TechDogs-"Machine Learning For Dummies: Part 2"

Emerging Technology

Machine Learning For Dummies: Part 2

By TechDogs Editorial Team

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Overview

We at TechDogs have an annual Academy Awards tradition of sitting together in front of the TV, munching on popcorn and trying to predict the winner for each category. Well, to be honest, we're not the best at it - but it's great fun! That being said, wouldn't it be really cool if we could correctly predict the winners before the award ceremony - just for the bragging rights!
 
It turns out that a Machine Learning model has been doing precisely that. Unanimous AI, an American tech firm, has been predicting each category's winner with an accuracy of 94 percent! Last year, the model predicted the right winner for 15 out of 16 categories. That's the power of Machine Learning (ML) on display!
 
Read on to understand why modern ML models are so good at predictions, their various industrial applications as well as the future of ML.
TechDogs-Tell Me About...-"Machine Learning For Dummies: Part 2"
We are exposed to Machine Learning (ML) every single day. Don't believe us? Do you use a voice assistant on your smartphone or an online translation service or even online banking? If yes, then you are already reaping the benefits of ML. It might not be very apparent but be assured; it has caused a digital revolution. According to Forbes, Amazon's current ML algorithm reduced the 'click-to-ship' time by a staggering 225%. Similarly, Netflix saved over $1 billion in 2017 after introducing its new ML algorithm.

As we previously said, ML is one of the hottest technologies in the world right now - from space exploration to image recognition to spam mail filtering, the applications of ML literally know no bounds. Part 2 of our Machine Learning series will dive into ML's other aspects, such as its commercial applications, the future outlook and why this technology could be a ticking time bomb for humanity. (If you haven’t read Part 1, give it a try, it totally holds up).

If you have read it already, let's jump right in!
 

The Magic Of Machine Learning


When our laptop or smartphone gets an update, we just tap the "Install Update" button and wait for the device to restart. ML models also need similar updates by adding new code (to the annoyance of programmers!). However, rather than having programmers write lengthy code, the model improves from its own experience. This not only saves time and human efforts but allows for pretty diverse applications across various domains.

Let’s look at some more real-life applications of ML to better understand what we mean and why ML is considered as a game-changer for many industries.
 

Applications Of ML


TechDogs-"Applications Of ML"-3D Image Showing Different Types Of Applications Which Includes Under Machine Learning

Some applications of Machine Learning include:
 

  • Image Recognition

    You might have noticed that whenever you upload a group photo on Facebook, it automatically provides suggestions to tag your Facebook friends visible in the image. This is Facebook's Deep Face algorithm, one of the most commonly used Machine Learning applications. You can thank ML's face detection and image recognition models for this time-saving innovation.

  • Speech Recognition

    Although we might not like to admit it, we have all used voice search to look up something we could have easily typed, had it not been for sheer laziness. That's okay because through the power of ML, we can train models to identify spoken words, convert them to text and generate a search query for those specific words. Google Assistant, Siri, Cortana and Alexa all use speech recognition to follow voice instructions. So, you no longer have to worry about "It's leviOsa, not levioSA!" because ML models know precisely what you mean!

  • Medical Diagnosis

    ML models have made their way into the medical sector, helping doctors predict and identify patients with metastatic cancer i.e., cancer where cells break away from where they were first formed. Comparing the data obtained from a new patient and that from previous cancer patients, the model can accurately predict the presence of cancer cells. This method can be expanded to include other ailments as well.

  • Product Recommendations

    ML is widely used by various Ecommerce and entertainment companies such as Amazon, Netflix, Spotify, etc. These services rely on models that track the users' interests and recommend similar products, TV shows or songs. This is why you might get an advertisement on Facebook for a product you browsed on Amazon, not because Big Brother is spying on you! 

  • Automatic Language Translation

    Thinking of canceling your dream trip to Spain because you can't speak a word of Spanish? Go ahead and book those flight tickets amigo, because ML has got your back. Machine Learning models can use Natural Language Processing (a field where linguistics and ML join hands) to provide the most accurate translation of any sentence, phrase or word in almost any language.  

 

What Else Can A Machine Learn?

 

 
Stating the obvious, yet again: Machine Learning is the next big digital revolution. Experts predict the global ML industry to reach a market value of around US$ 76.8 billion by 2026. Every industry uses some form of Machine Learning in their day-to-day business processes but ML's focus now is to make life simpler for the people.  
 
Ever received ads on your social media feed that bear no relation to your interests? Well, with sophisticated ML models, browsing the Internet will become highly personalized as these models will have more data to tailor ads based on each individual’s interest. These models will also have the ability to recommend products and services better suited to one's lifestyle. Yes, there might just be a Machine Learning model that can tell you if the blue dress fits better than the red one!
 
One of the most exciting future ML applications focuses on interfacing humans with the prowess of Machine Learning. Our favorite eccentric billionaire, Elon Musk, has launched a new project called Neuralink (aren't you glad he didn't name it like X ÆA-12) "to connect humans and computers."

Imagine having a chip implanted into your brain (not the Richmond Valentine kind) that can process information faster and more accurately to guide us with our day-to-day decision making. Other researchers are focusing on refining facial recognition, language and speech understanding, etc., to make ML applications feel and sound more human. “What more can a machine learn?” – that’s a question only time will answer. 


Artificial Intelligence – Coming Soon To Your Nearest Theatre!

 
"Upgrades, people, Upgrades," goes the memorable dialogue from the movie Robots. That's the name of the game for future data scientists and ML researchers. ML models have been learning, evolving, upgrading and then learning some more, making them more precise the longer they operate. However, combining ML with emerging technologies such as IoT, Edge Computing and Cloud Computing will enable us to enhance the current ML applications and take them to the next level – something we call Artificial Intelligence (AI) but that’s a topic for another time. These advanced ML models will be able to tackle as-yet-unchallenged issues, analyzing mountains of data, while we sit back and sip on a nice, hot cup of chamomile tea. The applications of ML are genuinely limitless. 

However, a group of experts, including Elon Musk and the late Stephen Hawking, have raised the issue of Machine Learning possibly being used for military applications in the future. A few Machine Learning models used in recruitment and hiring software have already shown a bias towards a specific gender or region and haven't we seen far too many movies to know why relying on a biased computer isn't a very bright idea! If we do manage to create an AI someday, we sure hope it behaves more like J.A.R.V.I.S. from Iron Man and not Ultron.

Frequently Asked Questions

What are some real-life applications of Machine Learning?


Machine Learning (ML) has permeated numerous aspects of our daily lives, powering technologies we often take for granted. Some notable applications include image recognition, where ML algorithms can identify objects and people in photos, enabling features like automatic tagging on social media platforms. Speech recognition is another significant application, allowing virtual assistants like Siri and Google Assistant to understand and respond to spoken commands. ML also plays a crucial role in medical diagnosis, assisting doctors in predicting and identifying conditions such as cancer based on patient data. Additionally, ML powers product recommendations on platforms like Amazon and Netflix, tailoring suggestions based on users' preferences and behavior. Moreover, ML facilitates automatic language translation, making communication across different languages more accessible and seamless.

How is Machine Learning shaping the future of technology?


Machine Learning is poised to revolutionize various industries, with experts predicting substantial growth in the global ML market in the coming years. ML's focus is on simplifying processes and personalizing experiences for individuals. Sophisticated ML models are expected to enhance internet browsing by providing highly personalized content and recommendations tailored to individual interests. Additionally, future ML applications aim to bridge the gap between humans and computers, with projects like Neuralink aiming to connect brains directly to machines for faster and more accurate decision-making. Researchers are also working on refining technologies such as facial recognition and speech understanding to make ML applications more human-like. The future potential of ML is vast, with ongoing advancements and innovations continually expanding its capabilities.

What are the concerns surrounding the future of Machine Learning?


While Machine Learning holds immense promise, there are also concerns about its potential misuse and ethical implications. Some experts, including figures like Elon Musk and Stephen Hawking, have raised concerns about ML being used for military purposes. Additionally, biases in ML algorithms have been observed in various applications, such as recruitment and hiring software, leading to discrimination based on factors like gender or region. These biases highlight the importance of developing ethical frameworks and regulations to govern the use of ML technologies. As ML continues to advance, it's crucial to ensure that it aligns with principles of fairness, transparency, and accountability to mitigate potential risks and ensure positive societal impacts.

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Machine Learning (ML)Machine Learning Process What Is Ml AI Big Data Data Science Deep Learning IoT Artificial Intelligence Clustering Supervised Learning Unsupervised Learning Reinforcement Learning

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