AI Articles and Analysis in Transportation

Allied Market Research estimated the value of the global autonomous vehicle (AV) industry to reach $54.23 billion in 2019, increasing to $556.67 billion by 2026 at an annual growth rate of 39.47% during that period. It follows that AI would find its way into the autonomous vehicle world. We detailed our own timeline for self-driving cars, pooling quotes and insights from executives at the top 11 global automakers.

MicKinsey estimated that by 2030, up to 15% of cars sold will be autonomous vehicles. We detailed our own timeline for self-driving cars, pooling quotes and insights from executives at the top 11 global automakers.

Computer vision, an AI technology that allows computers to understand and label images, is now used in convenience stores, driverless car testing, daily medical diagnostics, and in monitoring the health of crops and livestock.

According to research firm Zinnov, India is the fourth largest geography globally in terms of AI talent pool. Zinnov’s research says India is home to more than 200 AI startups that attracted about $200 million+ funding in 2017. A few major companies that are implementing AI include Amazon, AIG, Equifax, Infosys and NVIDIA - all of which we've covered in depth in our recent "AI in India" research.

Episode Summary: Natural language processing (NLP) has become popular in the past two years as more businesses processes implement this technology in different niches. In inviting our guest today, we want to know specifically which industries, businesses or processes NLP could be leveraged to learn from activity logs.

Episode summary: This week on AI in Industry, we speak to Rana el Kaliouby, Co-founder and CEO of Affectiva about how machine vision can be applied to detecting human emotion - and the business value of emotionally aware machines.

Over the past decade, the industrial sector has seen major advancements in automation and robotics applications. Automation in both continuous process and discrete manufacturing, as well as the use of robots for repetitive tasks are both relatively standard in most large manufacturing operations (this is especially true in industries like automotive and electronics).

Episode summary: In the heavy industry sector, the cost of unpredicted repairs or machine failures can be very expensive. For example: A cargo train with an engine failure in will incur costs from its own repairs, from the transit required to reach the broken down engine, and with holding up other trains and cargo in the process.