Blackberry has been having virtual events to make up for the COVID-19 cancellation of Blackberry World. At their latest event, they showcased how the AI technology created for autonomous cars could be used to massively transform hospitals into a far less costly, far easier to manage institutions.
Clearly, this could go beyond healthcare into airport management, retail stores, manufacturing, and other complex sites that currently require lots of people doing relatively repetitive tasks. As we face this unprecedented pandemic, maybe it is time AI took a broader role in keeping us all safe.
Let’s explore the broader application of Automotive AI this week.
What seemed like a relatively simple task of allowing a car to drive itself resulted in a massive effort to create what eventually could become a general use robot.
Initially, the auto industry thought that you could simply bury a cable in a road and have cars drive on what then would be virtual tracks along the lines of the car rides at places like Disneyland. Eventually, this evolved into creating small supercomputers that could take massive numbers of simultaneous sensor and camera inputs, resulting in the potential for computers that could out-drive humans.
Security problems were identified and overcome, a massive amount of processing power using a limited amount of energy was created, and simulation platforms were developed – all to create what should be a mass of autonomous cars coming to market over the next few years.
But all this processing power and sensor integration could be applied to other types of vehicles like trains and airplanes, personal robotics, and even buildings and smart cities. It becomes merely a matter of scale, and, at least with the fixed implementations, you don’t have to worry about automotive power limitations.
Now Blackberry has an impressive technology set applied to this opportunity. They provide binary scanning for automotive applications to assure their function and that they are secure, they design in Over The Air (OTA) update capability from a secure source, the solution included vehicle health monitoring for proactive maintenance, Blackberry protect for anti-virus, and Blackberry Persona so the car can tell who is driving it regardless of the key or fob.
Now imagine the systems in a hospital being able to tell who is operating them and flagging out if the operator wasn’t recognized. Or alerting if someone unknown was gaining access to patient records, assuring the software being installed did what it was supposed to and wasn’t compromised. This could provide for OTA software updates from a secured and approved sources, and could identify if a system like a Ventilator was showing signs of failure with plenty of time to correct the problem or replace it before the failure put the patient in mortal danger.
The hospital AI could identify and prioritize monitored events, identify people in the hospital that weren’t supposed to be there or who were inadequately protected, alert out if people entering protected areas were symptomatic, and could provide a hospital-wide control panel so that administrators would both know of a problem and timely. This system would even be capable of autonomous action if, during a crisis, staff were unavailable or unable to get to the patient in time.
Because the system was designed to be autonomous, it could embrace the coming wave of medical robots that would be better able to operate under these horrific pandemic conditions and the knowledge used to train one hospital could be applied through inference to other similar hospitals around the world.
And, at some future point, during critical times when staffing was short, and concerns surrounding infecting hospital staff made mitigation excessively dangerous, you could stand up largely automated emergency hospitals manned by robotic staff creating a far safer, from that staff’s perspective, environment for a highly contagious virus or disease.
Airports, manufacturing sites, food services, and even smart offices would be even easier to implement, and experimental programs like the Amazon Go automated markets (which are potentially far safer for staff than traditional markets) could all benefit from this technology. And, looking ahead 5 to 10 years, given the likelihood of both new COVID-19 infections and new pandemics, the need to automate these sites will undoubtedly drive their creation.
But I expect, as we advance Automotive AI, it will both scale up to buildings and cities and scale down to homes. NVIDIA has been telling a remarkably similar story and has already started moving into robotics, farming, and other adjacent markets.
Perhaps a general-purpose AI is a lot closer than we thought. Something to noodle on this week.
Huawei’s AI Update: Things Are Moving Faster Than We Think
FEATURE | By Rob Enderle,
December 04, 2020
Keeping Machine Learning Algorithms Honest in the ‘Ethics-First’ Era
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 18, 2020
Key Trends in Chatbots and RPA
FEATURE | By Guest Author,
November 10, 2020
FEATURE | By Samuel Greengard,
November 05, 2020
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 02, 2020
How Intel’s Work With Autonomous Cars Could Redefine General Purpose AI
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 29, 2020
Dell Technologies World: Weaving Together Human And Machine Interaction For AI And Robotics
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 23, 2020
The Super Moderator, or How IBM Project Debater Could Save Social Media
FEATURE | By Rob Enderle,
October 16, 2020
FEATURE | By Cynthia Harvey,
October 07, 2020
ARTIFICIAL INTELLIGENCE | By Guest Author,
October 05, 2020
CIOs Discuss the Promise of AI and Data Science
FEATURE | By Guest Author,
September 25, 2020
Microsoft Is Building An AI Product That Could Predict The Future
FEATURE | By Rob Enderle,
September 25, 2020
Top 10 Machine Learning Companies 2020
FEATURE | By Cynthia Harvey,
September 22, 2020
NVIDIA and ARM: Massively Changing The AI Landscape
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
September 18, 2020
Continuous Intelligence: Expert Discussion [Video and Podcast]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 14, 2020
Artificial Intelligence: Governance and Ethics [Video]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 13, 2020
IBM Watson At The US Open: Showcasing The Power Of A Mature Enterprise-Class AI
FEATURE | By Rob Enderle,
September 11, 2020
Artificial Intelligence: Perception vs. Reality
FEATURE | By James Maguire,
September 09, 2020
Anticipating The Coming Wave Of AI Enhanced PCs
FEATURE | By Rob Enderle,
September 05, 2020
The Critical Nature Of IBM’s NLP (Natural Language Processing) Effort
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
August 14, 2020
Datamation is the leading industry resource for B2B data professionals and technology buyers. Datamation's focus is on providing insight into the latest trends and innovation in AI, data security, big data, and more, along with in-depth product recommendations and comparisons. More than 1.7M users gain insight and guidance from Datamation every year.
Advertise with TechnologyAdvice on Datamation and our other data and technology-focused platforms.
Advertise with Us
Property of TechnologyAdvice.
© 2025 TechnologyAdvice. All Rights Reserved
Advertiser Disclosure: Some of the products that appear on this
site are from companies from which TechnologyAdvice receives
compensation. This compensation may impact how and where products
appear on this site including, for example, the order in which
they appear. TechnologyAdvice does not include all companies
or all types of products available in the marketplace.