Archive for the ‘VIP’ Category

The Last Mile

May 8, 2020

AutonomousDriving

FountainBlue’s May 8 VIP Roundtable was on the topic of ‘The Last Mile’. We were fortunate to have a diverse range of executives in attendance who shared a wide range of perspectives around the last mile opportunities and challenges.

There were discussions about the challenges for delivering products and services to the last mile and the complexity of tasks necessary to make this happen, including navigating (often crowded, inconsistent and poor) road conditions, and the contact-less movement of parcels for the sake of efficiency and safety. 

Our executives agreed that most of the expense and resources are around delivery to the last mile, and of that distance, the delivery to that last 100 meters – from the curbside to the right door, to the right person. 

Solutions ranged from simulations to robotics to drones, all taking into account privacy and security issues, all leveraging AI and data to optimize results. Below are predictions on how we will be delivering to the last mile going forward.

  • There may be more of an emphasis on commercial vehicles rather than on autonomous driving. 
  • There may be smaller and more frequent deliveries.
  • Enabling people to better work from home is not just relevant now, but also for the foreseeable future as the Future of Work has fundamentally changed.
  • Simulations of how we move and travel might help companies and leaders better plan for last mile deliveries.
  • AR/VR solutions might help companies serve their customers in their homes and businesses, without having to be physically present to do so.
  • Software and automation might help customers to personalize and troubleshoot on their own, with contact-less support.
  • Rural areas which have previously been beyond the reach of delivery services may soon receive deliveries to the door.
  • The use of lockers might become more popular, allowing delivery services to deliver to a local store or market rather than directly to the door of the customer.
  • Leveraging the data around how we commute and travel will help us better plan optimal transit options for workers and citizens.

Our final thoughts were around how we can all plan better to serve more people, including those in most need. Every company, every leader, no matter the background or industry, must be a digital leader, to better serve everyone in that last mile.

Industry 4.0 Opportunities and Challenges

April 10, 2020

Industrial Revolution IT Integration Smart Manufacturing Innovat

FountainBlue’s April 10 VIP roundtable was on the topic of ‘Industry 4.0 Opportunities and Challenges’. Please join me in thanking our executives in attendance for our fascinating, wide-reaching and thought-provoking online discussion, featuring our hosts at Honda.

We were fortunate to have a diverse range of executives in attendance who shared a wide range of perspectives around Industry 4.0 Opportunities and Challenges, especially they are impacted by COVID-19. Although we came from different roles and responsibilities, we agreed on many times:

  • Adopt and create technology that is more data-driven, more sophisticated, more integrated, more pervasive. Automation and process improvement is necessary to efficiently bring customized solutions to customers.
  • Remember that it’s always about the people. We need people as part of the solution – to adopt and integrate the technology, to run and implement and improve the processes, to continually update everything based on the needs of the customers, the needs of the team, the plant, the company.
  • Collaborate with business units and R&D teams will help improve our manufacturing and operations. 
  • Adopt innovative new solutions only if they are relevant and helpful now and in the long term, and not too difficult to implement and scale.
  • Collect masses of data and quickly filtering to collect relevant data points help us better understand the problem (and the opportunity) and better make informed decisions.
  • Understand the problem statement and articulating it well will help teams of engineers, data scientists, business professionals to collaboratively design solutions, create and vet prototypes, revise and refine models, and ultimately more efficiently manufacture goods.

Below are some thoughts of fundable opportunities:

  • Provide an offering which would help companies better bridge simulated scenarios with real-world results.
  • Focus on special edge cases/corner cases for manufacturing or distribution
  • Machines in manufacturing plants will continue to be monitored by sensors, which will in turn generate huge volumes of data. There are opportunities to leverage that data to get insights about maintenance, performance, anomalies, etc., and therefore make better informed decisions and forecasts. See Why TinyML is a Giant Opportunity.
  • Invest in sensors which would help better see environment and obstacles on the manufacturing floor
  • Design solutions which let manufacturers go from manual to automated, from automated to intelligent solutions, and learn and adjust.
  • Design Augmented Reality solutions with digital modeling to help manufacturing leaders better optimize for efficiency, accuracy, performance.
  • Create an offering with addresses the question ‘how do we go from screwdriver to software so that we can better optimize for Industry 4.0.’?
  • Design solutions which are both robust and reliable, while address edge and corner cases.

Below are some philosophical thoughts about Industry 4.0 opportunities and challenges.

  • Whereas it might be more difficult for manufacturing plants to convert into the production of N95 masks to support our healthcare providers during the pandemic, it may be more feasible to produce medical grade plastics, rubbers, mechanical parts – items which are just as useful.
  • The pandemic has further facilitated the convergence across industries – where industry leaders with manufacturing facilities are all supporting our healthcare workers as they serve those impacted by COVID-19.
  • Infrastructure innovations need to take place to ensure that people are better prepared for and better able to respond to the next crisis. The COVID-19 pandemic has wreaked havoc in our personal and work lives, and will have a lasting impact on everyone. 
  • Globalization will lead to localization, with a focus on customized local solutions. In turn, localized solutions will be applicable to global markets. The trick is knowing how to quickly and optimally manage the high variability of scenarios and deliver timely solutions.
  • Let’s design better contingency plans so that we are better prepared for another unforeseen scenario with global impact and ripple effects.
  • There are opportunities for each of us to collaborate as leaders, as technologists, as industries to better run our businesses while better taking care of everyone – doing well, while doing good.

Our final thoughts are around what we are all seeking: sustainability, continuity, innovation for ourselves, our companies, and all those we serve.

Opportunities and Challenges for Innovating on the Edge

March 13, 2020

EdgeComputing

FountainBlue’s March 13 VIP roundtable was on the topic of ‘Opportunities and Challenges for Innovating on the Edge’, with leaders from Maxim for leading the virtual discussion. Thank you also to our executives in attendance for their input and advice. Below are notes from the conversation.  

We were fortunate to have a diverse range of executives in attendance who worked in and around the edge computing field. As we grow solutions around edge computing, they agreed that it’s important to manage the following:

  • Seamless connection on an ongoing basis
  • Low latency/rapid response, especially when the stakes are high
  • Immersive experience so people can manage and use the solutions effectively
  • Connectivity wherever you go
  • Privacy and security of users and their data

In order to do that, we need to do the following:

  • Capture, manage and process the volumes of data generated by the growing number of sensors, devices, wearables
  • Increase speed of access to the data, without a gap
  • Gather, integrate, process and filter data between all sensors/devices/wearables on the edge in the cloud 
  • Send back filtered/processed data back to the edge for response and action

Challenges and opportunities abound. Below are some thoughts around the data.

  • Optimize the gathering/filtering/processing of data and returning only the ‘relevant’ data back to the edge/device/user
  • Validate the accuracy of the data generated.
  • Remember that where there is data, AI and ML can improve that data, making it more relevant and useful. 

Other challenges and opportunities are highlighted below.

  • Make algorithms effective enough to be useful, small enough to not consume too much power, not take too much time to process.
  • Design the architecture to better manage the power for devices/sensors/wearables on the edge.
  • Make the hardware small and compact, but also simple to integrate with the firmware and software.
  • The processing of images and videos will also provide many opportunities.

Below is advice on how to better innovate on the edge.

  • Provide options for selecting variables and rules which impact what data.
  • Validate the integrity of the data received from sources on the edge.
  • Make predictions about what’s going to happen based on patterns of what’s happened in the past.
  • Work with regulators so that they understand how technology works and can update their policies so that people are protected, but they can also get access to life-saving and life-improving solutions in such regulated industries as automotive and healthcare.
  • Proactively manage and maintain systems, computers and machines so that they can send data about system health and issues, including issues which might be related to their own functioning.
  • If you’re running multiple engineering/product teams, help them collaborate on common solutions, bringing the best brains and solutions together rather than working in silos
  • Provide personalized solutions for client companies which would have immediate benefits as well as scalable impact.
  • The mass adoption of 5G wireless has reached health and infrastructure obstacles, so don’t count on its adoption as part of your sales and marketing strategy for your edge computing solution.
  • Create edge computing solutions which meet the ‘hard constraints’ of being on the edge: the need for POWER, the SIZE of the device, and the COST to manufacture, distribute and maintain these devices/sensors/wearables. 

We end with the staggering thought that we will soon have 42 billion connected devices. The solutions that we are providing and planning today are real use cases. But think also about what’s transformational for the future – not just what devices are sensing, but also empowering a tool/process/human/algorithm to take proactive action, based on data generated, models created. We are not quite there, and is much thinking, collaboration, and working to do before we get there, and many safeguards to put in place to make sure that’s done right.

DevOps Opportunities and Challenges

February 15, 2020

DevOps

FountainBlue’s February 14 VIP roundtable, on the topic of ‘DevOps Opportunities and Challenges’. Thank you also to our gracious host at Comcast. Below are notes from the conversation.  

We were fortunate to have a diverse range of executives in attendance who worked in devops in many different ways. Collectively, they defined ‘devops’ in the following way:

  • tools and processes designed to empower and enable developers to better serve internal and external customers;
  • systems and solutions intended to help developers integrate solutions end-to-end, rather than handing off projects to other parties;
  • integrated solutions and processes which help individuals, teams, and leaders better respond to a fast-moving, highly-demanding customer base;
  • systems designed to facilitate the communication and coordination, encourage the collaboration between silos of stakeholders.

Our executives agreed that the many elements of devops solutions are integral to the success of ventures large and small, and that individuals and companies who don’t acknowledge and accept this fact will be left behind.

Below are thoughts on how best to support the adoption of devops principles.

  • Consider the needs of all stakeholders in designing solutions.
  • Align all stakeholders behind a corporate vision, a common goal.
  • Hold everyone accountable for the success of a project, rather than on 
  • Blur the line on role definition, boundaries between what you do and what others do. Focus on what we do together, what success together looks like, how to align behind a common mission/vision/milestone.
  • Help people plan from the top down, deliver from the bottom up.
  • Clear, transparent communication from the top-down, from the bottom up is critical.
  • Not everyone will embrace the new way of doing business with devops principles. 
  • Collaboratively design a process which delivers measured results. From there, you can decide on which tools and which people can help deliver those results.
  • Find and recruit the passionate, the talented, the open, the hungry and empower them to succeed.
  • Embrace a culture of accountability. Erase a culture of entitlement. 
  • Executive sponsorship and buy-in are essential to encourage a shift to a more open, more devops-oriented culture.
  • Consider Security and Scalability issues in designing extensible devops solutions.

We close with some key comments:

  • Partnerships within and across the company are key to all devops initiatives.
  • Devops leaders and innovators are resourceful, action-oriented and results-focused.

Thank you again for taking the time to join us and share your perspective and information. 

Healthcare Opportunities and Challenges

January 21, 2020

Healthcare

FountainBlue’s January 17 VIP roundtable was on the topic of ‘Healthcare Opportunities and Challenges’. Thank you also to our gracious host at Roche. Below are notes from the conversation.  

We had an outstanding group of diverse executives, all representing the breadth and depth of healthcare – from medical equipment and medical supplies and devices, to healthcare services and providers, to the biotechnology, pharmaceuticals, and miscellaneous scientific and professional services related to the curative, preventive, rehabilitative, and palliative care of patients of every ilk.

Through the variance of perspectives, our healthcare executives agreed the data revolution continues and is impacting healthcare in many ways, even enabling personalized medicine. For example, the sheer volume of knowledge is overwhelming and the accumulation of knowledge continues to escalate. In fact, accumulated medical knowledge took 50 years to double, but today, it takes 73 days.  

What becomes critical then is figuring out what data is relevant to whom for what purpose and how that relevant data will drive better decision-making for patients, practitioners, providers, vendors, care-givers, insurers, etc. 

Below are some opportunities highlighted by our executives:

  • Leverage the data to optimize diagnosis, decision-making, and treatment easier, more collaborative, more robust, more dynamic.
  • Embrace technological solutions to age-old health challenges.
  • Help institutions and providers leverage technology to be more effective and more efficient.
  • Provide integrated hardware and software solutions which help patients optimize their own health, manage their own conditions.
  • Efficiently provide comprehensive, individualized programs which are scalable and customizable, yet also cost-effective to manage and run.
  • Serve the proactive, informed patient/consumer who will increasingly demand more personalized services.
  • Offer technology solutions which enabled integrated health and wellness.
  • Create solutions which help hospitals integrate legacy data and hardware, while also improving processes and providing more digital functionality.
  • Consider opportunities around remote monitoring for the aging population, leveraging mobile devices and sensors.
  • Optimize logistics, delivery, fulfillment and retail support for the highly-regulated healthcare market.
  • Integrate today’s hot technologies into comprehensive healthcare applications: AI/ML, Edge Computing, IoT, Robotics, Deep Fake, 3D modeling, AR/VR…

A major theme in the discussion is that collaboration across leaders, organizations, nations, and industries is key.

  • Corporations continue to make build/buy/partner decisions with start-ups targeting specific niche markets.
  • The sharing of data, if managed well to respect privacy and access, can benefit all stakeholders.
  • Create platforms which would allow multiple stakeholders to collaborate in the service of patients, in the search for cures.
  • Industry leaders and technologists and advocacy groups need to partner with policymakers to improve the evaluation process, to better serve patients.
  • Genius ideas can come from anywhere – providing the data and information will help more geniuses step forward.

The bottom line is that no matter where we sit at the table, as a patient, as a technologist, as a provider, we are all in charge of our own health. Empowering all stakeholders with tools, resources and information will help us all make better healthcare choices.

Smart Cities, Smart Buildings

December 8, 2019

SmartCities

FountainBlue’s December 6 VIP roundtable was on the topic of ‘Smart Cities, Smart Buildings’. Thank you also to our gracious host at Hyundai. Below are notes from the conversation.  

As usual, our executives in attendance for this month’s roundtable represented a wide breadth of companies, industries, experience and perspectives. They shared many common thoughts around this month’s topic.

They each agreed that it’s always about the data. (Of course it’s about the data.!) However, instead of thinking about the vast volumes of generated data (which has doubled in the last 3-5 years!), think about how best to filter that data so that it’s immediately relevant, as defined by individual users.

In the context of smart cities and smart buildings, remember that we are talking about 1) physical hardware – from networks to computers to robotics and sensors – and 2) the data generated by all these physical elements (see above), and then 3) the leveraging of that data through software and integrated solutions so that we address specific customer and market needs. 

Below are several specific use cases.

  • Automobile manufacturers are becoming smart mobility partners as well. It’s not just about selling cars, it’s about providing an experience which keeps drivers and passengers connected and safe. 
  • Robotics solutions will help deliver goods to the last mile, within city infrastructure – both physical and digital (networks). 
  • Provide transit for the last mile in crowded cities – transit which is flexible, customizable and safe. 
  • Occupancy maps for buildings and more sophisticated lighting and heating options will optimize building efficiency. The technology is available for the most part, but the adoption may be slow.
  • Doors becoming sensors may help manage security and access into buildings.
  • Sophisticated cameras can help proactively target the type of outlying behaviors worthy of action, and quickly mobilize relevant authorities. 
  • Connecting inanimate objects with each other – car-to-car, car-to-building, sensor-to-building, etc., can help address specific communication and collaboration and safety goals. It will also generate huge volumes of data which need to be managed proactively.
  • Provide low-friction shared mobility in collaboration with local cities, businesses, citizens while also respecting the privacy and security of all participants. Then leveraging aggregated and anonymized data to better understand how we can anticipate and serve individuals, groups, etc., and better anticipate the motivations and behaviors of individuals. There are many business implications if this is done well. 

Below are thoughts on how generating relevant data will lead to new businesses and better business models.

  • With volumes of collected data, you can not just understand who’s going where when, but also look at the patterns of behavior and see what might be impacting specific behaviors. These ‘movement maps’ is machine learning at its finest!
  • The ability to dynamically filter data based on a multitude of factors will create endless business opportunities, especially if the same data set can serve many different niche customers, and deeply serve individual customers.
  • Understanding past behaviors and data, and also current patterns of behavior will help businesses better anticipate and address needs. The possibilities are endless.
  • Having a standard set of protocols and formats will help integrate and manage data. Collaboration needs to happen in order to set these standards.

The group shared some final thoughts in specific areas:

  • Personalization is key – how do you both provide exactly and specifically what someone wants while also dynamically serving everyone else and their specific needs?
  • Security is fundamental. 
  • Privacy is to always be respected. 
  • Collaboration between government authorities, businesses, investors, users, etc., is essential.

We concluded with many thoughts on the Circular Economy and asked ourselves how can we all do good – serving those with some basic human needs, while also doing well? What’s the business case for serving those with the basic needs and who will help bring everyone forward. We didn’t have an answer, but agreed with Margaret Mead. “Never doubt that a small group of thoughtful, committed, citizens can change the world. Indeed, it is the only thing that ever has.”

Data is the New Black

November 9, 2019

data

FountainBlue’s November 1 VIP roundtable, on the topic of ‘Data is the New Black’. Thank you also to our gracious host at Automation Anywhere. Below are notes from the conversation.  

Here’s the thing about data:

  • There’s a wealth of it, and it’s just getting overwhelming bigger.
  • It drives everything – every industry, every person, every company. 
  • It’s good news for the semiconductor industry and other sectors which make sure that we have the storage, the energy, the network needed so that people can keep getting access to that data.
  • Data within legacy systems might be valuable, but it is likely also difficult to access.
  • Data across multiple sources might be useful, but it is likely to connect data across multiple source into a common dataset, useful enough to understand problems and make decisions.

With that said, here’s the challenge and opportunity around data.

  • There’s so much of it that we need to filter it first to identify which data is relevant and then also for what we need immediately, what we need in the short term, and what we might need in the long term.
  • It takes a lot of energy and resources to keep the data, so we must be strategic about what data to keep and how we can efficiently get it into the hands of those who need it most.
  • Compliance to security and privacy issues make data management high-stakes for all. 
  • Having an interoperable standard for data sharing might help better integrate data across sources, teams, companies, industries.
  • Customers today are empowered and fickle. Companies must be able to innovate and customize more quickly to serve their needs.
  • Even adopted solutions have much shorter life cycles today, as customers want solutions which are better and faster and more battery efficient. 
  • People are at the heart of the problem around data privacy. They want their privacy and their access. It’s hard to give people both at the same time every time.  

Below are some shared best practices:

  • Make a plan on how data is gathered, managed and distributed. 
  • Plan for a future with much more data. Be selective about what data is important.
  • Collaborate with other people, companies and industries and share best practices.
  • Focus your data plans on the needs of your customers and your partners.
  • Consider the intentions and ethics around the people and companies providing the data.
  • Policy may not be the answer to managing data mishandling. Indeed, it may cause more complications, less fairness.
  • People should be responsible enough to know how their data is used and astute enough to take the data they receive with a grain of salt – even to the point of questioning the validity of the data and the intentions of the party providing the data.
  • Create solutions with tiny form factors to better address the needs of demanding customers.
  • Ask for less information from customers when you ask them to sign up for something – the less friction you’re providing to the customer experience, the better results you could get.
  • There will be a growing convergence of tech and ethics and values. Speak to the elephant in the room – facilitate that conversation between stakeholders within and across organizations.  
  • Use fewer resources to manage ‘garbage data’. Yes, all data might one day be useful, but focus on the data that’s more likely to be useful, now and soon, rather than data which might one day be useful. 

Below are thoughts on the future opportunities.

  • The future may have more self-learning – e.g. more AI, less raw data.
  • Use ML to identify patterns early enough to address and even prevent diseases. 
  • Making sense of unstructured data provides huge opportunities. 

The bottom line is that data is everywhere – the use of access and usage are complicated, the stakes are high – you want to give the right people immediate and full access without compromising the integrity and accuracy of the data, and while respecting the privacy of those who ‘own’ the data. 

Future of Mobility

October 14, 2019

Mobility

FountainBlue’s October 11 VIP roundtable was on the topic of ‘The Future of Mobility’. Thank you also to our gracious host at Samsung. Below are notes from the conversation. 

The executives in attendance remarked on the range of perspectives on the future of mobility – from semiconductors to pharma, from auto to software. We agreed on the following:

  • Moore’s Law will also apply to mobility – solutions will be better, faster and with lower latency with advancements happening in ever-shortening periods of time.
  • There will be a constant push-pull between privacy and access. Data ownership and access will be an issue which needs to be proactively managed.
  • Be careful who collects your own data.
  • Ensure that the data you’re collecting is valid and truthful and vetted.
  • The proliferation of devices and data will create increasingly more complex requirements on technologies, people and companies. And the pressure to get it right real-time will be increasingly overwhelming.
  • Build awareness and education so that individuals, leaders, companies will use data and information wisely and well, with integrity.

Below are the strategies for navigating the future of mobility.

  • Build and join ecosystems of partners to manage different facets of very integrated mobility options. Nobody can be an expert at all things.
  • Proactively manage the expectations around mobility solutions and sensors, so that you’re in line with common goals within and across individuals, teams and companies.
  • Accept that there will continue to be a proliferation of mobility solutions, and that there will be a lot of crossover between work and life. Plan your security and IT strategies accordingly.
  • Collaborating between entrepreneurs and corporates will continue to foster innovations in mobility.  

The identified opportunities include:

  • Power storage, distribution and management for mobile devices
  • Infotainment and telematics solutions which support connecting cars and supporting drivers and their passengers
  • 5G solutions which address latency challenges 
  • 3G solutions which provide access to the billions of people who currently don’t have access
  • Edge Computing solutions which facilitate quicker processing at the device level, for faster response times
  • Leveraging lidar and sensors to more accurately and more rapidly process the physical world
  • Providing immersive mobility experiences 

We also had a lively discussion about the role of humans as mobility solutions become more pervasive. We concluded that humans will always be necessary.

  • Mobility solutions might provide you with vetted information and dashboards, but humans will make the decisions.
  • Humans will make creative decisions which might better solve the problem. 
  • Humans will be the ones improving existing solutions and understanding the problems so that new solutions will be created.
  • Humans will be managing all the humans, the devices and solutions – and aligning all toward a common vision and result.

Internet of Everything

September 25, 2019

group hand fist bump

FountainBlue’s September 13 VIP roundtable, on the topic of ‘Internet of Everything’. Thank you also to our gracious host at Micron and to each of you for your input and advice. Below are notes from the conversation. 

On the one hand, the ‘Internet of Everything’ is inevitable and logical, but on the other hand, it’s overblown and ineffective. If first all collectively focus on creating a viable and flexible infrastructure to sustain it, if we could all collaborate to mitigate the downsides around privacy, security, and access, we could positively impact societies and people around the world.

Core to the success for Internet of Everything solutions is the need to optimize data, process, and people. 

  • Data: With the mind-boggling volumes of data available through the ever-growing mass of devices, we must quickly discover, filter, organize, communicate, report on and process real-data efficiency. 
  • Process: We must strategically create processes which would help us receive, manage, communicate, and report on data to the right stakeholders as quickly as possible. These processes must also optimize energy, dollars and people.
  • People: We must ensure that the right people get access to relevant and accurate information quickly so that they can respond accordingly.

As an enterprise leader and as an informed consumer, the Internet of Things is providing some daunting challenges.

  • The blurring line between work and home means that ‘home’ devices show up at work, which may endanger the enterprise network.
  • ‘Intelligent’ appliances might help you optimize what you buy when for example, but might also make you uncomfortable with who might know what about you.
  • Everyone wants everything seamlessly, wirelessly, and simply, but sometimes that’s not easy. We can assume that people will get ever more hungry for bandwidth, meaning a huge and growing demand. But creating that infrastructure is a challenging business, unless we can work together to collaboratively fund it.

Where there are challenges, there are also opportunities. 

  • Allow on-premise processing of data for the most important information.
  • Leverage mixed reality, holograms and simulations to connect with experts in support of people addressing specific on-site challenges. 
  • The volumes of generated data will help customers better understand a wide range of problems, and make better decisions, leveraging AI and ML.
  • The idea of ubiquitous communications means so much information from so many sources. Filtering out which communications are essential and important will be a huge ongoing need.

Our executives had some words of caution.

  • Segment out individual devices which may have access to your home or work network. Hackers generally get in on the weakest link.
  • Proactively manage your layers of risk. Ensure that greatest protection for your greatest assets. 
  • Know what’s likely to happen and plan accordingly.

In the end, our executives are practical, emphasizing the need to focus on ROI rather than IoT. 

Innovating on the Edge

August 13, 2019

EdgeComputing

FountainBlue’s August 9 VIP roundtable, on the topic of ‘Innovating on the Edge’. Please join me in  our gracious host at Intel and to each of you for your input and advice. Below are notes from the conversation. 

There are many factors which lead to the emergence and growth of Edge computing, including: 

  • the volumes of raw data generated by the exploding number of devices, processes, and programs;
  • the complexity of data available makes it more difficult to process, filter, understand; 
  • the users are demanding powerful, personalized, complex solutions which are secure and private; 
  • the imminent arrival of 5G solutions will push executables down faster to the ‘edge’, the device itself; 
  • the tremendous need for energy and power (and the associated expense) if everything is processed on the cloud itself;
  • the urgent need for quick responses, especially when safety and lives are on the line; and
  • the immediate and ongoing need to protect the privacy of users, the security of systems and devices and networks.

But it’s no easy task to innovate on the Edge.

  • Each solution must be able to efficiently filter out data, focusing on the ‘real’ data, the ‘relevant’ data for the problem at hand.
  • There’s a challenge to make strategic decisions around technology and business, while also not getting stuck with the decision made, in case things don’t go as planned.
  • The current investment environment is pro-software and less bullish on hardware in general. 
  • Each solution must navigate the technical, business and regulatory objectives and constraints, while also solving the problem.
  • The speed of change is mind-boggling, and innovating in that environment is difficult at best. But things also keep evolving and changing, which makes things even more difficult.
  • Memory and storage bottle necks may arise with the rise in volume and complexity of data and processing.
  • It’s a sobering thought, but devices and solutions on the edge which might be turned into weapons (including cars) have additional security and operational requirements.
  • Companies must also protect itself from financial, legal and brand exposure should a solution on the Edge cause unintended damage to users.

Below are some thoughts on how to keep that innovative edge.

  • Be strategic. 
    • Know what your customers need in the short term and for the long term and plan accordingly.
    • Work with an ecosystem of partners to deliver tailored solutions efficiently.
  • Adopt a set of Open Source tools which would help rapidly develop, deploy and manage solutions on the edge.
  • Develop hardware-agnostic solutions which are more versatile and adaptable. 
  • Adopt self-maintenance systems to ensure validity of solution and ongoing maintenance. With that said, do not delegate on management to automation. Know when the scenarios when you need proactive leadership and management and respond accordingly.  
  • AI will take you far – understanding the relevant data. ML can take you farther – it could help you understand the trend and make predictions beyond the historical data. Both are necessary and essential. Progressively more of the AI will take place closer to the edge. 
  • The speed and accuracy for data processing is essential for Edge Computing, as it is for just about everything else involving data. The ability to process unstructured data and video and the ability to focus on the deltas rather than the raw data will help solutions better manage and filter data.
  • Collaboration is key as there are so many players involved.
    • Carriers need to invest in 5G.
    • Cities need to adopt the infrastructure for 5G.
    • Each solution is a combination of hardware, software, processes, etc., Partnering with others in non-core offerings is essential.
    • Privacy and security must be maintained. Having ecosystem partners focusing on these areas will help companies focus on delivering on their core value.

In conclusion, our leaders agreed that innovators in the Edge Computing space must create an ecosystem of players and connect with players across the ecosystem at many levels.