Issue 15 - Tiny ML and Augmented AI
Focus on Emerging Tech: TinyML and Augmented AIIssue 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 AugmentedAugmented 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 CasesFocusing 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.
Issue 14 - Tiny ML and Augmented AI
There are no articles with the tag #Augmented AI in this issue.