What Real-world Business Problems Can AI Solve?

In his introduction to “Could AI Solve the World’s Biggest Problems?”  published in the MIT Technology Review, Will Knight alludes to the “wealth of promising opportunities for AI applications” and reiterates the importance of using AI to make the world a better place. Fortunately enough, large organization executives, like Eric Schmidt, the chairman of Alphabet, believe AI could, in fact, help us overcome global socio-economic challenges. But what about real-world business problems?

Can AI help us tackle the smaller day-to-day issues we experience in our, sometimes, siloed departments?

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Building Ethically Responsible AI-powered Environments

Perhaps you’ve encountered before the entreaty for the “democratization of AI.” Generally speaking, democracy has a good reputation, but what does this mean in the context of technology and artificial intelligence, and what are the dangers of the alternative? Consider the words of Andrew Ng, Chief Scientist at Baidu research, who has called AI “the new electricity,” and you’ll begin to get a sense of what we mean. At the moment, AI (and machine learning and deep learning) tools are mostly in the hands of researchers, industry, large enterprises, colleges, and labs. AI presents distinct advantages to businesses who have access to incorporating it into their systems or products, improving everything from logistical efficiency to positive user experience and everything in between; by definition, those who can’t access or incorporate AI/ML are at a disadvantage. The democratization of AI is a term that, in a nutshell, means leveling the playing field by making the advantages of AI available to all, and it’s an important aspect of the larger project of the ethical development of technology.

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How Influential Businesses like Google Are Using Artificial Intelligence and What We Can Learn from Them

AI is a hot buzzword right now and businesses of all shapes and sizes are trying to find a way to leverage its power for their own particular needs. Exciting, futuristic, and vaguely science-fictiony, AI is currently seen as a must-have tool for turbo-charging one’s business and improving the quality of customer experience. It’s been a game changer for enterprise companies like Google, Microsoft, Amazon, and IBM who have the computing power and resources to access field experts. Small companies often aren’t in the same ball game, yet there remains the need to get in the action if they are going to keep up with the times. Fortunately, cloud computing and open-source machine learning APIs are bridging the technical gap for smaller companies, making it possible for them to take advantage of the endless possibilities offered by AI. More than ever, this is the time for small businesses to jump in and start experimenting. The real challenge, however, is knowing how to utilize these new resources well. Here again, small businesses can look to larger enterprise companies, such as Google, to gain insight and build on their ideas. Here’s what we can learn.

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Arcbees Acquires Chalifour Digital Solutions


Québec, October 2, 2017– Arcbees, a leading technology company in artificial intelligence, announces the strategic acquisition of Chalifour Digital Solutions. This transaction will broaden the company’s areas of expertise, focus joint development efforts and strengthen its market positioning in intelligent business solutions.

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3 AI Fails and Why They Happened

In little over a decade, AI has made leaps and bounds. Every day, new headlines showcase the most recent advancement in AI. In fact, advancements are accelerating:

  • 2004 DARPA sponsors a driverless car grand challenge. Technology developed by the participants eventually allows Google to develop a driverless automobile and modify existing transportation laws;
  • 2005 Honda’s ASIMO humanoid robot is able to walk as fast as a human, delivering trays to customers in a restaurant setting. The same technology is now used in military robots;
  • 2007 Computers learned to play a perfect game of checkers, and in the process opened the door for algorithms capable of searching vast databases of information;
  • 2011 IBM’s Watson wins Jeopardy against top human champions. It is currently training to provide medical advice to doctors. It is capable of mastering any domain of knowledge;
  • 2012 Google releases its Knowledge Graph, a semantic search knowledge base, likely to be the first step toward true artificial intelligence;
  • 2013 Facebook releases Graph Search, a semantic search engine with intimate knowledge about Facebook’s users, essentially making it impossible for us to hide anything from the intelligent algorithms;
  • 2013 BRAIN initiative aimed at reverse engineering the human brain receives 3 billion US dollars in funding by the White House, following an earlier billion euro European initiative to accomplish the same;
  • 2014 Chatbot convinced 33% of the judges that it was human and by doing so passed a restricted version of a Turing Test;
  • 2015 Single piece of general software learns to outperform human players in dozens of Atari video games;
  • 2016 Go playing deep neural network beats world champion.

Source: Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures, https://arxiv.org/pdf/1610.07997.pdf

However, little information is shared on the failures in AI and even less on why they fail.

Failure is king

Failure is at the core of human advancement. For example, the microwave’s invention was a failed attempt at making a military grade radar during WW2. Percy Spencer noticed a melting chocolate bar in his pocket while working on magnetrons for Raytheon, a major U.S. defense contractor.

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A Guide to Working Remotely, as a Team.

How half our team traveled abroad for two weeks and still stayed productive.

We’re no strangers to working remote.

Back in October, I worked from Banff, Alberta because I am passionate about climbing mountains. (Summits are awesome!)

Our Branding Goddess and Design Adventures, Manon, spent 4 months working remotely while traveling the world last year. She wrote all about it in this great guide.


This year, we pushed the concept further. Eight of us moved to Puerto Rico for two weeks and still managed to produce great results. Here is how we did it and what we learned.

Continue reading “A Guide to Working Remotely, as a Team.”

A Non-Technical Guide To Understanding Machine Learning

In last week’s post, we discussed if machine learning was right for your business. As part of that effort, I recently went through the process of learning the ins-and-outs of machine learning and realized most information out there is technical and aimed at developers or data scientists.

I thought an explanation from a non-technical person might be of interest.

Let’s begin.

What exactly is machine learning?

The simplest definition I came across:

Machine learning is “[…] the branch of AI that explores ways to get computers to improve their performance based on experience”. Source: Berkeley

Let’s break that down to set some foundations on which to build our machine learning knowledge.

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Is Machine Learning Right For Your Business?

Most businesses recognize that machine learning can generate exceptional value but many still wonder how, in what specific areas, and if the time is right to integrate it within their data strategy. Today, we explore what questions you should be asking to know if machine learning is right for your business. Continue reading “Is Machine Learning Right For Your Business?”

Web Developer

Want to join our team? We’re looking for a Web Developer! Send your application to queenbee@arcbees.com.

At Arcbees, you will have to develop web and mobile solutions by utilizing several languages (Java, TypeScript and friends) in an environment where amazing coding skills meet an unmatched sense of humour. To be part of the Arcbees team, you will have to demonstrate your extraordinary potential and your motivation to become a coding god (just like Gohan looking for Old Kai). Continue reading “Web Developer”

How we used GWTP in Ruxit

When we initially considered options for developing Ruxit, we were faced with extremely high expectations from our executive team. We were tasked with creating the coolest, most modern, and responsive Web UI design possible. We were convinced that our goals could only be achieved through a client-side UI approach, so we started out with a vanilla JavaScript approach. However, because the Ruxit UI is so complex in terms of the number of elements, the amount of asynchronous communication between the browser and the backend, and the fact that we had multiple teams in three countries contributing to our UI, we recognized after about six months that our development approach couldn’t really handle the complexity of Ruxit. All was not lost, however…

When looking for a framework to build our codebase on, we came across GWT. Although we didn’t have any prior experience with GWT, we were a team of seasoned Java devs, so it seemed a natural fit for our skillset. Plus it offered the client-side UI building approach we still believed in. Still, a lot of base work was required to build out the basic infrastructure of our application. This is where the GWTP framework came in handy. It made our introduction to GWT much easier and gave us a headstart in development.     Post_GWTP_Story_v2-01

One of the major problems of our vanilla JS solution was that we had to take care of every single piece of application and UI logic ourselves. And, because Ruxit is a single-page application, there was a lot of logic to be tracked. GWTP provides lots of helpful boilerplate functionality like view lifecycles and connecting URLs to corresponding views. GWT is a great technology with a learning curve that’s not too steep. However it does take some time to adjust your mindset to the work approach that’s required for succeeding with GWTP.

As mentioned, GWTP made our start with GWT much easier but at the same time the framework it provides is not restrictive. Yet it covers most of the basics that are needed to successfully get your application up and running. Over the time that we’ve worked with GWTP—which is three years at this point—we’ve never felt that GWTP has constrained us, which is phenomenal. We’re convinced that it’s the balance between structure and freedom that makes GWTP so appealing.


One of our favorite features in GWTP is code-splitting. Sure, code-splitting is included with GWT, but you have to take special care to set the split points right. If you don’t get the split-points right from the beginning, it can be really hard (if not impossible) to introduce them later as the code is usually too tightly bound by then. GWTP’s Model-View-Presenter architecture offers an easy and efficient solution to this problem. By applying MVP, your code automatically comes in the right granularity for code-splitting. Without it, we would likely be in a very bad situation at this point, needing tens of megabytes of UI code to be loaded into the browser right from the start. Instead, when opening a Ruxit view for the first time, only the code required to render the current view is downloaded.

With GWTP your code is typically loosely coupled. The advantage to this becomes apparent once your team and code grow in size. Today we’re about three years into development with GWTP and we’ve grown into six teams spread across three countries with almost 230,000 lines of code checked into our repository. Thanks to GWTP our teams don’t step on each other’s toes; each team only runs the views that are relevant to their work. This makes GWT development much faster and less error-prone.


As we had a considerable amount of backend code running from the vanilla JS version we developed early on, we didn’t want to revise all of it just to match our new GWT frontend. That’s why we decided to stay with JSON for communication between our frontend and backend. With this approach, we were able to re-use nearly 100% of our backend functionality without losing anything. The web really is a great place to be a dev. 🙂

We believe that seeing is believing. So, want to see what can be achieved with GWT and GWTP? Have a look at the screenshots of Ruxit below, or better yet, sign up for a free trial of Ruxit.



We’re very proud of our results with GWTP. Having started several additional projects since then, no one was looking for a new development alternative when a new project came around.

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