Therein lies the challenge with today’s chatbots. The way we ask for their help – through text, not speech – is unnatural for humans. Which makes sense. We’ve been muttering and grunting at each other for at least 100,000 years, but writing things down for only 5,000 of them.
Text-based messaging works best with a human on both sides of the conversation. Humans understand the context, intent and sentiment of other humans. A conversation with a text-based chatbot lacks human emotion, clarity, and urgency. Surely there must be a better way?
As we enter the second year of the bot industry, entrepreneurs and investors are wondering about how bots will generate revenue and become sustainable businesses. In this article reviews the direct and indirect ways that bots can drive revenue to a business. It is important to note that this is far from a comprehensive list, as I am sure entrepreneurs will come up with many other ways to make money in this industry.
To create a chatbot, there is currently an incredible amount of platforms and tools, with different complexity levels, expressive powers and integration capabilities. Let’s suppose you want to develop a chatbot. The million-dollar question is: among all the existing platforms, which one fits my needs the best?
More than 5 billion people have access to SMS text messaging — far more than for our newer communication channels: Facebook, WhatsApp, Facebook Messenger, Instagram, Twitter or Skype. Furthermore, that number is still rising and is expected to peak in 1–3 years before it begins a slow decline over a several year period. Learn about the challenges and opportunities this presents.
We frequently hear about Machine Learning in the media, especially since the recent wave of interest in deep-learning. The perpetual improvement of Machine Learning techniques combined with the ever increasing amount of data that are stored suggests endless new applications. This article provides tips on choosing the right ML algorithm to solve your problem with minimal effort.