Artificial Intelligence has been one the hottest topics in the PR industry. Many Public Relations professionals believe that AI will continue to be a strong ally that will change the industry in a positive way. Yet, there is some anxiety about how AI will affect jobs.
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Everyone is talking about AI applications for healthcare, financial services and self-driving cars. At the same time, creative occupations were previously understood to be immune from the disruptions of AI due to the high levels of intuition and gut instinct, difficult to replicate by complex algorithms, but that is changing now. In this post, I want to talk about 7 lesser-known ways Artificial Intelligence is changing the world around us. Some of these applications might surprise you. Read More
Artificial Intelligence is changing many industries and Digital Marketing is no exception. Customers today expect personalized and consistent experience across every channel. For the second edition of the “State of Connected Customer” report, Salesforce Research surveyed over 6,700 consumers globally to better understand the mindset of the modern customer. The report revealed that 80% of customers think that the experience a company provides is as important as its products or services. 57% have stopped buying from the company because a competitor provided a better experience.
Savvy marketers know this and rely on Artificial Intelligence to analyze their data to gain a deeper understanding of consumers’ needs, then use these insights to help their organizations deliver improved customer experience. Read More
When thinking about machine learning, how often do you consider time? Time series analysis is an important area of machine learning because many predictive problems that ML is used to solve involve a critical time component. Read More
Digamma.ai AI Q&A Series: Jackie Snow, MIT Tech Review
1. We are in the very early stages of AI in history. Style is still so complex and there is this sense that AI is trending towards an intelligent assistant that will help us look like we shop at Saks Fifth Avenue regularly and yet do it under budget. In what areas do you believe AI will help consumers and what areas of the style and retail experience do you believe humans still need to do themselves?
I would agree that style is still too complex for AI to get a grip on. So, there’s a long way to go before AI is putting together an outfit for me. Right now, with everything that we’re seeing in the fashion world, I think it’s really geared towards predicting what sort of items a consumer might like to buy. That doesn’t really have anything to do with style. In the meantime, I do think we’re going to have AI that can help surface a lot of different items that we may not necessarily be exposed to through the online shopping environments that are available to us right now. Read More
Our team here at Digamma.ai is very excited to announce our partnership with the Institute of Mathematics of the National Academy of Sciences of Ukraine in Kyiv.
Through the Kyiv Academic University’s Dual Education Program, we will working with Masters and PhD students from the Department of Mathematics to tackle key machine learning projects together.
With mathematics and statistics as the foundational underpinnings of algorithms that are powering the emerging AI economy, the mathematics field — and researchers in the sector — are experiencing a flood of interest from the private sector.
Through this initiative, we will have an opportunity to work with some of the brightest mathematical minds at the University — which has a long-standing history of exceptional achievements in the field — and provide an environment for mathematics graduate students to apply their research and knowledge to solving real-life problems using machine learning methodologies. Read More
Digamma.ai CEO Q&A Series: Amar Chokhawala, CEO of Reflektion
Reflektion seeks to give retailers a deeper understanding of customer intent. How does your company do this from a technology perspective?
In today’s world, everyone is sharing everything. So, the customer’s intent almost starts with temporal signals. When I’m looking for a place to eat in the morning, that means I’m looking mostly at restaurants which are actually serving a breakfast or lunch. Here’s an example of how the temporal aspect comes into play. Imagine a three year old—if you asked her what an “apple” is, she would say it was a fruit. If you posed that same question to a thirteen year old, she would say that it’s the technology company. So, in order to understand customer intent in retail, we need to build a comprehensive user profile that takes into account this temporal dimension. Because if you don’t know the consumer, then you won’t know what the intent of that particular consumer is. Our technology is capable of building those user profiles. We focus on the user first and, to date, have built 600 million plus profiles. That allows us to gain a deeper understanding of customer intent. We use machine learning because, unlike other technology, it works more effectively with more data. The more data you have, the better the model performs. Read More
By 2018, 50,000 gigabytes of data will be created per second. A significant amount of that data will be stored in corporate server farms. A report from IDG found that “[m]anaging unstructured data is growing as a challenge – rising from 31 percent in 2015 to 45 percent in 2016.” IDC’s Digital Universe report found that “the amount of data stored in the world’s IT systems” doubles every two years. On one hand, many companies are eager to start confronting the challenge of big data. But according to an IDG Enterprise report, 90% of the companies surveyed reported running into major problems when implementing or developing their big data initiatives. No wonder an October 2016 report from Gartner found that most companies who attempted to implement a big data project were mostly stuck in the pilot stage. The challenge of what do to with big data is daunting for many companies. However, machine learning has an important role to play in “solving” big data. Read More
Digamma.ai CEO Q&A Series: Jonas Cleveland, CEO of COSY
What transformative effects do you intend COSY to have on the retail sector?
We describe COSY as an aisle intelligence company that’s using machine vision and AI to improve retail execution and inventory productivity for our customers in retail stores and warehouses. The major trend occurring in retail today is the evolution of the retail store floor into a distribution center. This is something that COSY has been talking about for some time. For consumers, this means being able to order online, show up to the store and grab what you ordered plus other things, such as fresh produce.
For retailers, this means that they need more stores so that they can reach more people efficiently. Today we see stores like Target moving into more urban environments. We also see many stores closing down as the overhead of these stores is too high.
There is also the issue of an inefficient use of space. So, really, what COSY enables is the ability to optimize the way this real estate is used. Essentially, being able to optimize how you place departments, products and organize them on the store floor to drive revenue higher for retailers. Read More
