This paper presents a retrospective overview of a decade of research in our department towards self-organizing personal knowledge assistants in evolving corporate memories. Our research is typically inspired by real-world problems and often conducted in interdisciplinary collaborations with research and industry partners. We summarize past experiments and results comprising topics like various ways of knowledge graph construction in corporate and personal settings, Managed Forgetting and (Self-organizing) Context Spaces as a novel approach to Personal Information Management (PIM) and knowledge work support. Past results are complemented by an overview of related work and some of our latest findings not published so far. Last, we give an overview of our related industry use cases including a detailed look into CoMem, a Corporate Memory based on our presented research already in productive use and providing challenges for further research. Many contributions are only first steps in new directions with still a lot of untapped potential, especially with regard to further increasing the automation in PIM and knowledge work support.

Datastores continue to advance on a number of fronts. Some of those that come to mind are adapting to faster networks (e.g. 'FARM: Fast Remote Memory') and persistent memory (see e.g. 'Let's talk about storage and recovery methods for non-volatile memory database systems'), deeply integrating approximate query processing (e.g. Today's paper gives us an exciting look at the untapped potential for network-accelerated query processing.

Trends like digital transformation even intensify the already overwhelming mass of information knowledge workers face in their daily life. To counter this, we have been investigating knowledge work and information management support measures inspired by human forgetting. In this paper, we give an overview of solutions we have found during the last five years as well as challenges that still need to be tackled. Additionally, we share experiences gained with the prototype of a first forgetful information system used 24/7 in our daily work for the last three years. We also address the untapped potential of more explicated user context as well as features inspired by Memory Inhibition, which is our current focus of research.

Knowledge workers face an ever increasing flood of information in their daily lives. To counter this and provide better support for information management and knowledge work in general, we have been investigating solutions inspired by human forgetting since 2013. These solutions are based on Semantic Desktop (SD) and Managed Forgetting (MF) technology. A key concept of the latter is the so-called Memory Buoyancy (MB), which is intended to represent an information item's current value for the user and allows to employ forgetting mechanisms. The SD thus continuously performs information value assessment updating MB and triggering respective MF measures. We extended an SD-based organizational memory system, which we have been using in daily work for over seven years now, with MF mechanisms directly embedding them in daily activities, too, and enabling us to test and optimize them in real-world scenarios. In this paper, we first present our initial version of MB and discuss success and failure stories we have been experiencing with it during three years of practical usage. We learned from cognitive psychology that our previous research on context can be beneficial for MF. Thus, we created an advanced MB version especially taking user context, and in particular context switches, into account. These enhancements as well as a first prototypical implementation are presented, too.

In next eight years, revenue from Artificial Intelligence (AI) market will grow 25-fold to be more than Rs 3.9 lakh crore by 2025. This year the revenues globally stood at Rs 15,628 crore, according to a report by Tractica, a market intelligence firm that focuses on human interaction with technology. The recent track of investments into the field is equally encouraging. In last four years, the investments into AI companies rose by almost 10-times reflecting the interest and investor sentiment regarding the new technology. The surging interest in implementing AI systems among institutions and companies across the world is responsible for the exponential growth projection.

Once cloud was accepted as something with various meanings, none of which our customers understood, the IT industry searched for the next big buzzword. It came up with not one but three terms often used interchangeably by people who don't know any better – bots, artificial intelligence and machine learning. This is great news for software developers, who can write some code and slap an AI label on it – right? Maybe we're not giving users enough credit here. You would hope they understood a chatbot returning an answer match from an FAQ set is different to facial recognition or sentiment analysis.

Chinese internet giant Baidu has released its fiscal 2016 results, reporting operating profit of 10.04 billion yuan, a 13.9 percent decrease from the year prior, on revenue of 70.5 billion yuan, up 6.3 percent from fiscal 2015. Mobile revenue represented 63 percent of total revenue in 2016, up from 2015's 53 percent, while online marketing revenues for the year reached 64.5 billion yuan, a 0.8 percent increase from 2015. Earnings before interest, taxation, depreciation, and amortisation (EBITDA) in fiscal 2016 was 15.8 billion yuan, down 5.2 percent from 2015, while operating cashflow stood at 22.2 billion yuan. In its full year and fourth quarter results, Baidu chair and CEO Robin Li said that the company is well-positioned to lead China's growth in artificial intelligence (AI), based on its technology, data, and talent pool. "Our existing platform, including our search and newsfeed products, are enhanced by AI and enriched by our content and services ecosystem," Li said.

Facebook could be in hot water over its facial recognition software. The social media giant is accused of violating users' privacy by collecting and storing biometric data without permission in order to make tagging suggestions. Facebook has argued to have the civil suit dismissed, but a US judge rejected this request. Facebook could be in hot water over its facial recognition software. The social media giant was accused of violating users' privacy by collecting and storing biometric data without permission in order to make tagging suggestions.

On the basis of the amount of start-ups working on bot related activities at Web Summit 2016, it would seem as if bots may be about to become mainstream after all. I counted 23 bot related companies exhibiting at the early stage (Alpha) area at Web Summit last week. These included bots for different kinds of services as well as bot building platforms. A year ago, this area might have been taken up by start-ups working on mobile apps. Is this a clear sign that bots are about to move beyond the nascent stage?

The Iller river stretches for 91 miles through southeastern Germany before meeting up with the Danube. This river, like all rivers, is filled with sediment-- rocks and pebbles from thousands of years ago that sit on the riverbed and along the bank. One day last year, Benjamin Maus was lounging near the Iller admiring a handful of pebbles. "I was basically just sorting pebbles and spraying them with sunscreen, which made the colors much more vivid," Maus recalls. At the time Maus, an artist, had no clue that these pebbles would inspire his latest work.