KisanHub, a Cambridge-founded startup applying AI to agriculture, has raised £1.12 million to accelerate its growth in the UK and Europe. The round was led by Low Carbon Innovation Fund 2 (LCIF2) with backing from the Future Fund. Existing investors IQ Capital, Notion Capital and Sistema VC also joined. The'seed to sale' connectivity platform combines crop intelligence with supply chain intelligence, to make sure what farms yield actually makes it to kitchens in good shape. Integrating data from crops, stores, load dispatches, satellites and field sensors, the platform helps growers, field staff, procurement managers and management teams make informed decisions and avoid bottlenecks.

In 1939, shortly before the German invasion of Poland, a British emissary, Lord Lothian, visited the White House with an unusual request. The United Kingdom was unable to protect the world from the Nazis, Lothian told President Franklin Delano Roosevelt. "Anglo-Saxon civilization" would thus need a new guardian. The scepter was falling from British hands, Lothian explained, and the United States must "snatch it up." Though informally made, it was an extraordinary entreaty.

A robotic cargo vessel has passed through the Panama Canal for the first time. The uncrewed ship, an Overlord Unmanned Surface Vessel (USV) of the US Navy, made a 4700 nautical mile (8700 kilometre) journey including passage from the Atlantic to the Pacific almost entirely without human assistance. Pentagon spokesman Josh Frey says the vessel was in autonomous mode for over 97 per cent of the trip's length. A remote crew assisted when needed.

A robotic cargo vessel has passed through the Panama Canal for the first time. The ship, an Overlord uncrewed surface vessel belonging to the US Navy, made a 4700-nautical-mile (8700-kilometre) journey including passage from the Atlantic to the Pacific almost entirely without human assistance. Pentagon spokesperson Josh Frey says the vessel was in autonomous mode for more than 97 per cent of the trip's length. A remote crew assisted when needed. The US Navy has two of the 59-metre Overlord vessels, modified from crewed fast transport ships.

An artificial intelligence technique--machine learning--is helping accelerate the development of highly tunable materials known as metal-organic frameworks (MOFs) that have important applications in chemical separations, adsorption, catalysis, and sensing. Utilizing data about the properties of more than 200 existing MOFs, the machine learning platform was trained to help guide the development of new materials by predicting an often-essential property: water stability. Using guidance from the model, researchers can avoid the time-consuming task of synthesizing and then experimentally testing new candidate MOFs for their aqueous stability. Already, researchers are expanding the model to predict other important MOF properties. Supported by the Office of Science's Basic Energy Sciences program within the U.S. Department of Energy (DOE), the research was reported Nov. 9 in the journal Nature Machine Intelligence. The research was conducted in the Center for Understanding and Control of Acid Gas-Induced Evolution of Materials for Energy (UNCAGE-ME), a DOE Energy Frontier Research Center located at the Georgia Institute of Technology.

What could be one of the most consequential First Amendment cases of the digital age is pending before a court in Illinois and will likely be argued before the end of the year. The case concerns Clearview AI, the technology company that surreptitiously scraped 3 billion images from the internet to feed a facial recognition app it sold to law enforcement agencies. Now confronting multiple lawsuits based on an Illinois privacy law, the company has retained Floyd Abrams, the prominent First Amendment litigator, to argue that its business activities are constitutionally protected. Landing Abrams was a coup for Clearview, but whether anyone else should be celebrating is less clear. A First Amendment that shielded Clearview and other technology companies from reasonable privacy regulation would be bad for privacy, obviously, but it would be bad for free speech, too.

Artificial intelligence is an innovation that is changing all social statuses. It is a wide-ranging tool that empowers individuals to reevaluate how we incorporate data, analyze information, and utilize the subsequent insights to improve decision making. AI is getting into the realms of policymakers, opinion leaders, and interested observers, and exhibits how AI as of now is modifying the world and bringing up significant issues for society, the economy, and governance. Artificial intelligence algorithms are intended to make decisions, frequently utilizing real-time information. They are different from passive machines that are competent just for mechanical or predetermined reactions.

Estimation models from connected vehicles often assume low level parameters such as arrival rates and market penetration rates as known or estimate them in real-time. At low market penetration rates, such parameter estimators produce large errors making estimated queue lengths inefficient for control or operations applications. In order to improve accuracy of low level parameter estimations, this study investigates the impact of connected vehicles information filtering on queue length estimation models. Filters are used as multilevel real-time estimators. Accuracy is tested against known arrival rate and market penetration rate scenarios using microsimulations. To understand the effectiveness for short-term or for dynamic processes, arrival rates, and market penetration rates are changed every 15 minutes. The results show that with Kalman and Particle filters, parameter estimators are able to find the true values within 15 minutes and meet and surpass the accuracy of known parameter scenarios especially for low market penetration rates. In addition, using last known estimated queue lengths when no connected vehicle is present performs better than inputting average estimated values. Moreover, the study shows that both filtering algorithms are suitable for real-time applications that require less than 0.1 second computational time.

This study presents a methodology to quantify vulnerability of cyber attacks and their impacts based on probabilistic graphical models for intelligent transportation systems under connected and autonomous vehicles framework. Cyber attack vulnerabilities from various types and their impacts are calculated for intelligent signals and cooperative adaptive cruise control (CACC) applications based on the selected performance measures. Numerical examples are given that show impact of vulnerabilities in terms of average intersection queue lengths, number of stops, average speed, and delays. At a signalized network with and without redundant systems, vulnerability can increase average queues and delays by $3\%$ and $15\%$ and $4\%$ and $17\%$, respectively. For CACC application, impact levels reach to $50\%$ delay difference on average when low amount of speed information is perturbed. When significantly different speed characteristics are inserted by an attacker, delay difference increases beyond $100\%$ of normal traffic conditions.

In the current industrial practices, the exponential growth in terms of availability and affordability of sensors, data acquisition systems, and computer networks forces factories to move toward implementing high integrating Cyber-Physical Systems (CPS) with production, logistics, and services. This transforms today's factories into Industry 4.0 factories with significant economic potential. Industry 4.0, also known as the fourth Industrial Revolution, levers on the integration of cyber technologies, the Internet of Things, and Services. This paper proposes an Augmented Reality (AR)-based system that creates a Cognition Level that integrates existent Manufacturing Execution Systems (MES) to CPS. The idea is to highlight the opportunities offered by AR technologies to CPS by describing an application scenario. The system, analyzed in a real factory, shows its capacity to integrate physical and digital worlds strongly. Furthermore, the conducted survey (based on the Situation Awareness Global Assessment Technique method) reveals significant advantages in terms of production monitoring, progress, and workers' Situation Awareness in general.