Hyunsoo Kim, a 29-year-old entrepreneur in South Korea, is on a mission to democratize artificial intelligence to enable more companies, both large and small, to utilize the emerging technology. So it's only fitting that Kim, cofounder of Superb AI, has been selected as the featured honoree for the Enterprise Technology category of this year's Forbes 30 Under 30 Asia list, leading a pack of several fellow honorees who founded startups based on AI. Since launching Superb AI in April 2018 with four cofounders, Kim has grown his startup to $2 million in revenues last year and 21 employees, fueled by increasing demand for AI. Profits are still in the future, but Superb AI also managed last year to join Y Combinator, a prominent Silicon Valley startup accelerator. So far, it has raised $2 million in funding from Y Combinator, Duke University and VC firms in Silicon Valley, Seoul and Dubai, giving it a valuation of $12 million as of March 2019.

United Arab Emirates-based global EdTech Alef Education is on a mission to digitally transform the education sector to support its most valuable resource: teachers. The United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics estimates that the world needs almost 69 million new teachers by 2030 to meet the deadline of the United Nations Sustainable Development Goal for quality education. But according to latest projections, the world will fail its education commitments without addressing the teacher shortage. Overwhelming teacher workload is a major contributor to teacher scarcity and the urgency to tackle this imbalance is a key driver for United Arab Emirates (UAE)-based global education technology Alef Education. The forward-thinking organization is shrinking teacher workloads and helping them better manage classrooms through its artificial intelligence (AI)-powered platform built on Amazon Web Services (AWS).

AI-powered optimization software provider Concertio today announced that it has raised $4.2 million, which it says it will use to scale its platform that boosts app performance by tailoring x86 server settings. Customers won't only benefit from faster, more stable apps and hardware as a result, says Concertio, but from lower infrastructure costs as well. Concertio's Optimizer Runtime tool, which runs on most CentOS and Debian Linux distributions running in the cloud or on-premises, monitors and learns from the interactions between apps and systems to tune parameters at each stage of development and deployment. An agent runs in the background and learns system metrics to detect different phases of execution, ingesting only a small sampling of data while dealing with system variability to optimize each phase separately. The Optimizer Runtime discovers hidden systems configurations that deliver optimal settings, and it optionally lets developers define optimization targets, including processor instructions, network bandwidth, database queries, and minimum server energy.

It's a moment most people have experienced. Their required to show their ID for something and then wait as the person studies both their face and the photo on the driver's license, passport, or other document, making sure the person is not an impersonator trying to pull a fast one. These days, artificial intelligence is playing a role similar to that security person, with software that allows validation of IDs remotely through digital document verification. This method allows doing business through a smartphone, and someone on the other end can make sure the person is who they say they are and that a thief hasn't stolen the identity. And that's especially important at a time when identity theft has been on the rise, says Stephen Hyduchak, CEO of Aver (www.goaver.com),

An examination of the implications for society of rapidly advancing artificial intelligence systems, combining a humanities perspective with technical analysis; includes exercises and discussion questions. AI and Humanity provides an analytical framing and a common language for understanding the effects of technological advances in artificial intelligence on society. Coauthored by a computer scientist and a scholar of literature and cultural studies, it is unique in combining a humanities perspective with technical analysis, using the tools of literary explication to examine the societal impact of AI systems. It explores the historical development of these technologies, moving from the apparently benign Roomba to the considerably more sinister semi-autonomous weapon system Harpy. The book is driven by an exploration of the cultural and etymological roots of a series of keywords relevant to both AI and society. Works examined range from Narrative of the Life of Frederick Douglass, given a close reading for its themes of literacy and agency, to Simon Head's critique of the effects of surveillance and automation on the Amazon labor force in Mindless.

Artificial intelligence (AI) is already deeply embedded in so many areas of our lives. Society's reliance on AI is set to increase at a pace that is hard to comprehend. AI isn't the kind of technology that is confined to futuristic science fiction movies – the robots you've seen on the big screen that learn how to think, feel, fall in love, and subsequently take over humanity. No, AI right now is much less dramatic and often much harder to identify. Artificial intelligence is simply machine learning.

The advent of artificial intelligence (AI) is providing financial services institutions with major opportunities for improving their client offerings, operations and compliance. Ben Nadel, Director at independently-minded management consultancy Woodhurst, explores four key areas where AI can ramp up effectiveness and efficiency while lowering costs. The rise of challenger banks has demonstrated how technology can drastically improve customer experience. Thirteen million people in the UK use challenger banks today, and that number is set to triple in the coming year. In order to remain competitive, traditional financial service providers are turning to emerging technology, including AI, to improve their customer experience.

Hong Kong/Beijing/Seoul/Tokyo – Fitness-tracking gadgets are selling out, home exercise classes have never been more popular and robotics crews are pivoting to making sanitation robots. The Covid-19 pandemic has triggered a seismic wave of health awareness and anxiety, which is energizing a new category of virus-fighting tech. The fear of infection has accelerated the adoption of apps and wearables as a means to feel better protected. "Having accurate and immediate feedback about our body temperature, blood pressure and other health signals helps to restore people's sense of control," said Andy Yap, a social psychologist at the INSEAD business school. Consumers, insurers and health-care providers are all seeing the benefit of the gadgets, in a shift expected to persist long after the outbreak subsides.

We are awash in digital images from photos, videos, Instagram, YouTube, and increasingly live video streams. Working with image data is hard as it requires drawing upon knowledge from diverse domains such as digital signal processing, machine learning, statistical methods, and these days, deep learning. Deep learning methods are out-competing the classical and statistical methods on some challenging computer vision problems with singular and simpler models. In this crash course, you will discover how you can get started and confidently develop deep learning for computer vision problems using Python in seven days. Note: This is a big and important post. You might want to bookmark it.

Michael is a hybrid thinker and doer--a byproduct of being a StrengthsFinder "Learner" over time. With 20 years of engineering, design, and product experience, he helps organizations identify market needs, mobilize internal and external resources, and deliver delightful digital customer experiences that align with business goals. Michael earned his BS in Computer Science from New York Institute of Technology and his MBA from the University of Maryland, College Park. He is also a candidate to receive his MS in Applied Analytics from Columbia University.