Progressive vs Disruptive Tech – What is The Meaning Behind Innovation?

This article is a companion piece to the Tech Made Fun Episode – TMF 022 – What Counts as Innovation – Progressive vs Disruptive Tech

Innovation revolves around progress in technology over the years – specifically we’ll be covering Progressive and Disruptive technology where after explaining these terms we talk about some of the disruptive tech that has made a large impact on the society at large through an average Bashir’s perspective. Starting with the mother of all disruptive tech – The Internet, we’ll cover technologies like Smartphones, 5G, Cloud Computing, IoT, Web3, Autonomous Driving and the newer Large Language Models.

Disruptive Technology

Technology that fundamentally changes the existing market or industry and replaces it completely with a newer perspective or paradigm. To explain it simply, we could say that disruptive technology is what creates a new unexpected path that is to be followed by those that will come after it.

Example:

ARM challenging x86 in personal computing space – For decades Intel’s x86 architecture has dominated the personal computing space with absolutely no other alternative. ARM’s debut into the computing industry through mobile computing space made it the de-facto standard for mobile computing with every large phone manufacturer choosing it as their processor architecture but with time that’s changing too as ARM has been making serious progress in the personal computing space especially laptops and even server computing space. To learn more about ARM, its promises and implications, check out TMF EP 20 where we’ve discussed this at length.

Progressive technology

Technology that builds upon existing concepts bringing incremental improvements with time is progressive technology. Unlike disruptive tech, the trajectory of progression in this case is expected or could be predicted.

Example

Transistor Scaling – Let’s use an analogy to explain this term:
New processors are released every year or so by major tech giants. Every year they bring some level of improvement from previous year’s processors but most of the time they are what is expected of them. Like NVIDIA’s 50 series Graphics cards are expected to be better than the current generation because it’s known that they would be more efficient and performant because of more transistors packed into the chip and better progress of efficient designs for building them. At the same time, we know they aren’t going to cause a massive disruption totally changing the industry.

Significant technologies of the last decades

Having given you an idea of progressive and disruptive tech we’re going to discuss some significant technologies that have come in the last decades. We’ll majorly discuss their impact on the Mango Man, if the technologies were successful or not and if we are researching further than those or not.

The Internet

Starting off with the mother of all disruptive technologies – The Internet. 

Though the Internet has existed in different forms since the mid 80s, It’s important to discuss where it all began after the personal computer revolution. The internet by its very nature has been a revolutionary concept, one that addresses the fundamental human need of communication, information sharing and connectivity.

The internet was the pivotal moment starting what we call  The Age of Information. Never before in the entire human civilization stretching millions of years have we ever been able to share and access information at such distances in a matter of seconds.

Impact

The Internet’s impact on the larger public has been unmatched by anything before it. It has turned the world into a global village. For an average Bashir it has changed how he does business, how he entertains himself, how he shares his opinions, his ideas, how he collaborates with those on the other side of the planet.

The impact’s been so massive that global cooperation organizations consider it part of the freedom of speech that is among the basic human rights. The open and decentralized nature has created rapid growth in the Internet allowing us to make more use of it giving birth to a plethora of technologies some of which we’ll discuss next.

Reasons

• Open – The Internet by concept is open to anyone irrespective of the race, color or country they come from.
• Decentralized nature – No one entity controls the entire Internet. It’s not someone’s property.
• Social Impact –  Fundamentally changed how humans interact and communicate with each other.
• Economic Impact – Billions of dollars flowing through the internet every other hour.

Further Advancement

Even though the internet is more than half a century old, it has been changing ever since. From Dialups, Broadbands, Fiber Optic connections to attempts to provide Internet through geo-orbital satellites, It’s been advancing.

Smartphones

If we use an analogy of a road with many cars and we assume the Internet as the road, then smartphones are the cars on that road. To understand better, let’s rewind back to when computers really started picking up in the early 80s-90s. Back then, a simple computer was the size of a double decker bus, a few megabytes of memory would be transported in trucks. The invention of Transistors, Integrated Circuits and Microprocessors down the road gave birth to personal computers that were small enough to put on a desk and further  advances in the integrated computing space led to smartphones. An average phone today has billions of transistors, millions of bytes of storage and a latency measured in thousands of a second.

It would have been impossible to explain half a century ago that one day computers would fit in one’s palms and allow him to see and talk to the person living on the other part of the world. The ability of smartphones to be able to communicate through a global network of computers (Internet) has revolutionized an average person’s interaction. The average Bashir couldn’t use the Internet on his own. Smartphones are something he can physically interact with to make use of the Internet. 

Impact

Where Personal computers democratized computing for the general home user, Smartphones expanded that to every person. Their cheaper cost, coupled with their smaller size than personal computers and ease of use helped turn them into a basic need.

Smartphones completely disrupted the communications sector which was traditionally wired with beefy terminals and slow routing mechanisms. Like internet, they again redefined how people conduct business, communicate to others and collaborate with each other. Smartphones led to further innovation in wireless communication technologies from near field technologies like Bluetooth and NFC to long range ones like GSM.

Reasons for Success

• Size – In contrast to the traditional computers of the time, the size of smartphones was the biggest factor differentiating them from the rest.
• Affordability – Unlike personal computers smartphones have been more affordable for the general public.
• Convergence  – Modern smartphones combine functionality of different devices into one package. It combines functionality of devices like camera, media player, telephone, personal computer, radio receiver, and more.
• Accessibility – Compared to personal computers, smartphones have presented a more accessible interface that is simple to use for the average Bashir.

Further Advancement

Since the earliest phones, modern smartphones have come a long way with each year showing progressive improvements over the later year. Manufacturers have been trying to pack in ever more performance in more integrated and smaller devices with sleek packaging. Though it might seem that the performance aspect of smartphones isn’t progressing at an exponential pace since they have become quite performant, the challenge of making them smaller and efficient while maintaining performance is what companies are investing a lot of money and effort on.

5G

5G short for fifth generation is a cellular communication standard. What it means for an average user compared to 4g is, more stable connections with higher bandwidth and lower latency. Much of the buzz around 5G is mainly on its potential to deliver instead of what it’s delivering right now. 5G’s promise of higher bandwidth and low latency has high bandwidth applications like cloud gaming boosting responsiveness and game fidelity. The stability and speed it promises could mean improvements for Driverless cars, Remote piloting drones and wherever time is crucial but most of this stuff is talk of the future since we are yet to have completely driverless cars on the road and remote drones in the air.

Other than just smartphones, In the future 5G could be crucial especially for Manufacturing Industries, Autonomous Cars, Augmented Reality headsets, Environmental sensors, Thermostats and other IoT gadgets. Industries could use 5G for maintaining high resolution video feeds of factory floors or for AR glasses.

Impact

For the average Bashir, 5G has yet to prove itself even though it promises some serious improvements in bandwidth, stability and latency over 4g. Right now we just don’t have a real killer application specifically for 5G that is more true in countries like Pakistan where even 4g coverage is uneven and unstable.

Reasons for lesser adoption

Cost – Unlike traditional 4G towers which operate on a specific frequency band, 5G covers a much broader frequency band in turn making it more expensive to implement and maintain, 5G devices are also expensive for the general user.

Infrastructure – Implementing 5G requires a complete upgrade from the existing system requiring more investment for the newer infrastructure and time.

Lack of present use-case – 5G has yet to show a use-case that is a general need since blazing fast speeds and lower latency that it promises don’t have a use-case right now. For browsing and social media that the most public use, 4G is sufficient.

Further Advancement

While 5G has been able to provide impressive performance over 4g, advancements are still underway to make it more available to the end users. Efforts are being made to make use of existing infrastructure to integrate it with 5G, this approach is known as NSA (Non-Stand-Alone) unlike SA (Stand Alone) approach where entirely new infrastructure is installed. AI and ML are being used to enhance the integration with 5G. Newer and efficient security protocols are being developed specifically for 5G.

---

Looking for more helpful tools, guides, and templates?

---

Cloud Computing

In the recent decade, Cloud Computing has emerged as a new way to compute that has changed not just how an average Bashir does computing but has completely changed many industries. Explained simply, Cloud Computing is just using another computer stored in some datacenter (a facility that houses a lot of computers) that you could access through the internet. Usually these computers are available to the public to be rented out mostly through a subscription model but instead of using the bare metal computers, most of the people access services hosted on them.

Think of it like this: A lot of people use storage services like Google Drive and iCloud to store data when their phone or laptop’s local store is full. Once it happens, any excess data is offloaded to the cloud which is really just a server computer in a datacenter whose purpose is to store data and share it with the user when he asks for it. The data exchange happens through the internet because the datacenter computers are connected to the internet.

Now, there are a few ways one can access the cloud. Let’s discuss the two most popular:

SaaS – Acronym for Software as a Service is the most popular way an average Bashir accesses the cloud. A large number of software one interacts with is hosted on the cloud. That saves the user from buying expensive licenses and the additional resources that they may require to further run that on their own computers.

IaaS – Short for Infrastructure as a Service, means that a user can buy a portion of a physical compute cluster or the actual machine by either renting it for some time or completely purchasing it. Companies often use IaaS to offload their non-critical compute to the cloud. This is mostly relevant to companies rather than individuals.

Impact

Cloud Computing has caused a significant shift to the traditional way we individuals and companies use computers. The impact for an average Bashir has been so broad that most of the services one interacts with are hosted on the cloud. From doing spreadsheets, streaming movies, playing games or using high workload applications – all of this could be done through the cloud.

On the corporate side, companies are increasingly leveraging cloud for their operations. Most of the big software makers like Microsoft, Adobe, Oracle, offer solutions hosting their software on the cloud.

Reason for Cloud’s success

Initial Cost – Instead of setting up on-premises solutions with entire server racks, specialized hardware, environment, trained maintenance and engineering staff, Cloud cuts all of this and provides a significantly lower initial cost to start operations with.

Convenience – When deploying to the cloud, the user does not need to think of redundant backups, security or maintenance of the infrastructure. This cuts up a lot of time and capital.

Integration – Cloud solutions are more easier to integrate with other platforms since many popular platforms provide cloud integrations by default.

Scalability – In the cloud, scaling from is a lot easier and almost instant compared to on-premises approach where it can take weeks and months to scale existing operations.

Further Advancement

Though Cloud Computing has been a revolutionary concept changing concept of computation for industries, it’s now going through a shift on its own where many companies over relying on cloud services have been changing their approach going for hybrid cloud and multi cloud models and some even considering on-prem due to challenges like vendor lock-in or centralized dependency on a single provider.

Other than the challenges, advancements are being made into serverless architectures to encourage developers into focusing more on the application itself. Containerization is also catching up in the cloud for faster deployment without manually managing dependencies and required libraries. 

Internet of Things (IoT)

IoT devices are devices that combine internet connected computers with sensors that can detect physical change, convert that to digital data and communicate that over the internet. These devices can be integrated into ordinary devices to make them “smart”. Slap an IoT device onto an ordinary TV and you now have a Smart TV, Throw it into a refrigerator and you have a Smart Refrigerator that tells you when you’re running out of milk or into an AC that is “smart” and automatically adjusts the temperature.

IoT devices work by collecting data through sensors, communicating it over the internet so it could be accessed by the end user through a common interface like a smartphone application or a web portal. IoT devices improve upon additional devices by building upon their functionality adding a sense of automation on something as static as a door lock.

Impact

Though numbers say the IoT market is trillions of dollars with billions of IoT devices reportedly out there, a large minority of the average public have mixed feelings about them. Among individual users there have been a lot of concerns about privacy and data sharing since most of the IoT devices lack even basic security features due to their low processing powers. Due to these concerns people have been asking for on-device processing. 

Challenges

Privacy & Security – Among the biggest public concerns in IoT devices are security and privacy of individuals which haven’t been priorities for IoT manufacturers.

Interoperability – Due to lack of standard protocols, IoT devices generally don’t operate or sync between other IoT devices which is a challenge.

Cost – Smart home devices generally cost more which is also one of the reasons it hasn’t caught up with the widest user segment.

Further Advancement

IoT devices are also going through a radical shift due to increased emphasis on user privacy by a large public. Newer ways are being developed to make these devices more secure and less vulnerable than they are right now. Other than the security side of things, Giant corporations like Google, Amazon, Apple are now investing into standardized communication protocols for IoT devices such as Matter which could address the Interoperability problem that exists right now. 

Matter is an open, unified communication standard being developed to address one of the biggest challenges faced by the IoT sector – Interoperability. It’s built with openness, privacy and security in mind with the aim of making more and more IoT devices compatible with each other. Matter certified devices favor local data processing in return providing better privacy along with the requirement of working without an internet connection. It may take some time before we see Matter in action since it is relatively new (It was released in 2022). 

Autonomous Driving

Autonomous Driving also known as Self-Driving is a technology and a concept that refers to computer assisted technology that enables cars to drive automatically with little or no human interaction. Autonomous vehicles are equipped with various sensors that collect data about the environment, that data is sent to the in-house computer to be processed and analyzed through advanced algorithms and machine learning models to predict movements and determine the safest path. Those predictions are sent to the vehicle’s control systems to perform the necessary action on the road.

Autonomous Driving is a reality and a concept at the same time because Autonomous Driving has multiple levels. The cars we drive presently have been able to achieve Level 2 with big names like Tesla able to reach Level 2 at the most. Let’s discuss the different levels to self driving:

• Level 0 (No Automation) – Driver is responsible for all driving and related tasks.
• Level 1 (Driver Assistance) – Driver is assisted with either steering, acceleration/deceleration but not both at one time. Examples include: Adaptive Cruise Control, Lane Assist.
• Level 2 (Partial Automation – Vehicle can control steering and acceleration/deceleration but the driver must remain engaged and monitor the environment and must have hands on the wheel at all times. Tesla Autopilot, GM Super Cruise are examples of L2 self-driving.
• Level 3 (Conditional Automation) – The vehicle can perform all driving tasks under conditions but the driver must be ready to take over when requested, This handover period can be several seconds. Audi’s Traffic Jam Pilot (limited to specific scenarios).
• Level 4 (High Automation) – Vehicle would perform all driving tasks but in specific conditions or environments (e.g urban areas, highways) without human intervention. Waymo self-driving cars are an example.
• Level 5 (Full Automation) – Vehicle would operate in all conditions and environments without any human intervention (no commercially available products).

Impact

Only after understanding the true meaning of the word Autonomous Driving could we begin to observe its impact. As for the general consumer, self-driving has certainly improved the way we drive cars. This is true especially for urban areas in large cities but the concept of fully autonomous cars is still a bit far fetched based on what we have right now. Carmakers have made bold claims before with industry pioneers such as Elon Musk claiming Tesla would have fully autonomous cars by 2018 which hasn’t been achieved yet since the latest Tesla cars require human intervention and oversight. 

Concerns

Public trust  – General public large right now are not trusting technology to completely automate the driving of their cards due to some accidents caused by existing self-driving systems.

Security – With the ever growing increase in cyberattacks with increasingly successful hacking attempts at Autonomous Driving systems, the thought of having their cars hacked remotely by bad actors is a dreadful one.

Regulatory concerns – Due to lesser public trust and security concerns in self-driving systems regulatory authorities have been hard on self-driving tech manufacturers. Lack of standardization is also a concern increasing regulators’ scrutiny.

Further Advancements

Elon Musk’s claims of developing fully autonomous cars by 2018 or his repeated talk of Level 5 autonomy or a fleet of a million robo-taxis by 2020 have yet to see the face of reality (He also claims Tesla will be selling their humanoid robots by 2026 ) but that doesn’t mean companies aren’t trying. Aside from the challenges, every large car manufacturer is trying to crack the next level of self-driving technology. With advancements in integrated computing, wireless technology and artificial intelligence, the goal is only going to be nearer. 

---

Web3, Blockchain & Crypto

Blockchain

In essence, Blockchain technology is basically a publicly distributed transparent ledger consisting of blocks that contain Cryptographically verified transactions related to a certain asset. That asset could be data about anything. Each transaction is a block and multiple blocks combines form a chain, that’s what makes up the word Blockchain.

A nasdaq article explains bitcoin technology through analogy of glass deposit boxes in a bank vault. A bank vault contains rows of deposit boxes. Each deposit box is made of glass, allowing people to easily view the contents of the box, although they do not have access to the box’s contents. An individual opening a deposit box will receive a key specific to that box. They do not own the box, although they now have access to the box’s contents. Similar to these glass boxes, a Blockchain contains content others can see and verify, but cannot change.

Cryptocurrency

Cryptocurrency is a form of digital/virtual currency based on Blockchain technology. Unlike traditional currencies like dollars, points or riyals issued by a government’s state bank (aka fiat currencies), Cryptocurrency is decentralized in nature and not controlled by a single institution or individual. Crypto is based on the Blockchain technology as explained earlier that uses Cryptography to verify the integrity of each transaction that is being made. 

NFTs

NFTs, or Non-Fungible Tokens, are unique digital assets that represent ownership or proof of authenticity of a specific item or piece of content, secured by Blockchain technology. Unlike Cryptocurrencies such as Bitcoin or Ethereum, which are fungible (each unit is identical and interchangeable), NFTs are one-of-a-kind and cannot be exchanged on a one-to-one basis.

Web3

Web3 is a new and still evolving concept that is meant to be the third evolution of the web as we know it today. To understand Web3 let’s revisit today’s Internet. Presently a good chunk of the World Wide Web is controlled by big tech like Google, Microsoft, Facebook and others. Many people when they refer to the Internet talk about these companies. Web3 is the response to authority, centralization of the internet.

It refers to a stage of the web where more and more web would be powered by decentralized technologies like dApps which are essentially apps that make use of Blockchain as their underlying technology. It is the idea of having Cryptocurrency and things like NFTs becoming more and more common which stand for Non-fungible token. Non-fungible means it is unique and can’t be replaced. NFTs use Blockchain to create a digital identifier to verify the owner of some asset like art pieces.

Impact of Crypto, NFTs and Web3

The impact of Crypto, Blockchain, NFTs, and Web3 on the average large user base has been a mix of disruption, progression, and fad elements. These technologies have introduced groundbreaking innovations and new opportunities but have also faced challenges related to hype, regulation, and practical implementation. Their future will depend on continued development, broader adoption, and the ability to deliver on their transformative promises.

Concerns

Regulatory issues – Due to their volatile nature with a higher risk of complexity for the average public, Blockchain tech especially Crypto has faced regulatory issues worldwide.

Complexity – The implementation of Blockchain tech like Crypto and NFTs have been complex to understand for a large amount of public.

Environmental impact – Mining blocks of Cryptocurrency requires a large amount of computer processing and power that has raised environmental concerns too.

Generative AI

Artificial Intelligence is human’s effort to simulate human intelligence and problem-solving capabilities using computers. Generative AI is a class of AI techniques designed to generate data similar to a given dataset. AI models using this technique are trained on a large set of data. Making use of high performance parallel compute mostly provided by GPUs  (Graphics Processing Units), such models can generate text, images, audio and even videos. We’ll discuss two of the most popular models in Generative AI:

Transformer Models

Let’s first understand what a neural network is. A neural network is a machine learning program, or model, that makes decisions based in a manner similar to the human brain. Transformer model is a neural network that learns context and meaning by tracking and understanding relationships in sequential data like the words in a sentence. It basically tries to make sense of data in a sequential order and tries to use advanced mathematics techniques like self attention to detect how distant data elements in a dataset depend upon each other to predict what it should generate based on that data.

Transformer models were first described in a paper from Google and are one of the most powerful classes of models invented to date with applications in drug design, near real-time text and speech translation, drug design, online fraud detection, search engines to name a few. Popular chatbots like ChatGPT and Gemini also make use of the transformer model. 

Diffusion Models

Diffusion models are a class of probabilistic generative models that learn to generate data by reversing a diffusion process. The diffusion process typically involves adding noise to data in a controlled manner until it becomes indistinguishable from pure noise. The generative process then attempts to reverse this noise addition step by step, transforming the noise back into the original data distribution.

Key Components:

1. Forward Process: This process progressively adds Gaussian noise to the data over several steps, gradually converting the data into a simple distribution, typically a Gaussian distribution.
2. Reverse Process: This is the generative process that learns to reverse the noise addition. Starting from a noisy version of the data, the model generates samples by iterative denoising until it reconstructs the original data distribution.

Using the forward and reverse processes mentioned above, Diffusion models can be used to generate high resolution images and even videos too. OpenAI’s DALLe and Sora make use of Diffusion models.

Impact

Transformers, GPT, diffusers, and tools like DALL-E and MidJourney represent significant advancements in AI and machine learning. They offer capabilities in language processing and image generation, impacting various industries and everyday users. However, their success will depend on overcoming technical and market adoption challenges. Though generative AI models have been disruptive in nature they have yet to impact the general public on a level as large as some of the tech we covered earlier.

How big tech thwarts disruption

A Stanford paper titled “Cooping Disruption”  claims that four tech companies dominate the American economy and have been trying to stifle competition especially in the AI, VR and automated driving industry. These companies are: Alphabet (who owns Google), Apple, Meta and Microsoft. Each of these companies commercialized a disruptive technology but in the last two decades no company has been able to commercialize technology that threatens these tech giants. The reason is that executives at these companies don’t want competition, They want to be the monopoly and for that they have created a four step approach of clearing out any disruptive innovation that competes with them:

• Find & Fund them out – The first step is identifying the potential companies that are working on disruptive technology, learning everything about them.
• Limit them – The next step is to do everything to  steer them away from competing with you by first limiting their access so they could not access the critical resources they would need to transform their innovation into a disruptive product and by partnering or investing in them. Big tech has established relationships with financial VCs that are tasked to gain positions of influence in their competition by strategically investing in them. 
• Call upon regulators – After trying to limit them, big tech would tell your government relations team to seek regulation that would build a competitive moat around your position and keep disruption out.
• Offer Acquisition – If one of the companies you were tracking nevertheless did start to develop a disruptive product, you would want to extract that innovation—and choke off the potential competition—in an acquisition.

Bringing Everything Together

We covered a handful of technologies discussing some of the influential tech in the last decades discussing their impact on the public at large, reasons for impact be it large or mixed, major challenges they faced and their future.

Disruption takes off with the Internet, discussing how it impacted the world and society at large and what reasons made it the Disruptive tech that had been unprecedented.

Moving over to smartphones we discuss the rise of integrated mobile computing and why it caused such a disruption in human lives and work directly impacting how we live our lives at individual level, conduct communication and share knowledge with those on the other side of the globe.

5G has great potential such as insanely high bandwidth and lower latencies that have a lot of applications coupled with challenges like increased cost and complexity. 

We also had a look over IoT devices, why they haven’t been as widespread and some of us had wanted, the present issues facing IoT devices like privacy and security along with their future potential if some things go in the right direction.

Cloud has taken off and has been a disruptive tech with almost every big corporation using it with a combination of hybrid solutions but challenges like vendor lock-in have led many to go on-prem or even adopt hybrid approaches for their specific needs. Going further, we’ve also discussed the future trajectory of cloud in containerization and serverless architecture.

We’ve also taken some time to discuss Elon Musk’s unreal claims of achieving Level 5 self-driving autonomy by 2020 or having deployed a fleet of million robo-taxis by that year. Off-course, we’ve first explained what these levels mean for the average user and where we currently stand in terms of progress on Autonomous Driving and what we can expect in the future.

Whether there would be a Web3 or not we have covered what we know and understand about it, starting from the underlying technology – Blockchain that powers all that is to Web3 to Crypto and NFTs too.

And lastly, like every other person in the tech world, we can’t forget AI so for our viewers we have tried to explain what it is, the most popular techniques – Transformers and Diffusion and their applications like ChatGPT and Dall-E.

Further learning and references

How the Internet of Things will explode in 5-10 years
IoT Devices – ARM
What Are Self-Driving Cars? The Technology Explained
The path to Autonomous Driving 
Understanding Blockchain Technology
Web3 and NFTs Explained
NFTs, explained
Blockchain, explained
What Is a Transformer Model?
How Big Tech Coopts Disruption–and What to Do About It
Coopting Disruption – Stanford

---

---

Everything you see here – and more is powered by you. Be part of the move.