Harald Sack is Professor for Information Services Engineering at two of the most renowned research institutions in Europe: FIZ Karlsruhe and AIFB. He is a part of SEMANTiCS' research and innovation track program committee as well as of the conference's permanent advisory board. His publications include more than 130 papers in international journals and conferences and three standard textbooks on networking technologies. In this interview he speaks about the limited capabilities of search engines, the necessity of data being open and the coffee culture in Vienna. You have been working in many research areas such as semantic web technologies, knowledge representations, multimedia analysis & retrieval.

The growth of the Artificial Intelligence (AI) sector is evident from the growing number of job roles in the industry. According to statistics from the job search engine Indeed, the start of this year had double the AI jobs advertised on its site than Canada experienced. Even for America, a country that will be at the forefront of the push to AI, the UK jobs advertised for the sector in the UK was in excess of 20% higher. For every one million UK jobs advertised on Indeed's website, 1,300 of them were for AI-related roles, which highlights the growing popularity of the sector, and the need to fill these roles. The government has made it clear that AI will play a huge role in the economy in future years; a tech sector deal worth £1 billion has been announced that is backed by a number of private sector organisations who will contribute approximately £300 million in funding.

Insurers must increase their efforts to integrate artificial intelligence efforts with an evolving workforce in order to take best advantage of the new technology, according to a report released Thursday by consultancy Accenture P.L.C. The report, Future Workforce Survey – Insurance: Realizing the Full Value of AI, said that artificial intelligence "is likely to transform the world of business." Artificial intelligence, the report said, must be seen as more than just a set of tools to make operations more efficient. "We believe AI, when synthesized with human ingenuity across the enterprise, will achieve exponentially more," the report said. Insurers which invest in such an AI and human-machine collaboration at the same rate of top-performing businesses could boost revenue by 17% and their employment 7%, on average, between 2018 and 2022, the report said.

Chatbots and artificial intelligence (AI) are becoming business essentials. If utilised correctly, the continent will be able to benefit from the wealth of data its citizens generate on a daily basis. You recently participated on a panel titled Entrepreneurial Perspectives on Emerging Technologies in the Field of Artificial Intelligence and Autonomous Systems in Switzerland. With the power of big data, companies in Africa are looking for opportunities to provide more personalised customer experiences, improve core business processes and spark innovation through the use of AI. Businesses use chatbots to collect meaningful data through conversation.

Many information retrieval algorithms rely on the notion of a good distance that allows to efficiently compare objects of different nature. Recently, a new promising metric called Word Mover's Distance was proposed to measure the divergence between text passages. In this paper, we demonstrate that this metric can be extended to incorporate term-weighting schemes and provide more accurate and computationally efficient matching between documents using entropic regularization. We evaluate the benefits of both extensions in the task of cross-lingual document retrieval (CLDR). Our experimental results on eight CLDR problems suggest that the proposed methods achieve remarkable improvements in terms of Mean Reciprocal Rank compared to several baselines.

Boolean tensor decomposition approximates data of multi-way binary relationships as product of interpretable low-rank binary factors, following the rules of Boolean algebra. Here, we present its first probabilistic treatment. We facilitate scalable sampling-based posterior inference by exploitation of the combinatorial structure of the factor conditionals. Maximum a posteriori decompositions feature higher accuracies than existing techniques throughout a wide range of simulated conditions. Moreover, the probabilistic approach facilitates the treatment of missing data and enables model selection with much greater accuracy. We investigate three real-world data-sets. First, temporal interaction networks in a hospital ward and behavioural data of university students demonstrate the inference of instructive latent patterns. Next, we decompose a tensor with more than 10 billion data points, indicating relations of gene expression in cancer patients. Not only does this demonstrate scalability, it also provides an entirely novel perspective on relational properties of continuous data and, in the present example, on the molecular heterogeneity of cancer. Our implementation is available on GitHub: https://github.com/TammoR/LogicalFactorisationMachines.

I had a new talk presented at "Codemotion Amsterdam 2018" this week. I discussed the relation of Apache Kafka and Machine Learning to build a Machine Learning infrastructure for extreme scale. As always, I want to share the slide deck. The talk was also recorded. I will share the video as soon as it was published by the organizer.

WASHINGTON--(BUSINESS WIRE)--The following is an opinion editorial provided by Brian Krzanich, chief executive officer of Intel Corporation. China, India, Japan, France and the European Union are crafting bold plans for artificial intelligence (AI). They see AI as a means to economic growth and social progress. Meanwhile, the U.S. disbanded its AI taskforce in 2016. The U.S. technology sector has long been a driver of global economic growth.

LONDON, ENGLAND - DECEMBER 05: Co-founder of Google DeepMind Mustafa Suleyman attends a Q&A during day 1 of TechCrunch Disrupt London at the Copper Box on December 5, 2016 in London, England. Google has found another use for DeepMind's machine learning software after buying the London artificial intelligence lab for a reported £400 million in 2014. Later this year, the search giant will roll out two new DeepMind-built Android features that are designed to improve battery life and optimise screen brightness levels. The features will be available to people with devices running the Android P operating system. The features -- announced during the Google I/O developer conference -- were built by a unit called "DeepMind for Google," which focuses on applying DeepMind's technology to Google products.

Are Healthcare Leaders Ready For AI-Driven Change? Last year I looked at a new report from the House of Lords that explored the'future of healthcare'. As the name of the report suggests, the nature of the work lended itself to longer-term thinking, and this is a central criticism of current NHS leadership. Whilst the Five Year Forward View published by NHS England in 2014 is widely supported, it doesn't look beyond 2019, and nothing has entered the public domain to highlight NHS policy beyond then. Unfortunately, it's not at all clear that the report fills that vacuum, despite a hugely impressive range of names summoned to give evidence to the committee.