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Will AI Replace The Intelligentsia? Google’s AI writes mournful poetry

Will AI Replace The Intelligentsia? Google’s AI writes mournful poetry

It is no new news that Artificial Intelligence can now control self driving cars; they can beat the best humans at highly challenging board games like chess, and even fight cancer. But still one thing it cannot do perfectly is communicate.

So, to help solve this problem Google has been feeding its Artificial Intelligence with more than 11,000 unpublished books, which include more than 3000 steamy romantic titles. And in response the AI has penned down its own version of mournful poems.

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The poems read something like this:

I went o the store to buy some groceries.

I store to buy some groceries.

I were to buy any groceries.

Horses are to buy any groceries.

Horses are to buy any animal.

Horses the favourite any animal.

Horses the favourite favourite animal.

Horses are my favourite animal.

And here is another one from Google’s AI:

he said.

“no,” he said.

“no,” i said.

“i know,” she said.

“thank you,” she said.

“come with me,” she said.

“talk to me,” she said.

“don’t worry about it,” she said.

 

The way this happened was, Google’s team fed their AI with unpublished works into a neural network and gave the system two sentences from the book; it was then up to this ingenious artificial intelligence to build its own poetry based on available information.

In example above, the team of researchers gave their AI two sentences one about buying some groceries and the other one about horses being a favourite animal (these are the first and the last lines of the above mentioned passages). The team then directed the artificial intelligence to morph between the two sentences.

In the research paper the team further went on to explain the AI system was able to “create coherent and diverse sentences through purely continuous sampling”.

With the use of an autoanecdoter, which is a type of AI network that makes use of data sets to reproduce a result, in this case that was writing sentences, using much fewer steps the team was able to produce these sentences.

The main principle behind this research is to create an Artificial Intelligence which will be proficient in communicating via “natural language sentences”.

This research holds the possibilities of developing a system that is capable of communicating in a more human-like manner. Such a breakthrough is essential in the creation of more useful and responsive chat bots and Artificial Intelligence powered personal assistants like that of Siri and Google Now.

In a similar project, the researchers at Google have been teaching an AI how to understand language by replicating and predicting the work of bygone authors and poets under their project Gutenberg.

This standalone team at Google fed the AI with an input sentence and then asked it to predict what should come next. And by analysing the text, the AI was capable of identifying what author was likely to have written the sentence and was able to emulate his style.

In another incident, on June, 2015 another team of talented researchers at Google were able to create a chatbot that even threatened its creators. The AI learned the art of conversation by analysis of a million movie scripts thereby allowing it to realize and muse on the meaning of life, the colour of blood, and even on deeper subjects like mortality; Ss, much so that the bot could even get angry on its human inquisitor. When the bot was asked with a puzzling philosophical question about what is the meaning of life, it replied by saying – “to live forever”.

In other such similar works, Facebook has also been teaching its artificial intelligence with the use of children’s books. As per the New Scientist which is a social network, it has been using novels such as The Jungle Book, Alice in Wonderland and Peter Pan.

If you are yearning for some more of AI’s written word, then here are the rest of Google AI’s poems.

You’re right.

“All right.

You’re right.

Okay, fine.

“Okay, fine.

Yes, right here.

No, not right now.

“No, not right now.

“Talk to me right now.

Please talk to me right now.

I’ll talk to you right now.

“I’ll talk to you right now.

“You need to talk to me now. —

 

Amazing, isn’t it?

So, what is it?

It hurts, isn’t it?

Why would you do that?

“You can do it.

“I can do it.

I can’t do it.

“I can do it.

“Don’t do it.

“I can do it.

I couldn’t do it. —

 

There is no one else in the world.

There is no one else in sight.

They were the only ones who mattered.

They were the only ones left.

He had to be with me.

She had to be with him.

I had to do this.

I wanted to kill him.

I started to cry.

I turned to him. —

 

I don’t like it, he said.

I waited for what had happened.

It was almost thirty years ago.

It was over thirty years ago.

That was six years ago.

He had died two years ago.

Ten, thirty years ago. — “it’s all right here.

“Everything is all right here.

“It’s all right here.

It’s all right here.

We are all right here.

Come here in five minutes.

“But you need to talk to me now.

 

To feed in adequate information on Machine Learning Using Python, reach us at DexLab Analytics. Our Machine Learning Certification is garnering a lot of attention owing to its program-centric course module.

 

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Understanding Time Series Method of Forecasting

The dictionary meaning of the word forecasting is to estimate what could possibly be the future outcomes within a business or operation. But when it comes to the sector of data analysis this method is used for translating the past data or experiences into future possible outcomes. This is a highly useful analytics tool that helps any company management to cope with uncertainty of the future. For both short term and long term decisions forecasts are highly important.

 
Understanding Time Series Method of Forecasting
 

Forecasting can be used by businesses in several areas, which may include: economic forecasts, technological forecasts, and also demand forecasts. Forecasting techniques can be classified into 2 broad techniques: quantitative analysis (objective approach) and qualitative analysis (subjective approach). For the quantitative method of forecasting technique an analysis of historical data is conducted and the past patterns in data are assumed to predict future data points. While on the other hand in the qualitative forecasting technique, the judgment of experts is employed in the specific field to generate probable forecasts.  These are mostly educated guesses or opinions of experts in that specific area of expertise. Continue reading “Understanding Time Series Method of Forecasting”

Olympics Spoiler Alert: We Predicted The Outcomes Of Rio Olympics

Being a part of the data awakened generation we acknowledge that data analytics and predictions form an integral part of everything we do. From sole trade predictions to outcomes of famous movie releases to results of sporting events, big data analytics is now the wizardry of obtaining the answers to questions that are still unasked.

 

Rio Olympics 2016

 

Recently following the ongoing trends, the company Gracenote which is the world’s leading provider of entertainment data and is a subsidiary of the Tribune Media Company claimed that they have made accurate predictions of the Rio Olympics outcomes. So, following Gracenote we have also used our sports data analytics expertise to predict which countries and athletes will step up and do well at the 2016 Summer Olympics Games. Continue reading “Olympics Spoiler Alert: We Predicted The Outcomes Of Rio Olympics”

Tutorial for creating a Speedometer dial in MS Excel

 Tutorial for creating a Speedometer dial in MS Excel

Here in this video tutorial we have discussed in detailed steps, how to create a Speedometer chart in MS Excel. A Speedometer chart is often called as a gauge chart and combines two different type of charts, a pie chart and a doughnut chart.

The Speedometer dial is made with the help of using a Doughnut chart and needle is actually a combination of two types of charts, another doughnut chart and a pie chart.

A speedometer chart or a gauge chart can be created in other data visualization software as well, like for instance in Tableau and is usually easier to create due to availability of better controls and features.  It is due to the simplistic nature of these charts which is well adjusted to context of data and is a great use of space in a spreadsheet that charts like these are popular with non-data executives. Usually such non-data personnel do not want to dig deep into the contextual details like an analyst which is why these charts are great for using in a presentation where diverse departmental executives will be participating.

Gauge charts pack in a lot of horsepower and form a sort of ubiquitous symbol when it comes to understanding business metrics from an analytical point of view. So, learn to create these charts with our simple tutorial and for more such interesting lessons on data analysis software, join us every day as we share technical posts based on data on a regular basis.

 

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The Dark Data on Why Crime Against Women are on The Rise in India

India, a land known for its diversity, rich heritage, culture, colourful and flavoursome food, a never-ending list of occasions and holidays and the slightly recent addition of rape and other violent crimes against women!

 

The Dark Data on Why Crime Against Women are on The Rise in India

 

We though enraged by the death toll of Nibhayas’ in Delhi and the rest of the country are not here to write an infuriating open letter to the World Wide Web. When India’s daughter, the documentary made by a British film-maker made big news after its release on YouTube, the country’s protectors and ‘patriots’ jumped right in with a concoction of nicely cooked data showcasing how the rate of crime against women are similar in the UK as it is in India! But we as a data-friendly nation often forget the main utility of data analysis. Continue reading “The Dark Data on Why Crime Against Women are on The Rise in India”

A Deeper Look at Rajnikanth’s Movie Kabali from the Perspective of a Data Analyst

A Deeper Look at Rajnikanth’s Movie Kabali from the Perspective of a Data Analyst

As we can see from the above analytical assessment that while sultan needed the help of other factors like a special occasion such as Eid, Kabali’s success which is almost unmatchable to the success of Sultan needed no such push. The numbers suggest that Kabali was able to make a bigger splash in the overseas fan base Sultan was only able to rule its own country’s fan base.

 

These were simply the statistical reports on the comparison of the above mentioned two films done with the help of SAS. We in no intend to spark a war between the fan-bases of respective actors and respect both their talents in their own domain. Who’s to say who the real Sultan of Indian Film Industry is still a question too big for simple data folks to ascertain. May be you could help us find an answer to this unique analytical problem? Feel free to add your thoughts in the comments below. 

 

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An Analysis of The Growing Popularity Of Pokémon Go

The virtual 8 bit Pokémon universe has now been unleashed into our HD smart phone screens which we carry with us everywhere. And there are players of this popular game walking around on their two feet with eyes glued to the mobile screen with the unrelenting thirst of catching them all! But why?! Why is this game of an almost forgotten popular cartoon show suddenly creating such an overwhelming hype? This craze of capturing all these digital monsters that have been placed in ones neighbourhood using the ingenious AR Technology, definitely a great time for game-lovers to be alive.

 

An Analysis of The Growing Popularity Of Pokémon Go

 

This game just released last Wednesday and has instantaneously become a growing global hit. This game has done the impossible, where the stereotypical imagery of computer nerds and gamers being over-weight or lazy and sitting around on their couches, have been transformed over-nightly into walkers around their parks, street corners and houses in search of these amusing virtual creatures. Even people who are older than the original fandom of the Pokémon series are now walking about to catch them all. The charm of augmented reality is such that it is sending the Android community in a frenzied treasure hunt like children. Continue reading “An Analysis of The Growing Popularity Of Pokémon Go”

The First Sci-Fi Movie Written By An Algorithm!

If you thought algorithms were these boring formulas that have no point, then it is time for you to rethink. Algorithms these days are replacing the need for human intellect altogether (do you smell a hint of irony in there?). As much as this may sound totally unbelievable but it is in fact the truth. The first ever short film has been made that is completely written by an algorithm, and is finally out and it is pretty great. Although the convoluted dialogues of the screenplay needs a few mental gymnastics to be performed by the audience’s brains, but then again isn’t that the best thing about sci-fi movies after all?

 

The First Sci-Fi Movie Written By An Algorithm!

 

The story behind this amazing film starts with an aspiring film-maker Oscar Sharp, named appropriately for the movie-making world (Again irony… Get it? Oscar… movies?!). This young screenplay writer wanted to submit a plot for Sci-Fi London’s 48 Hour Film Challenge. So, to create the next big hit in the world of Sci-Fi short films he read all the screenplays he could find, of the best sci-fi movies on the internet. Then the right inspiration struck him and he came up with the idea to feed all these movie plots into an algorithm, starting from movies like Ghostbusters to The X-Flies and movies like Interstellar, The Fifth Element and many more and let the algorithm work up on a script on its own. Ingenious you say or was it a complete idiocy?  Only to be discovered later that it was a great idea only with the right algorithm. Continue reading “The First Sci-Fi Movie Written By An Algorithm!”

Big Data Hacks: 5 Amazing Free Data Sources

Big data hacks: 5 amazing free data sources

With the data explosion revealing a continuum of numbers and facts and figures across the web and across businesses, it is of no doubt that data is omnipresent. But as the saying goes, sometimes it is hard to see the forest due to all the trees.  A big myth among several companies is that they need to hire data analysts to look for their own data for analysis and to reap the benefits from Big Data analytics. But you must realize that this is far from the truth.

There are more than hundreds in fact even thousands of free data sets available for analysis and use for those who are smart enough to know where to look for them. Here is a list of 5 most popular free data set sources that are widely used globally. There are several more out there for those who are keen enough to look for them.

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  • Data.gov: in compliance to the promise made by the US government last year all the government data is available for free on the internet in this site. The site is a useful source of information on everything starting from numbers in association to crime to climate change and much more.
  • Socrata: another great place to get scoop on the latest government related data along with some useful visualization tools that come built into the web portal.
  • org another place to access government data for free. One can get access to government data from the US, Canada, EU, CKAN and more.
  • World Health Organization data portal: a place to access all the statistics of hunger, health and disease of the world can be accessed here.
  • FaceBook Graph: FaceBook over the past few years has tightened their security and privacy settings. But there are still some amounts of data open to eyes without any privacy. And FaceBook provides information and access to all this data with their Graph API. While users may not be happy to share them with the world, they probably have not yet figured out how to hide them.

A bonus free data source that could also be fun to explore.

Face.com: get face recognition data with this fascinating tool and analyze possibilities like the creator.

These days a lot of forward thinking companies are trying to data driven, but they may not have ample resources to get their own data right away. So, it may be a good idea to begin with these publicly available free data sources. The best tip for data scientists is to learn to ask the right questions to get the right answers.

For more updates on big data hadoop training, follow DexLab Analytics. They are a premier big data training institution offering intensive career courses.

 

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