Month: May 2022

Categories
Information Warfare

Open Source Intelligence May Be Changing Old-School War | Wired

Shutterstock / Photo Contributor Panchenko Vladimir

How open-source intelligence is transforming the character of conventional warfare 

The panopticon of information technology is altering the collection and use of intelligence in conventional warfare. What was formerly prohibitively expensive for many is now accessible to various entities, including North Korea, the CIA, journalists, terrorists, and cybercriminals. A former U.S. intelligence officer claims that missing information might warn an adversary espionage outfit. In addition to preventing governments and the military from understanding themselves, excessive secrecy may lead to strategic errors. To fight Russian disinformation or share classified material with Ukrainian colleagues, the Biden administration declassified intelligence unprecedentedly. 

Attributing results in Ukraine to open sources might sometimes serve as a cover for more strictly guarded sources and techniques. This tendency is referred to as “radical war” by British researcher Matthew Ford, coauthor of a forthcoming book on the influence of information infrastructure and linked gadgets on military engagements. According to Ford, the Russian invasion of Ukraine was not just the first conventional war in Europe in the 21st century but also the “most technologically linked in history.” The goal of Ukrainian troops is to locate, repair, and eliminate Russian units faster than the Russians can. In the information era, erroneous assessments of the anticipated equilibrium between solid and weak nations, coupled with strategic surprise, may be commonplace. 

The use of open-source platforms and consumer devices by civilian noncombatants in support of hostile military activities raises fundamental problems regarding the blurring of the distinctions between civilian and combatant: This may result in the same persons being legal targets or having convicted for espionage following the rules of war. U.S. intelligence’s precise role and effect in Ukraine will be the subject of research and controversy for decades.  Source: https://www.wired.com/story/open-source-intelligence-war-russia-ukraine/

Categories
Machine Learning

Machine learning radically reduces workload of cell counting for disease diagnosis | Techxplore

Shutterstock / Photo Contributor Zapp2Photo

Utilizing machine learning to accomplish medical picture segmentation is a novel approach. 

China’s Beihang University has created a new training approach that automates a significant portion of the manual annotation labor performed by people. Machine learning can do blood cell counts for illness diagnosis instead of costly and often less precise cell analyzer devices. On April 9, an article describing their new training program has published in the journal Cyborg and Bionic Systems. 

Since 2015, researchers from China’s Beihang University have created a new training strategy for the CNN, or convolutional network segmentation model, frequently used in medical picture segmentation. They discovered that their training approach for segmenting multiple-cell-type photos reached the same level as training with manually annotated multiple-tone white images: 94.85 percent.  Source: https://techxplore.com/news/2022-05-machine-radically-workload-cell-disease.html

Categories
Robots

New ‘socially aware’ robot can predict what people will do | Tweaktown

Shutterstock / Photo Contributor Frame Stock Footage

A new way for robots to navigate the globe without clashing with humans 

University of Toronto (U of T) researchers have developed a new approach for robots to navigate the environment without clashing with humans. Their robot employs Spatiotemporal Occupancy Grid Maps (SOGM) to anticipate the movement of emotional barriers, such as humans, across time. LIDAR functions similarly to radar but use light beams rather than radio frequencies. 

Source: https://www.tweaktown.com/news/86390/new-socially-aware-robot-can-predict-what-people-will-do/index.html  

  

Categories
Space Force

Space Fence now has a direct link to key Space Force data hub | Defense News

Shutterstock / Photo Contributor Dima Zel

The newest military branch of the Department of Defense, the U.S. Space Force, has an operational cloud data environment. 

Friday, the United States Space Force revealed that its cloud-based data environment can now receive data straight from the Space Fence radar. The Space Force’s digital infrastructure relies heavily on the Unified Data Library. During the 30-day trial period, the service monitored the data flow. According to chief information officer Bruce Kimmich, the U.S. Space Force strives to link all of its sensors to the University of Defense Logistics Lab (UDL) “within the range of possibility.” 

According to him, the library’s cyber certification would provide it access to confidential and top-secret material from across the globe. Additionally, the service has initiated the building of an Allied Exchange Environment to link other nations for increased information exchange. 

Source: https://www.defensenews.com/battlefield-tech/space/2022/04/22/space-fence-now-has-a-direct-link-to-key-space-force-data-hub/

Categories
Artificial Intelligence

Meta wants to improve its AI by studying human brains | POPSCI

Shutterstock / Contributor majcot

How Computer Scientists are investigating the Brain to Aid Deep Learning in Language Understanding 

Together, Neurospin and INRIA analyze human brain activity and deep learning algorithms trained on language or voice tasks. The findings might help explain why humans understand a language far more effectively than robots. Theoretically, it might decipher how both human and artificial brains determine the meaning of language. Meta-AI researchers examine the brain’s reaction to words to see if they can be used to train AI computers. Using methods such as fMRI and magnetoencephalography, they monitor brain activity in response to particular words and phrases down to the millisecond. 

Detailed observation of the brain will enable researchers to determine which brain areas are engaged when hearing words such as “dog” or “table.” A team at Meta AI is constructing a collection of open-source transformer-based language models with millions or perhaps billions of parameters. With 175 billion parameters, the most significant model is comparable in scale to other industrial language models, such as GPT-3. Possessing a comprehensive understanding of a topic may be essential to developing improved AI systems for natural dialogue, which might power future virtual assistants one day. A solid language model is a crucial component for chatbots, conversation agents, machine translation, and text categorization. 

A transformer-based model “uses both a learned mechanism for encoding information sequences and a mechanism for attention,” according to the head of Meta AI Research Labs, Joelle Pineau. Meta AI is open-sourcing its language models to get input from other academics, especially those investigating the behavioral and ethical consequences of these massive AI systems. 

Source: https://www.popsci.com/technology/meta-ai-language-models/