The Rise of Deep Learning
Deep learning is becoming increasingly used throughout the world of technology, and there are now endless blogs, books, courses and other resources available for those to use. If that’s still not quite good enough for you and you don’t want to implement deep learning yourself…
Deep learning is becoming increasingly used throughout the world of technology, and there are now endless blogs, books, courses and other resources available for those to use. If that’s still not quite good enough for you and you don’t want to implement deep learning yourself, there are now several machine learning API services available that will do it for you. But, where has this rise in deep learning stemmed from you may be wondering?
Big companies use deep learning techniques in various practices throughout their businesses. They generate lots of data, and this is mega important to them as they can learn from this data which will ultimately lead to increased revenue. It’s used to predict who will want to buy what and when and uncover trends before they are even known as trends. The more the company sells, the more data it has to play with.
Microsoft, Amazon, Google, and Facebook all work like this, and all have some form of cloud computing technology to helps them to analyze all that data. This is where deep learning comes in. There are five relevant aspects it relates to when talking about computing mainly and they are: data, computing power, research, software, and Deep Learning tools. Most of these components complement each other, and more of any one of them will make the other stronger.
With these five components in mind, Amazon and Google make a lot of their money from computing power, data in a direct way, and software, whereas the likes of Microsoft tend to concentrate simply on data in a direct way (i.e. selling ML API’s). However, most of them still give out tools and data for free to try and commoditize their research and effectively make more money in the end. Deep Learning research is something that will continue for a long time to come, and it’s up to businesses to start taking advantage of it.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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