AI Articles and Analysis about Automation and robotics

Founded in 1984 by two computer scientists from Stanford University, Cisco Systems developed the local area network (LAN) concept and achieved a market capitalization of $224 million by the time of its IPO in 1990. Today, Cisco manufactures and markets telecommunications technology as well as other high-technology products and services.

Toyota came to the United States in the late 1950s, setting up its US headquarters in California. A decade later, the Japanese automaker became the third-largest import brand in the United States. In 1968, Toyota introduced the Corolla, now the world’s best-selling passenger car. Today, Toyota is rebranding itself as a mobility company. 

Founded in 2003 as Tesla Motors, the electric vehicle and clean energy company based in California currently has a market cap of over $700 billion - making it more valuable than the top seven automakers combined. Today, Tesla is well-known for its electric vehicles but the company also produces products for sustainable energy generation and storage such as solar panels, solar roof tiles, and more to enable “homeowners, businesses, and utilities to manage renewable energy generation, storage, and consumption”. 

The hypothesis is simple:

Equipment breakdowns or downtime is extremely expensive (imagine a train broken down on isolated tracks, hundreds of miles from the nearest depot)
Heavy equipment (engines, wind turbines, manufacturing machines) produce various streams of data (heat, vibration, time-series, etc)
Machine learning could be used to detect "failure patterns" in that data, helping businesses to maintain equipment health more effectively

In July 2017, The State Council of China released the “New Generation Artificial Intelligence Development Plan," outlining China's strategy to build a US$150 billion Chinese AI industry in a few short years, and to become the leading nation in AI by the year 2030. Other nations followed suit quickly with national AI strategies of their own - with the US trailing behind by nearly two years before developing a semblance of an AI initiative. The proposed 2021 budget for the national security budget in the US is $740 billion - with a billions of dollars being earmarked for AI specifically (learn more: US Public Sector AI Opportunity Report). 

Applying AI to the real world is much more difficult than applying it in digital ecosystems; this is what makes robotics use-cases in business so much more difficult than applications such as AI-enabled fraud detection.

The retail and eCommerce sectors were among the first to adopt natural language processing (NLP) in the enterprise, particularly by way of chatbots and conversational interfaces. In this article, we cover three ways retailers can use NLP to automate business processes and offer the customer a better experience. We also give examples of AI vendors that offer this technology and describe their products. The NLP capabilities we discuss include:

The military is always looking for ways to innovate its technology for weapons and vehicles, and it follows that AI and ML would become part of that work in the current decade. Currently, the Army is testing autonomous vehicles and aircraft for battlefield use. However, most AI applications for these vehicles do not have clearance to operate the weapons attached to them.