The Future of Software Innovation? Hardware-Enabled AI & ML Innovation

Hardware innovation is a fickle beast.  It takes money, lots of money.  It takes time, a great team, and execution in more than twenty separate domains, many of which are often overlooked until it’s too late (certifications anyone?!).  But, I’ve got some good news. Hardware is back and it’s about to get really exciting.

You’re probably thinking right now,  “All I ever read about is how AI, ML, blockchain, and XR are ready to revolutionize the world” and that’s exactly the point.  There are some amazing software technologies coming out, but this “new” software has hardware in its DNA.  Until recently, smart technologies have largely been limited by their access points: computers, tablets, smartphones, etc.  Going forward, hardware innovations will become increasingly integral and valuable as the interface for tomorrow’s software. Hardware will capture the data through wearables, hearables, cameras and an increasing variety of sensors and will then be leveraged as the outputs to interact with the world as robots, drones, and the myriad of other IoT devices that are being developed.

As the ecosystem of devices, computation, connection, and data evolve, the platforms, tools and systems are naturally finding more synergy and lowering the barriers of integration.   The line between what is a hardware or software product will continue to blur.  The sensor technologies leading the way are cameras and microphones. If there is a camera, there’s a good chance there’s an AI stack behind it, with self-driving cars being the most prominent example.   On the microphone/speaker side, the Smart Home assistants Amazon Echo, Google Home, and others are obvious and ubiquitous.

The beauty of hardware enabled AI/ML is that it not only crosses the boundary between the physical and virtual, but also between analog and digital.  It’s particularly valuable when interacting with the world and dealing with its messy data.  The next generation of AI hardware startups will take all that messy analog data and transform it into productive and executable knowledge that provide better experiences all the way from shopping to cancer treatments that enable personalized health care at scale.

While the future is clear, the hurdles are as well.  Processing power, robustness, generalization and cost are all tradeoffs future hardware products will need to balance.  Unlike the on-demand and scalable cloud and other services software enjoys, each hardware product will have onboard processing, sensors, connectivity tech, and other requirements that all make their way into the product cost.  Sure a GPU can be thrown into the BOM, but can the market accept the price?  High performance computing at the edge is still in its nascent stages so real-time processing of images and other data can be expensive as well.

At the same time, specific tools are being developed to improve this integration.  We’re seeing a lot of edge computing such as NVIDIA’s Jetson line and Google’s Edge TPUs. TensorFlow is probably the most common AI framework, since it has such broad support for hardware deployment, including Raspberry Pi. ROS is still fairly popular despite being a jumble of mismatched and complicated software, and people have done ports to OpenAI’s Gym environments.

The future of hardware is bright and full of highly accessible, processed, happiness-inducing data.

Join 600 hardware innovators, entrepreneurs, disruptors and investors at HardwareCon 2019, the premier event for hardware innovation.  Plan to attend April 17-18 at the Computer History Museum in Mountain View, California.  Use promo code: GIGA-OM-IL for a special 20% discount on the ticket. Visit to redeem the discount.

Author Bio

Greg Fisher is all about hardware innovation. As founder/CEO of Berkeley Sourcing Group, Greg has spent the last 13 years working with over 1000 hardware startups to develop and manufacture innovative products. Living in China one third of that time, he worked with hardware startups and factories to help improve their designs for manufacturing, qualify and select factories, manage factory negotiations and relationships, and develop and implement quality control processes. With this history, Greg has a unique perspective and immense passion for what it takes for hardware startups to build the right foundation and scale their operations.

Seeing the need for more support for hardware startups to realize success, Greg started Hardware Massive, which is now the leading Global Community/Platform for Hardware Startup Innovation, and HardwareCon, the Bay Area’s premier hardware innovation conference. Their missions are to empower hardware startups to succeed through networking, events, education, and providing access to resources.