Your Google Digital Assistant just got better, wiser, and “more human” with the tech-giant’s recent rollout. So much so that it sounds just like a real person!

The robotic assistant by Google has been smartly incorporated with person-like sounds and voices, leaving us to think — “technology is all dolling up for the future, and how!”.

The Google update was showcased to the world at this year’s I/O Conference held during 08th May to 10th May 2018 at the Shoreline Amphitheatre, CA.

Wherein, Google Head Sundar Pichai unveiled the AI, alongside comments that it can call up other businesses to check if they’re open at a given time. It can even call up restaurants and salons to make appointments and manage the call on behalf of the user.

During the event, the virtual assistant was made to book a table for four at a particular time, complementing the call with speech add-ons like “umms” and “uhs”. That’s why the restaurant staff weren’t aware of the artificial intelligence being on the other side — and not a real customer.

As observed, the tech giant is reaching out to more and more busy people who are unable to stay glued to their phones all the time. Thus adding much ease and simplicity to already fussy lifestyle. 

Google’s AI comes packed with the Duplex Technology. It has been developed to understand when and how to reply promptly just when a person says “Hello”. This is a clear example of the advanced concept of Machine Learning.

Machine Learning – The Next Step towards Future

This kind of technological advancement is the result of a futuristic concept called Machine Learning. On which, the latest update of the Google Digital Assistant is also based on.

Machine Learning is a blend of various statistical tools coming together. It empowers the computer systems with a super ability to “learn”, hence the name Machine Learning. It’s applications range from web searching and ad placements to stock trading and credit scoring too.

By ‘learning’ it means that the machines are progressively programmed to improve their performance on a particular task. They are incorporated with relevant coding language that not only helps them analyze huge data but also perform certain actions accordingly.                  

Voice-controlled AI in cars

The Machine Learning technology is being perceived as a fast-growing phenomenon today. Due to its ongoing advancements, the system has also been incorporated among other gadgets like automobiles.

Voice-controlled AI in cars in the form of Tesla Autopilot and Ford SYNC are making headlines across the globe, and for obvious reasons. They are one of the first smart cars to offer features like lane centering, self-parking, and automatic lane-changing without driver steering, etc.

What’s more? The hybrid cars are fully-integrated with in-vehicle communications and entertainment system to make lives easier. Gadget enthusiasts can enjoy making hands-free telephone calls, play music, and perform various other functions on the driver’s seat just through voice commands.

How leading companies across the globe are mobilizing Machine Learning

Source: Redpixie                                                                                       

Machine Learning – A branch of Data Science

Data Science is a technical field that uses scientific processes and systematic methods to analyze huge volumes of data. It is only after step-by-step analysis that insights are extracted and business plans are strategized from the data.

Machine Learning makes up for an integral part of Data Science. The branch develops a fundamental knowledge of concepts like algorithms, statistical techniques, and predictive analysis. It also gives a glimpse into Big Data analysis, Data Mining, R, SAS, Python, and Tableau as well.

Data Science teaches you:

  • How and why Machine Learning combines data analysis, algorithms, and statistics
  • How computer languages can be used to analyze various data patterns
  • How data patterns enable decision-making and predictive analysis in real-time scenarios
  • Ways to collect, prepare, and analyze data; dealing with missing data; and create user-based analytic solutions
  • When to apply algorithmic concepts like sorting, greedy algorithms, searching, and dynamic programming etc.

Enticed to go for Machine Learning? Well, if you wish to dig deeper and contribute your bit to the quick-advancing world of IT and technology, Data Science is just for you!