What is Deep Learning?
If you’ve explored the possibilities of AI for your business, you’re likely to have encountered the term, ‘deep learning’. Deep learning is complex, but the core tenets can be explained in relatively simple terms. The more information analysed by a bot, the greater its capacity to learn. The learning process is therefore very similar to that of the human brain. Deep learning provides the means for a bot to make advanced, independent decisions.
How Does Deep Learning Work?
AI works in a way that is more similar to the human brain than traditional computers. Humans learn by finding a certain subject and grounding themselves in the basic fundamentals. This gives us the foundation to pursue a deeper knowledge of the subject. In a similar vein, bots learn progressively and by experience. Over time, a bot will gain a deeper and more nuanced understanding of the information it analyses. The human brain contains large networks of neurons. These neurons pass electrical impulses to each other, helping the brain to process stimuli. In comparison, bots utilise an ‘artificial neural network’ to make sense of information. These artificial neurons are referred to as ‘layers’. When a bot receives complicated data, they pass it between these layers to help process it. Deep learning is the means through which these networks analyse data. The more data interpreted by a bot’s neural network, the more its ability to learn grows. This also means that more layers will be required to process complex information. The depth of these layers is where the term ‘deep learning’ originates.
What is the Difference Between Deep Learning and Machine Learning?
Rather than being two separate entities, deep learning is better understood as a subset of machine learning. Machine learning is the process through which bots ‘learn’ like humans. The main difference between deep learning and machine learning is human intervention. With machine learning, if the bot makes an incorrect calculation it will be adjusted by an engineer. With deep learning, however, the bot itself can determine if it is incorrect. Its neural network is capable of making autonomous decisions. To learn more about machine learning, you can read our article ‘What is Machine Learning?’
Deep learning in daily life
Artificial intelligence is becoming more and more present in our lives. What may not be obvious, however, is the extent to which deep learning shapes our experiences with AI. Here are a handful of examples of how deep learning has transformed online services:
Personalisation is key to the success of today’s brands. Service providers are able to customise the online experience to suit each customer. Two notable examples are Netflix and ASOS. Netflix is able to suggest new shows for regular customers. Similarly, ASOS recommends certain clothes based on a customer’s recently viewed items. Both of these service providers have been fed data based on your browsing habits. The more you use these services, the better the level of personalisation becomes.
Some people have noticed that, when uploading a photograph to Facebook, the website will automatically suggest a tag. This is because every time somebody is tagged in a photo, Facebook receives data that puts names to faces. The technology is still not 100% accurate – a new hairstyle is a common stumbling block – but over time Facebook’s AI has become better and better at recognising faces.
Voice assistants such as Siri and Cortana have two main functions. Not only do they have to understand instructions, but they also have to translate a person’s voice. The more commands an assistant receives, the easier it can discern vocal instructions. The technology is becoming widespread but is still in a relative state of infancy. For instance, voice assistants can still struggle to understand certain accents and dialects. You can learn more about voice assistants in our article ‘What is Voice User Interface?’
At first, chatbots were only able to understand rudimentary queries. Any slight ambiguity would lead to confusion. There’d also be no escalation in response. Instead, they’d repeat the same answer – “sorry, I don’t understand.” Whereas now, when a company uses chatbots, they’ll be programmed with data from past interactions. So, as chatbots communicate with people over time, they’ll be able to help with more complex issues. Artificial intelligence can do more and more for your business, thanks to deep learning. The longer you use AI, the more potential it has to transform workflow and engagement. If you’re interested in harnessing the power of AI, you should start considering it today. Contact We Build Bots to learn more about what AI can do for you.