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AI-Smart Assistants: A New Tech Revolution in the Make

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2018 has begun. And this year is going to witness a mega revolution in the field of technology – the rise of AI-powered digital assistants. Striking improvements in key technologies, like natural language processing and voice recognition are making smart assistants more productive, helping us use electronic devices just by interacting with them.

 
AI-Smart Assistants: A New Tech Revolution in the Make
 

Smart voice assistants are going mainstream. From Apple’s Siri to Google’s Assistant to Samsung’s Bixby, superior digital assistants are on a quest to make our lives easier, while taking us a step closer to a world where each one of us will have our own personal, 24/7 –all-ears AI assistants to fulfill our every wish and command.

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The Future of Technology is Here: 3 Tech Categories That Will Rule in 2018

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The Future of Technology is Here: 3 Tech Categories That Will Rule in 2018

No organization can survive without – technology. It has seeped into our lives for good, and is further predicted to expand its horizons across multiple sectors in the next couple of years. The forecasters has even predicted that 4% more would be spent on purchasing software, technology and hardware by government bodies and corporations, as well.

Now, this kind of growth and development will push the global tech industry to hit the $3 trillion mark. But amidst all this startling stats and discoveries, what still remains under the clouds is the fact how to decide which technology to invest in – or whether you should invest at all.

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Communication

Communication technology is crucial. It is more important for startups, where employees work remotely, as highlighted by a leading daily. In fact communication platforms offer a gamut of benefits, right from increased productivity to form superior teams and ability to nurture better company cultures. Furthermore, these technologies in the end help entrepreneurs monitor budget closely, which is enough to point out why strong communication is fruitful.

Cutting edge messaging services like HipChat and Slack ensures better communication networking for employees working outside the office. On the other hand, fantastic tools like Basecamp streamlines operations irrespective of the location of staffs, while LinkedIn and Ripple ensures better connectivity on a more personal level.

Artificial Intelligence

AI is a must-have technology tool for every organization coming up this year and ahead, because this field of science is expanding very rapidly. A lot of new discoveries and innovations are taking place around AI, and you need to be ahead of the curve. As more and more data gets churned out, deep-learning techniques starts to gain momentum, which tends to evolve the pattern of data analysis.

On this note, Google Home and Amazon Alexa launched their own virtual assistant – though the ability to interact with devices was in existence for quite some time now, these masterminds gave a push to this technology a little more.

Similarly, it’s been revealed in a McKinsey report that around 45% of work activities are going to be automated, thanks to the power of AI.

Blockchain Technology

Much more than just performing financial transactions, blockchain technology is a bright beacon of hope for all tech freaks. Though this technology was in active phase, it’s enjoying heyday now. Market Reports Hub predicts that this market will exceed $2 billion by 2021, and that definitely calls for a celebration!

The main objective of blockchain is to nurture and enhance the trust between enterprises. Though in the beginning, startups and entrepreneurs may feel a little bit intimidated to implement this new-age, ultra-famous tool of technology in their organization but later on they can’t thank more! Right from navigating through sales, finances, marketing, communication and creativity, Blockchain is a sure-fire way to make this New Year a booming success.

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The More, The Better: Why Focus on More Than One Coding Language for Better Developer Jobs?

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The More, The Better: Why Focus on More Than One Coding Language for Better Developer Jobs?

Attention all you developers: Be versatile, be ahead of the curve.

Excelling over just one programming language won’t do any good, and will restrict your career pathway. On closer inspection, you’d find that the top 25 Forbes listed companies never rely on a single coding language for their products and services – instead they prefer on applying at least 4 different languages to always be on edge.

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5G Mobile Innovation: 3 Key Takeaways That Every Business Leader Should Know About

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5G stands for fifth generation wireless connectivity based on the IEEE 802.11ac standard of broadband technology, though an official standard is yet to be fixed. It comes with a lot of promises – better bandwidth, faster speed and lower latency that affects (positively) customers and businesses, as well.

5G Mobile Innovation: 3 Key Takeaways That Every Business Leader Should Know About

Although it isn’t expected to roll out until 2020, a large number of companies have already started prepping up to adopt and incorporate 5G mobile connectivity into their business scopes and operations. As the biggest shift in technology is looming right ahead, business leaders around the world are leaving no stone unturned to fathom the rich impact of 5G on several next-gen techs, like self-driving cars and cloud computing.

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Here’s Why Indian Techies Need to Imbibe Rich AI and Data Science Skills to Ride High This 2018

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Here’s Why Indian Techies Need to Imbibe Rich AI and Data Science Skills to Ride High This 2018

Amid growing anxiety over machines replacing human intelligence, Indian IT sector is seeking out expert skills in new technologies, involving big data, artificial intelligence and machine learning. There exists a high demand for skills in such newer streams of technology, which now forms the backbone of businesses. It’s not like these jobs appeared out of thin air; after being labeled as “niche skills” for several years, they are now making their way into the mainstream industry. 

This year, this trend is going to gain more momentum. It is expected to create 180000 to 200000 new jobs in 2018, mostly related to these new technologies – Alka Dhingra, the general manager of IT staffing at TeamLease Services, stated. It is equally applicable for both large service organizations as well as budding startups.

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The Hot-List:

Here’re the notable areas, where job creation will hit in 2018:

Artificial Intelligence

Almost all Indian IT bigwigs are going gaga over AI. TCS, Infosys, Flipkart – nearly all native companies have started delving deeper into data to scale up their business operations and secure success in the future.

Though the world is being ruled by MACHINES, at the same time it’s HUMANS who train machines the way they function to perform human-like tasks. For that reason, the country’s IT unicorn, Tata Consultancy Services has trained more than 200000 employees about IoT and AI. Also, last month, India’s e-commerce giant, Flipkart launched an AI-inspired initiative known as AI for India, through which it has planned to leverage all the data it has gathered over the last few years to frame robust AI-driven solutions that will boost their operational activities further. Millions of dollars are being invested in this program – a company representative shared.

All this is going to need professionals skilled in the domains of deep learning, natural language processing and machine learning – look up to DexLab Analytics for data science online courses.

Data Science

For several years, native internet companies have been accumulating massive consumer data, which they now plan to mine it to their best interests. Just like Flipkart’s AI for India initiative, food-delivery-tech startup Swiggy is also working hard on its consumer data so that it can start making deliveries even more efficient and faster.

Some HR experts say that pharmacy analytics – an amalgamation of healthcare and analytics will also generate several new jobs for data scientists this new year– at present, machine learning, data analytics and data scientists’ jobs are the most searched jobs on all leading job portals in India.

Blockchain Technology

While bitcoin and cryptocurrency takes the world by storm, top-notch market specialists predict this advanced field of technology is going to create an exploding number of jobs. Cryptocurrency has already started drawing in a large pool of Indian investors, and legal experts are now asking for regulations.

“There could be regulations (for bitcoin) coming, and hence somebody who knows the subject is going to be in demand,” Aditya Narayan Mishra, CEO of CIEL HR Services, said.

Digital Marketing

Digital technologies are now omnipotent. All startups and matured companies across every domain are adopting suave digital solutions for various functions, like HR, manufacturing, operations, warehousing and communications. In the same manner, marketing too is not limited to its erstwhile conventional mediums; digital marketing is the new talk of the town.

“With more companies in India wanting to increase their digital presence, there is a visible surge in job searches for digital marketing jobs,” Sashi Kumar, the managing director of jobs portal Indeed India, said.

To learn more about how machine learning and artificial intelligence can help transform your business, enroll in a machine learning training course. DexLab Analytics’ Machine Learning Using Python course is superb; it helps students grasp the concepts better.

 

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Stories of Success: Molecular Modeling Toolkit (MMTK), Open Source Python Library

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Stories of Success: Molecular Modeling Toolkit (MMTK), Open Source Python Library

Welcome again!! We are back here to take up another thrilling topic and dissect it inside out to see what compelling contents are hidden within. And this time we will take up our newly launched Python Programming Training Module – Python, invented by Guido Van Rossum is a very simple, well-interpreted and goal-specific intensive programming language.

Programmers love Python. Since there is zero compilation step, debugging Python programs is a mean feat. In this blog, we will chew over The Molecular Modeling Toolkit (MMTK) – it’s an open source Python library for molecular modeling and simulation. Composed of Python and C, MMTK eyes on bio-molecular systems with its conventional standard techniques and schemes, like Molecular Dynamics coupled with new techniques based on a platform of low-level operations.

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It was 1996, when the officials from Python Org, including Konrad Hinsen (He was then involved in the Numerical Python project, but currently working as a researcher in theoretical physics at the French Centre National de la Recherche Scientifique (CNRS). He is also the author of ScientificPython, a general-purpose library of scientific Python code) started developing MMTK. They initially had a brush off with mainstream simulation packages for biomolecules penned down by Fortran, but those packages were too clumsy to implement and especially modify and extend. In order to develop MMTK, modifiability was a crucial criterion undoubtedly and they gave it utmost attention.

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The language chosen

The selection of language took time. The combination of Python and C was an intuitive decision. The pundits of Python were convinced that only a concoction of a high-level interpreted language and a CPU-efficient compiled language could serve their purpose well, and nothing short of that.

For the high-level segment, Tcl was rejected because it won’t be able to tackle such complex data structures of MMTK. Perl was also turned down because it was made of unfriendly syntax and an ugly integrated OO mechanism. Contrary to this, Python ranked high in terms of library support, readability, OO support and integration with other compiled languages. On top of that, numerical Python was just released during that time and it turned out to be a go-to option.

Now, for the low-level segment, Fortran 77 was turned down owing to its ancient character, portability issues and low quality memory management. Next, C++ was considered, but finally it was also rejected because of portability issues between compilers in those days.

 

The architecture of library

The entire architecture of MMTK is Python-centric. For any user, it will exude the vibes of a pure Python library. Numerical Python, LAPACK, and the netCDF library functions are observed extensively throughout MMTK. Also, MMTK offers multi-threading support for MPI-based parallelization for distributed memory machines and shared memory parallel machines.

The most important constituent of MMTK is a bundle of classes that identify atoms and molecules and control a database of fragments and molecules. Take a note – biomolecules (mostly RNA, DNA and proteins) are administered by subclasses of the generic Molecule class.

Extendibility and modularity are two pillars on which Python MMTK model is based. Without going under any modification of MMTK code, several energy terms, data type specializations and algorithms can be added anytime. Because, the design element of MMTK is that of a library, and not some close program, making it easier to run applications.

Note Bene: MMTK at present includes 18,000 lines of Python code, 12,000 lines of hand-written C code, and several machine-generated C codes. Most of the codes were formulated by one person during eight years as part of a research activity. The user community provided two modules, few functions and many ideas.

For more information, peruse through Python Training Courses Noida, offered by DexLab Analytics Delhi. They are affordable, as well as program-centric.

 

This article is sourced from –  www.python.org/about/success/mmtk

 

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Google is Back in China! It Decides to Open an AI Lab in the Far-East

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Google is Back in China! It Decides to Open an AI Lab in the Far-East

 

Google is strengthening its artificial intelligence base, including China.

 

And it is so doing by establishing a new AI research center in Beijing. Google is digging deep into China, where it contravened the government in 2010 committing a spectacularly principled act of self-sabotage by refusing to self-censor search content and later found most of its services to be blocked. The company’s decision to return back to China is more about safeguarding its future, and acknowledging the supreme importance of technology’s most competitive field: AI.

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Humans and Automation Shares an Everlasting Bond for a Successful Tech Future

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Humans and Automation Shares an Everlasting Bond for a Successful Tech Future

“God created the world in seven days, because he didn’t have to port anything from legacy systems” – the CEO of a blue chip IT company once quoted. A similar idea was even echoed by MIT’s former director of computer science and AI, Mr. Rodney Brooks who penned down an article “Seven Deadly sins of AI Predictions,” which largely focused on the rate of deployment and the influence of technology over it.

But for any technological revamp, humans are the key ingredient for successful implementation of AI – because they are the ones who have invented such striking tools of automation with their own wit and determination. AI has enhanced productivity, coupled with raising standards of living. Companies all across the globe are recognizing the benefits of AI, and contemplating investments in this budding field of science to trigger greater competitiveness.

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According to research, there exists a potent relationship between degree of automation and profit generation –the companies that have automated their business processes get to enjoy the perks of higher revenue growth six times more than those who didn’t. Also, they are twice more likely to supersede their pre-determined financial goals.

Now coming to our chief area of concern, how humans deliver a significant impact in coordinating automation with AI projects – their process of imagination, understanding, leadership quality, emotional intelligence and versatile management skills outweighs the very fundamentals of technology, hence it is said that for successful digital transformation, investment on human workforce is indispensable. To derive the best results, it is important to shell out money on crucial human elements that will lead to fuller automation and successful AI implementation.

Automation makes people more human. It liberates them from doing humdrum, repetitive work that pulls them back from doing something productive, or creative. Without AI, businesses can’t work or obtain competitive advantage in the future, making them defenseless. Nevertheless, you can’t expect AI to do a whole bunch of things for you, jobs that require creativity, empathy, critical thinking, leadership, artistic expression are meant for humans, and no automation will be able to fulfill those qualities. Humans are the meat and potatoes for AI, and we can’t agree more!

For better successful ventures, it is imperative to make humans and machines work together – it will only make us better in our job profiles. Also, this kind of relationships best augments the deep-rooted potentials of human beings, making humans more humane.

Research also says in the coming days, creative human skills will garner even more demand. Comprehensive training and skill development is highly advisable to remain ahead in the rat-race of advanced technology. Skills like, creativity, emotional intelligence, collaboration, critical thinking, communication and cognitive flexibility will become key skills to grab specific job titles. 

An advice to make: before entering the workforce, it is better seek broad educational experiences in the field of data science or computer science, or your preferred field of study, and then amp up your CV with a professional, program-centric Machine Learning training Delhi. In this way, you will be always updated and stay ahead of the curve.

 

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Bad Data is Really Bad for Machine Learning: Here’s Some Ways to Fix It

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Bad Data is Really Bad for Machine Learning: Here’s Some Ways to Fix It

The quality of data is the talisman of decision-making. Irrespective of the goals, the key to better decision-making lies in the quality of data. As it’s said, bad data takes its toll on organization’s data endeavors – as a result, only 25% of businesses are able to optimize the use of data for revenue generation, despite a volley of resources being thrown at them.

IBM has reckoned that bad data costs companies some $3.1 billion a year in the US alone, while as per Experian’s Data Quality survey, 83% of organizations alleged their revenue is affected by imprecise and incomplete customer or prospect data.

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