Emerging Tech: TinyML and Augmented AI

    Issue Fifteen focuses on the emerging technologies TinyML and Augmented AI, as they begin to take their place in the world of machine learning and deep science technology and product development. We especially see these technologies furthering the modalities where Azafran has focus: Voice, Acoustics and Imagery. “Human fears around artificial intelligence stem from an assumption that the ultimate goal of AI is to replicate, and surpass, human intelligence, thereby threatening our own existence.
  • Why the Future of Machine Learning is Tiny, and the Future of AI is Augmented

    Augmented AI For some time, our team has been scratching our heads at the loose interpretation of AI as a catch-all term, serving as both the umbrella for any tech or platform using machine learning, deep tech or science and their associated components, alongside the strict definition where AI is sentient machine intelligence, making decisions without human interaction.
  • Augmented AI and TinyML Use Cases

    Focusing on solutions within Azafran’s Thesis, following are a number of Augmented AI and Tiny ML use cases already out there in the world: TinyML One recent event in the advancement of TinyML was Apple’s acquisition of Xnor.ai, a Seattle startup spun off from the Allen Institute specializing in low-power, edge-based ML tools.
  • Azafran Fund I Portfolio Focus: Aspinity

    The Growing Demand and Market Drivers for Always‐on Sensing and Listening In the next five years, billions of handsfree, always‐on sensing devices that run on battery will assist us in our daily lives at home and at work: playing music on request, controlling our home’s temperature and lights, alerting us to danger, monitoring the wear and tear of factory equipment, even continuously monitoring our health.

Issue 14 - Tiny ML and Augmented AI

  • There are no articles with the tag #TinyML in this issue.

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