India is building a database for companies to train AI models: Rajeev Chandrasekhar (Mint)

Mint: India is building a database for companies to train AI models: Rajeev Chandrasekhar. “India is building a large database of anonymized non-personal data for Indian companies and startups that are using artificial intelligence (AI), said Rajeev Chandrasekhar, minister of state (MoS) for Electronics and Information Technology, at the Global Fintech Fest (GFF), an industry event, held in Mumbai on Wednesday.”

Siberian Federal University: Russian Scientists Have Taught a neural network to read handwritten Letters of the Russian Alphabet

Siberian Federal University: Russian Scientists Have Taught a neural network to read handwritten Letters of the Russian Alphabet . “SibFU scientists have developed a new convolutional neural network (CNN) capable of recognizing images of handwritten letters with high accuracy. The resulting algorithm transforms the image and recognizes the letter encrypted in it. According to the scientists, the algorithm’s accuracy is 99 %.”

Scientific American: Artificial General Intelligence Is Not as Imminent as You Might Think

Scientific American: Artificial General Intelligence Is Not as Imminent as You Might Think. “Machines may someday be as smart as people, and perhaps even smarter, but the game is far from over. There is still an immense amount of work to be done in making machines that truly can comprehend and reason about the world around them. What we really need right now is less posturing and more basic research.”

Tech Xplore: A new model to automatically detect and filter spam emails

Tech Xplore: A new model to automatically detect and filter spam emails. “Over the past few years, computer scientists have developed increasingly advanced computational models to automatically detect spam emails. To perform well, however, most of these models need to be trained on large email datasets, which were manually labeled by humans. Researchers at Sinhgad Institute of Technology Lonavala in India have recently created a new technique for the automatic detection of spam emails.”

Nature: Restoring and attributing ancient texts using deep neural networks

Nature: Restoring and attributing ancient texts using deep neural networks. “Ancient history relies on disciplines such as epigraphy—the study of inscribed texts known as inscriptions—for evidence of the thought, language, society and history of past civilizations1. However, over the centuries, many inscriptions have been damaged to the point of illegibility, transported far from their original location and their date of writing is steeped in uncertainty. Here we present Ithaca, a deep neural network for the textual restoration, geographical attribution and chronological attribution of ancient Greek inscriptions.”

The Register: Techniques to fool AI with hidden triggers are outpacing defenses – study

The Register: Techniques to fool AI with hidden triggers are outpacing defenses – study. “The increasingly wide use of deep neural networks (DNNs) for such computer vision tasks as facial recognition, medical imaging, object detection, and autonomous driving is going to, if not already, catch the attention of cybercriminals. DNNs have become foundational to deep learning and to the larger field of artificial intelligence (AI). They’re a multi-layered class of machine learning algorithms that essentially try to mimic how a human brain works and are becoming more popular in developing modern applications.”

Analytics India: Google AI researchers present a new method to train models, ‘DeepCTRL’

Analytics India: Google AI researchers present a new method to train models, ‘DeepCTRL’. “Google Cloud AI researchers have offered a unique deep learning training approach that incorporates rules so that the strength of the rules may be controlled at inference. DeepCTRL (Deep Neural Networks with Controllable Rule Representations) combines a rule encoder and a rule-based objective into the model, allowing for a shared representation for decision-making. Data type and model architecture are unimportant to DeepCTRL.”

Rock Paper Shotgun: Semantle is hard mode Wordle, powered by a Google neural network

Rock Paper Shotgun: Semantle is hard mode Wordle, powered by a Google neural network. “In many ways, Semantle is hard mode Wordle. Gone is the simplified dictionary and five-letter limit, meaning words can be any type and length, and gone is any indication of correctly guessed letters or positions. Instead, you’ve got two new helpers: the ability to make infinite guesses, and a neural network able to learn word associations telling you how close, conceptually, you are to the correct answer. I’ve yet to find the solution in fewer than 50 guesses.”

TU Wien: Studying the Big Bang with Artificial Intelligence

TU Wien: Studying the Big Bang with Artificial Intelligence. “It could hardly be more complicated: tiny particles whir around wildly with extremely high energy, countless interactions occur in the tangled mess of quantum particles, and this results in a state of matter known as ‘quark-gluon plasma’. Immediately after the Big Bang, the entire universe was in this state; today it is produced by high-energy atomic nucleus collisions, for example at CERN. Such processes can only be studied using high-performance computers and highly complex computer simulations whose results are difficult to evaluate. Therefore, using artificial intelligence or machine learning for this purpose seems like an obvious idea. Ordinary machine-learning algorithms, however, are not suitable for this task. The mathematical properties of particle physics require a very special structure of neural networks. At TU Wien (Vienna), it has now been shown how neural networks can be successfully used for these challenging tasks […]

British Library Digital Scholarship Blog: Intro to AI for GLAM

British Library Digital Scholarship Blog: Intro to AI for GLAM. “Earlier this year Daniel van Strien and I teamed up with colleagues Mike Trizna from the Smithsonian and Mark Bell at the National Archives, UK in a Carpentries Lesson Development Study Group with an eye to developing an Introduction to AI for GLAM (Galleries, Libraries, Archives and Museums) lesson for eventual inclusion in Library Carpentry…. The result is the framework and foundations for what we hope will be a useful, ever evolving and continuously collaboratively written workshop that can provide a gentle and practical introduction for GLAM to the world of machine learning and its implications for the sector.”

The Next Web: Research indicates the whole universe could be a giant neural network

The Next Web: Research indicates the whole universe could be a giant neural network. “Vitaly Vanchurin, a professor of physics at the University of Minnesota Duluth, published an incredible paper last August entitled ‘The World as a Neural Network’ on the arXiv pre-print server. It managed to slide past our notice until today when Futurism’s Victor Tangermann published an interview with Vanchurin discussing the paper.”

Why we need a new agency to regulate advanced artificial intelligence: Lessons on AI control from the Facebook Files (Brookings Institution)

Brookings Institution: Why we need a new agency to regulate advanced artificial intelligence: Lessons on AI control from the Facebook Files. “In this article, I lay out what we can learn about the AI Control Problem using the lessons learned from the Facebook Files. I observe that the challenges we are facing can be distinguished into two categories: the technical problem of direct control of AI, i.e. of ensuring that an advanced AI system does what the company operating it wants it to do, and the governance problem of social control of AI, i.e. of ensuring that the objectives that companies program into advanced AI systems are consistent with society’s objectives.”