Scaling Edge AI in a Data Driven World, Part Two

The Essence of Edge AI Many applications today need edge computing. However, due to privacy issues, the need for real-time responses, and lack of network connectivity, applications are often compromised.  A similar position supporting edge computing comes from the argument around network scalability. The cost and latency for network backhaul can be problematic, especially when ...

Scaling Edge AI in a Data-Driven World, Part One

Scaling Edge AI in a Data-Driven World, Part One Drowning in Data We live in a data-driven world where IoT devices are always on, always tracking, and always monitoring. Being perpetually connected also means that we’re producing mind-boggling amounts of data. In fact, IDC Research predicts by 2020 we will be generating 44 trillion gigabytes ...

AI’s Shocking Carbon Footprint

AI’s Shocking Carbon Footprint How Techniques First Invented in the 1920s are Changing That Introduction What do the melting glaciers of Greenland have in common with artificial intelligence? On the surface, not much. But if you dig just a bit deeper, the connection is scarier than you might imagine. Turns out that data is not ...

The Era of Commercializing AI, Part Two

Supporting Efficient Workflow for Commercializing AI  At the early stage of AI commercialization, we are faced with the “dark ages” of tools, infrastructure, and approaches. There are many analogies that we can draw upon to understand where we truly are at this moment. For example, in the early days of the Internet, everyone was building ...

The Era of Commercializing AI, Part One

Beyond the Valley of Innovation Death Rapid success in deep learning algorithms has spawned new applications in video analytics, speech processing, and natural language processing. New smart products with compelling user experience, driven by the power of AI, can create safer human environments, allows us to work more efficiently, and helps to make communication easier. ...

Latent AI, Adaptive AI Optimized for Compute, Energy and Memory

Originally published in Petacrunch on August 9, 2019. Latent AI has raised $3.5M in total. We talk with Jags Kandasamy, its CEO. PetaCrunch: How would you describe Latent AI in a single tweet? Jags Kandasamy: Latent AI brings Adaptive AI™ to the edge through our core technologies and platform tools enabling efficient, adaptive AI optimized for compute, energy, and memory ...

AI Moves to the Edge

Edge is Where the Opportunity is and Why AI Needs to Evolve This is a 2-part series on the impact of AI on the edge as compared to the core, and why the approach to building AI algorithms needs to change if they are to operate more efficiently on the edge Introduction From enabling autonomous ...

It’s Time for Adaptive AI to Enable a Smarter Edge

Most of us are familiar with this scenario:  “Hey Siri (or insert your favorite ‘wake’ word for your digital voice assistant), turn on the hallway light.”  Instantly and magically, that hallway light turns on, and life is good. But then, reality kicks in, and all of a sudden your internet service provider is experiencing an ...

Latent AI, Inc. Announces Seed Funding Led by Future Ventures

 An SRI International ventures startup, Latent AI emerges from stealth with the Latent AI Efficient Inference Platform™ toolset enabling Adaptive AI™ for a smarter edge.         MENLO PARK, CA, June 26, 2019 — Latent AI has spun out of SRI International, the leading independent research and technology center, and closed its first round ...

The Next Wave in AI and Machine Learning: Adaptive AI at the Edge

The accessibility of high-end GPUs and rapid development of machine learning software frameworks (Tensorflow, Pytorch, Caffe) have enabled recent success in the deployment of deep learning applications on the cloud. Applications in video analytics, audio processing, natural language processing (NLP) are becoming popular as consumers benefit from the new user experience, driven by the power ...

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