Grus blog

Edge computing and machine learning will transform the user experience

I think that the technology we make should be present with us, not for us. That requires those products to be damn smart. Simple IoT devices with messaging protocols won't cut that.

How to implement AI in your company (and why most companies lag behind)

As you might have been witnessing through our social media presence, we have recently focused our design efforts at Grus into machine learning hardware and AI applications on the edge. Designing customized machine learning hardware is exciting, since there is whole new wave of supply coming from chip designers, which

machine-learning

Machine learning workshop with Sparkfun Edge boards

We hosted a crash course/workshop with the Sparkfun Edge boards. Here are our key takeaways from the event, such that you can be one step ahead.

hardware

What is new in USB4 from a HW designer's perspective?

I know that there are still many blissfully ignorant years ahead of us, nevertheless I took a glimpse of the recently released USB4 specification and would like to share my thoughts here from a hardware-development perspective.

Comparison of two new machine learning accelerators, Coral and Jetson Nano.

We made some comments on both Google Coral and Jetson Nano as two machine learning accelerating hardware platforms. Now, we would like to wrap things up with a comparison post. Differing philosophies lead to different designs.It is really hard to resist the comparison. But it is particularly hard to

edge computing

Who will pick the strawberries?: 3 use cases of machine learning on the edge in agriculture

Edge applications in agriculture will create $4 to 11 billion in hardware value by 2025, enabling private, fast, efficient and offline machine learning capabilities.

machine-learning

Our first impression of Nvidia Jetson Nano

We have already made some comments on Google Coral, and now it's time to announce its rival in the super-lightweight class: Nvidia Jetson Nano. Nvidia has its own philosophy, it is founded as a hardware company. It also has a special place in the development community, since it was already

product-design

6 things you should look for in a design contractor

Building a product is a challenging task. Most design projects are bound with time and riddled with vagueness. Here is how we aid our customers in 6 steps.

machine-learning

Our first impression of Google Coral

Embedded developers celebrate small chips that punch above their weight. We reviewed Google Coral development board that showcases the latest capabilities of Google's AI accelerator.

digital transformation

How can Europe close its gap in digitalization and AI?

Europe’s digital gap with US and China, two world leaders in digitalization, is further growing due to its slowness in AI engagement. Without faster engagement in AI, the gap could widen.

digital transformation

3 barriers to digital transformation in manufacturing companies (and how to overcome them)

Digital transformation is the toughest challenge manufacturing companies is facing today. A well-thought digital transformation process involves rethinking your products and services. But the barriers to digital transformation are both structural and behavioral.

edge computing

Why is there a shift towards edge computing anyway?

Because computation became cheap and power efficient, it became possible to bud away from the cloud with all of its perks, and land where the service is.

our world

What we use: Capella for Modeling

Coming from hardware roots, we have an appetite for correct modeling of components within a system. That is, our product is a subsystem within a system, and our subsystem, being our product, has subcomponents, all that we design under clear assumptions on our part, resolving a specific need encapsulated into

our world

What we use: our homebrew

I have become a open source tool junkie on my journey to find the right tools, and I hope all that my wasted time in setup and configuration will be of use.

machine-learning

Introduction to speech recognition with DeepSpeech

We have spent one week to discover the current state of the art in machine learned speech recognition. Evidently, the state of affairs changed on late 2014 when a research by Baidu R&D on speech recognition surfaced. It was announced by the renowned AI expert Andrew Ng, then