Recent literature has seen a considerable uptick in $\textit{Differentially Private Natural Language Processing}$ (DP NLP). This includes DP text privatization, where potentially sensitive input texts are transformed under DP to achieve privatized output texts that ideally mask sensitive information $\textit{and}$ maintain original semantics. Despite continued work to address the open challenges in DP text privatization, there remains a scarcity of work addressing user perceptions of this technology, a crucial aspect which serves as the final barrier to practical adoption. In this work, we conduct a survey study with 721 laypersons around the globe, investigating how the factors of $\textit{scenario}$, $\textit{data sensitivity}$, $\textit{mechanism type}$, and $\textit{reason for data collection}$ impact user preferences for text privatization. We learn that while all these factors play a role in influencing privacy decisions, users are highly sensitive to the utility and coherence of the private output texts. Our findings highlight the socio-technical factors that must be considered in the study of DP NLP, opening the door to further user-based investigations going forward.

Nintendo surprised fans yesterday by announcing a new chapter in its 40-year-old Zelda saga, one of the Japanese video game titan's biggest franchises. During an event broadcast on the web, the firm said The Legend of Zelda: Echoes of Wisdom is scheduled for release on the Switch console on 26 September. Eiji Aonuma, producer of the Zelda series, said on a webcast that fans would be able to play as Princess Zelda herself rather than the elf-like warrior Link – a first for an official entry into the game's canon. "This time around Link has vanished and it's up to Princess Zelda to step into the protagonist's role," Aonuma said. Each new chapter of Zelda is eagerly awaited by fans – the franchise has racked up well over 140 million sales since it began in 1986.

Analysts at Deloitte have unveiled their predictions for what they believe will be the most important tech trends of the next 12 months. To do this, they have framed core trends, including machine learning, cloud computing, and blockchain, against the dynamically shifting industry backgrounds where they operate, aiming to focus on real-world use cases rather than just high-level technology concepts. I took the chance to review the selection with their chief futurist, Mike Bechtel, in order to gain some insights into why the consulting giant believes they will be so influential, and how we are likely to see them impacting our lives as we move into 2023 and beyond. Predicting the impact that the much-talked-about metaverse will have on our lives, Deloitte's report focuses on the concept of "Immersive internet for the enterprise." The true value of the metaverse, it is suggested, will be the new business models that it makes possible.

Artificial Intelligence (AI) is a trending topic for many industries now. A variety of organizations currently employ AI mechanisms to support their operational functions. Automated tasks, natural language processing, deep learning, and problem-solving; such AI characteristics have made business tasks much easier. The factor of security in AI is largely overlooked, and with the increasing number of cyber threats and attacks, AI security serves as a crucial element that should be paid attention to. Distinct capabilities of AI, for instance, deep learning and unsupervised learning, serve huge benefits for cybersecurity since it holds the ability to analyze and mitigate large sets of potentially malicious data without any human interaction, while providing recommendations for future threats.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.

My name is Sebastian, and I am a machine learning and AI researcher with a strong passion for education. As Lead AI Educator at Grid.ai, I am excited about making AI & deep learning more accessible and teaching people how to utilize AI & deep learning at scale. I am also an Assistant Professor of Statistics at the University of Wisconsin-Madison and author of the bestselling book Python Machine Learning.

As I prepare to embark on a new chapter in my career, pivoting to a venture investor role, I have spent some time reflecting on the evolution of technology, and what it means for our present and future worlds. Here are some of my thoughts. The Information Age is upon us in full force. Not a day goes by without AI being in the news. Or… you get the picture.

BERLIN (Reuters) - IBM is rolling out innovations in artificial intelligence, hybrid cloud operations and quantum computing as the company that created the personal computer follows through on a roadmap it set out a year ago. The U.S. company made the announcements to coincide with its annual Think Conference on Tuesday as it builds momentum following its $34 billion takeover of open-source software company Red Hat two years ago. IBM, which last month reported its strongest quarterly sales growth in two years, has been restructuring since Arvind Krishna became chief executive a year ago to focus on cloud computing and AI. Last October, IBM announced its legacy IT infrastructure business would shift into a separate firm. "This year, we are going to talk about progress - and we have made a lot of progress," President Jim Whitehurst told reporters ahead of its Think Conference.

As in the first edition, the main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic.

As the US launches a cyberattack against Iranian weapons systems and escalates their infiltration of the Russian power grid in the same month, it's clear a new chapter of warfare is well and truly underway. Fueled by the same complex mix of diplomatic breakdowns, economic sanctions and historical grievances as regular conflicts, cyberwarfare is the new threat facing developing nations. The crisis faced by every technologically advanced state is highlighted in the World Economic Forum's Global Risks Report 2019 which ranked cyberattacks as the 5th global risk of our time. The US is certainly not alone in developing a cyberwarfare arsenal, as preemptive strikes, espionage and counter-attacks all require nations to develop cybersecurity defenses and demonstrate their clout. Here, we know exactly what the digital battleground looks like, and the attempts nations can take to develop defenses against the latest cyberwarfare threats.