Tinder, the most popular dating app in the world, has banned teens under the age of 18 but it's not stopping them from signing up. A jilted Australian doctor pleaded guilty Monday to sending 9,000 abusive and threatening messages to her former Tinder date, according to a new report. Radiologist Denise Jane Lee, 40, of Sydney, copped to four of 10 charges against her ahead of a scheduled five-day hearing in the Downing Centre Local Court, the Australian Associated Press reported. Lee, who was arrested in February 2017, copped to three counts of using a carriage service to harass, menace or offend and one count of intimidation, according to the report. Six additional charges were withdrawn.

PyData is dedicated to providing a harassment-free conference experience for everyone, regardless of gender, sexual orientation, gender identity and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of conference participants in any form. All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate for any conference venue, including talks. Do not insult or put down other attendees.

Accounting and corporate finance are notoriously document-intensive. From invoices to expense receipts, employee signatures and purchase orders, documents in print or electronic form are a mainstay of finance life. However, document-centric systems and processes are tedious, time-consuming and error-prone. AI-based systems aim to address these needs by applying natural language processing, content summarization, computer vision and other technologies that allow companies to automatically process a range of documents. The market is already starting to see many vendors offering products with machine learning that can handle inbound invoices, process purchase orders, handle expense reports and reimbursements, and route everything to the correct departments, saving organizations both time and money.

With the power to transform the business of government, artificial intelligence offers agencies unprecedented opportunities to discover deeper insights and identify correlations critical to mission success faster than ever. However, faced with legacy infrastructure, an evolving workforce, and limited budgets, how can government actually harness this new wave of technology? During this digital viewcast, hear from government practitioners and industry experts about the practical path to implementing artificial intelligence for agencies of all sizes.

Autonomous Vehicles (AVs) are increasingly embraced around the world to advance smart mobility and more broadly, smart, and sustainable cities. Algorithms form the basis of decision-making in AVs, allowing them to perform driving tasks autonomously, efficiently, and more safely than human drivers and offering various economic, social, and environmental benefits. However, algorithmic decision-making in AVs can also introduce new issues that create new safety risks and perpetuate discrimination. We identify bias, ethics, and perverse incentives as key ethical issues in the AV algorithms' decision-making that can create new safety risks and discriminatory outcomes. Technical issues in the AVs' perception, decision-making and control algorithms, limitations of existing AV testing and verification methods, and cybersecurity vulnerabilities can also undermine the performance of the AV system. This article investigates the ethical and technical concerns surrounding algorithmic decision-making in AVs by exploring how driving decisions can perpetuate discrimination and create new safety risks for the public. We discuss steps taken to address these issues, highlight the existing research gaps and the need to mitigate these issues through the design of AV's algorithms and of policies and regulations to fully realise AVs' benefits for smart and sustainable cities.

Editor's note: This is a guest post written by S. Somasegar, managing director at Madrona Venture Group; and Daniel Li, principal at Madrona Venture Group. Artificial intelligence is a broad and overused term. Any startup raising money today needs to have a data and machine learning story, and every enterprise is trying to understand how they can unlock the value of their customer and transaction data with AI. We strongly believe that every application that is being built today is an intelligent application. Applications which don't use data to build continuous learning systems that provide better value with more data are going to become obsolete in the market as we move forward.

The field of AI is rapidly advancing, and pretty soon, we will get to the point where we no longer even have to search for something to find it. We will simply be able to point our smartphone cameras at it, and the AI algorithms will take care of the rest. Even though a lot of companies have been at the forefront of adopting this technology into their service offering, for the most part, it is still being used to extract information from a given image. In order to train the AI algorithms to identify objects or people in an image, researchers input lots of annotated data into the system so it can learn to recognize whatever is needed. The image data can be virtually in any form, such as video, views from many cameras, multi-dimensional data, and many other types.

Luminance, which provides Artificial Intelligence software for law firms and in-house teams, is gunning for the Disruptive Technology accolade in the 30th Anniversary Business Weekly Awards. Based at the Maurice Wilkes Building at St John's Innovation Park, Luminance prides itself as being the only platform to bring true artificial intelligence to the legal profession. Its submission says: "By deploying a unique blend of supervised and unsupervised machine learning, the core technology'LITE' is able to read and understand language in a way that is similar to the human brain and then learns from lawyers' interactions with documents as they conduct their review. "Luminance has enhanced the lives of lawyers in 165 countries globally, including 17 of'The Global Top 100', such as Holland & Knight, Slaughter and May and Bird & Bird, as well as each of the Big Four accounting firms." The company's pattern-recognition technology reads, understands and learns from the interaction between lawyers and documents, pinpointing warning signs that would be missed during a manual review.

The Machinery Directive is the core piece of EU legislation for the mechanical engineering industry: it promotes the free movement of machinery within the Internal Market, while setting out the'Essential Health and Safety Requirements' to be observed when placing a machine on the market for the first time. The mechanical engineering companies Orgalim represents really value this Directive: in addition to ensuring a high level of safety for employees and end users, it has provided a stable legal environment for businesses since it came into force over a decade ago. Particularly for small and medium sized enterprises (SMEs), this stability is invaluable. In the last year or two, however, the European Commission has been exploring the possibility of reviewing the Directive – prompted primarily by new developments in technologies like artificial intelligence (AI). AI has climbed up the political agenda in recent years, reflecting public concerns that this technology is somehow different; that, in the most dramatic scenarios, systems deploying AI could start to act autonomously and provoke new, unmanageable dangers.

There is wide speculation among readers about just how serious Yarvin is, including from his most prominent reader. "Vast structures of historical irony shape his writings, at times even engulfing them," says Nick Land. "Vast structures of historical irony" is a rather generous description of what's known on the internet as "shitposting." Know Your Meme defines the term as "a range of user misbehaviors and rhetoric on forums and message boards that are intended to derail a conversation."