Technology is intertwined in nearly every element of our lives. Which makes understanding that technology more important than ever.
In our on-going Tech Talk series, we’ll be leaning on the expertise of our CTO, Jonathan Salama, to decode the most prevalent tech terms of the day.
What is Artificial Intelligence?
Artificial intelligence is broadly defined as a computer or machine’s capability to imitate intelligent human behavior. When you drill down further, AI is categorized in three ways. Weak AI relates to systems that work properly but do not reason as human beings reason. Generally speaking, this type of AI focuses on a single narrowly defined task. Strong AI refers to a system that can think critically, just as humans do. This is an emerging field within AI, and can only be fully realized once science has a comprehensive understanding of the human brain. And finally, Artificial Super Intelligence (ASI) systems represent the final frontier in which AI is more capable than a human. This type of AI would possess emotional intelligence, creativity and precise decision making skills that could blur the lines between humans and machines.
AI At Work
The trucking industry has been notoriously slow to embrace technology. That reticence has prevented widespread adoption of emerging technologies that have the potential to increase margins across the board. To understand technology’s potential, particularly as it relates to AI, we sat down with one of Transfix’s senior data engineers, Hasan Masood.
What are the practical applications of AI here at Transfix?
As a digital freight brokerage, our business is geared around shipper and carrier satisfaction from efficient price discovery and optimization at multiple levels of the supply chain. We use machine learning techniques to estimate the cost of moving freight from one area to another nationwide given a set of market conditions. The models our data scientists have built sit at the core of our pricing system.
We see the opportunity to apply AI to a number of other areas, including getting the right loads and routes to our carriers based on their needs, so we can reduce wasteful deadhead and improve carrier payout, experience, and quality of life. AI can be used to predict accessorial costs and related operational risks as part of pickup and delivery at facilities.
Have there been major advancements in the use of AI within transportation in the last decade?
In the current context, we’re seeing long bets on AI quickly ripening primarily due to the dropping price points around sensors, computers and storage costs. Increasingly, data intensive techniques are becoming viable and a related proliferation of machine learning frameworks is happening in open source.
For the transportation sector, we’re seeing machine learning algorithms used in processing sensor data to enable self-driving vehicles, matching passengers optimally for efficient ride-sharing as well as predicting better traffic management from smarter cities. The stage is set for AI to influence our economy in a really big way in the 2020s.
Can AI replace human input, or will we always need someone at the controls, so to speak?
At present, AI systems are limited to not having consciousness, self determination or feelings. As a brokerage, people and relationships are at the heart of our business. Consequently, there is no competitive dynamic between humans and machines when it comes to some of the vital factors of production for our business.
However, some of the pain around coordinating between our shipper and carrier partners will be made easier through adopting this technology, but this will not be any sudden change. Similarly, our economy will gradually adjust to spend our human capital on areas that need the most focus while leaving the repetitive tasks to machines. In short, we see AI as a useful tool to enable our team members to do more with less.
If you have questions for our Tech Team, we’d be happy to answer them in upcoming posts! Tweet at us with the hashtag #TalkToTech.