Context-dependent semantic parsing has proven to be an important yet challenging task. To leverage the advances in context-independent semantic parsing, we propose to perform follow-up query analysis, aiming to restate context-dependent natural language queries with contextual information. To accomplish the task, we propose STAR, a novel approach with a well-designed two-phase process. It is parser-independent and able to handle multifarious follow-up scenarios in different domains. Experiments on the FollowUp dataset show that STAR outperforms the state-of-the-art baseline by a large margin of nearly 8%. The superiority on parsing results verifies the feasibility of follow-up query analysis. We also explore the extensibility of STAR on the SQA dataset, which is very promising.

Artificial intelligence is learning how to predict El Niño climate cycles. The hope is that the technology could be used to improve climate predictions and give policy-makers more time to prepare. El Niño can cause severe weather and devastating damage. A phase of the El Niño-Southern Oscillation, it occurs when water warms over the tropical Pacific Ocean, shifting east and increasing rainfall and cyclones over the Americas while pulling rain away from Indonesia and Australia. Strong El Niño events are associated with intense storms and flooding in some areas, and drought and fires in others.

RIYADH – Saudi Arabia alleged Wednesday an attack by drones and cruise missiles on the heart of the kingdom's oil industry was "unquestionably sponsored by Iran," naming but not directly accusing Tehran of launching the assault. Iran denies being involved in the attack claimed by Yemeni rebels, and has threatened the U.S. that it will retaliate "immediately" if Tehran is targeted in response. The news conference by Saudi military spokesman Col. Turki al-Malki comes after a summer of heightened tensions between Iran and the U.S. over President Donald Trump unilaterally withdrawing America from Tehran's 2015 nuclear deal with world powers. The U.S. alleges Iran launched the attack, which Yemen's Houthi rebels earlier claimed as a response to the yearslong Saudi-led war there that's killed tens of thousands of people. Al-Malki made a point not to directly accuse Iran of firing the weapons or launching them from inside of Iranian territory.

Sometimes, you can't see what's right in front of you. This is doubly true if what's in front of you is terabytes of data; the hundreds of thousands of text messages, images, videos, and phone records that constitute just a fraction of the evidence in a criminal investigation. Law enforcement agencies the world over are faced with this exact scenario--enormous amounts of data isolated in siloed systems. Sorting through information in search of relevant insights, the type of leads that could crack a case is often a tedious, manual process. That's where AI solutions based in Microsoft Azure can help.

Artificial intelligence (AI) technologies are forecast to add US$15 trillion to the global economy by 2030. According to the findings of our Index and as might be expected, the governments of countries in the Global North are better placed to take advantage of these gains than those in the Global South. There is a risk, therefore, that countries in the Global South could be left behind by the so-called fourth industrial revolution. Not only will they not reap the potential benefits of AI, but there is also the danger that unequal implementation widens global inequalities. AI has the power to transform the way that governments around the world deliver public services. In turn, this could greatly improve citizens' experiences of government. Governments are already implementing AI in their operations and service delivery, to improve efficiency, save time and money, and deliver better quality public services. In 2017, Oxford Insights created the world's first Government AI Readiness Index, to answer the question: how well placed are national governments to take advantage of the benefits of AI in their operations and delivery of public services? The results sought to capture the current capacity of governments to exploit the innovative potential of AI. The 2019 Government AI Readiness Index, produced with the support of the International Development Research Centre (IDRC), sees a development of our methodology, and an expansion of scope to cover all UN countries (from our previous group of OECD members). It scores the governments of 194 countries and territories according to their preparedness to use AI in the delivery of public services. The overall score is comprised of 11 input metrics, grouped under four high-level clusters: governance; infrastructure and data; skills and education; and government and public services. The data is derived from a variety of resources, ranging from our own desk research into AI strategies, to databases such as the number of registered AI startups on Crunchbase, to indices such as the UN eGovernment Development Index. We divided the countries by region, principally following UN groupings, with the chief exception of the Western European and Others Group, which we separated to allow more in-depth analysis of higher scoring governments.

CANBERRA – An Australian government minister on Wednesday expressed concern for three Australians arrested in Iran on suspicion of spying and separated their plight from a tense standoff in the Middle East over the weekend attack on Saudi Arabian oil facilities. Trade Minister Simon Birmingham was responding after Iran on Tuesday acknowledged for the first time that it is holding three Australian citizens, including two British dual nationals, on suspicion of espionage. "The government continues to seek information and clarity around these matters," Birmingham told Australian Broadcasting Corp. "We are concerned for the welfare of these individuals and work to make sure their treatment is as fair as possible." Iran confirmed the arrests of Melbourne University Middle East expert Kylie Moore-Gilbert in October and travel blogging couple Mark Firkin and Jolie King in July as fallout continues from Saturday's fiery missile and drone attack on the heart of Saudi Arabia's oil industry. Secretary of State Mike Pompeo was headed to Jiddah in Saudi Arabia on Tuesday to discuss possible responses to what U.S. officials believe was an attack coming from Iranian soil.

A lot of real-world applications could be modeled as the Mixed-Integer Non-Linear Programming (MINLP) problems, and some prominent examples include portfolio optimization, resource allocation, image classification, as well as path planning. Actually, most of the models for these applications are non-convex and always involve some conflicting objectives. Hence, the Multi-Objective Evolutionary Algorithm (MOEA), which does not require the gradient information and is efficient at dealing with the multi-objective optimization problems, is adopted frequently for these problems. In this work, we discuss the coding scheme for MOEA in MINLP, and the major discussion focuses on the constrained portfolio optimization problem, which is a classic financial problem and could be naturally modeled as MINLP. As a result, the challenge, faced by a direct coding scheme for MOEA in MINLP, is pointed out that the searching in multiple search spaces is very complicated. Thus, a Compressed Coding Scheme (CCS), which converts an MINLP problem into a continuous problem, is proposed to address this challenge. The analyses and experiments on 20 portfolio benchmark instances, of which the number of available assets ranging from 31 to 2235, consistently indicate that CCS is not only efficient but also robust for dealing with the constrained multi-objective portfolio optimization.

"I don't want you to be hopeful. I want you to panic. I want you to feel the fear I feel every day. And then I want you to act on changing the climate"– Greta Thunberg Greta Thunberg is a 16-year-old Swedish schoolgirl, who is famously called as a climate change warrior. She has started an international youth movement against climate change and has been nominated as a candidate for the Nobel Peace Prize 2019 for climate activism. According to a recent report by the Intergovernmental Panel (IPCC), climate change is seen as the top global threat by many countries.

Whether we know it or not, artificial intelligence (AI) is already steeped into everyday life. It's present in the way social media feeds are organised; the way predictive searches show up on Google; and how music services such as Spotify make song suggestions. The technology is also helping transform the way enterprises do business. Commonwealth Bank of Australia, for instance, has applied AI to analyse 200 billion data points to free up more time so its customer service officers can focus on doing exactly what their title suggests: servicing customers. As a result, the bank has seen a 400% uplift in customer engagement.

Telstra's independent venture capital arm has shown its intention to expand into the artificial intelligence data market following a $US100m (145m AUD) capital raising for San Francisco company Trifacta. Trifacta employs machine-learning technology to deduce a greater depth of insights from the increasing level of data migrating to cloud-based storage. Australia's largest venture capital fund, Telstra Ventures Fund No 2, led the investment, joined in the round by the likes of Energy Impact Partners, NTT Docomo, BMW Ventures and ABN AMRO. Telstra Venture joins a long and credible list of existing investors from Accel Partners, Greylock Partners, Ignition Partners and Google. "The share register for Trifacta is very impressive. It is great to have so many experienced and impressive co-investors in this deal. That is a really massive plus for us," Mr Koertge said.