In 2020, I wrote an article titled: The Next Big Thing” in Technology: 20 inventions that will change the world”. An update is necessary, highlighting the key technologies emerging today that will be all the rage by 2030 (or 2028… or 2032…).
Table of Contents:What’s Next for Conversational AI?
- Commercial nuclear fusion power
- Robot knowledge sharing
- DAOs
- Digital Twin of a customer
- 6G
- 4D printing
- Generative design AI
- High-temperature superconductivity
- Predicting the next big thing in technology
1. Commercial nuclear fusion power
Nuclear fusion, in its most common form, is the process of energy being released when bits (“atomic nuclei”, if you’re fancy) of hydrogen are exposed to extreme heat and combined. This process releases massive amounts of energy, which humanity is increasingly hungry for. That’s how the sun works too, by the way.
The importance of nuclear fusion lies in earth’s near-unlimited hydrogen supply, which can be extracted from water, and the fact that its only by-product is harmless helium. Fusion reactors are also safer than fission reactors, as they do not create any long-lived radioactive nuclear waste. If implemented, commercial nuclear fusion power would provide cheap utility-scale energy with very little environmental impact and improve energy availability and security.
Several countries have heavily invested in fusion research, and private companies are also conducting their own trials. The ITER reactor, which is under construction in France and due to begin operation in 2026, is the first reactor that should produce energy-positive fusion; but dozens of others are being built.
However, fusion research is slow and capital-intensive. The technology’s biggest issue is that rectors currently need to create temperatures hotter than those found on the sun to start the fusion reaction. Doing so requires more energy than what the reaction produces. Despite recent advances, commercial operation of fusion power is still uncertain and likely more than a decade away.
You can read more on commercial nuclear fusion power at the International Atomic Energy Agency.
2. Robot knowledge sharing
Whether they are in factories, in warehouses, at home, or on the street, robots are impressive… yet profoundly stupid. They work well in highly controlled environments, but every new situation stumps and/or breaks them, which tends to be very expensive. “Robot knowledge sharing” technology changes that. Researchers pushing the concept forward aim to create a standardised way for robots to share information with each other.
That information would be gathered through trial and error (aka reinforcement learning), which we know to be an efficient way for AIs to learn. It could take many forms, from the simple knowledge that an obstacle has appeared on a road, to the ability to grab a complex shape. Efficiency will go up exponentially, and costs will decrease at breakneck speed.
Once the genie is out of the bottle, we will not be able to put it back. But let’s hold the Terminator talks for 2040: hardware, sensors, ML processes, data configuration… much needs to be standardised before the concept works. All the big players will want their way to be the right way, and nothing may get done. At the end of the day, it may be humanity’s inability to agree on anything that saves it.
More on Robot Knowledge Sharing from the University of Southern California.
3. DAOs
Let me tell you about the future of work. You will work on something you love, without interviewing. You will work for numerous employers, all of which will pay you based on a contract you did not sign. You will compete for rewards with colleagues you don’t know, but you’ll see everything they do. You will get a say on the organization’s strategy, but so will all your customers. You’ll be remote, global, and always “on”. Sounds like a dream? You’re right. A nightmare? Right again. Welcome to the world of Decentralized Autonomous Organizations.
According to the technology’s (or is it a concept?) many fans, DAOs are how humans will soon come together as a group to make decisions in the digital world. They will do so with the help of two key tools. Firstly, the rules governing organisations will be expressed as a series of “IF/THEN” statements coded directly into a blockchain, rendering them both auditable and permanent. Secondly, voting shares will be issued to stakeholders in the form of “digital governance tokens” — also recorded on a blockchain. Doing things this way replaces, in theory, both the legal mumbo-jumbo of today’s organizations (as rules are coded) and their hierarchical nature (as every stakeholder has a voice).
Technically, all sorts of work structures can be created as Decentralized Autonomous Organizations. Investment companies, consulting companies, engineering companies, etc. But that’s just the theory; the reality is more complex… and more interesting.
Read more on Decentralized Autonomous Organizations The Pourquoi Pas.
4. Digital Twin of a customer
Have you ever wanted, like, the most boring crystal ball ever? Want no more: companies are building just that by using AI to create digital twins of customers. They will be able to predict the future… but only the part where you decide which brand of toilet paper you’ll buy. If that feels like a Balzac premise, trust your instincts.
With enough data and dynamic algorithms, it is now easy to create capitalistic digital replicas of specific persons or personas. This would be not only to understand and predict behaviors but how changes in purchasing environments will affect customer decisions based on what is known about them. As markets become tighter, and the cost of borrowing more expensive, companies must make sure they make the right choices about products, services, promotions, marketing campaigns… Being able to play with categories of customers as we once played The Sims will no doubt reduce the cost of failures and maximise stockholder profits. That’s the whole point, right?
This technology is already in progress and will no doubt work for personas/categories of customers. Things may be different for individuals, however. We may finally be wary enough of having our data harvested for manipulative purposes. Companies looking to create Digital Twins will need to establish trust in their process and use of the technology. And even then… how could they predict the unpredictable (2020, anyone)?
Read more on Customer Digital Twins at Absolute Data
5. 6G
Just 3 years ago, I was writing about 5G and the numerous industries it would transform: IoT, self-driving, entertainment… and we’re far from being done experimenting with it. And yet, it’s already time to look to the future of internet service: 6G. The good news for me is that 6G’s features are not yet fully agreed on. That way, we can hope for what it will be able to do and complain later when we’re inevitably disappointed. In this case, “later” may be a while away: though design and research has already begun, 6G commercialisation won’t be before 2030. This follows the telecom industry’s familiar pattern of adding a new generation every 10 years.
In the meantime, here’s what we do know: the technology will go above and beyond 5G with regards to providing higher peak data rate, lower latency, much more connection density, and energy efficiency. Whether the jump will be as significant as 4G to 5G was is still to be seen, though. Most experts agree that AI will be a key component of the technology, as will secrecy, security, and privacy.
What will be fully different from 5G is the government’s implication in its design: the Korean, Japanese, and American governments already intend to have a say in the future infrastructure of their country. Whether that’s a net positive for privacy is yet to be seen…
Read more about 6G Wikipedia
6. 4D printing
The name 4D printing can lead to confusion: I am not implying that humanity will be able to create and access another dimension. Put simply, a 4D-printed product is a 3D-printed object which can change properties when a specific stimulus is applied (submerged underwater, heated, shaken, not stirred…). The 4th Dimension is therefore Smart Materials.
The key challenge of this technology is obviously finding the relevant “smart material” for all types of uses (namely a hydrogel or a shape memory polymer for the time being). Some work is being done in this space, but we’re not close to being customer-ready, having yet to master reversible changes of certain materials.
The applications are still being discussed, but some very promising industries include healthcare (pills that activate only if the body reaches a certain temperature), fashion (clothes that become tighter in cold temperatures or shoes that improve grip under wet conditions), and homemaking (furniture that becomes rigid under a certain stimulus). Another cool use case is computational folding, wherein objects larger than printers can be printed as only one part.
Read more about 4D printing on Sculpteo
7. Generative design AI
Generative AI technology uses deep learning to generate creative assets such as videos, narratives, training data, designs, and schematics. While you may have played with (and enjoyed!) the likes of ChatGPT and Midjourney, they’re barely more than surface-level distractions.
Enterprise uses for generative AI are far more sophisticated. If used to its full extent, the technology can reduce product-development life cycle time, design drugs in months instead of years, compose entirely new materials, generate synthetic data, optimise part design, automate creativity… In fact, experts predict that by 2025, 30% of outbound marketing messages from large organisations will be synthetically generated, and by 2030, a major blockbuster film will be released with 90% of the film generated by AI.
The technology has very real use cases, that can be put in place today, and which will continue to be put in place with increasing success over the coming decade. That is if we can navigate the many risks associated with generative AI. I’m particularly worried about deepfakes, copyright issues, and malicious uses for fake news.
Read more about Generative Design AI on Gartner.
8. High-temperature superconductivity
High-temperature superconductivity (HTS) is the ability of certain ceramics to have zero or low electrical resistance at “high” temperatures compared to other superconductors. High here means above −196°C / −321°F. This means HT superconductors can be cooled with simple liquid nitrogen rather than require expensive and hard-to-handle coolants like liquid helium. they can also withstand much higher magnetic fields than Low-temperature superconductors.
There are a lot of applications for superconductive materials, but only one is truly transformative (while remaining utterly boring): HTS will improve the electric power sector and reduce its environmental impact by reducing technical losses and increasing energy efficiency. Down the line, there are discussions around its use within fusion reactors, but those conversations are too early to be definite.
In any case, HTS is still a relatively immature technology. Ceramic superconductors are becoming suitable for some practical use but are today more complex and costly than comparative conventional technology. As with everything else on this list… more research is needed!
Read more about HTS IBM.
Predicting the next big thing in technology
Technology tends to hold a dark mirror to society, reflecting both what’s great and evil about its makers. Today, more than ever, it’s important to remember that technology is often value-neutral; it’s what we decide to do with it day in and day out that defines whether we are dealing with the “next big thing”.
Good luck out there.
Source: by Adrien Book – https://www.wearedevelopers.com/magazine/technologys-next-big-thing – 06 02 23
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