MILAN/LONDON Feb 3 (Reuters) - Italy's Data Protection Agency said on Friday it was prohibiting artificial intelligence (AI) chatbot company Replika from using the personal data of Italian users, citing risks to minors and emotionally fragile people. Replika, a San Francisco startup launched in 2017, offers users customized avatars that talk and listen to them. It has led the way among English speakers, and is free to use, though it brings in around $2 million in monthly revenue from selling bonus features such as voice chats. The'virtual friend' is marketed as being able to improve the emotional well-being of the user. But the Italian watchdog said that by intervening in the user's mood, it "may increase the risks for individuals still in a developmental stage or in a state of emotional fragility".

Enveil, the pioneering Privacy Enhancing Technology company protecting Data in Use, announced that it has closed $25 million in Series B funding. The oversubscribed round was led by USAA with contributions from existing investors which include Mastercard, Capital One Ventures, C5 Capital, DataTribe, In-Q-Tel, Cyber Mentor Fund, Bloomberg Beta, GC&H, and 1843 Capital. Building on an over 300% increase in revenue achieved since closing its Series A funding, Enveil will leverage the capital to expand sales, product development, and marketing activity to capitalize on the accelerating market need to span global data silos and enable secure and private data usage, sharing, collaboration, and monetization. This brings the total amount raised by the category-defining startup to more than $40 million since its formation in 2016. "Modern digital business requires crossing global data silos and the current barriers of trust are leaving massive unrealized data value" Digital transformation, the rise of the digital economy, and the broad recognition of data as an asset have transformed global data usage requirements.

Computer vision is an interdisciplinary field that deals with how computers can be made for gaining high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do. Country: China Funding: $1.6B SenseTime develops face recognition technology that can be applied to payment and picture analysis, which could be used, for instance, on bank card verification and security systems. Country: China Funding: $607M Megvii develops Face Cognitive Services - a platform offering computer vision technologies that enable your applications to read and understand the world better. Face allows you to easily add leading, deep learning-based image analysis recognition technologies into your applications, with simple and powerful APIs and SDKs.

The 100 startups on our list have raised $11.7B in aggregate funding across 367 deals. Today, CB Insights unveiled the second annual AI 100 -- a list of 100 of the most promising private companies applying artificial intelligence algorithms across 25 industries, from healthcare to cybersecurity -- at the A-Ha! conference in San Francisco. The companies were selected from a pool of 2,000 startups based on several criteria, including investor profile, tech innovation, team strength, patent activity, mosaic score, funding history, valuation, and business model. The market map below categorizes the AI 100 companies based on their industry focus. Please click on the image to enlarge.

The 100 startups on our list have raised $11.7B in aggregate funding across 367 deals. Today, CB Insights unveiled the second annual AI 100 -- a list of 100 of the most promising private companies applying artificial intelligence algorithms across 25 industries, from healthcare to cybersecurity -- at the A-Ha! conference in San Francisco. The companies were selected from a pool of 2,000 startups based on several criteria, including investor profile, tech innovation, team strength, patent activity, mosaic score, funding history, valuation, and business model. The market map below categorizes the AI 100 companies based on their industry focus. Please click on the image to enlarge.

Via G. Galilei 5, 21027 Ispra (VA), Italy The period since the last conference in this series has been characterized by the explosive expansion of AI out of the confines of institutions of basic research like university departments into the worlds of industry, business, and government (a development I had long expected). But it seems to me that there are plenty-perhaps an overabundance-of other occasions, other conferences, other workshops, and the like, at which the applications of AI would appropriately be considered. In fact, it is ironic-though perhaps it may be understandable-that precisely now, when the outside world has discovered and started showing its appreciation of AI and its potential, there is a widespread malaise among research workers in the field about the health of their subject. This malaise has to do not only with logistic issues such as the drain of very good people from research into applications, or some of the gross inadequacies of structural and funding support by governments. It has to do also with the very heart and methodology of the subject.

The Voice of the Turtle: Whatever Happened to AI? On March 27, 2006, I gave a lighthearted and occasionally bittersweet presentation on "Whatever Happened to AI?" at the Stanford Spring Symposium presentation--to a lively audience of active AI researchers and formerly active ones (whose current inaction could be variously ascribed to their having aged, reformed, given up, redefined the problem, and so on). This article is a brief chronicling of that talk, and I entreat the reader to take it in that spirit: a textual snapshot of a discussion with friends and colleagues, rather than a scholarly article. I begin by whining about the Turing test, but only for a thankfully brief bit, and then get down to my top-10 list of factors that have retarded progress in our field, that have delayed the emergence of a true strong AI. When Marvin Minsky advised Arthur C. Clarke and Stanley Kubrick, 40 years ago, it seemed that achieving a full HALlike AI by 2001 was every bit as likely as, well, ...

The 1993-95 period presented various "identity challenges" to the field of AI and to AAAI as a leading scientific society for the field. The euphoric days of the mid-1980s AI boom were over, various expectations of those times had not been met, and there was continuing concern about an AI "winter." The major challenge of these years was to chart a path for AI, designed and endorsed by the broadest spectrum of AI researchers, that built on past progress, explained AI's capacity for addressing fundamentally important intellectual problems and realistically predicted its potential to contribute to technological challenges of the coming decade. This reflection piece considers these challenges and the ways in which AAAI helped the field to move forward. Adolescence, the twenties, and the forties each bring particular "developmental" challenges to people, and, though surely coincidentally, elements of those life stages seem also to characterize the period of my presidency.

Although AI and HCI explore computing and intelligent behavior and the fields have seen some crossover, until recently there was not very much. This article outlines a history of the fields that identifies some of the forces that kept the fields at arm's length. AI was generally marked by a very ambitious, long-term vision requiring expensive systems, although the term was rarely envisioned as being as long as it proved to be, whereas HCI focused more on innovation and improvement of widely used hardware within a short time scale. These differences led to different priorities, methods, and assessment approaches. A consequence was competition for resources, with HCI flourishing in AI winters and moving more slowly when AI was in favor.

Sensor abuse is a serious and debilitating condition. However, one must remember that it is a disease, not a crime. As such, it can be treated. This article presents a case study in sensor abuse. This particular subject was lucky enough to pull himself out of his pitiful condition, but others are not so lucky.