Regulators in the EU and US have recently drawn attention to the market power and monopolistic behavior of big tech firms. Lawmakers in the EU argue that'traditional businesses are increasingly dependent on a limited number of large online platforms' and that these'gatekeepers' leverage their privileged position to stifle competition and enter new markets at a rapid pace (EPRS 2020). Striking a similar tone, lawmakers in the US claim that these companies have'abused their dominant positions, setting and often dictating prices and rules for commerce, search, advertising, social networking and publishing' (Kang and McCabe 2020). Yet these arguments tend to focus mostly on the conduct and market position of online platforms, while ignoring the underlying technologies by which they operate. But what if techniques like machine learning (ML) are themselves factors in the continuous expansion of already oversized tech giants?

Yet it's possible to nudge people to more willingly pay their taxes on time. The Behavioural Insights Team, also known unofficially as the "Nudge Unit," was founded by the UK government in 2010 to use behavioral science to make public policies and services more effective. One of its more successful experiments is the use of peer pressure to improve tax collection. Ordinarily, HM Revenue and Customs, the department responsible for tax collection, sends a reminder notice to those who haven't paid their taxes on time. Only 33% of those who receive the reminders respond by paying their taxes.

Hundreds of Android apps sent user location data to a data broker that had been banned from the Google Play Store since December 2020. Close to 200 messaging apps, video and file converters, dating sites, and religious and prayer apps downloaded tens of millions of times had X-Mode installed. Despite the ban, only ten per cent of these apps have been removed from Google Play. The tracker caused controversy after Vice's Motherboard reported that the United States military was buying the granular movement data of users of a a Muslim prayer and Quran app that had more than 98 million downloads worldwide. The US military has reportedly used location data to target drone strikes.

The DARPA Subterranean Challenge planned to develop novel approaches to rapidly map, explore and search underground environments in time-sensitive operations critical for the civilian and military domains alike. In the Final Event, DARPA designed an environment involving branches representing all three challenges of the "Tunnel Circuit", the "Urban Circuit" and the "Cave Circuit". Robots had to explore, search for objects ("artifacts") of interest, and report their accurate location within underground tunnels, infrastructure similar to a subway, and natural caves and paths with extremely confined geometries, tough terrain, and severe visual degradation (including dense smoke). Team CERBERUS deployed a diverse set of robots with the prime systems being four ANYmal C legged systems. In the Prize Round of the Final Event, the team won the competition and scored 23 points by correctly detecting and localizing 23 of 40 of the artifacts DARPA had placed inside the environment.

Computer scientists at DeepMind and the University of Exeter in England teamed up with meteorologists from the Met Office to build an AI model capable of predicting whether it will rain up to 90 minutes beforehand. Traditional forecasting methods rely on solving complex equations that take into account various weather conditions, such as air pressure, moisture, and the temperature of Earth's atmosphere. The trouble is, at least in Blighty, these systems tend to predict what lies in store for us whole days or weeks ahead. Deep-learning models are better suited for making more near-term forecasts – such as within the next couple of hours – according to a paper published by the aforementioned boffins in Nature on Wednesday. There are advantages to using AI algorithms; they don't have to solve thermodynamic equations and are less computationally intensive than other predictive techniques.

NOAA and Saildrone Inc. are piloting five specially designed surface drones in the Atlantic Ocean to gather data around the clock to help understand the physical processes of hurricanes. NOAA and Saildrone Inc. are piloting five specially designed surface drones in the Atlantic Ocean to gather data around the clock to help understand the physical processes of hurricanes. Researchers for the National Oceanic and Atmospheric Administration have dispatched a surface drone inside Hurricane Sam as it barrels toward the Caribbean, giving scientists a new perspective of what it's like inside such a storm. The video and images shared were the first of their kind gathered by an "uncrewed surface vehicle" from inside a major hurricane as it moved across the Atlantic Ocean. The onboard camera shows eerily gray skies and turbulent ocean waters.

Verdict lists the top five terms tweeted on future cities in Q2 2021, based on data from GlobalData's Influencer Platform. The top tweeted terms are the trending industry discussions happening on Twitter by key individuals (influencers) as tracked by the platform. The importance of analytics and visualisations for city governments, how smart cities can unlock the full potential of IoT, and the applications of IoT in smart cities and smart buildings were some of the trending discussions in Q2. Kirk Borne, data scientist at DataPrime, an artificial intelligence (AI)-based solutions provider, shared an article on the importance of analytics and visualisation for city governments. Government policymakers are required to collect and store data to ensure data privacy across organisations and to enable the provision of services that boost the economy.

What a ride it has been in the Transportation and Logistics (T&L)sector regarding the B2C eCommerce growth boom world-wide, much of this driven by the global retail sales growth during COVID-19. This accelerated growth and now with global trade rapidly rebounding, the timing is right for the transportation and logistics industry to advance smarter digital transformations. According to McKinsey, this industry must be completely digital to secure its future – but what will it take? The future although seems rosy, is complex and challenging due to rapid industry consolidations, new technology acceleration, ever constant regulatory changes such as GDBR, and of course, Brexit impacting European markets. The World Trade Organization (WTO) has been most vocal reinforcing the importance of the T&L Industry to take heed on the importance of customer experiences – how courier drivers ship, route and deliver parcels and products with agile speed has become the new normal. Service speed from Amazon has shifted customer expectations on timeliness on B2B to be as resilient as their B2C personal experiences demanding instant quotations, real time tracking on orders, and personalize messaging on express services.

We use a dataset of U.S. first names with labels based on predominant gender and racial group to examine the effect of training corpus frequency on tokenization, contextualization, similarity to initial representation, and bias in BERT, GPT-2, T5, and XLNet. We show that predominantly female and non-white names are less frequent in the training corpora of these four language models. We find that infrequent names are more self-similar across contexts, with Spearman's r between frequency and self-similarity as low as -.763. Infrequent names are also less similar to initial representation, with Spearman's r between frequency and linear centered kernel alignment (CKA) similarity to initial representation as high as .702. Moreover, we find Spearman's r between racial bias and name frequency in BERT of .492, indicating that lower-frequency minority group names are more associated with unpleasantness. Representations of infrequent names undergo more processing, but are more self-similar, indicating that models rely on less context-informed representations of uncommon and minority names which are overfit to a lower number of observed contexts.

Afghanistan War veteran Rep. Mike Waltz, R-Fla., and Rep. Michael McCaul, R-Texas, weigh the consequences of Biden's overseas withdrawal. A senior al Qaeda leader has been killed in a drone strike in Syria, U.S. defense officials confirmed to Fox News Thursday. Salim Abu-Ahmad was killed in a U.S. airstrike near Idlib, Syria on Sept. 20. He was responsible for planning, funding, and approving trans-regional al Qaeda attacks. A U.S. Air Force MQ-1B Predator unmanned aerial vehicle (UAV), carrying a Hellfire missile flies over an air base after flying a mission in the Persian Gulf region.