Qeexo has officially debuted its EarSense software, made to eliminate the proximity sensor by performing its primary function on the software side. Where a traditional proximity sensor turns off a phone’s display if it detects that something is near it or it’s being covered, Qeexo’s EarSense software uses the device’s touch screen to detect a touch from a face or an ear, effectively mimicking the function of a proximity sensor. EarSense is now available for device manufacturers to license and use, meaning it could be making its way into consumer devices as early as this year, though nobody has thus far announced their intention to use the software.

Compared to a traditional proximity sensor which is a piece of hardware that is generally packed in the top bezel of our smartphones, EarSense is a software alternative – so it doesn’t take up any space on the phone. The goal of this proprietary software solution is to allow OEMs to free up space from inside the phone (for other components) as EarSense will be able to recognize contact with someone’s face and ears so that it can turn off the screen during a phone call – a function normally accomplished through use of the proximity sensor.

OPPO has been absent in the flagship smartphone space for a very long time. The company’s last flagship smartphone was the Oppo Find 7, which was released back in 2014. After three years of releasing phones with mid-range chipsets, Oppo announced the flagship Oppo Find X last month. Now, the company has launched the Find X in India. The phone will be available for pre-order via Flipkart from July 25, with sales beginning from August 3.

In 1943 neurophysiologist Warren McCulloch and mathematician Walter Pitts wrote a paper on neurons and how they work. A model was created using an electrical circuit and the neural network came into being. Seventy years later these beginnings have evolved into a number of large-scale projects by some of the top technology companies and technology communities around the globe – GoogleBrain, AlexNet, OpenAI, Amazon Machine Learning Platform are examples of some of the most well-known initiatives relating to AI and machine learning.

Qeexo spun out of Carnegie Mellon University, has for a long time developed multi-touch technology for handset manufacturers which does ML on the device level. It has applied this approach to a new AutoML technology that allows companies to embed ML into hardware and conduct learning on sensor data.

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.

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.

“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.”

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.

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.

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