In the previous blog, we studied Tech opportunities in systems software like Java Developer and Python development. I hope you go to this blog and all my last blogs related to System software, this is the Blog 4 of the System Software series
Here we will be going to learn about this technologies role in prominent companies or the use of this system software in many other tech-renowned or white label companies like IBM, MANG (Meta, Apple, Netflix, Google) and many more.
“Artificial Intelligence is in a golden age and solving problems that were once in the realm of science fiction. ” By Jeff Bezos
The global artificial intelligence (AI) market size was valued at US dollars 328.34 billion in 2021. The market is projected to grow from $387.45 billion in 2022 to $ 1,394.30 billion by 2029, exhibiting a CAGR of 20.1% during the forecast period.
So we have a bright future in Artificial Intelligence (A.I)
So talking more about those companies which are working in AI subdivision domains like machine learning, deep learning etc.
The companies which are focussing on ML(Machine Learning) are
Netflix Machine Learning
When we have the urge to watch some latest movies, shows, and popular web series of different countries but we are usually baffled or in a fix on what to choose from more than 25,000 of content**. However, Netflix provides solutions to this problem to more than 250 million subscribers (till the end of 2022) all over the globe. It helps us to decide which web series to watch according to our likes or dislikes from the pack of 25000 content streaming on Netflix**. It helps us to sort out this chaos by using Machine Learning and its different applications which give users suggestions, catered specifically to their unique interests.
Recommendation System
Creation
High Streaming Quality
Locations for the Shows
Apple Machine Learning
We all know that Apple electronic gadgets like android phones, MacBooks and tabs are quite popular worldwide. Apple's net worth as of August 12, 2022, is $2765.78B. Apple's business primarily runs around its flagship iPhone. However, the Services portfolio also includes various cloud services, App store, Apple Music, AppleCare, Apple Pay & licensing and various other services which become the cash cow.
Speech Recognition :
Used by Siri to give accurate answers to a user query.
Photo Apps:
Used in photos apps to automatically sort images into pre-define galleries, or to accurately give you photos of a friend named Selina when her name is entered into the app's search field.
Over the past decades, Apple performs machine learning tasks locally on the device, on hardware like the Apple Neural Engine (ANE) or the company's custom-designed GPUs (graphics processing units).
Meta (Earlier known as Facebook) Machine Learning
Meta is formerly known as Facebook. The company owns Facebook, Instagram, and WhatsApp, among other products and services. Meta is one of the most valuable/profitable companies. In 2022 net income of meta is US$41.270 billion and the total assets of meta are US$178.587 billion.
Blocking Offensive Content:
Meta makes use of machine learning and natural language processing to screen for and also remove disrespectful material such as sexual and violent content.
Virtual Reality Immersion:
Meta state uses computer vision algorithms to follow user movement in real-time for its Oculus product.
To Deliver Adds :
Meta uses different technologies to deliver advertisements.
Engagement Graph:
Any user's activities on Instagram help the ML algorithms to build a graph of their favourites, which is known as the User Engagement Graph. Each node in the graph represents content that the user has shown an explicit interest in. These nodes also represent seed accounts or accounts that the users have interacted with by liking or commenting on their or other posts.
Ranking System:
People have expectations for the type of content that each part of the app shows to them. They expect to see content from friends and family in their Stories, while the Explore page is meant for finding quality content from users they do not follow.
Google Machine Learning
Google is one of the most popular search engines but google is not only about search engines it’s much more than that. Products are Gmail, YouTube, maps, photos, drives, etc. At the end of 2022, Google's net worth will be more than USD 1450 billion.
Google Assistant(Alexa)
Translate
Maps
Google Search
Gmail
Google Photos and Music
Reverse Image Search
Google Adsense
Google Aword
IBM Machine Language
Inventions by IBM also include the automated teller machine (ATM), the floppy disk, the hard disk drive, the magnetic stripe card, the relational database, the SQL programming language and dynamic random-access memory (DRAM).
IBM produces and sells various computer hardware, middleware and software and provides hosting and consulting services in areas ranging from mainframe computers to nanotechnology.
It is also a major research organization, holding the record for most annual U.S. patents generated by a business for 30 consecutive years.
IBM, net worth is more than USD 120 billion
A Decision Process: In general, machine learning algorithms are used to make a prediction or classification. Based on some input data, which can be labelled or unlabeled, your algorithm will produce an estimate of a pattern in the data.
An Error Function: An error function serves to evaluate the prediction of the model. If there are known examples, an error function can make a comparison to assess the accuracy of the model.
A Model Optimization Process: If the model can fit better to the data points in the training set, then weights are adjusted to reduce the discrepancy between the known example and the model estimate.
The algorithm will repeat this evaluation and optimisation process, updating weights until the accuracy has been met.
I will be discussing, different technologies in a very detailed manner in the coming and their demand in the Tech Field. I will be posting The next blog soon and much other information related to this. If you have any queries please write them down in the comment box. And please like and share this. Stay tuned, and Stay Techcurious!