Create your own e- book

Create your own e- book

This Saturday, learn the tricks of self- publishing e- books from an experienced author

Event Details

Date | 1^st October 2016

Time | 2 pm to 5 pm

Place | Somaiya Centre for Lifelong Learning, Second Floor, Somaiya Bhavan, M G Road Fort

Call | 7045932204

Fees | 750/-

Regards

Pralhad Jadhav

Senior Manager @ Library

Khaitan & Co

Blog | http://pralhad-fyilibrarian.blogspot.in/

Note | If anybody use these post for forwarding in any social media coverage or covering in the Newsletter please give due credit to those who are taking efforts for the same.

Delhi High Court’s Ruling Against Publishers is a Triumph For Knowledge

The court conclusively stated that the reproduction of any work by a teacher or a pupil in the course of instruction would not constitute infringement.

In a landmark judgment, Justice Rajiv Sahai Endlaw of the Delhi high court has held that reproducing books and distributing copies thereof for the purpose of education is not copyright infringement. The ruling legitimises the practice of photocopying prevalent in universities and other spaces of learning. The question of whether such photocopying without the permission of the copyright holders was legal arose in 2013. A group of five prominent publishers had filed a suit against the University of Delhi and its photocopying service provider, alleging infringement of their copyrighted titles. Specifically, they argued that the infringement arose from widely used ‘course packs’ which were photocopies of collated passages and chapters from various titles and, sometimes included entire books as well. At the heart of the matter lay the interests of students and their rights and ability to access education, academics invested in the importance of readership and the free flow of knowledge and the publishers who claimed that photocopies hurt their sales and that they ought to benefit from this practice, monetarily. The publishers wanted the court to restrain the defendants from committing ‘institutionalised infringement’ and make them apply for bouquet licenses to carry on with the practice of photocopying.

The suit caused a huge furore. Soon, students and academics joined the fray to mount a stronger defence against the publishers. Notably, Amartya Sen wrote a letter urging the publishers to reconsider the action. Thirty three academics delivered a joint statement against the suit and intervened as the Society for Promoting Educational Access and Knowledge, or SPEAK, while students put forth their interests through the Association of Students for Equitable Access to Knowledge, or ASEAK.

Pending the adjudication of the matter, the court proceeded to temporarily injunct the preparation of such course packs.

The copyright law rests on a delicate balance between the interests of copyright owners (authors, publishers, creators, artists) and copyright users (those who use and enjoy the works). The law is designed to encourage the creation of works and simultaneously, to permit the users to enjoy the works and promote arts and knowledge.

In the Indian Copyright Act, 1957, section 52 lists a number of scenarios which do not constitute infringement, including a fair dealing provision. In other words, the section is the bulwark for public enjoyment of copyrighted work – it allows largely purposive acts, including fair dealing, tied to bona fide use and copying in research, educational institutions, libraries, review, reportage, criticism, incidental copying and a greater degree of use for the benefit of disabled people.

The act of photocopying, the court ruled, is reproduction of the work and constitutes infringement, unless it is listed under section 52. It found that the acts of photocopying, preparing course packs and their distribution fell within the ambit of section 52(1)(i), which states that “the reproduction of any work – by a teacher or a pupil in the course of instruction”, would not constitute infringement. Interpreting the clause in an expansive manner, the court deemed that the application of the clause is not limited to an individual teacher-student relationship, but is applicable to educational institutions and organisations such as DU and thus, the law must reflect the realities of our burgeoning educational system.

The publishers contended that use of the copyrighted material should occur only during the course of the instruction, that is, in classroom lectures. The court disagreed and held that the course of instruction “…include(s) reproduction of any work while the process of imparting instruction by the teacher and receiving instruction by the pupil continues during the entire academic session for which the pupil is under the tutelage of the teacher and that imparting and receiving of instruction is not limited to personal interface between teacher and pupil but is a process commencing from the teacher readying herself/himself for imparting instruction, setting syllabus, prescribing text books, readings and ensuring, whether by interface in classroom/tutorials or otherwise by holding tests from time to time or clarifying doubts of students, that the pupil stands instructed in what he/she has approached the teacher to learn.”

Whereas the court liberally interpreted the provision on educational institutions, it also rigidly laid out the contours of the copyright law, pivotal in enabling public enjoyment of works. It held that copyright is a statutory right and not a natural or a common law right. Thus, the nature of copyright is limited and is subject to limitations and exceptions set in the law.  It further added that “Copyright, specially in literary works, is thus not an inevitable, divine, or natural right that confers on authors the absolute ownership of their creations. It is designed rather to stimulate activity and progress in the arts for the intellectual enrichment of the public. Copyright is intended to increase and not to impede the harvest of knowledge. It is intended to motivate the creative activity of authors and inventors in order to benefit the public.”

On the issue of charging a nominal fee (40 paise per page), it was held that the said rates could not cumulatively amount to be competing with the sales price of the books. They were reasonable operational costs and only if the reproduction charges were similar to the books, could they have been said to be functioning commercially. Furthermore, the court observed that in an age of technological advancement, any act of copying for the purpose of education (within the ambit of section 52) – whether by pen and paper, or photocopying machines, or by students clicking pictures of textbooks on their cellphones should be permissible.

Justice Endlaw also pointed out that this flexing of user rights is in conformity with several international treaties. India is a signatory to the TRIPS Agreement and the Berne Convention, which allows India to decide “as to what extent utilisation of copyrighted works for teaching purpose is permitted..(provided) that the same is to the extent justified by the purpose” and does not “unreasonably prejudice the legitimate rights of the author.”

This fresh jurisprudence is a vindication of the freedom to exchange ideas and knowledge, which is crucial to fostering an excellent learning space. This will also ensure that eager students and teachers in developing countries freely share latest research and publications, without the slightest hesitation of operating in a grey area. Justice Endlaw’s judgment has aptly restored the public-serving face of copyright law, which is a huge triumph for access to knowledge.

Access Link | http://thewire.in/68151/delhi-hc-ruling-photocopying-du/#disqus_thread

Regards

Pralhad Jadhav

Senior Manager @ Library

Khaitan & Co

Blog | http://pralhad-fyilibrarian.blogspot.in/

Note | If anybody use these post for forwarding in any social media coverage or covering in the Newsletter please give due credit to those who are taking efforts for the same.

Google machine learning is smart, but not intelligent (yet)

Google's Senior Vice-President of Search John Giannandrea explains to us why true Artificial intelligence is still far away.

Artificial Intelligence has been the holy grail of Computer Science for over a hundred years and we are finally starting to scratch the first layer of this incredibly complex system. Currently, all the major players in the Technology business are investing heavily in the R&D of AI systems, but it would seem we are still very far away from the development of a true AI.

To truly get a good grasp on where the industry stood in its quest for intelligent machines, we sat down with John Giannandrea, the former Head of Machine Learning and currently the SVP Search at Google, for a one-on-one. From the conversation, it became clear that we have had the latest developments in automation all wrong, and here is the real picture.

John was quick to clarify that there are three distinct levels of Machine Intelligence; Machine Learning, Machine Intelligence and Artificial Intelligence. Machine Learning is what we have just started to get right and it’s a system where an algorithm can be written to train a machine to behave in a certain way, given certain kinds of inputs.

Machine Learning, a higher version would be where the machine is able to take what it has learnt and adapt it to a new concept and a true AI would be the kind which is able to teach itself new concepts and evolve, just like humans. We have just started to be able to get really good at generating Machine Learning algorithms, but John said we are still very far from having a system that can take what it has learnt, and adapt it to a new situation.

We’re Not in the AI Age, but the Machine Learning Era

John was quick to clarify that there are three distinct levels of Machine Intelligence; Machine Learning, Machine Intelligence and Artificial Intelligence. Machine Learning is what we have just started to get right and it’s a system where an algorithm can be written to train a machine to behave in a certain way, given certain kinds of inputs.

Machine Learning, a higher version would be where the machine is able to take what it has learnt and adapt it to a new concept and a true AI would be the kind which is able to teach itself new concepts and evolve, just like humans. We have just started to be able to get really good at generating Machine Learning algorithms, but John said we are still very far from having a system that can take what it has learnt, and adapt it to a new situation.

At the very core of any machine resembling the simplest levels of intelligence, is “training.” Every machine has to first be “trained” to process information a certain way.

Neural Networks, the Digital Training Grounds

At the very core of any machine resembling the simplest levels of intelligence, is “training.” Every machine has to first be “trained” to process information a certain way. For example, if you show a machine a photo of a Dog, it should be able to correctly label it as a dog. To be able to get that result, Google runs thousands upon thousands of training material through a neural network. A neural network is essentially multiple layers of digital filters that mimic the human brain.

Each layer has “ports” of sorts and they connect with corresponding ports just like the neurons in our brains, depending on the stimulus they carry. So on the input side, they will feed the neural network hundreds of thousands of images of dogs (and only dogs) and check that the output is “dog” for all images. Every instance there is an error, it is sent backwards into the neural network so it can “learn” from the mistake and adjust the recognition pattern. Google has managed to get some really great results from this and the proof lies in the Photos app, which is able to segregate photos based on their content.

You can type “cat” in the search bar in the Photos App and it will show you all the photos in your library with cats in them. That is Machine learning, and it is fairly limited as John pointed out that while you will get all the photos of cats, the “machine” would not be able to segregate them based on breed.

The True Limits of Machine Learning

While it may seem “really intelligent” for a piece of software to be able to separate your photos into albums based on their content, or suggest when you should leave for work based on traffic conditions (and the time by when you need to clock into work), Machine Learning at this stage, is extremely limited.

As pointed out by John, it may be able to distinguish cats from dogs, but it cannot identify breeds of cats yet. Machine Learning works only in a very limited scope of variables and the minute even a single variable changes, it will fail to execute perfectly. For example, if you were to dress up a cat as a dog, would the Photos app consider it a dog or a cat?

The Current State of Intelligent Affairs

Google’s Machine Learning API are, as per John, in their nascent stages, but are developing at a rather rapid pace. Google is using Machine Learning to augment their Search (auto complete), YouTube (suggested videos), Inbox and Allo just to name a few. Inbox has a feature where it generates automatic responses for emails based on its contents and as per John, 10 per cent of mails being sent out using Inbox are using auto-responses.

Allo takes this one step further where the machine learns the way you communicate and then makes suggestions for responses based on what it has learnt. The pinnacle of this technology, however, is the Google Assistant which is able to detect language and even separate commanding voice from ambient noise. Google Now uses Machine Learning to generate relevant information for you, based on your usage patterns.

The Privacy Issue

It is no secret that Google is collecting a lot of user data, and one way it uses this data to it train their Machine Learning APIs. When asked just how secure this was, John said that all data that is used for training, is aggregated into one large pool and is hence anonymised. None of that can really be traced back to where it came from. However, once the API is trained and implemented into a service, then it is able to read the information you have agreed to share with Google and make suggestions based on that.

The information sharing here is twofold, one to train the API itself, wherein your data is anonymised and then once the service is ready, it makes suggestions to you based on your activity. This is how Google is able to give us traffic information on Maps. It collects data from thousands on users who are commuting and displays it on the app, but you cannot identify which pixel on that red line corresponds to your car.

Future Prospects

While Google uses the ML algorithms across various of its products, it has also made various APIs available to many businesses and developers. What is interesting, however, is the medical potential the system holds. For example, if a voice assistant is able to identify extreme stress or depression in the voice of the speaker, it may be able to help by either automatically connecting the user with a loved one or suggesting various counsellors in the area.

The next step, which would be Machine Intelligence, is where the phone itself is able to offer suggestions for things even before you think of doing them. For example, if you’ve just managed to land a new job, the machine intelligence in your phone should be able to suggest that you buy a new wardrobe. If you are planning on hosting a party, it could generate a suggested guest list based on the people you’ve been interacting with, factoring in how you truly “feel” about them.

The best part about Google efforts is that they have made their Machine Learning resources available for free under the name of Tensor Flow and anyone can start using the tool to train machines for specific tasks.

Google truly is trying to make significant efforts into providing us a convenience that can have far reaching consequences in our daily lives. With the hectic lifestyles that have become commonplace, having a digital assistant who can keep track of your daily affairs is a rather helpful tool.

We take hundreds of photos every month and it is nice to see them get separated and organised into various categories by themselves. The most exciting thing is that we are just starting to scratch the surface of the convenience this new technological breakthrough can bring to our lives and better products are not very far into the future.

Access Link | http://indianexpress.com/article/technology/tech-news-technology/google-machine-learning-is-smart-but-not-intelligent-yet/

Regards

Pralhad Jadhav

Senior Manager @ Library

Khaitan & Co

Blog | http://pralhad-fyilibrarian.blogspot.in/

Note | If anybody use these post for forwarding in any social media coverage or covering in the Newsletter please give due credit to those who are taking efforts for the same.

Digital Marketing

Indian American Engineers Devise Way to Send Secure Passwords Via Human Touch

NEW YORK — A team of Indian American engineers has devised a way to send secure passwords through the human body using smartphone fingerprint sensors and laptop touchpads — rather than over the air where they're vulnerable to hacking.

Sending a password or secret code over airborne radio waves like Wi-Fi or Bluetooth means anyone can eavesdrop, making those transmissions vulnerable to hackers who can attempt to break the encrypted code.

Now, computer scientists and electrical engineers from the Seattle-based University of Washington have devised a way to send secure passwords through the human body — using benign, low-frequency transmissions generated by fingerprint sensors and touchpads on consumer devices.

"Fingerprint sensors have so far been used as an input device. What is cool is that we've shown for the first time that fingerprint sensors can be re-purposed to send out information that is confined to the body," said senior author Shyam Gollakota, assistant professor of computer science and engineering.

These "on-body" transmissions offer a more secure way to transmit authenticating information between devices that touch parts of your body — such as a smart door lock or wearable medical device — and a phone or device that confirms your identity by asking you to type in a password.

"Let's say I want to open a door using an electronic smart lock," said co-lead author Merhdad Hessar, an electrical engineering doctoral student. "I can touch the doorknob and touch the fingerprint sensor on my phone and transmit my secret credentials through my body to open the door, without leaking that personal information over the air."

The research team tested the technique on the iPhone and other fingerprint sensors, as well as Lenovo laptop trackpads and the Adafruit capacitive touchpad.

In tests with 10 different subjects, they were able to generate usable on-body transmissions on people of different heights, weights and body types.

The system also worked when subjects were in motion — including while they walked and moved their arms.

"We showed that it works in different postures like standing, sitting and sleeping," said co-lead author Vikram Iyer, an electrical engineering doctoral student. "We can also get a strong signal throughout your body. The receivers can be anywhere — on your leg, chest, hands — and still work."

The technology could also be useful for secure key transmissions to medical devices such as glucose monitors or insulin pumps, which seek to confirm someone's identity before sending or sharing data.

The new technique was described in a paper presented at the 2016 Association for Computing Machinery's International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016) in Germany this month.

Access Link | http://www.indiawest.com/news/technology/indian-american-engineers-devise-way-to-send-secure-passwords-via/article_4c80deea-85c9-11e6-8d17-dfaabd38e3f0.html

Regards

Pralhad Jadhav

Senior Manager @ Library

Khaitan & Co

Blog | http://pralhad-fyilibrarian.blogspot.in/

Note | If anybody use these post for forwarding in any social media coverage or covering in the Newsletter please give due credit to those who are taking efforts for the same.