Data Science, Machine Learning & Artificial Intelligence – What’s Trending?

Data Science, Machine Learning or Artificial Intelligence are significantly dependent on each other. When the world is moving towards the future to embrace IoT (Internet of Things), all these three domains play a very crucial role. They materialize the dreams of researchers about creating a smarter world for the human race.

Global technology leaders are spending a lot of revenue and time on these critical topics already. Data Science is all about studying the data and extracting valuable information to establish knowledge which in turn is used for Machine Learning. When a machine is capable enough to process data and learn something new which it can use on its own, as and when required, is known as Artificial Intelligence.

Artificial Intelligence has its advantages and risks. It has already started making the technology leaders re-think about the evolution of AI;

Recently the world witnessed Clash of Titans between the real-life Iron Man, Elon Musk and Mark Zuckerberg, Founder of Facebook, the biggest Social Media network. This war of words started when Elon Musk at a meeting of American governors, warned that the Artificial Intelligence is the biggest risk we face as a civilization.

A few weeks ago, Facebook had to shut down its two chatbots which started communicating with each other in a language they developed themselves and was not understandable by Humans.

Some of the major Machine Learning APIs and AI service providers are:

• IBM Watson
• Microsoft Azure Machine Learning API
• Google Prediction API
• Amazon Machine Learning API
• BigML

With the evolution of technology, more and more organizations are expected to explore the vast opportunities in the fields of Data Science, Machine learning and AI, to get a clear edge over the competitors. Hence, we can see some emerging trends in these fields, which will help the organizations to achieve their goals.

Data Science Trends

1) Hadoop and Spark Gaining Popularity

Big Data technologies like Hadoop and Spark are gaining popularity, as they have a clear edge above the other Data analysis tools. Hadoop can collect big data and then the data can be distributed to low-cost servers running parallelly.

2) Business Moving to Cloud for Data Analytics

As businesses are moving to Cloud, so is the Data. Hence, the organizations are moving to the cloud for Data Analysis as well, to reduce the complexity of administration and integrating the cloud computing resources.

3) Strong Data Security Controls

The cybercrimes are on a high and people are concerned about the data security and breaches in data privacy. So, we can expect a rise in the expenses from Organization’s point of view to ensure that the data used for Analytics or Machine learning is secured to meet the triads of security, Confidentiality, Integrity and Availability.

4) Deep Learning Technology

With most of the organizations moving forward to adapt themselves to Artificial Intelligence, data scientists are focusing more on Deep Learning nowadays. With the increase in computing power, deep learning applications are now available for the data scientists.

Machine Learning Trends

1) Machine Learning in Finance

Consider a machine, which can analyze the market trends and predict the behaviour of the financial market. For any organization, it will be a huge advantage to make their strategic decisions about the investments. This kind of application will bring a revolution to the world of trading.

2) Space Exploration

Machine learning is not new in the field of space explorations. NASA’s Mars Exploration Rover is a classic example of Machine learning, where although it can be managed remotely by human beings, the MER can understand and learn about its surroundings. With success of MER, researchers are now more motivated to use Machine learning and explore the farthest corners of the Galaxy.

3) Autonomous Driving

With the evolution of Machine Learning, autonomous driving is becoming an area where many of the car manufacturers are investing heavily. The growth in this field will be inversely proportional to the number of road accidents that take place across the world every day. The autonomous driving is expected to be a much safer ride as compared to the manually driven trips, as the vehicle is smart enough to understand and access any risk and act on it at the right time to avoid any accidents.

4) Healthcare and Medicine

The constant changes in biometrics can be streamed by wearables that collect data constantly. The analysis of this data can help in prescribing the correct medicines for the patients. This is only possible once the machine learning is evolved to that extent so that we can develop such precise learning tools which can work consistently.

5) Humanitarian Aid

Using drone for supplying logistics and supplies to the remote areas or areas affected by natural calamities. Drones can learn on their own about the environment, without any prior knowledge.

Machine learning is the crust of many future inventions, that will help to improve the way things are performed.

Artificial Intelligence Trends

1) Intelligent Mobile Applications

With the incorporation of artificial intelligence, the apps are becoming intelligent. How? With the help of smarter machine learning methodologies and AI-based applications are quickly providing smarter responses based on huge raw data provided by Data Science methods, which was almost impossible for the conventional mobile apps.

2) Open Source AI Platforms

Since organizations are nowadays interested in creating tools for AI and Machine learning, it has become a necessity to have platforms available which can support the AI tools and apps. Tools like TensorFlow, H2O, MLlib, Caffe have already set the trend for open source tools. These AI tools are helping the smaller businesses to adapt to the changes happening in the surrounding and having a smooth transition to the AI.

3) Sophisticated Range of GPU Driven Hardware

Japan is already working on a GPU-driven AI-supercomputer. As the AI will need a lot of additional computing, the current set of hardware will not be able to support this additional overhead. Hence, the growth in the industry of hardware manufacturing, which can support AI, will be on the rise. These advance hardware will help the systems to evolve as more intelligent and smart machines.

4) Language Generation

Your gadget follows your instruction through techniques like voice and image recognition. AI is working on the language processing for a machine so that a better understanding of language can make it more effective. At present, you can instruct your smartphone to dial a number but can’t expect to have a deep and meaningful conversation. With AI, expect it to happen anytime soon.

5) E-commerce and Retail players to Rely More on AI

People prefer to do online shopping than walking into a store to get stuff. Hence, for the online retailers, it is important to gather as much data as possible so that they can analyze them and understand the trends. This trend analysis helps the businesses to make strategic decisions. To analyze and act upon these trends as quickly as possible, experts are building AI systems which can work according to the situation and take necessary decisions as well.

6) The Power of AI Delivered with the Cloud

Cloud services are highly scalable; hence they can support machine learning and AI algorithms. With Cloud service providers delivering both Machine learning and AI solutions, the implementation is becoming a lot easier for the organizations.

7) AI Systems Would Mean Better User Interface

Chatbots are already trending, but now organizations are focusing on developing better user interfaces for better user experience. As businesses are more focused on selling the experience rather than selling the product, a user-friendly interface along with a smart chatbot creates a better user experience helping organizations to attract users. The investment in creating these smart interfaces along with chatbots will see a rise in the upcoming few years.