Friday, September 13, 2019

Brain drain from academics is hurting economy

The study, the first of its kind, was conducted by researchers at the University of Rochester. They found that over the last 15 years, 153 artificial intelligence professors in North American universities left their posts for industry. Another 68 moved into industry while retaining part-time roles with their universities.


SAN FRANCISCO: For years, big tech companies have used huge salaries, bonuses and stock packages to lure artificial intelligence experts out of academia. Now, a study released on Friday says that migration has hurt the post-college prospects of students.

The study, the first of its kind, was conducted by researchers at the University of Rochester. They found that over the last 15 years, 153 artificial intelligence professors in North American universities left their posts for industry. Another 68 moved into industry while retaining part-time roles with their universities.

From 2004 to 2009, 26 university professors moved into industry. In 2018 alone, 41 professors made the move. The exponential rise in departures over the last decade and a half indicates that the trend will continue. The talent shift could accelerate the development of artificial intelligence inside tech giants like Google, Microsoft, Amazon and Apple.

But at the universities the professors left behind, graduating students were less likely to create new AI companies. When they did, they attracted smaller amounts of funding, according to the study. The effect was most pronounced in the field of “deep learning,” a technology that has become a crucial part of new AI systems.

In time, the brain drain from academia could hamper innovation and growth across the economy, the study argued. “The knowledge transfer is lost, and because of that, so is innovation,” said Michael Gofman, a professor of finance at the University of Rochester and one of the authors of the study.

Deep learning is driven by “neural networks,” complex mathematical systems that can learn tasks on their own by analysing vast amounts of data. By pinpointing patterns in thousands of dog photos, for instance, a neural network can lear n to recognise a dog.

Big tech companies have hired many of the academics who specialized in the technique. Three longtime academics recently won the Turing Award — often called the Nobel Prize of computing — for their work on neural networks. Two have moved into industry, one to Google and the other to Facebook.

Tech and automobile industry’s interest in artificial intelligence of all kinds has increased, according to the study. Google and DeepMind, both owned by Alphabet, have hired 23 professors. Amazon has hired 17 professors. Microsoft has hired 13 professors. And Uber, Nvidia and Facebook have each hired seven.

Tech companies disagree with the notion that they are plundering academia. A Google spokesman, for example, said the company is an enthusiastic supporter of academic research.

The study found that students most affected by the departures were those who graduated four to six years later, meaning they probably had little interaction of the departing professors. At any given university, a significant increase in the number of departing professors reduced the number of AI entrepreneurs by 13%.

Experts are split on whether a decline in the startup economy will harm the progress of AI. But many agree that university funding should be increased to ensure that the next generation is properly educated.

AI could improve police paperwork: MHA think tank

BPRD’s futuristic vision for law enforcement , especially in smart cities, Prime Minister Narendra Modi’s ambitious project, is part of a concept note the body has drafted.
In a recent interview with The Economist, author Malcolm Gladwell, too discusses the importance of AI in the criminal justice system.(HT image)


The use of Artificial Intelligence in police paperwork, including charge sheets could remove flaws and prejudices from creeping into investigations, India’s Bureau of Police Research & Development (BPRD), a think-tank of the ministry of home affairs (MHA), believes.

BPRD’s futuristic vision for law enforcement , especially in smart cities, Prime Minister Narendra Modi’s ambitious project, is part of a concept note the body has drafted.

“A machine-learning algorithm can generate chargesheets specific to an incident with complete legal validity without any exclusions or non-conformity. This allows minimal manual intervention; hence the scope for malicious intent is not there in any way and the ability of the legal system to prosecute to the fullest extent of the law is always available. In the charge sheet, references from other judgements as well as other outcomes can also be included to make it more effective,” reads the note, a copy of which has been seen by HT.

Asserting that AI based systems have outperformed lawyers as well as judges in some cases, the BPRD note adds: “A neural network based system over a period of time can also create sensor based inputs in order to predictively allow for the analysis of outcome of cases as well, helping speed up the judicial process. The consequent burden on the policing system goes down”.

In a recent interview with The Economist, author Malcolm Gladwell, too discusses the importance of AI in the criminal justice system. Citing an example of judges taking bail decisions, Gladwell says, “..Defendants stand in front of the judge, the judge has to decide whether I released this person until the trial or I put the person in jail. Are they likely to commit another crime in the interim? That’s an extremely difficult decision to make. And when we look at how effective judges are in predicting the dangerousness of the defendant, they are not very good at it. But look how the machine learning algorithm tends to do better, actually much better than the judge. So there is an instance where we have clear evidence that a disembodied computer can be more accurate in making a prediction about the human being than a judge.”

Gladwell, however, also argues that there is a need to combine both the decision making of humans and AI, a view that many proponents of AI have also advocated.

According to BPRD, AI models coupled with crime mapping can be developed “to analyse crime patterns and identify hotspots which act as a useful tool for predictive and preventive policing”.

The police can also use AI based on algorithmic software at a crime scene for immediate recognition of perpetrator (s) based on modus operandi, pattern of crime/criminals in the area, biometric data, forensic data etc, the note claims. The BPRD note cites the example of San Francisco based Deep Science AI which has developed AI Surveillance (AIS) platform which uses deep learning to identify real people concealing their faces/firearms of intruders.

AI can also be used to manage traffic in smart cities, BPRD has suggested in its note.

To be sure, all this needs integrated data on video surveillance of public places, a wide CCTV camera network, sensors just about everywhere, databases of criminals, information on public transport, real-time tracking of events, and other such, the note admits. It also adds that privacy concerns need to be factored in while using such technologies.

When asked how AI can help police smart cities, Tarun Wig, co-founder of Innefu, a data analytics and cyber security company which provides predictive intelligence systems to various government institutions said: “The AI based system will read the text on a particular case which has to be charge sheeted and extract data on similar charges and relevant law provisions. It can read the type of crimes and tell police how to use its resources”.

BPRD and MHA officials did not respond to queries seeking comment on the concept note.

Wednesday, September 11, 2019

'Make in India' push: ABB, NITTTR set up digital simulation lab in Chandigarh

Supporting the nation’s vision of becoming a global manufacturing hub, ABB partnered with NITTTR, for a digital simulation of a CoE lab for students and faculty
The funding for the project is part of ABB India's CSR initiative



New Delhi: Swiss power major ABB India on Tuesday announced the company and the National Institute of Technical Teachers Training and Research (NITTTR) have set up a digital simulation lab in Chandigarh.

The first-of-its-kind multi-physics 'Simulation Center of Excellence' (SCoE) in the country will enhance skill development for critical electro-mechanical equipment design and manufacturing, catalysing 'Make in India' for the students and the faculty members of the institute, according to a statement by ABB India.

The funding for the project is part of ABB India's corporate social responsibility (CSR) initiative.

The Center has added another feather in the cap of educational hub of Chandigarh and Mohali, having institutes of repute ranging from business schools to state-of-the-art research institutions. Chandigarh and its adjoining areas have also become a sought-after destination also for outsourcing industries.


Students from electrical and mechanical engineering departments of the institute have been working with ABB on online remote condition monitoring of motors and issues of motor casings.

Though the SCoE was established with focus on electromechanical systems, the high-performance computing feature of workstations in SCoE has also been used by students of the computer science department of the NITTTR for their postgraduate thesis work in the domain of machine learning.

"A combination of knowledge and expertise developed through the right skilling initiatives would be key to take the Indian economy to the next level of growth. ABB India over decades has been working on various initiatives to catalyse teaching, learning and skill development on best-in-class global technology and practices," said ABB India Managing Director Sanjeev Sharma in the statement.


"The upgraded computing, simulation and analysis facilities available in SCoE has brought opportunities for NITTTR students and faculty for research of complex industrial systems. With the availability of SCoE infrastructure, NITTTR faculty has been able to introduce new short-term courses in the domain of Finite Element Analysis for the technical teachers," said NITTTR Director Shyam Sundar Pattnaik.

In a bid to spur NAAC accreditation, UGC assigns Telangana i

Bill to merge AICTE, UGC in final stages

The HRD ministry’s five-year Education Quality Upgradation and Inclusion Programme (EQUIP), which was released in June, called for the need to set up a Higher Education Commission of India (HECI).

The official however, refused to share more details about the elements of the bill.(HT image)

A bill that aims to merge the University Grants Commission (UGC) and the All India Council for Technical Education (AICTE) to create a single regulator for higher education in the country is in the final stages of preparation and likely to come up before the cabinet next month, according to an official aware of the development.

Till now, the UGC regulated the functioning, accreditation and also fund disbursal to 40 central varsities while the AICTE played a similar role for technical institutions. The government has been considering setting up a single regulatory body that would focus on imparting quality education and learning outcomes. The function of fund disbursal would not be a role for such a body.

“The India Higher Education Commission Bill to replace the UGC and the AICTE has been prepared in consultation with the states. The ministry plans to take it to the cabinet next month,” the official said on condition of anonymity. The official added that the bill is in its final stages.

The official however, refused to share more details about the elements of the bill.

The HRD ministry’s five-year Education Quality Upgradation and Inclusion Programme (EQUIP), which was released in June, called for the need to set up a Higher Education Commission of India (HECI).

The plan envisaged the HECI as a regulatory body to promote the quality and standards of education by merging the UGC and AICTE.

According to the suggestion of the EQUIP report, the HECI will primarily focus on academic and quality matters related to ensuring learning outcomes, mentoring of institutions, training of teachers and administrators. It would also seek to promote education through Information and Communication Technology (ICT) initiatives.

According to the EQUIP report, which HRD officials terms as their five-year implementation plan, the HECI will grant autonomy to best performing higher educational institutions and award them powers to confer degrees.

The disbursal of funds that the UGC presently undertakes will be kept separate from the commission, according to the EQUIP report. “Disbursal of the funds shall be done through an SPV [Special Purpose Vehicle]. The HECI shall provide for comprehensive and holistic growth of higher education and research in a competitive global environment,” the report said.

A bill seeking the formation of a National Research Foundation (NRF) is also ready and expected to be placed before the Union cabinet for approval.

In her budget speech in July, finance minister Nirmala Sitharaman proposed to the formation of the NRF to fund, promote and coordinate research in the country. “The NRF will assimilate the research grants being given by various ministries independent of each other,” she had said.

“The need to create an umbrella body for the higher education sector has been felt for a long time. However, what kind of relations it has with other bodies including varsities and institutions would define its success. Its role vis-à-vis all other bodies will have to be carefully defined,” said former UGC member Prof Inder Mohan Kapahy.

New Arrivals: September 9-13, 2019


Accession Number 
Class No. 
Author/Editor 
Title 
Publisher 
Year 
No. of Copies
Branch / Subject 
27321-27330
343.7309 VIS 
VISWANATHAN/ SURESH T.  
BHARAT'S THE INDIAN CYBER LAW 
BHARAT LAW HOUSE
   
2015 
10
INFT/CMPN/ExTC/ Cyber Security and Laws
27331-27335
620.112 SUB 
SUBRAMANIAN/ R.  
STRENGTH OF MATERIALS 
 OXFORD UNIVERSITY PRESS

   2016 
5
 MECHANICAL/Strength of Materials
27336-27365
005.8 GOD/BEL 
GODBOLE/ NINA/ BELAPURE/ SUNIT  
CYBER SECURITY: UNDERSTANDING CYBER CRIMES, COMPUTER FORENSICS AND LEGAL PERSPECTIVES 
WILEY INDIA
2011
30
INFT/CMPN/ExTC/ Cyber Security and Laws
27366-27370
005.8 CHA/CHA 
CHATTERJEE/ MADHUMITA/ CHAUDHARY/ SANGITA/ SHARMA/ GAURAV  
CYBER SECURITY AND LAWS: AN INTRODUCTION 
STAREDU SOLUTIONS
   
2019 
5
CMPN/Cyber Security and Laws
27371-27440
621.4021 KHU/KHU 
KHURMI/ R.S./ KHURMI/ N.  
STEAM TABLES WITH MOLLIER DIAGRAM 
S. CHAND
   
2018 
70
MECHANICAL/Thermodynamics

The Top Programming Languages 2019

Python remains the big kahuna, but specialist languages hold their own
By Stephen Cass

Welcome to IEEE Spectrum’s sixth annual interactive ranking of the top programming languages. This year we’ve done a major overhaul, changing some of the underlying metrics and building a new streamlined interface. But our basic idea and methodology remains the same: combining data from multiple sources to rank the popularity of the programming languages that are used for the type of coding you are interested in.

We take this approach to get around the two fundamental obstacles to all attempts to determine the popularity of programming languages: (1) No one can actually look over the shoulder of every coder around the world as they tap away at the keyboard, and (2) a language that’s a cornerstone of one programming domain might be utterly irrelevant in another. Spectrum gets data for 11 metrics from 8 sources that we think are good proxies for popularity, and we combine the results in an app that lets you filter languages and adjust the weights given to each metric. The upshot is a ranking that’s right for you. (As part of our overhaul, we’ve retired two metrics that we used in previous years because we didn’t think they were yielding good quality data anymore, incorporated data from the IEEE Job Site, and added some new languages to the list, such as Dart.)

Of course, we’ve also got some preset weightings built in that are optimized for job seekers, for example, or folks interested in diving into an open-source side project. Our default weighting is optimized for the typical Spectrum reader, so let’s take a look at what it shows as the top 10 languages of 2019.

Although the changes in our underlying metrics mean that we have to be careful when directly comparing this year’s rankings to last year’s, the general outline of results remains similar, with Python firmly on top. Python’s popularity is driven in no small part by the vast number of specialized libraries available for it, particularly in the domain of artificial intelligence, where the Keras library is a heavyweight among deep-learning developers: Keras provides an interface to the TensorFlow, CNTK, and Theano deep-learning frameworks and tool kits. Deep learning isn’t the only field where Python is having an impact that could not have been anticipated when the language was first released in 1991. The dramatic increase in computing power found in microcontrollers means that embedded versions of Python, such as CircuitPython and MicroPython, are becoming increasingly popular among makers.

Next comes Java, C, and C++, a group whose members have long jostled with one another and with Python for the top spot, although with our adjusted metrics the distance between these contenders has widened, with C++ coming in with a score of 12.5 points below Python. (In any given ranking, the highest-ranked language is assigned a score of 100, and the scores of lower-ranked languages are scaled to that.) The number-crunching language R rounds out the top five. Despite being a much more specialized language than the others, it’s maintained its popularity in recent years due to the world being awash in an ever-growing pile of big data.

Moving further down the top 10, the presence of Matlab—a proprietary language developed by MathWorks and intended for numerical computing—may be a surprise to some, but it simply reflects the language’s prominence in hardware engineering, especially for those interested in running simulations or creating control systems via MathWorks’ graphical Simulink package.

Below the top 10, some items of note include Arduino at No. 11 and HTML/CSS at No. 12. In previous years, some readers have complained that neither should appear on a list of programming languages. In the case of Arduino, the argument is that there is no such language, that “Arduino” is actually the name of the family of hardware platforms on which the language runs, and that this language should be called Wiring (or sometimes C or C++ for historical reasons). In this, we are led by simple pragmatism: When faced with a programming question, the overwhelming majority of Arduino developers search Google using terms like “Arduino Code for…,” rather than any alternative. By choosing the de facto name, we avoid deeply discounting the popularity of programs written for the Arduino and similar microcontrollers.

Pragmatism is also the name of the game when it comes to HTML, with the objection here that it is not a real programming language because it doesn’t have branching or loop constructs. But given the huge popularity of HTML and CSS among developers, and the fact that they are used to instruct billions of computers to do things daily, we feel any academic arguments about Turing completeness and so on are beside the point. A markup language is still a language.

Finally, some older languages are still alive and kicking. In particular, despite being over 60 years old, Fortran still comes in at No. 38, likely due to the enormous legacy power of being the original scientific computing language. The language is still under active development, with the most recent Fortran standard released at the end of 2018, incorporating improved interoperability with C and better support for massive parallel computations.

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