Welcome to the fourth edition of the AI Index Report. This year we significantly expanded the amount of data available in the report, worked with a broader set of external organizations to calibrate our data, and deepened our connections with the Stanford Institute for Human-Centered Artificial Intelligence (HAI). The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Its mission is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, executives, journalists, and the general public to develop intuitions about the complex field of AI. The report aims to be the most credible and authoritative source for data and insights about AI in the world.

Harm wrought by AI tends to fall most heavily on marginalized communities. In the United States, algorithmic harm may lead to the false arrest of Black men, disproportionately reject female job candidates, or target people who identify as queer. In India, those impacts can further impact marginalized populations like Muslim minority groups or people oppressed by the caste system. And algorithmic fairness frameworks developed in the West may not transfer directly to people in India or other countries in the Global South, where algorithmic fairness requires understanding of local social structures and power dynamics and a legacy of colonialism. That's the argument behind "De-centering Algorithmic Power: Towards Algorithmic Fairness in India," a paper accepted for publication at the Fairness, Accountability, and Transparency (FAccT) conference, which begins this week. Other works that seek to move beyond a Western-centric focus include Shinto or Buddhism-based frameworks for AI design and an approach to AI governance based on the African philosophy of Ubuntu.

Farmers Edge Inc, an AI startup to help growers increase crop yields, plans to go public on Canada's largest Toronto Stock Exchange under the ticker symbol "FDGE". The company seeks to raise CAD 100 million (approximately USD 79 million). Founded in 2005, Farmers Edge uses AI technology to collect and analyze local weather, soil moisture and satellite data to help farmers improve crop efficiency and yield. Besides the Canadian Prairie, the company currently hosts offices in the United States, Australia, Russia, Brazil and Ukraine. As of the end of 2020, more than 3,000 growers have used the Farmers Edge products, covering more than 23 million acres of land in six countries.

The information presented in Lega-Tech Artificial Intelligence Market Report 2021 includes qualitative and quantitative insights. Under the qualitative analysis part, manufacturing base, raw materials data, Lega-Tech Artificial Intelligence status, trends, SWOT analysis, PESTEL Analysis, distribution channels, driving factors, and a competitive structure is presented. Under the qualitative analysis part, market value/volume, production analysis, consumption data, import-export data, or each region and country are explained. Also, industry size by Lega-Tech Artificial Intelligence type, application, demand and supply scenario, and economic status are explained. Also, comprehensive information on the latest product development, growth opportunities, industry strategies, cost structures, and recent policies are enlightened in the Lega-Tech Artificial Intelligence report.

What are the opportunities and threats faced by the vendors in the international market?

Machine learning key to discovery of over 1200 gravitational lenses. Data from the DESI (Dark Energy Spectroscopic Instrument) Legacy Imaging Surveys have revealed over 1200 new gravitational lenses, approximately doubling the number of known lenses. Discovered using machine learning trained on rea

Artificial Intelligence researchers at Open AI, a startup founded by Elon Musk, have discovered neurons within an AI system that have only previously been seen in the human brains. According to a blog post, researchers uncovered what is referred to by neuroscientists as a'multimodal neuron', within the murky inner workings of one of its most advanced neural networks. The researchers said that the discovery was made using a general-purpose vision called CLIP, which trains itself on complex datasets to recognise objects and people within abstracts, such as cartoons or statues. We've found that our latest vision model, CLIP, contains neurons that connect images, drawings and text about related concepts. The company said that they have discovered neurons in CLIP that respond to the same concept whether presented literally, symbolically, or conceptually.

We introduce the task of changing the narrative point of view, where characters are assigned a narrative perspective that is different from the one originally used by the writer. The resulting shift in the narrative point of view alters the reading experience and can be used as a tool in fiction writing or to generate types of text ranging from educational to self-help and self-diagnosis. We introduce a benchmark dataset containing a wide range of types of narratives annotated with changes in point of view from deictic (first or second person) to anaphoric (third person) and describe a pipeline for processing raw text that relies on a neural architecture for mention selection. Evaluations on the new benchmark dataset show that the proposed architecture substantially outperforms the baselines by generating mentions that are less ambiguous and more natural.

Olist is the largest eCommerce website in Brazil. It connects small retailers from all over the country to sell directly to customers. The business has generously shared a large dataset containing 110k orders on its site from 2016 to 2018. The SQL-style relational database includes customers and their orders in the site, which contains around 100k unique orders and 73 categories. It also includes item prices, timestamps, reviews, and gelocation associated with the order.

When you download a dating app, fill out a profile with some of your most private information, and select "allow app to access location" to locate nearby potential love interests, you may feel a little exposed, but you proceed anyway, in order to find those dates. But there is reason to believe that by using these sites, you may be unknowingly submitting to government tracking--and we can't know for sure because of all of the secrecy involved with deals that data brokers make with government agencies. It's yet another demonstration of the need to bring transparency to the data-collection industry. Dating apps ask users for a variety of highly personal information and retain it indefinitely, potentially forever. This can include photos and videos, text conversations with other users, and information on gender, sexual orientation, political affiliation, religion, desire to have children, location, HIV status, and beyond.