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AI
The holy grail of AI research is general AI, a machine that is aware and has intelligence equal to human intelligence. Such a theoretical system would be our intelligence level. Well, until v2. 0 drops, and we fall a distant second.
Until then, we have a narrow AI, a system that performs very specific tasks. It may seem too strict, but narrow AI already supports systems like spam filters, Google maps and virtual assistants like Siri. And its use cases are expected to be much more diverse.
“What we’re seeing right now is that machine intelligence is expanding a little bit from the narrow tops and getting a little bit broader,” Max Tegmark, a physicist and machine learning researcher, told Big Thinktank.”
There are chatbots, logistics, autonomous vehicles, virtual nurse assistants, personalized learning materials and teachers, and even artificial creativity. These are just some of the applications that narrow AI could improve or unlock in the coming years.
5G and the Internet of Things
5G may not seem very interesting. We already have 4G, what’s another G? But the difference will be exponential. 5G networks could end up being 100 times faster than 4G. This allows more devices to be connected, significantly reduces latency to zero and provides a more reliable signal.
This wireless technology will play a key role in the Internet of Things (IoT), extending the capabilities of the Internet beyond computers to a wide range of things, processes and environments. The Internet of Things is a key technology for futuristic scenes such as smart cities, robot-controlled agriculture, and autonomous highway systems.
For businesses, this one-two combination will continue the recent trend and take it one step further. Remote offices will be more secure under the 5G paradigm, and the sharing of real-time event or desktop capture data will be seamless. For the Internet of Things, this helps eliminate the intermediate steps that reduce productivity. You can collect, process and send data from the factory floor, so why would anyone waste time collecting data from the factory floor?
Serverless computing
Serverless computing is not really “serverless.” Some serious dark arts have touched mountains; it’s impossible to provide computing resources without a physical server somewhere. Instead, this technology allocates those resources more efficiently. If an application is not in use, no resources are allocated. When needed, processing power is automatically expanded.
These technological changes mean that companies no longer have to worry about infrastructure or bandwidth reservation, which promises ease of use and cost savings.
Eric Knorr, editor-in-chief of International Data Group Enterprise, writes, “One of the benefits of this architecture is that it only charges the cloud provider when the service is running. You don’t have to pay for idle capacity; you don’t have to think about capacity. By default, the runtime environment waits in event standby, and so the corresponding function switches to the runtime environment and executes. This allows you to create large and complex applications at no cost until they are running.”
Biometrics
A biometric system allows us to recognize a user by biological markers such as a face, voice or fingerprint. Many people already have one or more laptops and smartphones, but as technology improves and becomes more widespread, it may finally end the password paradigm.
Because most people have inefficient passwords, use the same passwords for all accounts and never change them, it usually only takes one hit for hackers to gain access to all of a person’s personal and professional data. Even those who use their passwords correctly may find that managing their systems is a nightmare.
For this reason, biometrics promises much-needed security for important data. Fingerprints are much harder to crack with raw arithmetic than passwords, and the difficulty increases because of the size of multiple tokens at once.
Augmented/Virtual Reality.
With lower hardware costs, more computing power and the emergence of big names like Google and Facebook, the day of virtual reality may have finally arrived. And the wider adoption of augmented reality apps on smartphones may make it easier to sell such technology in the future.
The recently announced Microsoft Mesh and its competitors hope to take advantage of our new era of remote working. The concept combines these “mixed reality” technologies to create a virtual shared space that business teams can use to conduct meetings or complete projects.
Peter Diamandis, chairman and CEO of the XPRIZE Foundation, believes the technology could revolutionize the consumer experience in retail. For example, customers could change into virtual avatars or sit in an amphitheater before making a purchase.
Blockchain
It may seem surprising that Bitcoin, a popular cryptocurrency, is missing from the list. But the online registry of its technology, blockchain, has replaced digital denomination as the rising business star.
Unlike traditional centralized records, blockchain is decentralized. Permanent records are not stored in one place, but they exist on nodes spanning the entire system. This design makes it difficult for records to be lost or manipulated.
“[Blockchain] systems are effectively resistant to evidence of censorship or confiscation,” tech entrepreneur Elad Gil told Big Thinktank. This means that if you’re in a country with very bad governance, or some third party can’t suddenly or accidentally erase your data, or can’t hack a third party to access your data (although, obviously, you can still hack your blockchain).
That’s why blockchain is attracting the attention of organizations (i.e., all organizations) that need to keep records. And the potential uses are impressive. Blockchain could be used by hospitals to store and share medical records. It could be the basis of a secure online voting platform. It could track logistics throughout the international supply chain. And, of course, there are also many cybersecurity applications.
Robotics
The first industrial robots were born in 1962. Since then, technological advances have steadily expanded the representation of the robotics workforce, and over the next few years, robots will continue to move from the factory to First Street to perform basic tasks such as cleaning and delivery.
These developments have supported the Luddite fires for more than a century, so one of the challenges for organizational leaders will be to convince their teams that robots are not here to replace them. In fact, as more people move to soft skills and human-centered occupations, they will find this change helpful.
“Introducing robots into the workplace can be challenging and dynamic. Employees may start with the feeling that their jobs are at risk, but the end result is a warehouse full of happier, healthier people that remains the central axis of a competitive business.” Here’s what Melonie Wise, CEO of Fetch Robotics, writes at the World Economic Forum.
Natural Language Processing
Natural language processing is a field of artificial intelligence that aims to develop systems that can analyze and communicate using human language. Does that sound simple? If it is, it is only because you are reading these words with a mind evolutionarily endowed with the talent for language.
Algorithms are not so lucky. They struggle to analyze the eclectic array of symbols, gestures, sounds and cultural cues we use to express meanings and ideas.
“There is a clear problem with applying deep learning to language learning. Words are arbitrary symbols, and so they are fundamentally different from images. For example, two words can contain completely different symbols and at the same time have similar meanings. And the same word can mean very different things in different contexts,” writes Will Knight of MIT Technology Review.
When the algorithm finally does crack the language, the business use case will be significant. Think chatbots, virtual editors, market analysis, real-time instant conversation translation, resume readers, and automated phone recorders, and don’t interrupt all your calls.
Quantum computing.
Quantum computing is “using the collective properties of quantum states, such as superposition and entanglement, to perform operations.” Translation: Solve problems faster and more accurately. In some cases, this may interfere with the latest supercomputers.
We should not expect quantum computers anytime soon, but we can expect quantum computers to be the basis of the new technologies listed above. Such machines already exist today, and IBM has announced plans to create a 1,000-cubit version by 2023, says pioneering physicist Jay Gambetta, whose science reflects an “inflection point.”
The technology makes it easier to manage big data. Fast modeling reduces costly and complicated development time and simplifies multidimensional optimization problems. Finally, it can help you deal with problems that are currently difficult to deal with, such as the problems you encounter with natural language processing.
Quantum computing also shows why it is important for organizational leaders not to develop tunnel vision. Focusing on new technologies or future models jeopardizes the well-being of the company. The question is not which technology will dominate, but how each technology will work together with the potential it will bring.
Mike Haynes, chairman of the Emerging Technology Community Council Mike Haynes said: “Especially, as I said earlier, the simultaneous use of these technologies will lead to tremendous innovation over the next few years, and the customer decisions that affect these technologies will actually affect a paradigm shift.” I said: “Oh my goodness.” Said the TIA Biz Tech Podcast.
Navigating these technological changes will undoubtedly be challenging for business leaders in the coming years. But by keeping the possibilities open, you can anticipate the risks and take advantage of these new technologies.
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