How Neural Networks helping industries and big companies like google.
What are neural networks ?
Deep learning or neural networks in a leemman term can be said the advance of machine learning. Neural networks are a set of algorithms, they are designed to mimic the human brain, that is designed to recognize patterns. They interpret data through a form of machine perception by labeling or clustering raw input data.
Let’s take a moment to consider the human brain. Made up of a network of neurons, the brain is a very complex structure.
It’s capable of quickly assessing and understanding the context of numerous different situations. Computers struggle to react to situations in a similar way. Artificial Neural Networks are a way of overcoming this limitation.
🎈Now lets see how google is using ML/DL/AI/NN and becoming moe and more popular🎈
In modern times, Google is everywhere!!! So much so that you are most probably reading this article using Google Search. And while Machine Learning has long been a part of Google, now it seems that ML is everywhere! From Google Search to Google Photos to even Google Translate, everything uses Machine Learning.
And these are only the more common items! In fact, Google and its parent company Alphabet are heavily invested in Machine Learning Research in almost all imaginable fields like Ethical Principles, Quantum Computing, Healthcare, Robotics, Perception, etc. Sundar Pichai, the CEO of Google commented that “Machine learning is a core, transformative way by which we’re rethinking how we’re doing everything. We are thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. And we’re in early days, but you will see us apply machine learning in all these areas.”
So it is obvious that Google eventually plans on fully integrating Machine Learning in all its operations. But that futuristic world is still a little far away! For now, let’s see some of the ways in which Google currently uses Machine Learning so that we can understand the full scope of its applications in the future.
1. Google Translate
Want to translate a text from English to Hindi but don’t know Hindi? Well, Google Translate is the tool for you! While it’s not exactly 100% accurate, it is still a great tool to convert text, images, or even real-time video from one language to another. And in case you wonder how it translates more or less accurately, well Google Translate uses Machine Learning of course!
It uses Statistical machine translation (SMT) which is a fancy way of saying that it analyses millions of documents that are already translated from one language to another (English to Hindi in this case) and then looks for the common patterns and basic vocabulary of the language. After that, it picks the most accurate translation possible based on educated guesses that mostly turn out to be correct. For Example: Let’s see how Google Translate translates “Machine Learning is cool” into Hindi!!!
Image Source: Google
2. Google Photos
In case you are a millennial, I am sure you are a selfie addict! And of course, you use Google Photos a lot if you are an Android user as well. And it’s no shock that you do! Google Photos allows you to back up all your photos in a single location even if they were shot from multiple devices and it also offers lots of other cool effects using Machine Learning.
For Example, Google Photos also automatically creates albums of photos taken during a specific period without any input from you. And that’s not all, it can also select the “best photos”. And in case you haven’t sorted all your pictures into albums, you can also search for them by typing in names. Suppose you want to find a picture with your dog, type in “Dog” and you will get all the dog pictures! This is done using Image Recognition, wherein Deep Learning is used to sort millions of images on the internet in order to classify them more accurately. So using Deep Learning, the images that are classified as “Dog” in your Google Photos are displayed.
3. RankBrain
Suppose you want to know who is the CEO of Google? And then you want to know who is his wife? But how do you search this on Google? You cannot exactly write the name of Sundar Pichai or his wife since you don’t know it! In this case, you can simply search “CEO of google wife” on Google and you will get the required results. This is achieved using RankBrain in Google Search.
Image Source: Google
RankBrain is basically a deep neural network that is helpful in providing the required search results. It is one of the factors in the Google Search algorithm that determines which search pages are displayed. In case there are any unique words or phrases on Google Search (like “CEO of google wife” in our case!) then RankBrain makes intelligent guesses to find which search results fit the situation and filter them accordingly. In fact, RankBrain is currently so important that Google says it is its third most important page ranking factor for the results of a search query.
4. Google Assistant
Want a little help in organizing your calendar? Want to know the best Italian restaurants near your home? Want to book movie tickets on the go? Well, never fear!!! Google Assistant is here to make your life easier! It is basically a personal assistant that is enabled using a combination of Google Knowledge Graph, Image Recognition, and Natural Language Processing.
The Google Assistant is envisioned as a chatbot by Google which can be connected to your phones, TVs, speakers, etc. with the ability to actually have a conversation with you. Here the Google Knowledge Graph provides information gathered from various sources while Natural Language Processing allows the Google Assistant to interact with you and formulate its answers according to your questions.
5. DeepDream
We all know that humans dream? Well, what if computers dream as well?!! This is the premise of Google DeepDream that used convolutional neural networks to find random patterns in various images and amplifies them in different ways. These images can be tweaked in any possible manner using the input data and various parameters so that the results obtained can be funny, weird or even trippy!!!
Image Source: Google
There are multiple layers in the neural networks in DeepDream wherein each layer extracts more and more high-level features from the input image until the final output is produced by the end layer. To demonstrate this, we have an image from Google DeepDream that is a weird hybrid of a woman and lots of gears. All in all, it’s very difficult to just explain the complicated effects of DeepDream so its best that you just try it yourself by uploading any image you want and then just watching the show!
This is normally done by using the algorithms like GANs. one more great example of this you can see by visiting this site
Some Myths related to ML/AI and jobs🙂
🤔Artificial intelligence is becoming good at many “human” jobs — diagnosing disease, translating languages, providing customer service — and it’s improving fast. This is raising reasonable fears that AI will ultimately replace human workers throughout the economy. 🤔
But that’s not the inevitable, or even most likely, outcome. Never before have digital tools been so responsive to us, nor we to our tools. While AI will radically alter how work gets done and who does it, the technology’s larger impact will be in complementing and augmenting human capabilities, not replacing them.
🎇Certainly, many companies have used AI to automate processes, but those that deploy it mainly to displace employees will see only short-term productivity gains. In our research involving 1,500 companies, we found that firms achieve the most significant performance improvements when humans and machines work together. Through such collaborative intelligence, humans and AI actively enhance each other’s complementary strengths: the leadership, teamwork, creativity, and social skills of the former, and the speed, scalability, and quantitative capabilities of the latter. What comes naturally to people (making a joke, for example) can be tricky for machines, and what’s straightforward for machines (analyzing gigabytes of data) remains virtually impossible for humans. Business requires both kinds of capabilities.🎇
“Job profiles would change, not the number of jobs but yes we have to be get upgraded with the new new techs coming in the market”
for eg- when computers came, then it was thought that all human beings would be replaced by computers especially in banks and commerce side BUT reverse happened. computers gave job to millions of people.
Computers were having capability to change world and hence people started learning it. Now in this era, technologies change the world so, we have to learn them.😊
