Hits And Misses of 2021

There is always this surge of expectation when there is something new on the horizon. You anticipate it, wait patiently, imagine the possibilities of what it can do.

This year agility has risen to be the core of businesses: AI was injected in the cloud, hybrid working became a norm, and everyone talked about NFTs. At the same time, not all technology trends lived up to the hype generated. Take, for example, hyper automation. We look at those that have gained importance and a few tech gems that were promised, but not delivered.

Here’s our 2021 list of hits and misses.


NFTs Are Worth Millions

In 2021, NFT, or non-fungible token, was suddenly everywhere. Be it Twitter CEO Jack Dorsey auctioning his first tweet, or the Kings of Leon selling their latest album.

NFTs are now the digital answer to collectables. It has been around for years, but used only by a small tech-savvy minority. This year, however, these digital collectibles captured the attention of the public and gained traction with creators, who see them as an innovative way to monetise their works. In June, transaction volume across NFT marketplaces stood at $500 million, compared to just $200 million for the entirety of 2020.

Here are some notable million-dollar sales this year: An animated Gif of Nyan Cat was sold for more than $500,000. Musician Grimes sold some of her digital art for more than $6 million. It is not just art that is tokenised and sold. Twitter’s founder Jack Dorsey promoted an NFT of the first-ever tweet, with bids hitting $2.5 million. Christie’s sale of an NFT by digital artist Beeple for $69 million set a new record for digital art. French firm Sorare, which sells football trading cards in NFTs, has raised $680 million.

NFTs, for sure, have tapped into a primal desire for ownership that could see them become a permanent fixture. Or maybe it’s just a craze, but they’re certainly worth keeping an eye on.

Crushing The Code

This year, “low-code” and “no-code” were circulating in discussions, and empowered business specialists with out-of-the-box solutions-building capabilities. The trend is gathering steam, and quantifiably so. One estimate predicts a CAGR of 28 per cent between now and 2026 for the worldwide low-code development platform (LCDP) market. It brought a significant shift in app development for businesses across industries, making app and software development more accessible for small businesses and organisations without the budget to hire engineers and developers.

While no-code platforms are exactly what they sound like — meaning you can know nothing about how to code and still create an app — low-code platforms require some coding, but not as much as traditional platforms.

This made app development faster. For organisations that want quick solutions or for those who want to develop an app for testing, like a video streaming app, no-code and low-code platforms are a viable way forward. Microsoft has created a whole new programming language for low-code, named Power Fx, which is available under an open-source licence and put up on GitHub for everyone to use and contribute.

Cloud Betting High On AI

In 2021, businesses optimised cloud technology for scalability and security while infusing digitalisation to the IT assets. Cloud empowered organisations to re-envision business intelligence and analytics platforms, while big cloud service providers injected artificial intelligence (AI)-driven tools in their cloud offering, taking agility a notch higher.

Google, which is betting big on AI to help take its cloud computing business to the next level, launched an AI-driven tool. Named Visual Inspection AI, the new solution allows businesses in the manufacturing sector to maximise operational savings by quickly training and deploying AI models to detect production defects.

Amazon came up with a similar offering in the form of Amazon Lookout for Vision that helps businesses inspect manufacturing defects using computer vision and AI. Both Google and Amazon systems can be trained with a handful of images and can be run at the edge and rolled out as-a-service to help businesses further reduce deployment costs.

Meanwhile, Microsoft has given businesses access to OpenAI’s powerful AI language model GPT-3, through Microsoft Azure. The potential enterprise uses for GPT-3 range from email composition to text summary, website design, software code generation to generating new content for blog posts. Users can also teach the models to meet specific business needs using their own data — they just need to show the models a few examples of the kinds of outputs or responses or code they want it to generate.

Present And Future Of Work

Remote and hybrid work can increase productivity and lower costs. Employees want to continue to do it, with companies saying they plan to continue hybrid models as they have noticed employees are more productive working from home and reduced operating costs. Now, to promote equality among hybrid teams, companies are thinking “remote-first” when establishing business norms and interactions among employees.

A Gartner survey indicated that in the longer term, 82 per cent of businesses would let staff work remotely. Meanwhile, not surprisingly, video and team collaboration tools remained an enterprise priority, collaboration tools of all stripes proved important. Data from analyst firm IDC indicates that around half of businesses globally (48 per cent) increased spending on collaboration software in 2021.

The Rise Of XaaS

Businesses across the globe adopted Everything as a Service (Xaas) method for delivering just about, well, everything — your 600 video streaming apps, your cloud storage, certainly, but also your to-do list app. XaaS has been a hit, and it’s only going to continue. More things you once bought as a one-time payment are now offered instead as a recurring payment or subscription.

Perhaps one of the biggest features of Xaas is that you can use cloud services and do not actually have to buy a product outright. The internet of things is another cornerstone of many businesses that need to function online, and XaaS is a major contributing factor to how well this works, too.

Expect new sorts of service-focused offerings, too, especially tied to your hardware purchases more. Rolls-Royce is seeking to provide its customers with a jet engine rental service that helps “customers to maximise the flying potential of their engines.” Through its TotalCare program, Rolls-Royce offers customers a way to off-load the burden of engine maintenance while “reducing waste, increasing efficiency, and enhancing the robustness of our supply chain.”


FLoC In To Nothing

Leading the charge to replace third-party cookies with a new suite of technologies to target ads on the Web, Google’s Federated Learning of Cohorts (FLoC) is perhaps not what it says it is. Well, privacy advocates aren’t buying into Google’s rhetoric.

Meant to be a new way to make your browser do the profiling that third-party trackers used to do themselves, Google FLoC will boil down a user’s recent browsing activity into a behavioural label, and then share it with websites and advertisers.

Instead of tracking individual users, Google argues that by grouping users based on their interests and demographics, derived from their browsing history, FLoC will help deliver advertisements without using privacy-invading third-party cookies.

Although the technology will avoid the privacy risks of third-party cookies, but may, according to experts, also exacerbate many of the worst non-privacy problems with behavioural ads, including discrimination and predatory targeting.

Google’s pitch for FLoC is based on the premise that we have to choose between “old tracking” and “new tracking.” Instead of re-inventing the tracking wheel, experts say, we need a solution for a world without the myriad problems of targeted ads.

Meanwhile, every major browser, including Microsoft Edge, that uses the open source Chromium project has declined to use FLoC, and Chrome Canary, Google’s web browser that is mainly targeted at developers, seasoned techies, and browser enthusiasts, has added an option to disable the controversial FLoC feature.

No Show Rides

Apple promised the much-hyped autonomous car, but that never arrived. Earlier this year, Hyundai and its subsidiary Kia said they are no longer in negotiations with Apple to manufacture the Apple Car. Some reports also say that Apple is in discussions with at least six Japanese automakers over possible production and supply partnerships for the Apple Car. But nothing has been finalised yet.

It would follow, then, that all those mutterings about the Apple Car being released now seem misplaced. In an interview with The New York Times, Cook was reluctant to share details surrounding Apple’s plans for autonomous cars. Given the relative silence surrounding the project until now, it looks the Apple Car is unlikely to make it to the mass market before 2025.

Meanwhile, we’ve been thinking about the Tesla Cybertruck, the wild electric truck, which CEO Elon Musk revealed back in 2019. What do we actually know about it two years later? Nothing. We expect to be waiting a long while to see it on the road.

Where’s The Next Text-Generator?

Have OpenAI given up on GPT-4? Or are they working on it in silence? We hope it’s the latter. OpenAI has been releasing GPT models yearly since it presented GPT-1 in 2018. In 2019 it launched GPT-2 in, and GPT-3 in 2020, which is shockingly good, creating human-like text on demand. Following this pattern, we expected a GPT-4 this year.

Ilya Sutskever, the Chief Scientist at OpenAI wrote that in 2021, “language models will start to become aware of the visual world”. The next generation of models, Sutskever said, will be capable of “editing and generating images in response to text input, and hopefully they’ll understand text better because of the many images they’ve seen”.

But that didn’t happen. Exactly what’s going on inside GPT-4 isn’t clear. Much hype was built around it, with a report saying that the new language generator could have 100 trillion parameters and will be “five hundred times” larger than GPT-3. The sheer size of such a neural network could entail qualitative leaps from GPT-3. Maybe in 2022, we might see the first neural network capable of true reasoning and understanding.

The Truth Of The Matter

The new Matter smart home standard being supported by Google, Apple, Amazon, Zigbee and others, was supposed to be released in 2021. But it didn’t. Another promise, another no show.

According to a blog from Tobin Richardson, president and CEO of the Connectivity Standards Alliance (formerly the ZigBee Alliance), who is a member of the Matter Standards Working Group, the new standard development is proceeding as planned but requires more support, testing and refining.

It’s in the works since 2019. Formerly known as Project CHIP, later rebranded as Matter, it is a joint effort by over 170 companies. The Matter smart home standard claims to be an industry-unifying standard that will provide reliable, secure connectivity and offer consumers a seal of approval that devices will work seamlessly together.

Hyper automation Wasn’t Worth Its Hype

Gartner’s number one tech trend for 2021 was hyper automation, claiming that organisations will be able to lower operational costs by 30 per cent by combining hyper automation technologies with redesigned operational processes. But was it really worth the hype?

In theory, this technology can be transformative, but enterprises aren’t yet ready to implement it. For hyper automation to work, all the other automation tools must be up and running. The challenges of rolling out RPA have been well documented — in a recent Pega survey of enterprises adopting RPA, 50 per cent of respondents reported that RPA was harder to deploy than initially expected.

Business leaders are not yet aware of the possibilities of automation — hyper or not — and it isn’t part of their transformation efforts yet. While many enterprises enthusiastically implement automation, they don’t think through what and where the value of automation truly lies. As a result, these projects have the potential to fail altogether.

Also, not many vendors have all the components needed to create an end-to-end automation platform, especially one that can be put into production quickly.

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