How MNCs Are Leveraging The Power Of Neural Networks
Today, Neural Networks have brought a next-level revolution in the field of Artificial Intelligence.
No one could have imagined what would happen when machines will be given the same intelligence and the way of operating like that of a human mind. And one can clearly see, it has ended so well that now machines are trained to learn, recognize patterns, and make predictions in a humanoid fashion as well as solve problems in every business sector.
In this article, you will find some of the greatest use-cases of Neural Networks and you will also get to know how some of the biggest MNCs are leveraging the power of Neural Networks in today’s world.
What are Neural Networks?
A branch of machine learning, neural networks (NN), also known as artificial neural networks (ANN), are computational models, essentially algorithms. Neural networks have a unique ability to extract meaning from complex data to find patterns and detect trends that are too convoluted for the human brain or for other computer techniques.
Neural networks have provided us with greater convenience in numerous ways, including through ridesharing apps, Gmail smart sorting, and suggestions on Amazon.
“Human brains and artificial neural networks do learn similarly,” explains Alex Cardinell, Founder and CEO of Cortx, an artificial intelligence company that uses neural networks in the design of its natural language processing solutions, including an automated grammar correction application, Perfect Tense.
The architecture of Artificial Neural Networks
ANNs are statistical models designed to adapt and self-program by using learning algorithms in order to understand and sort out concepts, images, and photographs. For processors to do their work, developers arrange them in layers that operate in parallel.
The input layer is analogous to the dendrites in the human brain’s neural network. The hidden layer is comparable to the cell body and sits between the input layer and output layer (which is akin to the synaptic outputs in the brain).
The hidden layer is where artificial neurons take in a set of inputs based on synaptic weight, which is the amplitude or strength of a connection between nodes. These weighted inputs generate output through a transfer function to the output layer.
Top MNCs Using Neural Networks
Here are the top MNCs that are using Neural Networks and Machine Learning at its best:
Google is known to be the greatest and the most advanced company when it comes to the field of AI and Machine Learning.
The main reason for this is probably the amount of money the company has spent acquiring startups — Google has spent more than any other, according to CB Insights.
Google is taking complete advantage of Neural Network, deep learning and AI. Google had launched multiple AI chatbots that answer messages for you — like a more sophisticated auto-response email — in a range of contexts, including Skype, Slack and Twitter direct messages.
But Google’s strongest point in this area is probably the range of cloud-based services it offers developers, including the Google Cloud AI machine learning tools.
2. Baidu
Another company which has been very active in the mergers and acquisitions scene is Chinese search giant Baidu.
The company is particularly interested in natural language processing, with a view to developing a workable voice-activated search function.
One of the many machine learning acquisitions Baidu made was Kitt.ai, which is said to have a portfolio of chatbots and voice-based applications. The financial terms of that particular deal were not disclosed but Baidu is said to be the 10th biggest-spender on acquisitions in the world, according to CB Insights, which says Google spends the most.
3. Apple
There might be a perception that Apple is late to the machine learning party, but that’s probably not true, especially since it was the first to launch a voice assistant on a smartphone.
Millions of people talk to Siri, even if we don’t, and Apple is looking to extend the application of the talking assistant through its new smart home device or speaker, the HomePod.
Apple has also been active in acquisitions — second only to Google.
One of the more notable purchases has been Lattice Data, which has a machine learning system for converting unstructured data — like random text and pictures — into structured data.
4. Microsoft
Microsoft was actually the third-biggest spender on acquisitions over the past few years, according to CB Insights.
The company is well and truly into the internet market, especially after its $26 billion purchase of LinkedIn a couple of years ago.
But probably the most significant acquisition Microsoft made in the machine learning space was Maluuba, which the tech giant says has “one of the world’s most impressive deep learning research labs for natural language understanding”.
Conclusion
The computing world has a lot to gain from neural networks. Their ability to learn by example makes them very flexible and powerful.
Furthermore, there is no need to devise an algorithm in order to perform a specific task; i.e. there is no need to understand the internal mechanisms of that task. They are also very well suited for real-time systems because of their fast response and computational times which are due to their parallel architecture.
At last, even though neural networks have a huge potential, we will only get the best of them when they are integrated with computing, AI, fuzzy logic and related subjects.
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