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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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Chief Data Officer Is the Next “Commander” To Join the Digital Kingdom and Here’s Why

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Chief Data Officer Is the Next “Commander” To Join the Digital Kingdom and Here’s Why

An over-empowering digital transformation is here and it is wreaking havoc in the C-Suite. CDOs have started taking a front line in managing and pushing new tech like AI and machine learning to alter business landscapes forever.

As a matter of fact, this promising job title has existed for years, even decades – mostly in the financial market. But now when data is being generated at record high speeds, the job role of the CDO is emerging out bigger and better. No more a single person or a general crew is enough to tackle such challenging data issues – to fulfill complicated data management tasks, management is now looking up to specialized data experts.

Gartner predicts that 90% of multinational organizations will appoint a CDO by 2019. Though the first generation CDOs were only concerned about data governance and management, of late, they have been shifting focus on how to best implement data as the best strategic asset in organizations to trigger optimum results.  

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Take a look down to know how CDOs can add value to your organization, while streamlining data and developing strategies:

Be competitive, be ahead of the curve

The best way to ace is by taking over your competitors. In corporate jargon, it means to understand your competitor’s strategies better and arm yourself in the way. Also, it calls up to know your customers better, including the things they like to purchase and know ways you can fulfill their needs. Glean all of these observations with the flattering tool of IoT and machine learning, including social media and supply chain.

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Share information through Data silos

Think how would you feel if you are unable to share information within your department? It can be exasperating. But in reality, it happens. Employees working in the same company, even in the same team forget to share information – data is treated as a commodity that is traded for. That’s why, chief data officers break down data silos in an organization to make sure everyone within the framework get access to data to boost decision-making.

CDOs infuse life into data

All analysts are not good with data. No matter how much they pore themselves over into pie charts and bar diagrams, they just can’t nail it. Machine learning using Python and other related technologies has made things easier – now CDOs can infer trends and draw meaningful insights necessary for a better company future. And mind it these analyses eventually saves hours of production time, millions of losses and much more.

repsoitory-choices

There’s nothing better than cleaner, fresh data

Unkempt data is no data at all. In fact, data comes handy only when it is clean. Today, with the influx of so many data, organizations falter to keep pace with so much data extravagance data starts becoming dirty or of little use. This results in – every report run is full of flaws, estimates are wrong and lists compiles are inaccurate. As a savior in troubled situations, CDOs help in churning out crystal clear, consistent data by taking care of all the business processes, and making sure that they are properly maintained by the users.

CDOs are the meat and potatoes of C-Suite team

Not only they understand the intricacies of the subject matter, CDOs undoubtedly makes better use of your data, and looks forward to ways to use them in more meaningful manners. They are not here to hoard the data, but to share it extensively among the people working in the organization to produce fascinating results all around.  

Now that you know how important CDOs are, enroll for a reputable business analytics online certification by DexLab Analytics. Business analytics certification is the key to good times, go get one for yourself today!

 

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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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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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