Yaroslavl Oblast
Reverse Modeling in Large Language Models
Yu, Sicheng, Xu, Yuanchen, Du, Cunxiao, Zhou, Yanying, Qiu, Minghui, Sun, Qianru, Zhang, Hao, Wu, Jiawei
Humans are accustomed to reading and writing in a forward manner, and this natural bias extends to text understanding in auto-regressive large language models (LLMs). This paper investigates whether LLMs, like humans, struggle with reverse modeling, specifically with reversed text inputs. We found that publicly available pre-trained LLMs cannot understand such inputs. However, LLMs trained from scratch with both forward and reverse texts can understand them equally well during inference. Our case study shows that different-content texts result in different losses if input (to LLMs) in different directions -- some get lower losses for forward while some for reverse. This leads us to a simple and nice solution for data selection based on the loss differences between forward and reverse directions. Using our selected data in continued pretraining can boost LLMs' performance by a large margin across different language understanding benchmarks.
Russia, Ukraine trade drone attacks in renewed escalation
Russia has launched several strikes across Ukraine, killing at least five people and wounding several, in an attack that appeared to target energy infrastructure. Ukraine also launched a drone attack on Russia's central region of Saratov, injuring four. The exchange began around midnight on Sunday and continued beyond daybreak on Monday. Ukraine's air force reported multiple groups of Russian drones moving towards its eastern, northern, southern, and central regions, followed by numerous cruise and ballistic missiles. Authorities in at least six Ukrainian regions said blasts had been heard.
Authorship attribution for Differences between Literary Texts by Bilingual Russian-French and Non-Bilingual French Authors
Do bilingual Russian-French authors of the end of the twentieth century such as Andre\"i Makine, Val\'ery Afanassiev, Vladimir F\'edorovski, Iegor Gran, Luba Jurgenson have common stylistic traits in the novels they wrote in French? Can we distinguish between them and non-bilingual French writers' texts? Is the phenomenon of interference observable in French texts of Russian authors? This paper applies authorship attribution methods including Support Vector Machine (SVM), $K$-Nearest Neighbors (KNN), Ridge classification, and Neural Network to answer these questions.
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
Harl, Maximilian, Herchenbach, Marvin, Kruschel, Sven, Hambauer, Nico, Zschech, Patrick, Kraus, Mathias
In recent years, large pre-trained deep neural networks (DNNs) have revolutionized the field of computer vision (CV). Although these DNNs have been shown to be very well suited for general image recognition tasks, application in industry is often precluded for three reasons: 1) large pre-trained DNNs are built on hundreds of millions of parameters, making deployment on many devices impossible, 2) the underlying dataset for pre-training consists of general objects, while industrial cases often consist of very specific objects, such as structures on solar wafers, 3) potentially biased pre-trained DNNs raise legal issues for companies. As a remedy, we study neural networks for CV that we train from scratch. For this purpose, we use a real-world case from a solar wafer manufacturer. We find that our neural networks achieve similar performances as pre-trained DNNs, even though they consist of far fewer parameters and do not rely on third-party datasets.
'High-tech' robot on Russian TV was man in suit: report
MOSCOW - Russian media say a contraption presented by Russian state television as a high-tech robot was in fact a man in a commercially available robot costume. The footage was shot at a high-tech show in the city of Yaroslavl that opened last Tuesday, featuring "Boris the Robot." Forum organizers used Boris to enliven the event, having him dance to a pop song. But a crew for Russian state television apparently thought Boris was real, and used footage of him dancing and speaking as an example of Russian technological prowess. Online TJournal noted the lack of sensors, human-like movements and other discrepancies, and revealed that Boris was in fact a human clad in a costume sold under the name Alyosha by the Russian company Show Robots.
The threat of killer robots
Artificial intelligence (AI) has a growing number of applications in the security and military areas. It facilitates manoeuvres in the field, and can save lives when things go wrong. It also boosts the performance of armies by providing robot allies to combat forces. According to some experts, Lethal Autonomous Weapons Systems (LAWS) are creating a "Third Revolution" in warfare, after gunpowder and nuclear weapons. It is time we start worrying about the day when armies of robots are capable of conducting hostilities with full autonomy, without humans to command them.
Putin warns: AI will be the ultimate weapon for world dominationโฆ (and Google is working on it)
The Russian president has become the latest person to warn of the dangers of artificial intelligence (AI), actually predicting that whoever masters the technology first can rule the world. Addressing students last week, Vladimir Putin said that there are legitimate concerns about AI and that its development will produce "colossal opportunities and threats that are difficult to predict now." Going further, Putin warned that "the one who becomes the leader in this sphere will be the ruler of the world." He added: "Artificial intelligence is the future, not only for Russia but for all humankind," according to Russia Today. Putin added that he does not want to see the technology "monopolized," and added that Russia would share it with the world if Moscow develops advanced AI first.
'Whoever leads in AI will rule the world': Putin to Russian children on Knowledge Day
"Artificial intelligence is the future, not only for Russia, but for all humankind. It comes with colossal opportunities, but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world," Russian President Vladimir Putin said. However, the president said he would not like to see anyone "monopolize" the field. "If we become leaders in this area, we will share this know-how with entire world, the same way we share our nuclear technologies today," he told students from across Russia via satellite link-up, speaking from the Yaroslavl region.
Putin says whoever cracks AI will 'rule the world'
Russian President Vladimir Putin says that whoever reaches a breakthrough in developing artificial intelligence will come to dominate the world. Putin, speaking Friday at a meeting with students, said the development of AI raises'colossal opportunities and threats that are difficult to predict now.' He warned that'the one who becomes the leader in this sphere will be the ruler of the world.' Russian President Vladimir Putin, right, attends a meeting with students in Yaroslavl, Russia, Friday, Sept. 1, 2017. Putin, speaking Friday at a meeting with students, said the development of AI raises'colossal opportunities and threats that are difficult to predict now' 'Artificial intelligence is the future, not only for Russia, but for all humankind,' Putin said during the discussion, according to RT.
Putin: Leader in Artificial Intelligence Will Rule World
Russian President Vladimir Putin, center, applauds during a meeting with students in Yaroslavl, Russia, Friday, Sept. 1, 2017. Putin said that whoever reaches a breakthrough in developing artificial intelligence will come to dominate the world. Putin, speaking Friday at a meeting with students, said the development of AI raises "colossal opportunities and threats that are difficult to predict now."