Bottom Line: The leading growth strategy for manufacturers in 2019 is improving shop floor productivity by investing in machine learning platforms that deliver the insights needed to improve product quality and production yields. Using machine learning to streamline every phase of production, starting with inbound supplier quality through manufacturing scheduling to fulfillment is now a priority in manufacturing. According to a recent survey by Deloitte, machine learning is reducing unplanned machinery downtime between 15 – 30%, increasing production throughput by 20%, reducing maintenance costs 30% and delivering up to a 35% increase in quality. Accenture, Manufacturing The Future, Artificial intelligence will fuel the next wave of growth for industrial equipment companies (PDF, 20 pp., no opt-in) How the IIoT can change business models. How emerging technologies can transform the supply chain.
The Singapore edition of World AI Show reinvigorated the nation's AI efforts by bringing in top global investors, startups, digital companies, solution providers and AI experts such as Dr Terence Hung from Rolls-Royce Singapore; Sutowo Wong from the Ministry of Health, Singapore; and Guido Jouret, Chief Digital Officer of ABB; to name a few. Given its infrastructure capacity, education system and investor-friendly laws, Singapore has all the right ingredients to nurture a robust AI ecosystem that could be the cornerstone for the small island's economic upswing. According to a recent report by Accenture, AI could add up to US$215 billion in gross value across 11 industries in Singapore by 2035. With the Singapore government's vehement efforts to foster initiatives in the AI space, the nation was the ideal location to host the 9th edition of the global World AI Show series that had hit the ground running for the second time in Singapore on 24 July 2019. The show was organised by international business events and consulting firm, Trescon.
Karl Smith Director and Founder of Decision Point AI a business unit of Veriluma a Sydney based AI company joins the Veriluma board as an advisor. He brings with him 30 years' of experience includes Artificial Intelligence (AI), Internet of Things (IoT) and Blockchain. Karl has a track record of building new technology products & consulting professional services from the ground up into successful revenue generating offerings including the launch of Wipro Digital and Accenture EUX. I'm looking forward to evolving the commercial application of an AI technology currently mainly adopted and focused in the intelligence market As we evolve Veriluma AI patented technology in Scotland for markets in Europe and the USA, we see the need for both professional services consulting and a research group.
Why is change so hard? We delight in things that are new. I'm thinking about how history has treated new technology. Things that are designed to make life easier (the steam engine, factory automation) are initially met with cynicism. Today we're a decade into mainstreaming artificial intelligence (AI), and organizations are excited about the potential, but still cautious about adoption.
Playing is always good, especially this time of the year. Last week our blog post was a memory game highlighting the most conspicuous facts that kept us busy in 2018. More than the GDPR fog before May 25, or the new VAT Grouping regime voted in July, there was an algorithmic-related topic that stole the front page of printed and digital media, and it was a widespread topic on social media. We decided, then, to celebrate capodanno – or the New Year – with a game dedicated to artificial intelligence! Yes, you've got it right.
In partnership with British Triathlon, we have created the'Athlete Genome'; a technology solution aimed at enhancing athletic performance, with the ambition to ensure British Triathletes are the best prepared athletes at the Olympic and Paralympic Games in Tokyo. The Athlete Genome is an industry-first, developed through the application of Accenture thinking and leading-edge technologies and in partnership with British Triathlon. The solution, a platform which integrates performance data with psychological data in sport, creates a hyper-personalised view of the impact of cognitive state on performance, and gives British Triathlon's athletes and coaches the ability to make meaningful decisions based on this interaction. Working alongside British Triathlon and the world-leading English Institute of Sport, we are developing and validating the use of sentiment analysis in elite performance sport. By integrating technologies including artificial intelligence, machine learning, the cloud, wearables and cognitive and performance data from TrainingPeaks, the Athlete Genome seeks to understand the relationship between cognitive state and performance.
We've heard this advice when it comes to everything from what you should order at a new restaurant to who you should marry. But as you might imagine, some decisions are better not left to the gut. That's where technology comes in. Hiring managers, company executives and everyone else in an organization benefit when decisions are informed by data. Christy Pettey at Gartner, however, cautions that there is a balance: Decision-makers must allow technology to complement, rather than replace, gut feelings and natural tendencies.
CHICAGO -- Grant Thornton LLP is collaborating with Microsoft and Hitachi Solutions to turn information into foresight. The collaboration uses artificial intelligence (AI) and machine learning (ML) to help Grant Thornton identify its clients' nascent business needs. Grant Thornton can then design solutions to address its clients' challenges before they balloon. As one of the nation's largest accounting, tax and consulting firms, Grant Thornton works with clients to overcome all manner of hurdles, from financial and operational to technological and risk-related. "We focus on staying ahead of our clients' needs," explains Nichole Jordan, Grant Thornton's national managing partner of Markets, Clients and Industry.
Newton sits underneath an apple tree. History is spiced with Eureka! moments when human understanding leaps forward. Thomas Edison chose a more deliberate approach: Rather than waiting for lightning to strike, he saw innovation as a replicable, continuous process. His facility in Menlo Park, New Jersey, was the first industrial lab specifically designed to produce a continuous stream of commercially viable technology innovations built on new and emerging technologies.1 Of course, the pace of technology innovation today--and its impact on business--is exponentially faster than in Edison's industrial age.