Right now, major tech players are investing in or developing hardware and semiconductor technologies to create AI chips.
Because creating newer and better semiconductors is an undeniable necessity to meet the demands of major applications like AI, autonomous vehicles and Internet of Things (IoT) technologies. You may not realize it, but if you’re reading this, AI and machine learning are literally at your fingertips, brought to you by microelectronics.
Billions of people are reliant upon computers and handheld devices just to find the quickest route to work (Waze), communicate with family and friends (Facebook), or to get great deals on Cyber Monday (Amazon). With such a vast marketplace to penetrate and countless applications that harness the power of AI and machine learning, the race to create is driving an exponential need for semiconductors.
Remember the first computer? And how giant it was? Sure, we’ve seen significant improvements in hardware since then, but the trend to encourage work and talent development in software is causing a shift in balance leaving hardware behind. Now, tech giants are now clamoring to find people who can build faster hardware that can keep up with the demands of new software.
Because who wants to play a VR game that loads like dial up internet?
Google, Amazon and Facebook each hold an enormous wealth of data on high-speed computers from different sources. In order to use that intelligent data, smart algorithms run on semiconductor based hardware platforms. Without further developments in sophisticated hardware, this data is at risk of becoming redundant and underutilized.
At the core, these platforms are absolutely dependent on advanced AI chip designs and architectures.
To solve this, Google announced its own AI chip earlier this year that will allow users to build and operate software through the internet using deep neural networks and machine learning. It will fuel everything from speech recognition to robotics. In fact, Google’s AI chip and others like it substantiates and complements similar initiatives by other technology giants in the race to create pioneering hardware based platforms.
IBM is increasing focus on products for businesses that want to implement machine learning by placing its Linux servers on its Power9 processors, working closely with NVIDIA to do so. IBMs cognitive computing initiative is a perfect example of the industry’s emphasis on and validation of hardware development to support AI.
But what does this mean for SMEs and startups that are considering implementing AI?
Markham, as part of York Region, is home to many of the world’s largest patent recipients and pioneers of foundational technologies required to achieve the computing capabilities that power consumer goods, retail, autonomous vehicles, infrastructure, healthcare and advanced manufacturing. Every one of these verticals integrates and embeds artificial intelligence and machine learning into their business processes to better serve customers.
In York Region alone, there are over 4,300 tech companies and more than 60,000 tech jobs. There is a unique cluster of head offices for global multinationals who have invested billions of dollars in the region to establish significant operations in R&D, marketing, sales, finance and human resources.
More than 400 global powerhouses have set up Canadian head offices in Markham, including AMD, Qualcomm, IBM, OpenText, Huawei, Honda and GM. This creates a hotbed of highly scarce technical talent and experienced leaders that fuels a vibrant innovation community. This means that uniquely Canadian public-private collaborations are fostered and encouraged amongst start-ups, scale-ups, global multinational, community partners, investors, academic institutions and government.
Markham is the innovation capital of Canada. For SMEs and start-ups in the AI space, this is the place to be. Nowhere else can you find software and hardware talent along with the experienced knowledge-based experts absolutely necessary to make any company implementing AI successful.
Hardware is an absolute necessity to achieve the full capabilities of AI and machine learning.
In order to be disruptive and on the leading edge of technology, companies like Google, Facebook, Tesla and Amazon have identified a significant gap between the software being produced and the capabilities of the hardware that currently exists. Work in microelectronics and semiconductors must absolutely be pushed further to achieve the full potential that AI, IoT and machine learning promises to deliver.
Hardware is what makes Artificial Intelligence possible. Are you ready?
ventureLAB is where talented entrepreneurs bring their innovations to market and is a partner in StartUp HERE Toronto.