More data is always an advantage when coupled with the means to use it. Over the last decade, web-based platforms have exponentially improved the way data can be used to one’s advantage over its life cycle. Real-time analytics, cloud networks, and cross-device compatibility have been great achievements. However, they bring us closer to a future that spells or at least seems to spell, u.t.o.p.i.a. for business intelligence. The latest IT implementations have set the ball rolling for organizations to maximize access to data alongside ‘miniaturizing’ the workstation. The hybrid architecture concept leads the way to organizations perceiving dependency on globally connected devices, internal devices, and external sources of raw data, correlations, etc. In such an environment, organization workers may be connected through personal devices to sensor-based utility devices, smart machines, stock markets, global weather systems, smart homes, and smart offices. A telling sign that they will, is increasing adoption of web-based platforms to ensure seamless data flow and robust analytics, which communicate via personal devices as well. Factors currently...Read More
Today, Machine Learning, Artificial Intelligence, Deep Learning, Big Data, and Analytics are talked about quite often. However, Advanced Architecture is something that is fading and not given much significance. When researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) created an app called Pic2Recipe that correctly identified recipes, everyone appreciated the effort that was taken towards AI and Deep Learning. However, very few paid attention towards Advanced Architecture. Advanced Architecture is required for solving problems related to image and voice. One should understand the concept of computer vision before proceeding towards Deep Learning’s advanced architecture. Deep Learning was used by Google in its voice and image recognition algorithms by Netflix and Amazon, to decide what people wanted to watch or buy next. Moreover, it was also used by researchers and solution providing companies to predict the future. As Deep Learning algorithms consist of a different set of models due to the flexibility, the neural network allows it to build a full-fledged end-to-end model. Computer vision is building an artificial...Read More
How can the new wave of technologies make the automotive industry more personalized and responsive to drivers?
The advancement in technology has modernized the driving experience in recent years. As solutions based on Artificial Intelligence (AI), that encompasses Machine Learning (ML) and Deep Learning (DL) are providing a more personalized, connected, safe, intelligent, secure, user-friendly and seamless driving experience. The concept of technological personalization for drivers did not exist before. It was difficult to imagine having a vehicle that would be so user friendly, thus refining the driving experience for both drivers as well as passengers. However, with change and modernization of technology, thanks to AI and Big Data Analytics, vehicle personalization is no longer restricted to aesthetics, brand and style elements. It is more to do with the experience of drivers while they use the vehicle. The more time one spends in a vehicle must lead to increase in brand association. Harvard Health Watch recently reported that an average American spends close to 101 minutes each day driving their car. NCHS, National Vital Statistics System, has stated that the average life expectancy in the US...Read More
One of the major challenges while dealing with heavy machineries is to keep them running for as much time as possible or say to reduce the down time to increase productivity. If a machine breaks down during scheduled operating hours, it can bear huge financial losses. But few machines are operated with a goal to let it run for as long as it can. Once it fails or malfunctions, it is repaired/replaced. This is called Corrective Maintenance. But for most machines, operating it till it fails is not an option. To avoid failures, maintenance is scheduled at regular intervals. This is called Preventive Maintenance. It is costly and requires a lot of resources. But with the advent of sensor, IIoT and cloud technologies, now the actual condition of machines can be monitored continuously and maintenances can be done when truly needed. This is called Predictive Maintenance (PdM). It is much more efficient and hence most cost-effective as well. The process by which PdM is done is called Condition Monitoring....Read More
With more than 3.8 billion digital users, the retail world is at the cusp of an omnichannel revolution. Artificial Intelligence (AI) has been at a prime modernization since the advent of digital and mobile technology. AI has promised to enrich various aspects of our lives through self-driving cars, smart homes, and even medical diagnosis. AI, Big data, Machine Learning, Predictive and Forecasting are helping retailers engage with their customer in innovative ways allowing them to take significant decisions swiftly. Retail is one such segment where AI has found instant acceptance. According to a study, 77% of UK retail directors think that AI, deep learning, and device learning implementations will have a remarkable impact on their businesses with 23% claiming they’re already seeing results. To sustain in the retail world, following are the essentials for each retailer: 1. A.I based recommendation engine: Through Artificial Intelligence, retailers can provide accurate and relevant product recommendations to a customer which sparks a shopper’s interest and brings conversion. Brands possess extensive data on demographical,...Read More