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The Role of Fog Computing in the Internet of Things

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fog computing


Fog computing refers to a decentralized computing structure. The resources, including the data and applications, get placed in logical locations between the data source and the cloud. One of the advantages of fog computing is to keep many users connected to the internet at the same time. In essence, it offers the same network and services that cloud-based solutions provide, but with the added security of a decentralized network.

Difference Between Cloud Computing and Fog Computing

Cloud Computing

Cloud computing refers to the provision of computing and storage resources geographically distributed. Computing can occur over a variety of platforms, including public cloud and private cloud.

The cloud-computing platforms offer the opportunity to share and mix the workloads among the users over a scalable system. Cloud computing is essentially the ability to store and regain data from an off-site location.

Cloud computing is one of the main reasons conventional phones got “smart.” Phones don’t have sufficient, built-in space to store the data necessary to access apps and services. All the data is transmitted from and to the cloud to provide the services we need. Still, cloud computing technology has a challenge – the bandwidth constraint.

Fog Computing

Fog computing will be dominating the industry in the near future. The domination of Fog will be driven by a need to gather data closer to the source of the data (the user device). Devices are not able to perform the necessary processing in the cloud and the devices are physically constrained (low power and small size).

The ability to process the data locally is more important than in the past because fog computing increases the data’s security. With the evolution of the Internet of Things, more and more devices are being added to the network. Each device is wirelessly connected for data transmission and reception.

Fog computing is about how efficiently data is stored and accessed. Fog computing refers to the networking of the edge computing nodes dispersed in a network so that they can be geographically distributed but still provide an organized communication between those nodes.

The use of fog computing involves a complex process of interconnected edge devices. The edge devices include sensors, storage systems, and networking infrastructure that work together to capture and distribute data.

However, the flexibility of fog computing and its ability to gather and process data from both the centralized cloud and the edge devices of a network make it one of the most useful ways of dealing with the information overload we face today.

                                                                                                                                                                  Image Credit: nikhomk panumas; pexels

 

Are Fog Computing and Edge Computing the Same Thing?

Fog computing is also referred to as “edge computing.”  Edge computing is designed to solve issues by storing data closer to the “ground.” In other words, edge stores data in storage devices and local computers, rather than running all the data through a centralized DC in the cloud.

In essence, fog computing is responsible for allowing fast response time, reducing network latency and traffic, and supporting backbone bandwidth savings in order to achieve better service quality (QoS). It is also intended to transmit relevant data to the cloud.

IDC estimates that about 45 percent of the world’s data will be moved closer to the network edge by the end of 2025. Fog computing is claimed to be the only technology that will be able to withstand artificial intelligence, 5G, and IoT in the coming years.

Another IDC study predicts that edge devices will generate 10 percent of the world’s data even in 2020. Edge devices will fuel the need for more effective solutions for fog computing, resulting in reduced latency.

Edge Computing

Edge computing is, basically, a subset of fog computing. It refers to the data being processed close to where it emerged. Fog computing allows for more effective data processing, thereby reducing the possibility of data latency.

Consider fog computing as the way to process the data from where it is generated to where it is stored. Edge computing refers only to the processing of the data close to where it is generated. Fog computing encapsulates the edge processing and the network connections required to transfer the data from the edge to its end.

With edge computing, IoT devices are connected to devices such as programmable automation controllers. The automation controllers perform data processing, communication, and other tasks. With fog computing, the data is transferred from endpoints to a gateway. Then the data is transferred to sources for processing and return transmission. The geographically distributed infrastructure is aligned with cloud services to enable data analytics with minimal latency.

Both fog and edge computing help to turn data into actionable insights more quickly so that users can make quicker and more informed decisions. Then, fog and edge allow companies to use bandwidth more effectively while enhancing security and addressing privacy concerns. Since fog nodes can be installed anywhere there’s a network connection; fog computing is growing in popularity in industrial IoT applications.

The Role of Fog Computing in IoT

When a device or application generates or collects huge amounts of information, data storage becomes increasingly complex and expensive. When handling this data, network bandwidth also becomes expensive, requiring large data centers to store and share the information.

Fog computing has emerged as an alternative to the traditional method of handling data. Fog computing gathers and distributes resources and services of computing, storage, and network connectivity. It significantly reduces energy consumption, minimizes space and time complexity, and maximizes this data’s utility and performance.

The “Smart City”

Let’s take a smart city as an example. Data centers are not built to handle the demands of smart city applications. The ever-increasing amount of data transmitted, stored, and accessed from all IoT devices in a city will require a new kind of infrastructure to handle this volume. It is these applications that need fog computing to deliver the full value that IoT will bring to them.

Utilities

Water utilities, hospitals, law enforcement, transportation, and emergency management applications in smart cities need the latest data and technology to deliver information and services to support their operations.

Information about water leakages, carbon emissions, potholes, or damage can be used to update billing information, improve operations, save lives, and increase efficiencies. The benefits of capturing and analyzing this data can be directly applied to smart city applications.

Fog computing doesn’t move you from one place to another. Instead, fog is a method for deploying Internet of Things networks where they provide the best return on investment.

Benefits of Using Fog Computing

Fog computing can be used in applications that deal with large volumes of data, network transactions, and fast processing. The benefits of using fog computing include real-time, hybrid, and autonomous data centers that improve operational efficiency and security. Additionally, fog computing can help ensure your systems stay available and optimized without the need to invest in power, data center security, and reliability.

Fog computing reduces overhead costs by concentrating on computing resources across many nodes. The location of the fog nodes is chosen based on their availability, efficiency, and use. It also reduces the load on the data centers of organizations. The reduction in data traffic is another major advantage of fog computing.

Many companies are using fog computing to deploy software applications distributed in many places. Companies deploy many systems over a network to achieve better efficiency and reachability.

Fundamentally, fog computing gives organizations more flexibility to process data wherever it is most necessary to do so.  For some applications, data processing should be as quick as possible, for instance, in manufacturing, where connected machines should respond to an accident as soon as possible.

Fog computing can also provide companies with an easy way to know what their customers or employees are up to in real-time. With the implementation of fog computing, companies can expect to take on new opportunities and increase their profit with IoT technology. But more than that, this technology has the potential to save a lot of money for governments, companies, and even individual users.

Bottom Line

As cloud technologies continue to penetrate into the enterprise environment, fog computing usage will also continue to increase. Cloud computing distributes computing workloads through an elastic computing infrastructure, enabling the real-time processing of data in the cloud.

Edge computing is a major focus area of the IoT fog computing segment. Edge computing is the technology of computing resources deployed at the edge of the network, outside of the cloud. It allows computing resources at the edge of the network to be accessed, analyzed, and then sent back to the network’s edge. This allows for real-time processing of data.

Fog computing solutions will enable companies to implement real-time computing in the Internet of Things. As a result, the IoT fog computing market will be a major contributor to the cloud computing market.

Image Credit: riccardo bertolo; pexels

Victoria Puzhevich

Lead Specialist

Lead Specialist at SCAND with over 15 years of experience in the IT sphere, keen on sharing expert advice and share relevant industry experience.

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How to Build a Startup Team With an Entrepreneurial Mindset – ReadWrite

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Nate Nead


Much of your startup’s success will depend on the quality and integrity of the team you put together. With talented, committed, hardworking people, even a merely decent idea can turn into something groundbreaking. Conversely, even a great idea can struggle to survive if it doesn’t have a solid team in place to support it. 

Obviously, you’ll need to work hard to choose the right people for your team – individuals with a solid experiential background, proof of ample talent, and genuine passion for the business. But beyond that, you’ll need to work actively to equip your team with the right mindsets and philosophies to guide them to productive, innovative work. 

While there are conflicting opinions for what type of company culture works “best,” there’s no denying that your company can (and likely will) benefit from building a team with an “entrepreneurial mindset.” But what is this mentality, and how can you construct it from scratch? 

What Is an “Entrepreneurial Mindset?” 

Let’s start with a description of the “entrepreneurial mindset.” This is an internalized mentality, philosophy, and approach to working within the members of your team that mimics what the most ambitious entrepreneurs tend to feel. 

The mindset includes: 

  • Creativity. Entrepreneurs are creative types. They want to create new ideas, modify existing ones, and come up with inventive new ways to deal with problems. They’re not afraid to think outside the box and try out new concepts – even if they don’t work out. They also like to encourage and promote creative ideas from other people, providing feedback, direction, and motivation to their teammates. 
  • Autonomy and independence. The entrepreneurial mindset also prioritizes autonomy and independence. Entrepreneurs in a business environment don’t wait for someone else to tell them what to do, and they generally don’t have to run their ideas through a bureaucratic chain of command to take action. Instead, they trust themselves, they operate decisively, and they remain agile. In an entrepreneurial environment, your employees will function autonomously in most cases as well. 
  • Change and growth. To be an entrepreneur is to accept the importance of change and growth. The only way for your business to reach more people and make more money is to evolve; that means adding new products and services, changing internal processes, and sometimes, pivoting the entire brand. 
  • Experimentation and adaptation. You probably already know how important it is to remain flexible and adaptable when growing your business. It’s also important for your workforce. With an entrepreneurial mindset, your team of employees will be much more likely to experiment with different approaches and adapt to new scenarios. 
  • Ambitious problem solving. Successful business owners are primarily ambitious problem solvers; they understand there’s some weakness or challenge in the world and are driven to “fix it.” With this mentality, your employees will be more likely to show enthusiasm when solving problems and rising to meet challenges. 

The Value of an Entrepreneurial Team 

So what’s the real value of an entrepreneurial team? 

For starters, you can cut back on direct management and oversight. When all members of your team feel like they have a direct impact on their work environment, and when they’re empowered to do their best, they don’t need as much direction or supervision. Instead of looking over their shoulder, giving them project details, or micromanaging your employees, you can set priorities for them, trust that they’re going to work toward them, and shift your attention to more important matters. This lends itself to a less stressed, more inviting workplace – and allows you to be more productive while tackling the most important projects for your startup

An entrepreneurial mindset also leads to a diversity of thought. When individuals are encouraged to have their own ideas, thoughts, and opinions, they tend to speak more openly in a collaborative environment. They’re more willing to volunteer ideas, offer constructive criticism, and provide meaningful feedback to each other. Such an environment makes it much easier to identify and get rid of bad ideas (before it’s too late), while simultaneously establishing the groundwork for the presentation of highly ingenious concepts. 

Additionally, startups need to keep adapting if they’re going to stay alive. Over time, your target market might change, you might face new competition, and new challenges will threaten your previous approaches. The only way forward is to adapt, incorporating new systems and processes and changing your infrastructure. Ordinarily, teams of employees are reluctant to adapt – after all, most of us don’t particularly like change. However, when the team accepts the importance and value of ongoing adaptability, they’ll be much more likely to be onboard with your latest changes and experiments. 

How to Build a Startup Team With an Entrepreneurial Mindset

Now for the big question – how can you build an entire startup team with a baked-in entrepreneurial mindset? 

  • Create the culture. Everything stems from your company culture. Before you employ any of the following strategies, make sure you have a solid idea for what you want your company culture to be. What are your core values? What is the “ideal” employee mindset? How should this mindset be fostered? What rules exist, if any, to enforce this? Document your company culture guidelines first. 
  • Choose the right candidates. With a culture document in place, you’ll find it much easier to interview candidates – and find out whether they’re a good fit for this environment. Even if they have a lot of talent and experience, they may not thrive in an entrepreneurial workplace; figure this out early, before you hire someone. 
  • Lead by example. You’re the leader, so set the tone. People will follow your example. Whatever habits you want your employees to practice, incorporate them into your own daily work. 
  • Nurture from the top down. You’re not the only leader within your organization, so make sure you select and support strong leaders who can embody and spread your desired entrepreneurial culture from the top down. 
  • Encourage independent management and decision making. Sometimes, employees will have to run their idea “up the ladder” before taking action. But as much as possible, it’s important to encourage autonomy and independent decision making. Empower your employees to make their own decisions, set their own goals, and devise their own approaches to work.  
  • Stimulate creativity. Creativity is vital for an entrepreneurial mindset to thrive. Use creative brainstorming sessions, music, art, and other exercises to encourage your team to think in novel ways. 
  • Get everyone to contribute in meetings. Encourage every member of your team to contribute in your meetings. More contributors will foster an environment of openness and collaborative sharing; it will also help you ferret out the best ideas, which otherwise might be held back by nervous participants. 
  • Reward good ideas. When a member of your team comes up with a good idea or solves a complex problem, reward them and publicly praise them. It will encourage further idea generation in the future and motivate other team members to volunteer their own ideas. 
  • Respect bad ideas. It’s not just about good ideas; it’s also important to tolerate and even respect bad ideas. When someone volunteers a questionable idea or makes a poor decision, show your support. Feel free to offer feedback and criticism, but don’t make the person feel bad for trying to do something inventive or helpful. You don’t want to punish people for trying something new. 
  • Remain adaptive. The most innovative, disruptive businesses are the ones that can adapt. Encourage your team members to remain similarly adaptable, keeping an open mind for new ideas and being willing to change when necessary. 

Once your team is full of people thinking and acting like entrepreneurs, your company will be much more flexible, innovative, and productive. And best of all, this entrepreneurial culture tends to be self-sustaining; your employees will naturally spread it to new recruits and continue to foster this creative, efficient environment. 

Nate Nead

Nate Nead is the CEO & Managing Member of Nead, LLC, a consulting company that provides strategic advisory services across multiple disciplines including finance, marketing and software development. For over a decade Nate had provided strategic guidance on M&A, capital procurement, technology and marketing solutions for some of the most well-known online brands. He and his team advise Fortune 500 and SMB clients alike. The team is based in Seattle, Washington; El Paso, Texas and West Palm Beach, Florida.

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Will AI dominate in 2021? A Big Question – ReadWrite

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Faraz Qureshi


In 2020, AI had rapid transformations and unexpected developments along with excellent innovations. We, as humans have entered into the most digitalized era of all times.

Due to the pandemic of coronavirus, technology has become the central focus like never before. Internet and social media witnessed a tremendous boost as well. No doubt but the COVID-19 brought about massive success to most technological fields.

Will AI dominate in 2021? A Big Question

With progressive developments and advanced modifications in technology, Artificial Intelligence needs no introduction. This groundbreaking technology has been so promising for the past several years and is moving at an advanced pace.

We are Captivated by Artificial Intelligence

Agreeing with the fact that the technologies are captivating us completely with their interesting innovations and gadgets. From Artificial intelligence to machine learning, IoT, big data, virtual and augmented reality, Blockchain, and 5G; everything seems to take over the world way too soon.

Keeping it to the topic of Artificial Intelligence, this technology has expanded its grip on our lives without even making us realize that fact. In the days of the pandemic, the IT experts kept working from home and the tech-grounds kept witnessing smart ideas and AI-driven innovations.

Artificial Intelligence is also the new normal.

Artificial Intelligence is going to be the center of our new normal and it will be driving the other nascent technologies to the point towards success. Soon, AI will be the genius core of automated and robotic operations.

In the blink of an eye, Artificial Intelligence can be seen adopted by companies so rapidly and is making its way into several sectors. 2020 has seen this deployment on a wider scale as the AI experts were working from home but the progress didn’t see a stop in the tech fields.

For the year 2021, Artificial Intelligence is expected to level up to a great extent and is going to deliver phenomenal AI implementation.

Artificial Intelligence in 2021

Even if we talk about the days before the pandemic, AI and ML were already causing drastic changes and widespread disruption in all sectors and industries. Now after the whole year that is passed in the quarantine, in 2021 — we are expecting everything to resume back to normal.

Artificial intelligence and related technologies are going to be the biggest key components that would be impacting almost every sector. Yes, this impact is definitely going to be highly positive so we don’t have to look at the darker side — yet.

With the passing of time, AI would become a key trend that will reshape our home, personal, and work life. This can be pretty alarming right away but soon you will find the advantages that AI will bring.

-The global artificial intelligence software market is estimated to grow speedily in the coming years and would reach up to $126 billion by 2025, a recent report reflected.

In this article, I will show you the impact of Artificial Intelligence on the whole world. With the below-written trends, you will be able to gain an insight into how Artificial Intelligence is reshaping every sector.

It is predicted that whoever leads artificial intelligence in 2030 will continue to rule the world in 2100.

Trends in Artificial Intelligence for 2021

Will AI dominate in 2021? It is the hottest topic and the biggest question running through everybody’s mind.

Hyperautomation:

Artificial Intelligence is going to bring a huge change in the industry and in almost all sectors. We are looking forward to seeing Hyperautomation in every field. This is basically the idea of embedding everything with the automated processes. The repetitive tasks must be done with automation.

AI-powered solutions will help businesses a lot over here and would help these businesses to be redefined. Intelligent technologies will also reshape workplaces with phenomenal capabilities.

AI-driven dynamic operating models:

Most industries are going to adopt Artificial Intelligence for data-driven strategies and to come up with smart technologies and solutions. Due to the pandemic, almost every business has witnessed a loss. Now, everybody is pretty clear that their future plans need to be smoothed out, via Artificial intelligence.

Also, Artificial intelligence is going to bring rapid changes in decision-making as well. Companies look forward to saving their time and cost both and this would be enabled by using the AI.

Autonomous operations for increased efficiency:

In almost every sector, management looks for options that can help the company to be efficient and more secure than ever. AI will bring a boost and the businesses will implement the technology to bring autonomous operations on the stage that will enhance efficiency and the processes will get simplified.

Multiple technologies will play a significant role and the AI will become the center of the activities. Taking care of all the operations and making them more simplified and enhanced, AI will play a vital plank.

AI Engineering:

The field of Artificial intelligence engineering is on the rise. People look forward to pursuing their career paths in the niche of AI to get a secure job future. CEOs and IT leaders of the company are looking forward to deploying new artificial intelligence systems that are maintained and more simplified.

AI is also becoming the core of education and we are going to witness a huge change in the education field knowing as the personalized learning in the form of ML or machine learning. Companies are also going to go for robust engineering strategies to enhance performance.

Convergence of AI into AIoT:

The AI and IoT are turning old concepts into the new concept of AIoT — and it’s on the rise. The internet of things and artificial intelligence are being combined to come up with a newer form of technology. Adding AI into the IoT would help the AIoT to complete the tasks and to learn the data without the involvement of humans.

AIoT will be a lot more defined and will dominate the tech industry. Up to 21% of homes will become smart homes in 2021. AIoT will also be able to adjust in the cities and buildings.

Edge AI:

Another amazing concept is brought about by Artificial intelligence and the technology of the internet of things. Edge-AI is the technology of moving the decision-making process seamlessly and the provision of secure and analyzed data is the responsibility of edge AI as well. This is the pure blend of edge computing and artificial intelligence.

With the help of edge-AI, the smart devices would use AI algorithms and edge computing to come up with the data processing. This will be deployed to every smart gadget and device including mobiles, laptops, drones, robots, self-driven cars, and cameras, etc.

The total cost of AI:

Earlier, it was considered as only the tech giants can use the AI technology but now the startups and the small software initiatives can also look out for the deployment of Artificial intelligence. It is now more accessible to all the companies and they can use the tools of their choice along with the frameworks.

The projects that are powered by AI and ML are expected to grow tremendously. The companies are looking forward to integrating AI into their systems and making their processes go seamless.

Explainable AI:

Explainable AI is going to be in the trend of 2021 and is going to dominate for sure. The explainable AI would help the data scientists to create trust across all the companies and the merchandise that are dealing with the AI and ML projects. The model explainability will also be kept in front of AI experts.

The biggest artificial intelligence vendor, Google, has also offered the development tools and frameworks revolving around the concept of explainable AI. We are looking forward to seeing some more interesting projects that are based on the explainable modules of AI.

Quantum computing on rise:

If we say AI is here to stay — then it would definitely not be wrong. As we can see that along with AI, quantum computing is also on the rise. Here AI will combine with the quantum theory that revolves around the concept of computer technology and its principles. Both the technologies together are going to bring drastic changes.

With the increased demand for computer science and technology, artificial intelligence and quantum computing are the most thriving technologies of the industry.

AI as the service:

The demand for AI is rapidly increasing. People are looking for the experts of AI and the professionals who can create custom AI projects so this is indirectly helping the artificial intelligence experts to rise in demand. These professionals are working to provide IT services as well.

Artificial intelligence will continue to thrive for a very long so if the students are going to opt for this career field, they are definitely going to land a bright future.

Parting Shot:

Artificial Intelligence will continue to dominate the world in 2021. It will soon take over every sector and industry and will continue to thrive.

Faraz Qureshi

Faraz Qureshi is one of the most eminent and exceptional content writers, who has been a part of the writing industry for quite some time now. He has also been associated with assignmentmaster.co.uk as a research analyst. He has the skills to mold the words that impress others immediately.

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How Do We Innovate in a World of Slowing Growth? – ReadWrite

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The Communication Pain Points for Remote Teams (and How to Solve Them) - ReadWrite


Millions of would-be startup entrepreneurs, software developers, and other innovators are struggling. They want to create new products, design new technologies, and introduce the world to new heights of productivity and wellbeing. But we’re entering an era of slowed technological growth – at least in some ways.

How Do We Innovate in a World of Slowing Growth?

Innovation is at the heart of any thriving economy. New technologies mean new companies, new jobs, and new opportunities for all existing companies – not to mention a higher quality of life for everyone involved (in most cases). But if our rate of innovation is unsustainable, where do we go from here?

Are We Really Slowing?

First, let’s explore the idea that innovation is slowing down – because it’s not a foregone conclusion. There are strong signs that innovation is slowing in some respects, but other experts have argued that many of these forms of deceleration are temporary.

For starters, productivity growth in the United States has been slowing consistently over the past few decades.

In the 1950s, American productivity was increasing by more than 3 percent each year. By the 1980s, that rate of increase had fallen to 2 percent, and today, the rate of increase is less than 1 percent annually.

What accounts for this slowing over the past few decades?

There are several potential factors. For starters, research-centric universities like MIT and Harvard were getting more funding and more attention. Major corporations like General Electric and Ford were investing heavily in R&D departments.

And technologies originally developed during World War II (often to fuel the war effort) were commercialized and distributed, with widespread access to them for the first time.

Some experts have suggested that the lack of innovation is a direct result of a lack of investment. If we invest more heavily in R&D in corporate departments and universities alike — we’d be able to see better results.

But this doesn’t necessarily stand to reason; our R&D spending is, collectively, many times higher than it’s ever been before. And yet, the productivity rate growth remains.

Is technological innovation to blame? How can that be?

Others suggest that this is the inevitable effect of technological innovation, which we would see in any society of intelligent beings. Major breakthroughs in technology function like low-hanging fruit; they’re relatively easy to brainstorm, and it’s only a matter of time before they get developed.

Once developed, breakthroughs increase our capacity and make other “low-hanging fruit” technologies easier to think up and develop. From the 1700s through the 1950s, we saw the development of technologies like the steam engine, running electricity, nuclear power, and of course, the internet.

What’s New in Tech?

But now that we’re here, the low-hanging fruit is no longer available. Scientists and researchers are spending all their efforts making our existing technology better – not necessarily coming up with something new.

We’re developing quantum computers as a kind of last area of research for computers, since we’re already pushing up against the boundaries of physics as we know it today.

We’re coming up on some hard limits of human knowledge.

Our model of physics is relatively unchanged since the 1980s. We haven’t made many major advancements in fields like chemistry for decades. And Moore’s Law, which once practically dictated the pace of improvement for transistors — is at its end.

Are we on a tech plateau?

That said, there are some arguments that we’re merely on a temporary plateau. The idea is that, sooner or later, new technology will come along to help us ascend to new heights, opening the door to other technological developments. For example, next-generation artificial intelligence (AI) could make it possible to solve problems that are currently unthinkably hard to address.

What about rates of productivity growth?

There’s also the argument that slowing rates of productivity growth are actually because of innovation, not due to a lack of it. When innovation happens quickly or occurs in an unexpected direction, it can disrupt the economy in such a way that interferes with GDP growth.

For example, when the internet began to encroach on the territory of newspaper companies, it shrunk the profitability of an entire industry.

Directions for Innovation

So how do we continue to innovate in an era with slowing growth?

There are a handful of important possibilities to note:

  • “First principles” thinking. One of the most important avenues for progression is going to be “first principles” thinking. In other words, we need to return to the ground level and rethink some of our longest-standing assumptions. When it comes to innovation, we tend to upgrade various components of an existing system or machine. For example, cars haven’t fundamentally changed in many decades; every component of modern cars is superior, in some way, to older variants, but we’re still working with an engine and four wheels. First principles thinking would encourage us to start from scratch, reimagining what a “car” is from the ground up and challenging our previous assumptions.
  • Lateral expansion. We could also attempt to innovate and expand laterally. Admittedly, this doesn’t qualify as “innovation” in the purest sense. Rather than inventing something totally new, you’ll be entering new, previously unexplored territory. That could be something as simple as reaching a new target audience with your digital advertising strategy, or as complex as introducing a new industry to a developing country that currently lacks it. Existing technology is highly advanced, but not all people of the world can access it equally. New audience targeting, geographic expansion, and cost cutting can all help us progress in this area.
  • Combination and repackaging. In the past decade, most of our best “innovations” have been novel ways of combining and repackaging other existing technologies. For example, the pinnacle of modern technology is, in many ways, the smartphone. But even Apple’s first-generation iPhone didn’t introduce many new features; calling, texting, emailing, and browsing the internet were all already in existence. They just weren’t packaged together conveniently. Since then, we’ve seen many new phone models, but the upgrades are relatively minor, such as more detailed cameras and slightly faster processors.

Supporting Further Innovation

Innovation doesn’t typically happen in a vacuum. It most often happens in dense teams, with strong leaders, and the backing of tons of interested investors and supportive partners. In other words, our best innovators need support.

So how do we, collectively, support further innovation and growth?

  • Investment. One straightforward method is to pour mor money into research and development. With more investment, scientists, inventors, and developers can do more. Of course, there are some limitations here; our R&D spending is higher than ever, yet it’s not giving us a steady conveyor belt of new technologies.
  • Risk. Culturally, we need to embrace risk and rethinking long-standing structures and systems. It’s a risky move to rethink our concept of a car from the ground up, especially if you’re starting a brand new company to do it.
  • Public recognition. We also need to recognize that innovation is slowing and behave accordingly, as consumers. The most recent iPhone isn’t substantially different than the previous generation; perhaps we can throw our enthusiasm behind more novel, innovative presentations.
  • Political theories. It’s also worth noting that people from different political backgrounds have different ideas for tackling this issue. For example, some could suggest the best solution is to foster a truly free, capitalistic market that naturally encourages entrepreneurs. Others may believe that more government control and investing could develop ideas that a free market may not support.

Toward the Next Generation of Technology

The human thirst for innovation and growth is unquenchable, so if we’re currently in the middle of a technological slowdown, the optimistic view is that this is only temporary. We’ll continue making iterative progress in areas that can continue progressing and eventually stumble upon a major breakthrough that forces us to reconsider everything we used to know.

However, if we’re going to find that new technological breakthrough, and support a healthy economy while we wait for its arrival — it’s important that we recognize this slowdown and foster innovation in any way we can.

Productivity increases may have slowed, but they’re still increasing – and that should give us plenty of momentum to keep growing for decades to come.

Image Credit: susanne jutzeler; pexels – thank you

Timothy Carter

Chief Revenue Officer

Timothy Carter is the Chief Revenue Officer of the Seattle digital marketing agency SEO.co, DEV.co & PPC.co. He has spent more than 20 years in the world of SEO and digital marketing leading, building and scaling sales operations, helping companies increase revenue efficiency and drive growth from websites and sales teams. When he’s not working, Tim enjoys playing a few rounds of disc golf, running, and spending time with his wife and family on the beach…preferably in Hawaii with a cup of Kona coffee.

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