Visual Analytics (VA) integrates humans, data, and models as key actors in insight generation and data-driven decision-making. This position paper values and reflects on 16 VA process models and frameworks and makes nine high-level observations that motivate a fresh perspective on VA. The contribution is the HDMI Canvas, a perspective to VA that complements the strengths of existing VA process models and frameworks. It systematically characterizes diverse roles of humans, data, and models, and how these actors benefit from and contribute to VA processes. The descriptive power of the HDMI Canvas eases the differentiation between a series of VA building blocks, rather than describing general VA principles only. The canvas includes modern human-centered methodologies, including human knowledge externalization and forms of feedback loops, while interpretable and explainable AI highlight model contributions beyond their conventional outputs. The HDMI Canvas has generative power, guiding the design of new VA processes and is optimized for external stakeholders, improving VA outreach, interdisciplinary collaboration, and user-centered design. The utility of the HDMI Canvas is demonstrated through two preliminary case studies.

This article explores human-like movement from a fresh perspective on motion planning. We analyze the coordinated and compliant movement mechanisms of the human body from the perspective of biomechanics. Based on these mechanisms, we propose an optimal control framework that integrates compliant control dynamics, optimizing robotic arm motion through a response time matrix. This matrix sets the timing parameters for joint movements, turning the system into a time-parameterized optimal control problem. The model focuses on the interaction between active and passive joints under external disturbances, improving adaptability and compliance. This method achieves optimal trajectory generation and balances precision and compliance. Experimental results on both a manipulator and a humanoid robot validate the approach.

We introduce a novel classification framework for time-series imputation using deep learning, with a particular focus on clinical data. By identifying conceptual gaps in the literature and existing reviews, we devise a taxonomy grounded on the inductive bias of neural imputation frameworks, resulting in a classification of existing deep imputation strategies based on their suitability for specific imputation scenarios and data-specific properties. Our review further examines the existing methodologies employed to benchmark deep imputation models, evaluating their effectiveness in capturing the missingness scenarios found in clinical data and emphasising the importance of reconciling mathematical abstraction with clinical insights. Our classification aims to serve as a guide for researchers to facilitate the selection of appropriate deep learning imputation techniques tailored to their specific clinical data. Our novel perspective also highlights the significance of bridging the gap between computational methodologies and medical insights to achieve clinically sound imputation models.

Artificial intelligence has been given new capabilities never seen before, computer scientists have claimed. Researchers were able to use AI to help prove and suggest new complex mathematical theorems. Scientists hailed the breakthrough as a major step towards giving major new capabilities to such systems. "Problems in mathematics are widely regarded as some of the most intellectually challenging problems out there," said Geordie Williamson, a mathematician who was a co-author on a new paper describing the breakthrough. "While mathematicians have used machine learning to assist in the analysis of complex data sets, this is the first time we have used computers to help us formulate conjectures or suggest possible lines of attack for unproven ideas in mathematics."

There seems no end to the plethora of software solutions suddenly seeming to have acquired the quality of artificial intelligence (AI). Little more than a decade after phones reportedly grew "smart," you might now be wondering whether technology had crossed yet another historic threshold. For those of us who grew up watching 2001 A Space Odyssey and Knight Rider, the concept of non-human intelligence--whether benevolent or malevolent--is nothing new. Not only does science fiction fuel our expectations, it has often demonstrated an uncanny ability at predicting real life technological advancements. Is the age of artificial intelligence now upon us?

Let's escape the narrow mindset that Google and search engines only prize three primary ranking factors. As important as links and publishing content remain, search engines are growing far more complex than relying on traditional text and document analysis to rank its index. Instead, we should view SEO as an organic ecosystem, where each small snippet of code directly or indirectly ties into the performance of your website. Link building to a slow site becomes useless, as is publishing content that gets interrupted by obtrusive interstitials on a mobile device. Following the best practices is pointless, unless you're following all of them.

Let's escape the narrow mindset that Google and search engines only prize three primary ranking factors. As important as links and publishing content remain, search engines are growing far more complex than relying on traditional text and document analysis to rank its index. Instead, we should view SEO as an organic ecosystem, where each small snippet of code directly or indirectly ties into the performance of your website. Link building to a slow site becomes useless, as is publishing content that gets interrupted by obtrusive interstitials on a mobile device. Following the best practices is pointless, unless you're following all of them.

The TNW Festival in Amsterdam took place in the hometown of our Head of Sales BENELUX, Roy Somaroo. So naturally, Roy went along to find out what the hottest topics in the tech scene are. As I bounced between the nine different themes of TNW I was struck by the convergence of thoughts. Despite the variety of speakers and opinions, it seemed there were some themes that you just couldn't avoid. For me, it all boiled down to two things: technology and experience.

CONVERSATIONS on the future have seen a common theme emerge - that it is disrupted and predominantly digital. Technological advancements in artificial intelligence, robotics, sharing platforms and the Internet of Things are fundamentally altering business models and industries. These changes are often not only alien to businesses; they are taking place at unprecedented speed. Many organisations, in particular the larger established ones that are encumbered by complex structures and bureaucratic processes, may find adapting to the pace of change a real struggle. Entrepreneurial businesses are often said to have a huge competitive advantage by virtue of their smaller size and simpler business model, which affords them the needed agility.