Aspinity is excited to announce our collaboration with @RenesasGlobal. Don't miss our ultra-low power glass break demo in the Renesas booth (Hall 1, Stand 234) at the embedded world Exhibition&Conference. Book a meeting with us:

Join Tom and other industry leaders on the panel “AI and Video Analytics: Driving More Value for the Smart Home,” at 12:15 p.m. eastern time during the last Virtual CONNECTIONS conference session of the year on Thursday, November 10.

This is an important conversation about analog's impact on energy consumption that we were glad to have with Brian Bailey for Semiconductor Engineering.

Always-on can be part of a sustainable future - if it's power intelligent.

Battery life matters and minimizing data quantity and movement is one of the most effective ways to reduce system power. That's why the Sensors Converge Conference just awarded the AML100 analog machine learning processor the Best of Sensors Award in the AI/ML category!

“While today’s glass break detection solutions force designers to trade off battery life or accuracy, Aspinity’s solution frees designers from having to make that undesirable choice.”.

Aspinity is thrilled to announce that our AML100 has been named a Best of Sensors 2022 finalist for Innovative Product of the Year! Keep a look out to see if the AML100 comes out on top when the winners are announced at @SensorsConverge on June 28.

Aspinity is heading to Sensors Converge. Visit us in booth #933 and don't miss CEO Tom Doyle's speaking session on June 29 @ 2pm about using analogML to extend the battery life of always-on intrusion detection sensors. Register here

The tinyML Summit is next week and we are a silver sponsor! Don't miss this opportunity to hear CSO David Graham's talk about why we need to inference in the analog domain to enable a world of battery-operated always-on devices.

We are excited to announce the AML100 – the first member of our analogML family and the industry’s first machine learning chip that processes natively analog data and boosts battery life by 20x. Learn all about the AML100 here:

We're looking forward to the Fierce Electronics Embedded Innovation Week Don't miss Tom's talk tomorrow, Tuesday, Feb 15, at 2:30PM eastern to learn the most efficient way to save power in always-on systems. Register for this free virtual event here:

If you think that machine learning is synonymous with digital computing - check out this blog by Majeed Ahmad in Planet Analog explaining how inferencing in the analog domain is poised to revolutionize battery-operated always-on sensing.

Are you going to CES? It's not too late schedule a time to catch-up with the Aspinity team in person. Send an email to sales@aspinity.com or use this form to schedule a time to meet with us:

As we wrap up this busy year, it's fun to take a look back at how it all got started. Thanks to Jonathan Kersting and the other folks at the Pittsburgh Technology Council, you can reminisce with us.

If you think that the analogML core is just an ultra-low power analog neural network on a chip, then you need to read our latest blog article and find out why it's so much more than that.

Aspinity is hiring! We're currently looking for engineers in many different hardware and software disciplines to join our growing team. If you would like to work on innovative technology that is revolutionizing the world of always-on sensing, click here:

Will you be at CES? We're looking forward to finally meeting face-to-face! Schedule a meeting with us:

All of the edge computing predictions for 2022 from IT Business Edge have one thing in common - the need to for long lasting remote always-on sensing. Pulling machine learning into the analog domain is an important first step.

Per Semiconductor Engineering, the conversations about system partitioning are so important for power and data efficiency. Don't forget to include the partitioning of data analysis between the analog and the digital domain as part of the conversation.

Wouldn't it be great to have a sophisticated analog processor whose performance isn't impacted by CMOS process variations? Good news! You can! Check out the latest installment of our 5 Myths About AnalogML blog series to understand how.