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 third of the moment , he worked together with hardware startups and factories to help qualify and select improve their designs for fabricating factories, manage mill discussions and connections, and develop and implement quality management processes. With this history, Greg has a unique view and immense passion for what it can take for hardware startups to build the right base and scale their operations.

The premier event for hardware innovation, join 600 hardware innovators, entrepreneurs, disruptors and investors at HardwareCon 2019.   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. Stop by to redeem the discount.

Innovation is a fickle Creature.   It requires lots of cash, money.   It requires time, a great team, and execution in over twenty separate domain names, many of which are often overlooked until it is too late (certificates anyone?!) .   But, I’ve got some fantastic news. Hardware is back and it’s about to get really exciting.

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At the same time tools have been developed to enhance this integration.   We are seeing a great deal of edge computing such as the Edge TPUs of Google and NVIDIA line. TensorFlow is the AI framework, as it has such broad support for hardware deployment, including Raspberry Pi. ROS is popular despite being a mess of complicated and mismatched software, and people who have done ports to the Gym environments of OpenAI.
Seeing the need for greater assistance for hardware startups to realize success, Greg started Hardware Enormous, which is the for Hardware Startup Innovation, also HardwareCon, the Bay Area’s premier hardware invention conference. Their missions are to succeed through media, events, schooling, and providing access.
You’re probably thinking right now I read about is how XR, ML, blockchain, and AI are ready to revolutionize the world” and that’s exactly the point.   There are some Remarkable software technologies coming out, but this”new” software has hardware in its DNA.   Until recently, smart technologies have largely been restricted by their access factors: computers, tablets, smartphones, etc..   Moving hardware inventions will become precious and integral as the interface to get tomorrow’s applications. Hardware will be leveraged as the sparks to interact with the world as drones, robots, and the myriad of other IoT devices which are being developed and will capture the data via an increasing number of sensors, hearables, cameras along with wearables.

Since the ecosystem of computation devices, connection, and information evolve, the platforms, systems and tools are obviously finding synergy and lowering the barriers of integration.    The line between What’s a hardware or software product will continue to blur.   The sensor technology are microphones and cameras. If there is a camera, there is a chance with self-driving automobiles being the most prominent example, there’s an AI stack behind it.    On the microphone/speaker side, the Smart Home urges Amazon Echo, Google Home, along with many others are omnipresent and obvious.
Hardware’s near future is bright and full of happiness-inducing data.
The Attractiveness of hardware empowered AI/ML is that it not only spans the boundary between the physical and virtual, but between digital and analog.   It’s particularly valuable when interacting with the world and dealing with its data that is cluttered.   The following generation of AI hardware startups will take all that messy analog information and change it into productive and executable knowledge that provide experiences all of the way.

While the future is clear, the barriers are.   Processing power, robustness, generalization and cost are tradeoffs future hardware items will need to equilibrium.   Contrary to services applications enjoys along with the cloud, each hardware item will have onboard sensors processing , connectivity technology, and other requirements that all make their way into the merchandise cost.   Sure that a GPU can be thrown in the BOM, but can the Purchase Price be accepted by the marketplace?   High performance computing in the edge is in its nascent stages so processing of information and images can be costly.