The Modi 2.0 is all set to launch a national Artificial Intelligence (AI) Programme soon, which will see the formation of a task force under Principal Scientific Advisor K Vijay Raghavan to identify projects and initiatives in which to implement the AI technology. The policy will also include a national artificial intelligence centre, which has been delayed because of a long-standing tiff between NITI Aayog and the Ministry of Electronics and Information Technology (MeitY) on which will be the department that will anchor the project. The proposed policy and the centre could finally see the light of day as the finance ministry has cleared the NITI Aayog's Rs 7,000-crore plan. "The expenditure finance committee has cleared the spending of Rs 7,000 crore till 2024-25. The NITI Aayog is likely to be the line ministry for this initiative. The Cabinet note is being circulated by NITI Aayog and is likely to be cleared soon," said a government official.

The Modi 2.0 is all set to launch a national Artificial Intelligence (AI) Programme soon, which will see the formation of a task force under Principal Scientific Advisor K Vijay Raghavan to identify projects and initiatives in which to implement the AI technology. The policy will also include a national artificial intelligence centre, which has been delayed because of a long-standing tiff between NITI Aayog and the Ministry of Electronics and Information Technology (MeitY) on which will be the department that will anchor the project. The proposed policy and the centre could finally see the light of day as the finance ministry has cleared the NITI Aayog's Rs 7,000-crore plan. "The expenditure finance committee has cleared the spending of Rs 7,000 crore till 2024-25. The NITI Aayog is likely to be the line ministry for this initiative. The Cabinet note is being circulated by NITI Aayog and is likely to be cleared soon," said a government official.

MOSCOW – It's mission over for a robot called Fedor that Russia blasted to the International Space Station, the developers said Wednesday, admitting he could not replace astronauts on spacewalks. There's nothing more for him to do there, he's completed his mission," Yevgeny Dudorov, executive director of robot developers Androidnaya Tekhnika, told RIA Novosti news agency. The silvery anthropomorphic robot cannot fulfill its assigned task to replace human astronauts on long and risky space walks, Dudorov said. Fedor -- short for Final Experimental Demonstration Object Research -- was built to assist space station astronauts. A storm of publicity surrounded Fedor's space odyssey and provided some light relief for Russia's beleaguered space industry. In the last year it has seen the unprecedented failure of a manned launch and continuing delays on construction of the Vostochny spacepad where President Vladimir Putin upbraided officials last week. But Fedor turned out to have a design that does not work well in space -- standing 180 centimeters (six feet) tall, its long legs were not needed on space walks, Dudorov said. The Russian space agency said the legs were immobilized during the trip and Fedor was not programmed to grab space station hand rails to move about in microgravity. Dudorov said developers were sketching out plans for a replacement "that must suit the demands of working on the outside of the ship." Fedor, officially Skybot F-850, rocketed to the ISS on Aug. 22, entering the orbiting laboratory five days later. On the station, the robot posed holding a Russian flag and for hugs with cosmonauts who were assigned to train it before touching down back on Earth on Monday. A final tweet posted in an account in the robot's name said: "Now I'm in my case.

Not nearly enough thought has gone into the tremendous potential AI holds for decision support in governance. One hears a lot of worried talk about the potential of future robots or AGIs "taking over the world." However, while working to avoid negative outcomes is certainly worthwhile, it's equally important to think imaginatively and practically about positive potentials. We humans are not doing a tremendously great job of running our own world at present. The biggest risks concerning AI are situated at the intersection of the current sociopolitical system (wracked as it is with conflict, confusion, and unfairness) with advanced narrow AIs and early-stage AGIs. It seems clear that we could use a helping hand with governance and general management of human society on multiple levels.

The announcement Tuesday of a nearly $1 billion federal commitment toward artificial-intelligence research drew a mixed response from business leaders who said the U.S. needs to do more to maintain a competitive edge in AI. Government agencies requested $973.5 million in nondefense AI research spending for the fiscal year ending in September 2020. It is the first time the federal government has calculated agency-specific requests for spending on artificial intelligence. AI spending for the Defense Department is classified.

Kannada is the official and administrative language of the state of Karnataka in India with nearly 60 million speakers worldwide. Also, as per articles 344(1) and 351 of the Indian Constitution, Kannada holds the status of being one of the 22 scheduled languages of India . The language is written using the official Kannada script, which is an abugida of the Brahmic family and traces its origins to the Kadamba script (325–550 AD).

A plan for how the government can harness new technologies to transform public services has been set out by the Minister for Implementation, Oliver Dowden. In a speech at the start of London Tech Week today (10 June), the Minister launched a new guide to help government embrace artificial intelligence and an online marketplace to support tech start-ups sell to the public sector. These measures accompany a new Technology Innovation Strategy, setting out the government's approach to enabling widespread adoption of new technologies across the public sector. The new AI Guide will be used across government to help departments implement new opportunities for AI, such as how to make cancer diagnosis more reliable and reduce fraud, in an ethical and safe way. The guide also brings together, for the first time, research on how artificial intelligence is already being used by the public sector to save money and improve services.

Google entering verticals and competing directly against publishers, advancements in machine learning and AI and zero-click searches are the trends most likely to affect SEO in the next three years, according to a SparkToro survey of over 1,500 SEOs. Trends that are here to stay? Respondents were presented with a list of choices and asked, "How much of an impact do you believe the following trends will have on SEO in the next 3 years?" Options were ranked on a zero-to-four scale; zero meaning "no impact" and four meaning "huge impact." The trend that professionals responded were least likely to affect SEO included outcomes from US Congressional and Department of Justice investigations, visual search advances and "content-nudging" products such as Google Discover.

This research introduces a framework for forecasting, reconstruction and feature engineering of multivariate processes. We integrate derivative-free optimization with ensemble of sequence-to-sequence networks. We design a new resampling technique called additive which along with Bootstrap aggregating (bagging) resampling are applied to initialize the ensemble structure. We explore the proposed framework performance on three renewable energy sources wind, solar and ocean wave. We conduct several short- to long-term forecasts showing the superiority of the proposed method compare to numerous machine learning techniques. The findings indicate that the introduced method performs reasonably better when the forecasting horizon becomes longer. In addition, we modify the framework for automated feature selection. The model represents a clear interpretation of the selected features. We investigate the effects of different environmental and marine factors on the wind speed and ocean output power respectively and report the selected features. Moreover, we explore the online forecasting setting and illustrate that the model exceeds alternatives through different measurement errors.

Event series, such as the Wimbledon Championships and the US presidential elections, represent important happenings in key societal areas including sports, culture and politics. However, semantic reference sources, such as Wikidata, DBpedia and EventKG knowledge graphs, provide only an incomplete event series representation. In this paper we target the problem of event series completion in a knowledge graph. We address two tasks: 1) prediction of sub-event relations, and 2) inference of real-world events that happened as a part of event series and are missing in the knowledge graph. To address these problems, our proposed supervised HapPenIng approach leverages structural features of event series. HapPenIng does not require any external knowledge - the characteristics making it unique in the context of event inference. Our experimental evaluation demonstrates that HapPenIng outperforms the baselines by 44 and 52 percentage points in terms of precision for the sub-event prediction and the inference tasks, correspondingly. 1 Introduction Event series, such as sports tournaments, music festivals and political elections are sequences of recurring events. Prominent examples include the Wimbledon Championships, the Summer Olympic Games, the United States presidential elections and the International Semantic Web Conference. The provision of reliable reference sources for event series is of crucial importance for many real-world applications, for example in the context of Digital Humanities and Web Science research [7, 9, 25], as well as media analytics and digital journalism [15, 23].