Beyond hypes and fads, AI works because it amasses significant benefits for the manufacturing sector, such as enabling smart production, developing predictive and preventative maintenance, offering supply chain optimisation, improved safety, product development, and optimisation, facilitating AR/VR (Augmented and Virtual Reality), cost reduction, quality assurance and enabling green operations (energy management), to name a few. Manufacturing companies are adopting AI and ML with such speed because by using these cognitive computing technologies, organisations can optimise their analytics capabilities, make better forecasts and decrease inventory costs. We see that scaling AI implementations beyond a proof-of-concept (POC) level remains one of the biggest challenges in manufacturing, as well as other industries including but not limited to logistics, healthcare, insurance, finance and audit. For instance, even when people are aware that the inventory recommendations for raw materials or deliverables are accurate, they feel more comfortable holding a little extra stock or to be a little protective in the supply chain. Digital twins work by essentially evolving profiles of past and current behaviours of physical objects or processes that can be effectively analysed to optimise business performance.

A global KPMG survey showed that organizations cannot yet reap all the benefits of data analytics due to data quality issues and a lack of capable resources. In 30 years' time, developments in data analytics itself could solve this issue, making many current professions in the sector obsolete. The impossible will become possible, and this may well lead to an autonomous decision-making process. Data analytics is expected to radically change the way we live and do business in the future. Already today we use the analytics in our technology devices, for many decisions in our lives.

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Half of business technologists now produce capabilities for users beyond their own department or enterprise. That's the top finding in a new report from Gartner, which cites "a dramatic growth" in digitalization opportunities and lower barriers to entry, including low-code tools and AI-assisted development, as the core factors enabling this democratization beyond IT professionals. What's more, Gartner reports that 77% of business technologists -- defined as employees who report outside of IT departments and create technology or analytics capabilities -- routinely use a combination of automation, integration, application development, or data science and AI tools in their daily work. "This trend has been unfolding for many years, but we're now seeing a tipping point in which technology management has become a business competency," Raf Gelders, research vice president at Gartner, told VentureBeat.

Domestic surveillance programs may be in for an AI upgrade. The National Security Agency of the United States just awarded a $2 billion contract to Hewlett Packard Enterprise to develop high-performance computing power that the agency will use to reach its data analytics and artificial intelligence needs, according to a Wednesday statement from the company. However, it's important to keep in mind that the NSA has repeatedly pushed for access to private information from telecommunications companies and internet servers, which could mean a major upgrade is in store for the surveillance of ordinary people. During the course of the 10-year contract, the NSA will pay to employ HSE's computing technology, which will also build a new platform that will blend the company's ProLiant servers with its Apollo data storage system. Combined, the new system will "ingest and process high volumes of data, and support deep learning and artificial intelligence capabilities," read the company press release.

Gartner, Inc. identified the top 10 data and analytics (D&A) technology trends for 2021 that can help organisations respond to change, uncertainty and the opportunities they bring in the next year. "The speed at which the COVID-19 pandemic disrupted organisations has forced D&A leaders to have tools and processes in place to identify key technology trends and prioritise those with the biggest potential impact on their competitive advantage," said Rita Sallam, distinguished research vice president at Gartner. D&A leaders should use the following 10 trends to determine investments that accelerate their capabilities to anticipate, shift and respond. The greater impact of artificial intelligence (AI) and machine learning (ML) requires businesses to apply new techniques for smarter, less data-hungry, ethically responsible and more resilient AI solutions. By deploying smarter, more responsible, scalable AI, organisations will leverage learning algorithms and interpretable systems into shorter time to value and higher business impact.

Nothing strikes terror into the hearts of humans more than the idea of an intelligent robot gone bad. The fear is that a robot can acquire the ability to learn and adapt to the point of superseding their human creators…and with evil intentions. From Gort ("The Day the Earth Stood Still") to Sonny ("I, Robot"), films provide a wide variety of potential robot scenarios. Only a few of these film robots have demonstrated artificial intelligence to the point where they have threatened humankind (like the Cyberdyne Systems series T-800 Model 101 in "Terminator" and the unnamed NS-5 robots in "I, Robot"). However the one evil robot that demonstrated its ability to continuously learn through experimentation and failure would be theOmnidroidfrom the "The Incredibles".

While the prospect of deriving reliable insight with machine learning (ML) and AI-driven data analytics may seem overwhelming, it doesn't have to be, says Cloudreach Chief Technologist, John Loughlin. In a June 2020 webinar, we discussed how to approach data analytics with pragmatism and confidence using Google Cloud Data (GCD) Services. Here we'll recap that advice, providing an overview of how businesses can implement the building blocks of becoming a data-driven organization using GCD Services. Keep in mind that the overarching goal – to enable the analysis that opens the door to better business decisions – rests on the core values of security and governance, which together provide the context for making effective use of technology. Safeguarding data is fundamental to your program and to doing right by your stakeholders.

The convergence of machine learning and business intelligence is upon us, as BI tool makers increasingly are exposing ML capabilities to users, and users are performing ML activities in their BI tools. That's according to the latest Gartner report on analytics and BI tools, which was released this week. In its February 11 Magic Quadrant for Analytics and Business Intelligence (ABI) Platforms, the storied Stamford, Connecticut analyst firm did its best to quantify and qualify the trends in the sector. While BI and ML have largely existed on parallel tracks, with BI seeking to report what happened and ML seeking to predict what will happen, Gartner sees the two disciplines converging, at least as far as the toolsets are concerned. Not all ML work will occur within BI tools, of course.

Hewlett Packard Enterprise Tuesday unveiled a new version of its Aruba Central network management platform outfitted with artificial intelligence-based analytics. "This is a breakthrough with artificial intelligence-based analytics being integrated into Aruba Central for the first time," said Hewlett Packard Enterprise Vice President Dr. Tom Bradicich, HPE Fellow and global head of IoT and Edge Center of Excellence and Labs. "The impact this is going to have on customers is tremendous because these analytics are no longer on a separate tool, program or screen." The new Aruba Central capabilities for the first time allows partners to proactively optimize an SD-WAN rollout based on the AI based analytics from Aruba Central. Aruba Central now includes branch management capabilities with a new SD-WAN Orchestrator that makes it easier for partners to deploy what HPE calls a "large scale edge infrastructure connecting thousands of branch locations with multiple data centers."

I lead the technology industry business unit for a fast-growing analytics firm. And one of the perks of my job is the numerous conversations I get to have with a variety of prospects or clients. I recently read the book'The Art of Thinking Clearly' by Rolf Dobelli, which deals with systematic cognitive errors of human beings as a result of our evolution. I enjoyed reading the book immensely, relating those cognitive errors to what I experience every day. I am selecting a few rampant cognitive errors mentioned in the book and linking them to situations I have come across.