Lithuania's Foreign Minister, Gabrielius Landsbergis, talked with Fox News Digital about Russia, China and the'global rules-based order' on the 20th anniversary of his country joining NATO. Lithuania commemorated its entry into NATO this last week and its long-standing partnership with the U.S. as leaders look ahead to the increasingly complex security landscape developing around the world. President George W. Bush visited the Lithuanian capital of Vilnius 20 years ago to welcome the country into the still-growing NATO alliance, applauding the character of member states to "stand in the face of evil, to have the courage to always face danger." "President [George W.] Bush made the most famous speech any American has ever made in Lithuania exactly 20 years ago," Lithuanian Foreign Minister Gabrielius Landsbergis told Fox News Digital in an exclusive interview. "That was even before we were a member of NATO, and it was probably the most important security guarantee that we got before Article Five started covering us with its umbrella."

AI is approaching the next level of maturity, coming out of the hype cycle, says Gartner. Its adoption is expanding across industries beyond automation to building new-generation intelligent products and services for business growth. However, half of them acknowledge that they don't have skilled talent to make the most of AI advances. This is where experienced AI consulting firms come in to help. The market of AI consulting is vast, ranging from tech giants like IBM and Accenture to Big 4 firms and smaller-scale innovators.

The phenomena of the internet is constantly evolving and these developing circumstances need constant monitoring. We are all familiar with the concept of the dark web and the terrifying practices that are conducted through these platforms. Pretty much everything we do on basic internet platforms is visible, traceable, and is being monitored by government officials and other companies. However, the dark web is beyond our reach. The deep web consists of various areas that carry out malicious activities including hacking major organizations, illicit drug trades, terrorist operations, and others.

The European Union (hereinafter "The EU") often leads the way in establishing comprehensive legal frameworks regarding novel issues. As a reminder, it was a pioneer in the area of data protection through its adoption of the EU Data Protection Directive as early as 1995, and more recently through its enactment of the General Data Protection Regulation (GDPR) in 2016, the most severe international law in the field of data protection. Similarly, the EU is currently pushing for the adoption of a detailed regulation for artificial intelligence (hereinafter "AI") systems, the Regulation of the European Parliament and of the Council Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) and Amending Certain Union Legislative Acts (hereinafter "the EU AI Act draft"). First presented in April 2021 by the European Commission, this law is a breakthrough endeavor which will surely have many repercussions, on the EU's level, but also internationally. Currently, in the sector of AI, the EU AI Act is a flagship initiative, which seeks to ensure the safety and trustworthiness of high-risk AI systems developed and used in the EU. It is the first law to solely address AI, and it is expected to become a "GDPR for AI".

The Federal Communications Commission voted 4-0 to ban sales of new telecom and surveillance equipment made by several Chinese companies, arguing that their ownership and practices threaten U.S. national security. The rule change affects 10 companies already subject to other restrictions and prohibits them from marketing or importing new products. The FCC made its order public Friday. The latest order stops short of requiring U.S. equipment buyers to remove items they have previously purchased or stripping authorizations for electronics models that already exist. A spokesman for Hikvision said the FCC's decision won't protect U.S. national security, "but will do a great deal to make it more harmful and more expensive for U.S. small businesses, local authorities, school districts, and individual consumers."

An Artificial Intelligence Incubation Hub (AIIH), set up jointly by the Army and Bharat Electronics Limited (BEL) as part of a pact inked earlier this year, will be identifying artificial intelligence projects that may be critical for the Army and coordinate the evaluation of trials in those cases, News18 has learnt. As per defence sources, the AIIH will also be tasked with identifying partners from the industry, academia or start-ups to check the feasibility of ideas related to AI projects for implementation and will be responsible for hiring of resources and necessary hardware for validation of suggested AI projects for the force. Based on BEL's research and development expertise and areas where the Army could use AI, the new hub will be working in major domain areas of machine learning, auto-platforms, AI-based swarm technology, robotics, big data analytics, image processing as well as cyber security and AI-based response mechanism. In March this year, the Army and BEL had inked a pact to collaborate in AI for defence applications. The step was taken after the defence ministry had pushed for fast-tracking incorporation of the new tech for defence applications, as part of which the defence services were asked to collaborate with defence PSUs.

When it comes to artificial intelligence and edge computing across the U.S. Department of Defense, we're no longer in the talking phase, we're in the doing phase. That's evidenced by the Joint All Domain Command and Control effort and the recent introduction of the DoD's Chief Digital and Artificial Intelligence Office. Air traffic controllers can now use AI-type analytics to keep track of "good aircraft" (i.e., a passenger jets) and "questionable aircraft" (an unexpected aircraft moving in an unexpected manner such as traveling at Mach speed or even a weather balloon). Thanks to AI-driven image processing and its ability to analyze different characteristics of objects, including size, weight, speed and more, military commanders can gain better situational awareness and accurately determine whether an object seen from afar or on the radar is innocuous or a possible threat. All this information can be processed and delivered in near real-time, thanks to Field Programmable Gate Arrays, which is a fancy term for CPU accelerators.

Meta AI has released a fascinating AI-infused diplomacy acting app that plays the famous board game known as Diplomacy, doing so to a level seemingly on par with human players. We take a close look and assess the AI, along with considering crucial AI Ethics and AI Law facets.

The accurate characterization of the severity of the wildfire event strongly contributes to the characterization of the fuel conditions in fire-prone areas, and provides valuable information for disaster response. The aim of this study is to develop an autonomous system built on top of high-resolution multispectral satellite imagery, with an advanced deep learning method for detecting burned area change. This work proposes an initial exploration of using an unsupervised model for feature extraction in wildfire scenarios. It is based on the contrastive learning technique SimCLR, which is trained to minimize the cosine distance between augmentations of images. The distance between encoded images can also be used for change detection. We propose changes to this method that allows it to be used for unsupervised burned area detection and following downstream tasks. We show that our proposed method outperforms the tested baseline approaches.

Skillful streamflow forecasts can inform decisions in various areas of water policy and management. We integrate numerical weather prediction ensembles, distributed hydrological model and machine learning to generate ensemble streamflow forecasts at medium-range lead times (1 - 7 days). We demonstrate a case study for machine learning applications in postprocessing ensemble streamflow forecasts in the Upper Susquehanna River basin in the eastern United States. Our results show that the machine learning postprocessor can improve streamflow forecasts relative to low complexity forecasts (e.g., climatological and temporal persistence) as well as standalone hydrometeorological modeling and neural network. The relative gain in forecast skill from postprocessor is generally higher at medium-range timescales compared to shorter lead times; high flows compared to low-moderate flows, and warm-season compared to cool ones. Overall, our results highlight the benefits of machine learning in many aspects for improving both the skill and reliability of streamflow forecasts.