Neural Networks — Industry Use Cases
8 min readJun 17, 2022
WHAT ARE NEURAL NETWORKS ???
- Neural networks, as the name defines, are modeled on neurons in the brain, they use artificial intelligence to untangle and break down extremely complex relationships & patterns.
Neural network as a black box —
- A supervised neural network, at the highest and simplest representation, can be presented as a black box with 2 methods learn and predict as following :
- A neural network is a network of equations that takes in an input (or a set of inputs) and returns an output (or a set of outputs).
- The learning process takes the inputs and the desired outputs and updates its internal state accordingly, so the calculated output get as close as possible to the desired output.
- The prediction process takes an input and generate, using the internal state, the most likely output according to its past “training experience”, that’s why machine learning is called sometimes model fitting.
- With their brain-like ability to learn and adapt, Neural Networks form the entire basis and have applications in Artificial Intelligence & consequently, Machine Learning algorithms.
Types of Neural Networks —
- Neural networks have advanced so much that there are now several types of neural networks, but below are the three main types of neural networks that you’ll probably hear about often :
Artificial Neural Networks (ANN) :
- Artificial neural networks, or ANNs, are like the neural networks in the images above, which is composed of a collection of connected nodes that takes an input or a set of inputs and returns an output.
- This is the most fundamental type of neural network that you’ll probably first learn about if you ever take a course.
Convolutional Neural Networks (CNN) :
- A convolutional neural network (CNN) is a type of neural network that uses a mathematical operation called convolution.
- Wikipedia defines convolution as a mathematical operation on two functions that produces a third function expressing how the shape of one is modified by the other.
- Thus, CNNs use convolution instead of general matrix multiplication in at least one of their layers.
Recurrent neural networks (RNNs) :
- Recurrent neural networks (RNNs):are a type of ANNs where connections between the nodes form a digraph along a temporal sequence, allowing them to use their internal memory to process variable-length sequences of inputs.
- Because of this characteristic, RNNs are exceptional at handling sequence data, like text recognition or audio recognition, Real-World Applications.
Real Industry Use Cases In Multiple MNC’s :
1) Google
- Google has been a powerful force in championing the use of Deep Learning — A technology now so prevalent in cutting edge applications that its name is pretty much synonymous with artificial intelligence.
- Deep Mind(UK based Deep Learning startup Acquired in 2014) pioneered work in connecting existing machine learning techniques to cutting edge research in neuroscience, leading to systems which more accurately resembled “real” intelligence (I.E brains).
- Deep Mind was responsible for the creation of Alpha Go, which used video games, and later the board-game Go, to demonstrate the ability of their algorithm to learn how to carry out a task and become increasingly good at it.
- Google Cloud Video Intelligence focuses on opening up video analytics to new audiences. Video stored on Google’s servers can be segmented and analyzed for content and context, allowing automated summaries to be generated, or even security alerts if the AI thinks something suspicious is going on.
- Google Assistant speech recognition AI uses deep neural networks to learn how to better understand spoken commands and questions , It’s Translation Service was also put under the umbrella of Google Brain.
- Google’s self-driving car division “Waymo”, has incorporated deep learning algorithms into their autonomous systems, in order to make self-driving cars more efficient at analyzing and reacting to what is going on around them.
- Deep Mind is currently working on healthcare-focused projects involving detecting early signs of eye damage, and cancerous tissue growth.
- Google has been an effective force in pioneering, championing and bringing deep learning to the masses.
2) APPLE
- Apple, one of the world’s largest technology companies, selling consumer electronics such as iPhones and Apple Watches, as well as computer software and online services.
- It’s SIRI (Smart Assistant) — Machine Learning in it drives several aspects from speech recognition to attempts by Siri to offer useful answers, etc.
- Machine learning is used to help the iPad’s software distinguish between a user accidentally pressing their palm against the screen while drawing with the Apple Pencil.
- Apple’s software and hardware updates over the past couple of years have emphasized Augmented Reality features that were made possible by using Machine Learning.
- Apple Watch, just like a health monitoring device, that comes with ECG which helps to monitor any irregular rhythm and to alert you immediately in case of any impending danger with help of AI / ML approach in it.
- Apple’s Neural Engine, which allows Apple to implement Neural Network and Machine Learning in a more energy-efficient manner than using either the main CPU or the GPU.
3) FACEBOOK
- Facebook builds its business by learning about its users and packaging their data for advertisers, It then reinvests this money into offering us new, useful functionality.
- Textual Analysis : Facebook uses a tool it developed itself called DeepText to extract meaning from words we post by learning to analyze them contextually, Neural networks analyze the relationship between words to understand how their meaning changes depending on other words around them.
- Facial Recognition : Facebook uses a DL application called DeepFace to teach it to recognize people in photos, It says that its most advanced image recognition tool is more successful than humans in recognizing whether two different images are of the same person or not , with DeepFace scoring a 97% success rate compared to humans with 96%.
- Targeted Advertising : Facebook uses deep neural networks , the foundation stones of deep learning , to decide which adverts to show to which users.
- Designing AI Applications : Facebook has even decided that the task of deciding which processes can be improved by AI and Deep Learning can be handled by machines.
- A system called Flow has been implemented which uses Deep Learning analysis to run simulations of 300,000 machine learning models every month, to allow engineers to test ideas and pinpoint opportunities for efficiency.
4) AMAZON
- Amazon Go : Go is Amazon’s cashier-less grocery and it’s latest algorithmic venture. To figure out what items the shopper is picking up they are relying a bank of video cameras (an alternative may have been to use barcodes, RFID on items to figure out what is being shopped) — to build a profile (3D).
- This helps in tracking arms and hands as they are being used to handle and pick products from the shelves, and bill customers when they walk with their selections from the store.
- Fulfillment Centers : Robots shuffle ‘pods’, algorithmically, inside Amazon’s giant warehouses — in fenced off areas. Amazon associates interact with the robots/pods in specially created gaps on the fence.
- AI & algorithms work relentlessly to optimize the delays and efficiencies of product movement using the combination of Robots, Pods and Associates towards the goal of speedier product delivery.
- Amazon Alexa : Virtual Assistant AI Technology, capable of voice interaction, music playback, making to-do lists, setting alarms, streaming podcasts, playing audiobooks, and providing weather, traffic, sports, and other real-time information, such as news.
- Alexa can also control several smart devices using itself as a home automation, Data and Machine Learning is the foundation of Alexa’s power.
- AWS (Amazon Web Services) : AWS offers the broadest and deepest set of machine learning services and supporting cloud infrastructure, putting machine learning in the hands of every developer, data scientist and expert practitioner.
- It’s AI,ML & Deep Learning Frameworks are quite powerful.
- It uses the same deep learning technology that powers Amazon.com and their ML Services.
5) MICROSOFT
- Tech giant Microsoft is at the forefront of developing the AI tools and services that are increasingly being adopted into all areas of business and society.
- Microsoft has been building intelligent functionality into many of its products and services.
- Microsoft 365 [AI to simplify work and life] : Across Microsoft 365, AI powers innovative apps that can help you write and design better, visualize maps and charts in Excel and streamline user inbox, AI makes Office apps easier to use, more collaborative & more secure.
- Cortana [Personal Productivity Assistant] : It leverages AI for natural language interactions across Microsoft 365 — can use spoken requests to send messages, check schedules, join meetings, add tasks, and more. From helping an individual to prepare for meetings to managing the inbox hands-free, it helps user to focus on what matters and save time.
- Bing uses AI to make it even easier to find what a user is looking for. With its powerful understanding of the web, it gives quick, well-rounded answers, even when a user questions are nuanced. It also lets user to search within an image so he/she can find what they see.
- Multiple AI powered apps such as : MyAnalytics, Power BI, Schedular, Microsoft Pix, etc are provided by Microsoft that uses AI / ML & Deep Learning in the core.
- Microsoft Azure’s Machine Learning services empowers user with most advanced machine learning capabilities on cloud.
- Quickly and easily build, train and deploying machine learning models by user by using Azure Machine Learning, Azure Databricks and ONNX Runtime which Optimizes and accelerates ML inferencing and training.
- Also it Develop models faster using automated machine learning & Managing the user ML models across the cloud and the edge.
- Similarly in every sector “ Neural Network ” is playing a very important role to solve multiple problems which were impossible at a time & it still have so much exciting future ahead.
- Thank You for reading.
