GlobalData has identified ten of the biggest influencers in AI on Twitter during Q3 2019, using its Influencer Platform. GlobalData research has found the top AI influencers based on their performance and engagement online. Using research from GlobalData's Influencer platform, Verdict has named ten of the most influential people in AI on Twitter during Q3 2019. Ronald van Loon is a Big Data expert and Director at Advertisement, a data and analytics consultancy firm. He helps data-driven companies in executing data and analytics strategies to become more successful.

Data science is a new area of study that branches from disciplines such as statistics, computing, mathematics, software development, ML and many more. However, with the increasing demand of data scientists and their skillsets, should data science in fact be considered its own discipline? A statistician usually comes from a background in statistics. A software developer would have studied software development. A mathematician most definitely studied mathematics at university.

GlobalData research has found the top artificial intelligence (AI) influencers based on their performance and engagement online. Using research from GlobalData's Influencer platform, Verdict has named ten of the most influential people in artificial intelligence on Twitter during Q2 2020. Evan Kirstel is a B2B thought leader with extensive experience across enterprises sales, alliances, and business development. He currently serves as chief digital officer and advisor of NYDLA.ORG, a remote, distance/digital learning and collaboration association. Kirstel is of the opinion that the role of artificial intelligence accelerates the opportunity for increased customer and agent engagement alike.

GlobalData research has found the top artificial intelligence influencers based on their performance and engagement online. Using research from GlobalData's Influencer platform, Verdict has named twelve of the most influential people in artificial intelligence on Twitter during Q1 2020. Ronald van Loon is a recognised thought leader and a top technology influencer. As director of Advertisement, the influencer provides insights and secures analytics data quality, among other responsibilities. He also serves on the Advisory Board of the wefox Group, a Europe-based insurtech start-up.

GlobalData research has found the top artificial intelligence (AI) influencers based on their performance and engagement online. Using research from GlobalData's Influencer platform, Verdict has named ten of the most influential people in artificial intelligence on Twitter during May 2020. Ronald van Loon is a recognised thought leader in technologies including AI, big data, IoT, machine learning, deep learning, 5G, predictive analytics, cloud, edge and data science. He currently serves as principal analyst and CEO of the Intelligent World, an influencer network that connects experts, businesses, and influencers to new audiences, helping them collaborate, create and share diverse content. Loon is of the opinion that AI has progressed at a furious pace over the past few years, and though it has usurped large chunks of the big data, the technology is nowhere near human intelligence.

At the Intercon conference, Dr. GP gave a motivational keynote speech on Deep Reinforcement Learning and the landscape of machine learning and artificial intelligence that inspired the audience. He noted that the MIT Technology Review has downloaded 16,625 research papers from arxiv that are publicly available under the computer science and artificial intelligence section through November 2018. Through natural language processing techniques on the abstracts, the words "constraint," "theory," "rule," "logic," "program," "learning," "network," "data," "task," and "performance" have been evaluated to find the reinforcement learning boom in recent times. Dr. GP said trends have shown the rise of traditional neural networks in the 1950s and 1960s, symbolic approaches in the 1970s, knowledge-based and rule-based systems in 1980s, support vector machines in 1990s, and the reign of neural networks in the 2010s with the advent of heavy implementation of deep neural networks. Deep Traffic is a reinforcement learning simulation based on the 24,000 entries received on MIT's Deep Traffic competition on self-driving cars that drive on a multi-lane freeway with a model-free off-policy reinforcement learning process that inspires a number of data scientists and machine learning enthusiasts to evaluate the Deep-Q-Learning reinforcement learning network variants and hyperparameter configurations with episodic iterations training of 96.6 years of RL simulations, 572.2 million crowdsourced and optimized DQN hyperparameters to train the agents successfully.

There has been tumultuous excitement in the Computer Science field surrounding the potential of applying machine learning algorithms to the commercial problems at enterprise scale over the last few decades. Solving complex conundrums and HPC at web scale will need a new enterprise-grade operating system and hardware data flow computing with ASIC or FPGA chips to minimize the data movements and maximize the shorter communication paths to reboot the fourth industrial revolution and execute more parallel instructions on a single semiconductor chip die. The data lifecycle management of IoT requires unlimited number of threads to spawn on an operating system at the same time simultaneously with guaranteed QoS. All the IoT operating systems such as Android Things, Arm Mbed OS, Embedded Apple iOS and macOS, Google Brillo, Green Hills Integrity, Nucleus RTOS, RIOT OS, RTOS, Windows, WindRiver VxWorks, or Linux targeting Raspberry Pi or BeagleBoards, Intel Edison IoT Boards, and Arduino platforms can provide the performance based on the number of cores in the machine without unlimited threads. However, regardless of an exponential increase in the hardware resources to deliver the multitasking capabilities and memory management, corporations have hit the wall on Moore's Law plagued with communication delays requiring precision programming in C and C through Open MPI and heavy parallelprogramming which does not seem to be the norm for developing regular applications.

Artificial Intelligence is the hottest buzzword in the tech industry. There have been a lot of predictions and speculations on how AI is going to take the world by storm. What is your prediction on how AI will impact the enterprise workplace? A quick note: The opinions of all the experts are their own. Acuvate doesn't share or have any comment on any of their views/opinions.