Matt co-founded Afresh with the belief that fresh food is the future of what we eat, yet is underserved by retail technology. It's been a decade since Marc Andreessen penned his prescient essay declaring that "software is eating the world." We need only look at a few software companies with massive impact on our daily lives (Uber, DoorDash and Slack, to name a few) to understand that this is true. Yet currently, multiple multitrillion-dollar industries such as retail, supply chain, food and energy have critical workflows and decision-making processes that rely on Excel spreadsheets or literal pen and paper. The answer lies in the physicality, dynamism and unpredictability of the non-digital world.

At Landing AI, we are building next generation AI products and solutions to help transform traditional industries like manufacturing and agriculture. This is an ambitious goal that requires close collaboration between people from different disciplines, including product, machine learning engineers and software engineers. In this blog post, we talk with some of our software engineers, who play an important role in building and executing AI solutions, to get their perspectives on what a software engineer's work life is like at Landing AI. What is it like working as a SDE at Landing AI? What's your typical day look like? Pingyang: Besides designing and building various kinds of innovative systems and solutions, I have also been spending a lot of my time learning new things that I was not able to learn elsewhere. I got more opportunities to build tools and frameworks that I'm not allowed to touch or modify in big companies.

DataVisor, the leading fraud detection company with solutions powered by transformational AI technology, announced the availability of dEdge, an anti-fraud solution that detects malicious devices in real-time, empowering organizations to uncover known and unknown attacks early, and take action with confidence. "Most consumer-facing organizations today provide their customers opportunities to interact with the business through an online channel. Even traditional industries like banking enable customers to bank through mobile applications. To validate the authenticity of this interaction, data needs to be collected and analyzed at the source" With growing adoption of mobile devices and the emergence of the always-on economy, by many measures, when organizations realize that they have been subject to a cyber-attack, it is already too late. Modern fraud detection and prevention require a transformational approach, one that represents a shift back to an earlier point along the timeline of a fraud attack.

What comes next – more consolidation and an industry slow down, or more exciting innovation and industry expansion? We asked some of the industry's leading voices for their 2020 predictions. DRONELIFE asked participants to comment on 3 important questions- and the variety of answers may surprise you. Read on to see what our panel agreed upon – and how their predictions differed widely. What new vertical market or application will be the number one growth opportunity in 2020?

Jia Li is very passionate about artificial intelligence (AI) and how it can improve healthcare. When one of her close family members suffered from a skin condition, she worked on developing an image recognition technology to help classify such diseases and diagnose them better. Now, as the head of R&D for Cloud AI, Google Cloud and an adjunct professor at Stanford University's School of Medicine, Dr. Li and her team at Google focus on research and innovation to solve real-world problems. This includes developing AI products on Google Cloud to power solutions for diverse industries. Edited excerpts: Dr. Li who before joining Google led research and innovation efforts at Snapchat's parent company Snap and Yahoo!

Implementing deep learning in enterprise settings requires a lot more than just downloading some open source algorithms, but with talent scarce, businesses are finding it takes creativity and an open-minded approach to achieve results. "Established industries are largely missing out on the benefits of AI," said Ryan Kottenstette, co-founder and CEO of Silicon Valley geospatial data company Cape Analytics LLC. "If you're not in the tech sector, you might be waiting a bit longer for the benefits of AI to be realized." In recent years, deep learning has taken huge strides. Algorithmic processes like neural networks, which historically lived more in the realm of mathematical theory, have moved into some enterprise use cases, like computer vision and process automation. But adoption has been uneven.

Kevin Du is travelling to the United States this week to visit Harvard Business School. But he has other things on his mind. He plans to make a side trip to other top universities and technology companies, part of his regular day job as a headhunter, looking to rope in engineers, programmers and coders to work in China. China, already the world's largest market for automatons, e-commerce and smartphones, is also the job market for artificial intelligence, big data analytics and robotics. The Chinese government has just unveiled a road map to global dominance in AI by 2030, forecasting the industry to be worth 1 trillion yuan (US$151 billion) by then.

GIC's annual thought leadership event, GIC Insights, was held here on 15 September 2017. It saw 110 prominent global business leaders deliberate long-term issues relevant to the international business and investment community. The theme was Asia's Evolving Role in an Uncertain World, and topics included Asia's Challenges and Prospects over the Next Decade, Artificial Intelligence for Traditional Industries and A Long-Term Future in an Uncertain World. Artificial intelligence (AI) is significantly changing and disrupting a wide range of industries, including industrials, agriculture, finance, and more. From self-driving trucks and autonomous factories, to Ebola cures and hunter-killer drones, AI can drive new solutions at a far lower cost than traditional companies like 3M and Boeing.

The hype surrounding machine learning and artificial intelligence (AI) is higher than ever. Nevertheless, despite much anticipation, many businesses are still hesitant about the technologies' ability to change their business. This attitude is far from surprising. With the media and technology experts focusing on the most visual consumer-focused applications of the technology (AI assistants, chatbots, self-driving cars, etc.), there is little doubt as to why traditional organisations believe that disruption will only happen within the "new" economy, leaving them unaffected by the new arrivals. See also: What is machine learning?

This article is part of a special insideHPC report that explores trends in machine learning and deep learning. The complete report, available here, covers how businesses are using machine learning and deep learning, differentiating between AI, machine learning and deep learning, what it takes to get started and more. The impact of AI on business functions will play out differently in different industry sectors. In financial services firms, AI's impact is expected to be felt most strongly in the area of customer interaction, and in manufacturing organizations-- product development. Health and life sciences, meanwhile, anticipate the AI impact will be greatest in management decision-making.