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Top 10 Interesting ML Dissertations From Ph.D. Students

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Top 10 Interesting ML Dissertations From Ph.D. Students

This article features the top 10 ML dissertations for Ph.D. students to try in 2022.

Choosing interesting dissertation topics in ML is the first choice of Master’s and Doctorate scholars nowadays. Ph.D. candidates are highly motivated to choose research topics that establish new and creative paths toward discovery in their field of study. Selecting and working on a dissertation topic in machine learning is not an easy task as machine learning uses statistical algorithms to make computers work in a certain way without being explicitly programmed. The main aim of machine learning is to create intelligent machines which can think and work like human beings. This article features the top 10 ML dissertations for Ph.D. students to try in 2022.

Text Mining and Text Classification: Text mining is an AI technology that uses NLP to transform the free text in documents and databases into normalized, structured data suitable for analysis or to drive ML algorithms. This is one of the best research and thesis topics for ML projects.

Recognition of Everyday Activities through Wearable Sensors and Machine Learning: The goal of the research detailed in this dissertation is to explore and develop accurate and quantifiable sensing and machine learning techniques for eventual real-time health monitoring by wearable device systems.

Computer Vision: Computer Vision is a field that deals with making systems that can read and interpret images. In computer vision, data is collected from images that are imparted to systems. The system will take action according to the information it interprets from what it sees.

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Voice Classification: Voice classification or sound classification can be referred to as the process of analyzing audio recordings. Voice and Speech Recognition, Signal Processing, Message Extraction from Voice Encoded, etc are the best research and thesis topics for ML projects.

Deep in-memory computing: There is much interest in embedding data analytics into sensor-rich platforms. Such platforms often need to implement machine learning (ML) algorithms under stringent energy constraints with battery-powered electronics.

Object Detection with Deep Learning: Object Detection with Deep Learning is one of the interesting machine learning projects to create. When it comes to image classification, Deep Neural Networks (DNNs) should be your go-to choice. In this Machine Learning project, you will solve the problem of object detection by leveraging DNNs.

Algorithms and analysis for non-convex optimization problems in machine learning: This dissertation proposes efficient algorithms and provides theoretical analysis through the angle of spectral methods for some important non-convex optimization problems in machine learning. In this research, a novel algorithm is proposed that can flexibly learn a multi-view model in a non-parametric fashion.

Supervised Machine Learning: It is a good topic for ML dissertation Ph.D. students. It is a type of machine learning algorithm which makes predictions based on known data sets. Supervised Learning is further classified into classification and regression problems.

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Collaborative detection of cyberbullying behavior in Twitter data: It is critical to efficiently detect cyberbullying behavior by analyzing tweets, in real-time if possible. This dissertation proposes a new approach called the distributed-collaborative approach for cyberbullying detection.

Bayesian Network: It is a network that represents probabilistic relationships via Directed Acyclic Graph (DAG). There are algorithms in Bayesian Network for inference and learning. Bayesian Network finds its application in bioinformatics, image processing, and computational biology.

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Artificial Intelligence Market Size To Reach US$407 Billion By 2027

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Artificial Intelligence Market Size To Reach US$407 Billion By 2027

The artificial intelligence market size is driven by big data, cloud applications, and services

Artificial Intelligence is inarguably the most popular technology right now. The artificial intelligence market size is expected to grow from US$86.9 billion in 2022 to US$407 billion by 2027, at a Compound Annual Growth Rate (CAGR) of 36.2% during the forecast period. The three main growth drivers are an increase in big data, cloud application and service usage, and demand for intelligent virtual assistants.

The year 2050 is marked by experts as the year when AI will be able to perform every kind of human activity. Already intelligent machines are contributing significantly to the daily operations of big and critical industries. For instance, the information security world is forever short on skilled human capital which eventually exposes systems to criminality. But with the intrusion of AI, the scene has drastically changed with the first-generation AI solutions providing value creation from massive data and threat detection features.

The rate of progress and development in AI has been intermittent and unpredictable. There have been significant advances in technology since its inception. It is an over-arching concept that entails multiple disciplines and is transforming every walk of life. Organizations are already implementing AI for numerous business applications. If deployed effectively, the technology provides real-time data gathering, forecasting, and trend analysis for delivering greater insight.

The growth of the AI market can be attributed to the rapid surge in cybersecurity incidents and ransomware attacks across the globe during the COVID-19 pandemic, the increasing need for new use cases for businesses such as interactive games, decision support, and real-time retail recommendation engines, is expected to drive the artificial intelligence market size growth. North America is expected to account largest market share during the forecast period. The region is one of the leaders in technological advancements and is home to major AI providers.

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A Brief History Of Manufacturing Robots

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A Brief History Of Manufacturing Robots

Manufacturing robots are a relatively new technology, but they have quickly become integral to many factories and manufacturing plants. While the first industrial robot was designed in the early 1960s, it wasn’t until the late 1990s that manufacturing robots began to be widely used. In this article, we will briefly examine the history of manufacturing robots and explore some of the factors that have led to their growing popularity.

 

The history of robotics can be traced back to the early 1800s

The origins of robotics can be traced back to the early 1800s when scientists began experimenting with automatons, or self-operating machines. In the following decades, these rudimentary robots were developed into increasingly complex machines, capable of performing a variety of tasks.

In the 1950s, the field of robotics took off, thanks to pioneers like George Devol and Joseph Engelberger. Devol’s invention of programmable universal automation controllers laid the groundwork for modern industrial robots, while Engelberger’s company, Unimation, built the first robot arm used in factories.

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Today, robots are integral to many industries, from automotive manufacturing to healthcare. And as they continue to evolve, it is clear that the history of robotics is only just beginning.

 

Industrial robots began appearing in factories in the 1950s

Industrial robots are machines that are used to perform tasks that are typically too difficult or too dangerous for humans. They began appearing in factories in the 1950s, and their use has been steadily increasing ever since.

Today, industrial robots can be found in a wide variety of settings, from car assembly plants to food processing facilities. In many cases, they have significantly improved efficiency and safety. For example, robotic welding arms can work faster and more accurately than human welders, and they are less likely to suffer from fatigue or make mistakes.

As industrial robots continue to become more sophisticated, their use will likely become even more widespread in the years to come.

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Modern manufacturing robots are much more sophisticated

The manufacturing industry is one of the most important sectors of any economy. It produces various goods, from food and clothing to vehicles and electronic devices. In recent years, there has been a shift towards automation in manufacturing, with robots increasingly being used to carry out tasks that human workers previously carried out. This has resulted in a significant increase in productivity and efficiency and a reduction in costs.

The latest generation of robots is even more sophisticated than its predecessors, with the ability to carry out complex tasks such as assembly and welding. This has led to fears that robots will eventually replace human workers altogether. However, it is worth noting that manufacturing remains a highly skilled profession and that robots cannot wholly replicate the work of human workers.

As such, the role of humans in the manufacturing process is likely to remain important for the foreseeable future.

 

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Robotics is becoming increasingly important in the manufacturing industry

Robotics is becoming increasingly important in the manufacturing industry. By automating tasks that are either too difficult or too dangerous for human workers, robots are able to boost efficiency and productivity while reducing risks.

In addition, robots are often more precise than human workers, meaning they can produce products with higher quality control. As the cost of robotics technology continues to decline, even more factories will likely begin to integrate robots into their production processes. Ultimately, the increasing use of manufacturing robots will profoundly impact the economy and workforce.

 

Robotics offers many benefits to manufacturers

Robotics has become an increasingly popular option for manufacturers in recent years, and it is easy to see why. Robotics offers a number of benefits, including increased efficiency and reduced costs. In terms of efficiency, robotics can work around the clock without needing breaks and can be programmed to handle tasks that are too difficult or dangerous for humans. In terms of cost, robotics requires a lower initial investment than traditional manufacturing methods, and the ongoing costs are also lower. As a result, it is no surprise that robotics is playing an increasingly important role in the manufacturing industry.

 

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The future of robotics looks bright

It is safe to say that the future of robotics looks bright. With rapid technological advances, we see more innovative robotics applications. In the coming years, robots will be used in various settings, from manufacturing and healthcare to transportation and logistics.

Robotics will also play an increasingly important role in our daily lives, as they can perform tasks that are too difficult or hazardous for humans. As technology develops, we can only imagine the types of robots that will be created in the future. Whatever form they take, it is clear that robotics will significantly impact our world.

 

At the end of the day

Although the industrial revolution brought about many changes to society, it is clear that robots’ invention and implementation have perhaps had the most significant impact on manufacturing. With continued advancement in robotics technology, it is exciting to think about what the future may hold for both human and robot collaboration in factories worldwide.

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It Is Not Just Meta In The Metaverse, Know The Other Tech Giants Shaping The Metaverse

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It Is Not Just Meta In The Metaverse, Know The Other Tech Giants Shaping The Metaverse

The buzzword of the moment is ‘metaverse’. But who came up with this? This whole concept started with Meta CEO Mark Zuckerberg’s push for the creation of the metaverse.  Mark Zuckerberg and Meta’s role in the metaverse landscape began in 2014 when the company acquired the virtual reality platform Oculus.

Despite all the ongoing trends in the metaverse, a lot of things still remain uncertain. Meta is the main company developing Metaverse for users and players to be in the vast network of real-time 3D virtual worlds while maintaining identity and payment history.

There is no doubt that Meta company is directly linked with Metaverse, but there are companies as well shaping the Metaverse.

Starting with NVIDIA, it is one of the top companies for Meta to strike a deal with the Metaverse market. It took an initiative to distribute free copies of a program built for developing Metaverse-ready assets known as Omniverse.

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Epic Games is at the forefront of big companies developing Metaverse with a significant wave of development and innovation.

Microsoft is a famous company for Meta focused on developing a series of Metaverse applications on top of the Mesh platform. It is also building a new augmented reality chipset for Metaverse with Qualcomm for providing access to new features.

Apple is known as a well-known company for Meta for creating a Head-Mounted System (HMD) virtual meetings app. It will incorporate physical hand and arm movements to be present and interact in virtual meetings.

Decentraland is one of the big companies developing Metaverse as a platform for content producers and enterprises looking for a new artistic medium or any commercial opportunity.

With the way, it’s going it won’t be long before all the biggest tech enterprises join in this Metaverse race.

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