April 3, 2017 | Written by: Whitney Magnuson
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Love them or loathe them, buzzwords are everywhere in IT. Technology changes, and suddenly, new buzzwords pop up in the IT lexicon.
But understanding the actual technology behind the buzzwords — and how it can bring value to your business and your clients — can help to keep you on the cutting edge of the connected economy. Here’s our list of 5 must-know buzzwords for the IT industry:
AI or artificial intelligence applies to giving devices, machines or even software intelligent behavior that simulate human thought processes, including the making of autonomous decisions and “learning” preferences and processes over time. The field of AI is really broad, but that means it has many facets – and many potential advantages for organizations. AI is now finding its way into consumer-driven applications including smartphone apps as well as household appliances and self-driving cars.
Machine and deep learning
Two common components of AI are machine learning and deep learning, which encompass a variety of algorithms and methodologies that enable software to be trained with data and policies. As the application gains experience with more input, the accuracy improves. For example, while it still can’t predict tomorrow’s stock prices because too much randomness exists in the market, banks are discovering that machine learning applications can detect types of fraud that rules-based solutions can miss.
Deep learning is applying these algorithms in a “neural network” that is modeled after what we know about the human brain. As one of the most promising ways of enabling cognitive enterprises, IBM has tapped into open source deep learning innovation with PowerAI, a simple, easy to install toolkit of the most popular deep learning distributions like Caffe, Torch, and Tensorflow.
Also under the AI umbrella is cognitive computing. Cognitive computing refers to systems that learn at scale, reason with purpose and interact with humans naturally. Rather than being explicitly programmed, they learn and reason from their interactions and experiences with their environment. Systems enabled with cognitive computing technology like IBM Watson allow companies to solve problems and respond to opportunities in entirely new ways through solutions that harness AI, machine learning, natural language processing and intelligent APIs. In the insurance field, for example, cognitive systems are helping underwriters assess the individual risk of each customer by factoring in things like the weather data from where they live. If your neighborhood is prone to tornados, cognitive systems could be the reason your rates are a little higher.
We’ve written about blockchain here in the past. Although bitcoin is the best-known example of blockchain technology to date, organizations of all kinds are discovering that they too can benefit from embedding distributed ledger technology in their own solutions.
To help advance cross-industry blockchain technologies for business, groups of companies including IBM got together to create the Hyperledger project, an enterprise-scale, open source blockchain platform that has comprehensive security options. Leaders in banking, finance, the Internet of Things, manufacturing, supply chains and technology have joined in this global collaboration. The goal is to encourage communities of software developers to build blockchain frameworks and platforms and develop what is expected to be a new generation of transactional apps based on the blockchain concept.
In many of today’s data centers, HPC or high-performance computing involves the use of parallel processing that spreads machine instructions across multiple processors so they can run advanced applications efficiently, reliably and quickly. Because HPC is unusually compute-intensive and is also relational and parallel, it can’t be achieved through the sequential transaction-centric computing characteristic of most data center servers.
In the enterprise, the best practices of HPC have been adapted into high-performance data analytics, or HPDA. By using the parallel processing and acceleration techniques pioneered in HPC, enterprises can gather insights from data in real time. Running programs within these environments like cluster virtualization software can even further optimize and accelerate HPC and HPDA workloads, simplifying deployments and system sharing and scaling of resources all while controlling costs. By providing the ability to combine traditional HPC, analytics and AI applications on the same compute resources and sharing the same data sets, IBM can deliver efficiency and results faster and with less overhead.
Walking the talk
Look beyond the buzz. You can start to evaluate leading-edge tech in the context of your business – how it will impact your customers, your competitive edge and your bottom line. Given the unprecedented speed of innovation (and disruption) these technologies can bring, you must take stock in how your architecture and IT environment are adapting to changing demands to deliver long-term value. Learn more by clicking here.