AMPLYFI, global business intelligence and research firm, has applied its leading AI-based technology, DataVoyant, to identify and statistically quantify mega technology trends out to 2050 across a range of industries and sectors. In finding, harvesting, and reading over 1,000,000 open-source documents, such as academic papers, patents, journals, news items and government white papers, located on both the Surface and the Deep Web, the machine-driven analysis projects likely future trends and timescales to next expected peaks in technologies’ maturities.
Of the 2,639 broad themes identified, the top mega tech trends and where they are likely to really start impacting our everyday lives are readily identified. Top technologies to watch out for in 2019 are, unsurprisingly, artificial intelligence, the IoT, and distributed ledger technologies. Looking beyond this, the realms of energy, mobility, medicine, and our domestic lives appear strong candidates for technology-led disruption on multiple fronts.
Projected Mega Tech Trends
| 2019 | Next 5 Years | 5 to 10 Years | Beyond 10 Years |
| AI data collection and analysis | Graphene-based TVs | Solid State Batteries | Implantable Biofuel Cells |
| 3D Printers in Manufacturing | Energy Harvesting Wearable Technologies | High Temperature Super Conductors | Fully Autonomous Cars |
| Growth in Connected Devices | Robotic Process Automation | AI-driven Medical Diagnosis | Smart Cities |
| Distributed Ledger Technologies to Improve Digital Security | Universal Personalised Digital Assistants | Bio-printed Organ Transplants | Cybernetic Technologies |
| Voice-first Machine Interaction | Remote Patient Monitoring | Personalised Medicine | QuantumComputing |
The process of generating the projections required DataVoyant’s proprietary AI algorithms to first identify key technologies and quantify their relevance based on a number of factors, including frequency, inter-connectivity to related topics, and importance within each document that they feature in. Extracting date stamps from websites and from within documents, the machine then automatically generated historic trends for each technology. From here, deep learning algorithms enabled the machine to learn the ‘historic context’ i.e. the changing interconnectedness and dependencies across hundreds of thousands of variables to create a basis to project forward into the future.
Chris Ganje, CEO and co-founder of AMPLYFI comments, “The power of AI to capture, analyse, and make sense of huge datasets is enabling levels of insight that were previously impossible under traditional business intelligence and research techniques. Our analysis of mega tech trends is just one example of where AI can either affirm or challenge the opinions and perceived wisdom of a minority of often highly influential commentators. The richness and detail lying behind the results allow us to spot early-stage convergence between innovative technologies and business models, as well as track the development of enabling technologies that will ultimately underpin future phenomena such as smart cities. Crucially, the machine is able to simultaneously monitor all of this globally, continuously tracking whether context changes sufficiently to materially alter its projections.”
“Where the deployment or commercial application of technologies is likely to be hampered by regulatory hurdles or public opinion, such as home deliveries by drones or selective human gene editing, AMPLYFI’s DataVoyant technology enables us to monitor developments in these fields globally too. Conversely, it enables us to monitor where regulation is evolving to select and incentivise specific technologies.”
“In a world where there are more questions than answers, we believe it is better to base business decisions from a position of informed knowledge than from mere opinion. AMPLYFI’s business intelligence platforms, driven by AI and machine learning technology, enable our clients to unlock the entire internet for themselves, both the Surface and Deep Web, in order to generate insights that their competitors are not seeing and to provide quantifiable windows into the future.”
