The latest release of Qeexo AutoML makes the automated TinyML model development and deployment platform available as a web application hosted on Amazon Web Services (AWS).
“Qeexo, the Carnegie Mellon University spinoff, is expanding public cloud access to its automated machine learning platform as it pushes its no-code “TinyML” approach to the network edge.”
The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting the enterprise through leading edge products and services. We’re happy to publish this evolving list of the industry’s most impactful companies!
Every now and then I see technology that’s so impressive, I can’t wait to write about it, even if no one else finds it cool. I had that experience last week while watching a demonstration of a machine learning platform built by Qeexo.
Many companies are scrambling to find machine learning engineers who can build smart applications that run on edge devices, like mobile phones. One company that’s attacking the problem in a broad way is Qeexo, which sells an AutoML platform for building and deploying ML applications to microcontrollers without writing a line of code.
“Our Qeexo AutoML platform can automatically build ‘TinyML’ solutions, the lightweight machine learning that brings the benefit of intelligence to all sorts of small devices. Arm’s new Cortex-M55 and Ethos-U55 processors allow Qeexo to further innovate embedded ML solutions for endpoint devices with the combination of unprecedented high performance, low latency, and ease of developing machine learning for microcontrollers.”
Qeexo is a machine learning startup that develops AutoML software specifically tuned to automatically detect patterns in sensor data. Models developed by Qeexo AutoML (which it touts as a “one-click, fully automated platform”) are designed to run on low-power edge devices that are sensitive to network latency, such as mobile apps, IoT devices, wearables, and automobiles.
As technology pervades more devices, the assumption is that these gadgets should have some form of internet connection. But some of my favorite gadgets this year have been devices or services that don’t require a connection back to the web to work. Instead, they apply sensors and other technology in novel ways to deliver a tech-enabled product that I view as smart, but not connected.
