We focus on the scenario in which an agent can exploit his information advantage to manipulate the outcome of an election. In particular, we study district-based elections with two candidates, in which the winner of the election is the candidate that wins in the majority of the districts. District-based elections are adopted worldwide (e.g., UK and USA) and are a natural extension of widely studied voting mechanisms (e.g., k-voting and plurality voting). We resort to the Bayesian persuasion framework, where the manipulator (sender) strategically discloses information to the voters (receivers) that update their beliefs rationally. We study both private signaling, in which the sender can use a private communication channel per receiver, and public signaling, in which the sender can use a single communication channel for all the receivers. Furthermore, for the first time, we introduce semi-public signaling in which the sender can use a single communication channel per district. We show that there is a sharp distinction between private and (semi-)public signaling. In particular, optimal private signaling schemes can provide an arbitrarily better probability of victory than (semi-)public ones and can be computed efficiently, while optimal (semi-)public signaling schemes cannot be approximated to within any factor in polynomial time unless P=NP. However, we show that reasonable relaxations allow the design of multi-criteria PTASs for optimal (semi-)public signaling schemes. In doing so, we introduce a novel property, namely comparative stability, and we design a bi-criteria PTAS for public signaling in general Bayesian persuasion problems beyond elections when the sender's utility function is state-dependent.

Existing approaches to few-shot learning deal with tasks that have persistent, rigid notions of classes. Typically, the learner observes data only from a fixed number of classes at training time and is asked to generalize to a new set of classes at test time. Two examples from the same class would always be assigned the same labels in any episode. In this work, we consider a realistic setting where the similarities between examples can change from episode to episode depending on the task context, which is not given to the learner. We define new benchmark datasets for this flexible few-shot scenario, where the tasks are based on images of faces (Celeb-A), shoes (Zappos50K), and general objects (ImageNet-with-Attributes). While classification baselines and episodic approaches learn representations that work well for standard few-shot learning, they suffer in our flexible tasks as novel similarity definitions arise during testing. We propose to build upon recent contrastive unsupervised learning techniques and use a combination of instance and class invariance learning, aiming to obtain general and flexible features. We find that our approach performs strongly on our new flexible few-shot learning benchmarks, demonstrating that unsupervised learning obtains more generalizable representations.

If we look back on the past five years, we would find many breath-taking tech advancements. Smart cities, micro-drones, Internet of Things, connected logistics, artificial intelligence, etc. have put us on a platform where pride comes naturally. We can talk about the coronavirus pandemic and lockdowns all we want. However, we shouldn't forget one thing. Technology has empowered us with numerous advantages to fight this crisis.

The world of food production has been forever changed by genetic modification, and artificial intelligence has played a big role. Join us on December 9 as we host a panel discussion to talk about the promise the genetic modification brings as well as the issues surrounding it such as EU laws. The digital event is free to both members as well as prospective members. This project is funded by Akademiska Fo reningen (https://www.af.lu.se/).

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. U.S. Army weapons developers, Pentagon leaders and industry armored vehicle builders are all experiencing tremendous enthusiasm over progress with a new light tank, called the Mobile Protected Firepower (MPF), as well as its emerging fleet of Next-Generation Combat Vehicles (NGCV). These programs have many new features, including AI-enabled sensors and an ability to operate multiple air and ground drones with manned-unmanned teaming. More importantly, these vehicles will have new levels of survivability while also being a lighter-weight, faster, more expeditionary and deployable fleet of armored vehicles.

I frequently emphasize the importance of data in the U.S. Food and Drug Administration's work as a science-based regulatory agency, and the need to "unleash the power of data" through sophisticated mechanisms for collection, review and analysis so that it may become preventive, action-oriented information. As one example of this commitment, I would like to tell you about cross-cutting work the agency is undertaking to leverage our use of artificial intelligence (AI) as part of the FDA's New Era of Smarter Food Safety initiative. This work promises to equip the FDA with important new ways to apply available data sources to strengthen our public health mission. The ultimate goal is to see if AI can improve our ability to quickly and efficiently identify products that may pose a threat to public health. One area in which the FDA is assessing the use of AI is in the screening of imported foods.

Europa Technologies has enhanced the address search capabilities of its viaEuropa API with artificial intelligence (AI) based strategies. The use of AI methods improves search and geocoding accuracy, especially for incomplete or poor-quality addresses. The viaEuropa API provides premise level address search using several data products including OS AddressBase Core/Plus/Premium (optionally including AddressBase Islands Plus/Premium), OSNI Pointer, Royal Mail PAF and AddressHub – a new enhanced PAF product from Europa Technologies. It delivers high quality, fully maintained, digital maps and location data directly to web applications, desktop GIS and mobile apps. With a range of customers including commercial and public sector organisations, the viaEuropa service is under a programme of continuous improvement. The use of AI in address search is a powerful example of the company's nimble and innovative approach.

As the world anticipates a new US Congress and a new administration, we need a strategy to reimagine and rebuild communities, industries, companies, and nations. As we battle cascading disruptions from a global pandemic, economic strain, climate-related crises, and unrest over racial injustice, technology should be part of a solution--but technology alone is not enough. Satya Nadella is the CEO of Microsoft. Marco Iansiti is a professor of business administration at the Harvard Business School and chairman of Keystone.AI. To more evenly spread economic opportunity and resilience, we must democratize "tech intensity," a combination of tech and people skills--including among citizen developers.

Now calculate cosine similarity between each document and each query. For each query sort the cosine similarity scores for all the documents and take top-3 documents having high scores.

While a hot topic of late, it is easy to forget that the concept of artificial intelligence (AI) is not new. Early philosophers and mathematicians theorized that mechanical reasoning could one day be taught to robots, automatons, and smart machines. However, AI advancements slowed over the next few decades due to competing funding priorities, moral/ethical concerns, and the limitations of computing technology and data storage. It was not until the late 1990s/early 2000s that most of these challenges and concerns were alleviated and computer and data technologies advanced, becoming more affordable. Today, significant investment can be seen in health care-related AI with well-known companies like Microsoft, Google, and IBM heavily involved in promoting AI solutions in eye care,and smaller startups even attaining FDA-approval as standalone diagnostic technology.2-6