Deep Learning is recited among top three technologies of year 2017, which is expected to welcome high demand in next few years. It is predicted that the deep learning market is expected to be worth USD 1772.9 Million by 2022, growing at a CAGR of 65.3% between 2016 and 2022. This article mainly focuses on what is Deep Learning, overview of patentability hurdles for Deep Learning in Europe and USA region and few solutions to overcome the hurdles faced.
Scientific American, in collaboration with the World Economic Forum, published a special report on The Top Ten Emerging Technologies of 2017, which recites Deep Learning among top three technologies which is expected to welcome high demand in next few years, based on selection by Global Panel Experts. 
Although deep learning is not a new technique, having its roots in 1943, when Warren McCulloch and Walter Pitts create computational model for neural networks based on mathematics and algorithms called threshold logic, it caught major attention and resurgence of interest only after Google DeepMind's algorithm, AlphaGo masters art of the complex board game Go, and beats the professional go player, Lee Sedol at a highly publicized tournament in Seoul, in 2016. 
Deep learning aka deep structured learning or hierarchical learning is branch of machine learning based on learning data representations rather than task-specific algorithms. Learning can be supervised, partially supervised or unsupervised. Deep learning or Artificial intelligence was once part of thriller and Science Fictions, who can forgot the Arnold Schwarzenegger's Terminator, but now it is a reality and is currently being used in various areas like healthcare, education, and finance in a very impressive way. Scientists had used deep learning algorithms with multiple processing layers (hence "deep") to make better models from large quantities of unlabeled data (such as photos with no description, voice recordings or videos on YouTube).
Deep learning is a topic that is making big waves at the moment. Google's search engine, voice recognition system and self-driving cars all rely heavily on deep learning. Google has also created one program that picks out an attractive still from a YouTube video to use as a thumbnail.
According to a market research report on deep learning, this market is expected to be worth USD 1772.9 Million by 2022, growing at a CAGR of 65.3% between 2016 and 2022. Report also indicates the advertisement, finance, and automotive as the major drivers for the growth of the market . Many companies has invested their time and research to take advantage of speed and quality of Deep learning algorithm for expanding their business to a newer heights or in dynamic areas. Hence it is necessary, to protect their intellectual property.
IP issues mainly have two business objectives, first one is maintaining freedom to operate without violating third-party rights, and protecting own investments in AI research and development. As deep learning is basically a computer algorithm to collect, recognize, analyze and/or categorize the audio or visual, mathematical data, it is non-patentable generally in majority of countries, leaving it as "open to use" invention although it demands tremendous development efforts.
For example, processing of a digital sound recording to clean the recording of noise would be considered "technical"; processing row entries in a database of information technology assets to remove duplicates for licensing purposes would likely be considered "non-technical"
For example, machine learning algorithm that adaptively arranges icons on a smart phone according to use may receive objections on the grounds that features relate to mathematical methods (the algorithm) and presentation of information (the arrangement of icons on the graphical user interface)