IFTTT can tell you when to change your home's air filter: Last month on our IoT Podcast, we mentioned the new Ecobee service that sends you air filters for your HVAC system. Thanks to IFTTT, if you use 3M Filtrete Smart filters, you can set up an IFTTT recipe when it's time to replace that filter, even if you don't have a smart thermostat. You can't set up an automatic order based on the sensor in the filter, but with IFTTT, you could change the color of a light, add a task on your to-do list, or create some other action that tells you it's time to buy a clean filter replacement. The new IFTTT integration is one of several the company debuted this month. Covariant raises $40M to build better AI for robots: Covariant, a robotics startup that was initially born as an academic research project, raised $45 million in Series B funding this week.

Take a moment to listen to the world around you. Maybe you are listening to a podcast or the sounds of office life filtered through noise-canceling headphones. Or perhaps you're on a train or lulled by the sound of a dishwasher. Our brains are constantly taking in the sounds around us and giving us useful information. In the coming few years, computers will begin to also process those noises to understand what's happening around them to modify the environment, improve hearing, and notify us if something is wrong.

The smart home is dead. I'm not sure exactly when the time of death should have been called, but it happened at some point between Google trying to rebrand the smart home as "the helpful home" and the publication of this article, which expresses dismay that at five years of age, Amazon's Alexa offers little more than a new way of interacting with things, without deep functionality or truly new use cases. This week in New York, at an IoT Consortium event, I listened to executives of dozens of companies associated with the smart home talk around its death but never address the fact directly. Instead, they talked about a lack of compelling use cases, how to move beyond a device-specific mindset, and the ways they are trying to handle consumer demand for interoperability in the smart home without actually providing such interoperability. For example, Google's Mark Spates, who works in the smart display and speaker division, said onstage, "I don't think we've done a good job explaining our value proposition to consumers. We have to come up with new stories that isn't just'Go buy another Mini.'"

Microsoft Research, the research arm of the software giant, is taking a counterintuitive approach to AI at the edge; it's pushing machine learning to the smallest processors out there, the microcontrollers commonly used in battery-powered sensors and wearables. In a conversation with Byron Changuion, a principal software engineer at Microsoft Research, he explained that bringing AI to the very edge of the network gives users more privacy, lowers power consumption, and speeds up response times. Microsoft still has a group focused on machine learning in the cloud, complete with its own specialty silicon that relies on field programmable gate arrays (FPGAs), but it seems fairly unique in trying to push machine learning to microcontrollers. To do this, it has built the Embedded Learning Library (ELL), a repository of code aimed at developers and makers who want to experiment with AI at the extreme edge. Microsoft Research hasn't been able to take the ELL down to the sensor level yet, but that is the ultimate goal.

Every innovation comes with a learning curve. In particular, every new technology has a period when people are just trying to figure out what they can do with it. But technology adoption is moving ever faster. Indeed, the chart showing how long it took Americans to adopt most technology compared to how quickly we've made smartphones, computers, and the internet a regular part of our daily lives would be shocking only to those who haven't experienced it firsthand. So it stands to reason that the adoption of smart home technology will see a rapid rise.

This week, the Federal Communications Commission begins an auction for two chunks of radio waves that have long been considered useless. Thanks to new technologies and demand for wireless broadband, the market is ready to buy 24GHz and 28GHz spectrum. Meanwhile, in the unlicensed band, which anyone can use and isn't sold off by the FCC, another of the so-called millimeter wave spectrum bands is gaining interest. Roughly a decade ago, engineers had hoped to use the 60GHz band for sending fat files over short distances using a technology called ultra-wideband. At the time, the market didn't see a compelling need for the technology, so it was shelved.

There is a gold rush under way, this time in chips trying to optimize for artificial intelligence. Google and Apple have both built custom silicon for the job, while an entire range of startups are trying to serve up a more efficient way of running AI workloads in both the cloud and at the edge. The challenge is that most of the chips trying to run or train AI models are doing a lot of math. When it comes to edge devices, whether it is a cell phone or a sensor, power is in short supply. So the last thing that consumers need is plethora of new home gadgets that require the power draw of a gaming rig.

Obviously without any details on Amazon's plans, we can only guess what possible uses Vesta will have. But I think that at least one of them will be similar to what I said I wanted: On the podcast, I proposed grafting a battery-powered smart assistant device on a Roomba for mobility.