Artificial intelligence (AI) has finally caught the Indian government's attention. On Feb. 01, delivering his budget speech, finance minister Arun Jaitley told parliament that the government think-tank, Niti Aayog, will spearhead a national programme on AI, including research and development. The intent showed in the numbers: Budget allocation for Digital India, the government's umbrella initiative to promote AI, machine learning, 3D printing, and other technologies, was almost doubled to Rs3,073 crore ($477 million) this year. "It's extremely encouraging to see the government recognise the need for research in cutting-edge technologies," Subrat Kar, CEO and co-founder of Noida-based video intelligence platform Vidooly, told Quartz. Niti Aayog's support will "allow us to indigenously develop technologies on par with our Silicon Valley counterparts, and reduce dependency on them," Kar said. Niti Aayog, led by CEO Amitabh Kant, has been a key promoter of various digital campaigns in the country, including the massive biometric programme, Aadhaar, and the India chain project, which is creating blockchain infrastructure to support IndiaStack, a set of codes developed around Aadhaar.

Legislators are working to get a grip on the thorny issue of artificial intelligence by conducting a series of congressional hearings to guide government understanding and adoption of the technology. Senators explore government's role as both an end user and enabler of artificial intelligence. The use of artificial intelligence a mainstream business tool grew 60 percent over the last year. Successful integration of AI into government agencies will reduce costs and increase service management efficiencies. The hearings by the House Oversight and Government Reform's Subcommittee on Information Technology are "an opportunity to leverage technology to make us more efficient," Rep. Will Hurd (R-Texas) said in a video produced by the Committee.

The UK Home Office on Monday unveiled a £600,000 artificial intelligence (AI) tool to automatically detect terrorist content. The Home Office cited tests that show the new tool can automatically detect 94% of Daesh propaganda with 99.995% accuracy. That accuracy rate translates into only 50 out of one million randomly selected videos that would require human review. The tool can run on any platform and can integrate into the video upload process to stop most extremist content before it ever reaches the internet. The tool was developed by the Home Office and ASI Data Science.

Many machine learning algorithms are vulnerable to almost imperceptible perturbations of their inputs. So far it was unclear how much risk adversarial perturbations carry for the safety of real-world machine learning applications because most methods used to generate such perturbations rely either on detailed model information (gradient-based attacks) or on confidence scores such as class probabilities (score-based attacks), neither of which are available in most real-world scenarios. In many such cases one currently needs to retreat to transfer-based attacks which rely on cumbersome substitute models, need access to the training data and can be defended against. Here we emphasise the importance of attacks which solely rely on the final model decision. Such decision-based attacks are (1) applicable to real-world black-box models such as autonomous cars, (2) need less knowledge and are easier to apply than transfer-based attacks and (3) are more robust to simple defences than gradient- or score-based attacks. Previous attacks in this category were limited to simple models or simple datasets. Here we introduce the Boundary Attack, a decision-based attack that starts from a large adversarial perturbation and then seeks to reduce the perturbation while staying adversarial. The attack is conceptually simple, requires close to no hyperparameter tuning, does not rely on substitute models and is competitive with the best gradient-based attacks in standard computer vision tasks like ImageNet. We apply the attack on two black-box algorithms from Clarifai.com. The Boundary Attack in particular and the class of decision-based attacks in general open new avenues to study the robustness of machine learning models and raise new questions regarding the safety of deployed machine learning systems. An implementation of the attack is available as part of Foolbox at https://github.com/bethgelab/foolbox .

Two controller cards that the JSC team suspected could be the culprits were even shipped back to Earth for testing.

Regardless of the media's incessant worship of the new "Zucks", and the President's desire for "every kid to code", there is something to be said for an individual that views themselves and their efforts as a part of the bigger picture. Striving for knowledge brought me beyond the horizons of discernible. Herzlichen Dank! to my publisher BIZCATALYST 360, so big-heartedly edited by Mr. Dennis J. Pitocco, who, I believe is turning undiscovered talents into international success stories. And by that I mean people who want to read … Herzlichen Dank und viele Grüße to all my readers worldwide! The word'unprecedented' seems too weak to convey just how much the dimensionless operational space of digital (r)evolution requires instantaneous reaction.

China is racing ahead in AI. Deep learning is getting a make over. AI is coming to Cannabis tech. Artificial intelligence is changing the fundamental structure of every industry in areas ranging from agriculture to cybersecurity to commerce to healthcare, and more. We're interacting with technology in new ways, from giving voice commands to washer-dryers to playing advanced gesture-controlled video games.

The U.S. government is looking to integrate more AI capabilities across agencies. The next iteration of the FITARA scorecards will start asking federal CIOs what they are doing to introduce AI into their agencies, according to Rep. Will Hurd, R-TX, at a House Oversight and Government Reform committee hearing Wednesday. Artificial intelligence experts from big tech and academia recommended that the federal government promote STEM education and research funding, open data access and ensure a light regulatory touch to amplify the track of the nascent technology and facilitate its adoption at the federal level. While AI has many applications for cybersecurity, there are also security concerns regarding the technology that need to be addressed. Not enough focus is being devoted to thinking about how adversaries might manipulate AI systems and how, once deployed, these systems will learn and change and that process might be influenced by an outside actor, said Dr. Charles Isbell, senior associate dean at Georgia Tech's College of Computing, at the panel.

Nearly 100 new planets orbiting stars outside our solar system have been found by Nasa's Kepler telescope. Researchers confirmed the presence of the 95 worlds after studying 275 possible candidates from data provided by the probe. Kepler, which is currently on the K2 mission to discover exoplanets, has found thousands of candidates since it was launched almost a decade ago. The latest discovery raises hopes that astronomers may soon find a system similar to our own that hosts alien life. Danish researchers have located 95 new planets using the Kepler telescope that was launched nearly a decade ago.

In today's complex IT environment, identifying security events fast is critical to minimizing the impact. However, in order to detect and remediate attacks in this environment, security teams need the proper tools to process and correlate massive amounts of real-time and historical security event data. By applying advanced analytics techniques to these huge amounts of data, infosec teams can better detect and defend against sophisticated attacks. Implementing this in the real world is easier said than done. The sheer variety of attack vectors, along with the volume of data to sift through, means that getting insight for security is hard.