AI - Artificial Intelligence (AI) describes computers/machines/devices that mimic cognitive functions that humans associate with the human mind. AI is characterized as a system capability to effectively ingest new data, to link various data sources, to correlate data elements, to learn from the relevant data, and to use these learnings to achieve specific objectives by performing tasks through flexible adaptation in a supervised or unsupervised mode. The maturing of Big Data engineering, integration, transformation, and composition techniques enable AI to become industrialized. Automated AI is growing strong, helping accelerate, scale, and democratize AI more widely in the industry. AI as a service is moving fast with more innovation applications created in different sectors.
Multicloud - The public cloud space has become a 3-horse race: AWS, Azure, and GCP. Google made big moves in 2019, in an attempt to rise to No.2 or overtake No.1. Microsoft also grew significantly in catching up with the market leader Amazon. An enterprise should choose to take the multicloud approach, rather than using a solitary cloud vendor. This will provide the best of breed features, location flexibility in compliance with local regulations, redundancy insurance against outage, on-demand scalability for peak hits, increased agility with no vendor lock-in, risk reduction, real-time cloud arbitrage, dynamic workload management, and pricing advantages. Companies need to plan ahead to carefully deal with interoperability, complexity, security, packaging, integration, testing, governance, standards, and overheads in the deployment to multiple clouds.
Autonomics - Robotic process automation (RPA) is a form of business process automation technology based on metaphorical software robots (bots). An RPA system observe the user performing the tasks in the graphical user interface (GUI) of an application to develop the action list and sequence, and then automate the execution by repeating those tasks directly in the GUI. RPA reentered the spotlight recently, shifting from a point solution previously to comprehensive offerings. Unassisted RPA is emerging, which mobilizes businesses to leverage RPA without investing a big effort of development work. The combination of RPA with other disciplines such as machine learning and process mining provides hyperautomation to augment end users and enhance processes in the ways that have much more significant impacts than traditional automation capabilities.
Blockchain - A blockchain is an open distributed ledger with transaction records linked via cryptography. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data. A blockchain is typically managed by a peer-to-peer network collectively adhering to a protocol for inter-node communication and validating new blocks. Hybrid blockchains are growing to combine the centralized and decentralized features. Federated blockchains are on the rise. Blockchain platforms like Ethereum and Hyperledger will continue to evolve to be more mature. Interoperability across different blockchain networks will be the focus to boost the adoption and usage.
IoT - Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people with unique identifiers (UIDs). IoT provides the capability to transfer data over a network in machine-to-machine interactions. Smart devices are becoming more commonplace. IoT metadata are crucial to business. Sensing and tracking become more context-aware and relevant, without violating the privacy regulations and preferences. IoT-driven personalization and customization will go to another level. Home devices/appliances and personal wearables will be more connected and orchestrated with voice-based interactions in conversations. Sensing as a Service (SEaaS) is gaining momentum.
Edge computing - Edge computing is a part of a distributed computing topology to process information at a location close to the edge. It brings computation and data storage closer to the devices where data is captured, rather than relying on a remote central place. It provides the capability to process and store time-sensitive data faster at a lower cost, enabling more effective processing of critical applications with minimum latency in real time. Edge computing is not limited to just local processing, as a hybrid of local and cloud processing can optimize the workload management and provisioning on the fly. Data streaming is a necessity on the edge. 5G will help accelerate the growth of Edge computing.
The outlook of future technologies is more promising than ever. The best is yet to come in the new decade.
For more information, please contact Tony Shan (blog@tonyshan.com) or leave your comments below.
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