Robots were on the main expo floor at CES this year, and these weren't just cool robots for marketing purposes. I've been tracking robots at CES for more than 10 years, watching the transition from robot toys to real robots. Increasing prominence has been given to self-driving cars, LiDARs and eVTOL drones, but, in my mind it was really the inclusion of John Deere and agricultural robots last year that confirmed that CES was incorporating more industry, more real machines, not just gadgets. In fact, according to the organizing association CTA or the Consumer Technology Association, these days CES no longer stands for the Consumer Electronics Show. CES now just stands for CES, one of the world's largest technology expos.

Ships are a major means of commercial transport, contributing to 80% of global goods and energy trade. However, they emit exhaust gases--from the engines when they are sailing, and from the engines and boiler when they dock in ports. These emissions negatively affect not only human health, but also the environment. Therefore, the International Maritime Organization has imposed regulations on the type of fuel used in ships. While efforts are being made to reduce the level of emissions from ships, a completely eco-friendly fuel is yet to be developed.

An oil tanker associated with an Israeli billionaire has been struck by a bomb-carrying drone off the coast of Oman amid heightened tensions with Iran, an official has told the Associated Press. The attack happened on Tuesday night off the coast of Oman, the Middle East-based defence official said. The official spoke on Wednesday on condition of anonymity as they did not have authorisation to discuss the attack publicly. The United Kingdom Maritime Trade Operations, a British military organisation in the region monitoring shipping, told the AP: "We are aware of an incident and it's being investigated at this time." The official identified the vessel attacked as the Liberian-flagged oil tanker Pacific Zircon.

Modern neural language models widely used in tasks across NLP risk memorizing sensitive information from their training data. As models continue to scale up in parameters, training data, and compute, understanding memorization in language models is both important from a learning-theoretical point of view, and is practically crucial in real world applications. An open question in previous studies of memorization in language models is how to filter out "common" memorization. In fact, most memorization criteria strongly correlate with the number of occurrences in the training set, capturing "common" memorization such as familiar phrases, public knowledge or templated texts. In this paper, we provide a principled perspective inspired by a taxonomy of human memory in Psychology. From this perspective, we formulate a notion of counterfactual memorization, which characterizes how a model's predictions change if a particular document is omitted during training. We identify and study counterfactually-memorized training examples in standard text datasets. We further estimate the influence of each training example on the validation set and on generated texts, and show that this can provide direct evidence of the source of memorization at test time.

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.

There is no need to raise an alarm over loss of jobs from induction of existing technology, because even more jobs are being created in its wake, says Raveendran Kasthuri, ex-IBMer and Group CEO of the Uralungal Labour Contract Cooperative Society (ULCC), based in Kozhikode, Kerala. Started as a cooperative society by labourers, ULCC has now grown to become one of the largest workers' cooperatives in Asia, at a time when, back home, cooperatives have come under the regulatory scanner for many reasons. As Group CEO, Kasthuri also looks after UL technology Solutions (ULTS), which was established in 2011 to maintain a balance between traditional and modern technologies. It offers a unique mix of traditional values and modern technological insights in its services and helps to formulate and implement comprehensive solutions for clients. ULTS describes itself as a cooperative corporate, with a focus on technology verticals such as Geographic Information System (GIS), Enterprise Resource Planning (ERP), Internet of Things (IoT), Blockchain, Artificial Intelligence (AI) and analytics.

ABS and Samsung Heavy Industries (SHI) are to collaborate on the use of digital technologies to streamline designing, building, and classing assets in a joint development project (JDP) signed yesterday (Sep17) at Gastech 2019. The JDP encompasses 3D digital disclosure, data exchange, and the use of analytics to support the new construction process and pilot the survey of the future. "Data and digitalization are revolutionizing the marine and offshore industries. This JDP is further evidence of how ABS is leading the way and working with innovative partners such as SHI to shape the future of our industry," said Patrick Ryan, ABS Senior Vice President, Engineering and Technology. "ABS is committed to realizing the potential benefits of these technologies for members and clients while advancing safety at sea." "We have been leading digital innovation from design to production in order to adapt to the fourth industrial revolution and to ensure continued competitiveness," said Jong H Youn, Vice President of SHI.

We propose a new framework for constructing polar codes (i.e., selecting the frozen bit positions) for arbitrary channels, and tailored to a given decoding algorithm, rather than based on the (not necessarily optimal) assumption of successive cancellation (SC) decoding. The proposed framework is based on the Genetic Algorithm (GenAlg), where populations (i.e., collections) of information sets evolve successively via evolutionary transformations based on their individual error-rate performance. These populations converge towards an information set that fits both the decoding behavior and the defined channel. Using our proposed algorithm over the additive white Gaussian noise (AWGN) channel, we construct a polar code of length 2048 with code rate 0.5, without the CRC-aid, tailored to plain successive cancellation list (SCL) decoding, achieving the same error-rate performance as the CRC-aided SCL decoding, and leading to a coding gain of 1 dB at BER of $10^{-6}$. Further, a belief propagation (BP)-tailored construction approaches the SCL error-rate performance without any modifications in the decoding algorithm itself. The performance gains can be attributed to the significant reduction in the total number of low-weight codewords. To demonstrate the flexibility, coding gains for the Rayleigh channel are shown under SCL and BP decoding. Besides improvements in error-rate performance, we show that, when required, the GenAlg can be also set up to reduce the decoding complexity, e.g., the SCL list size or the number of BP iterations can be reduced, while maintaining the same error-rate performance.

We propose a new polar code construction framework (i.e., selecting the frozen bit positions) for the additive white Gaussian noise (AWGN) channel, tailored to a given decoding algorithm, rather than based on the (not necessarily optimal) assumption of successive cancellation (SC) decoding. The proposed framework is based on the Genetic Algorithm (GenAlg), where populations (i.e., collections) of information sets evolve successively via evolutionary transformations based on their individual error-rate performance. These populations converge towards an information set that fits the decoding behavior. Using our proposed algorithm, we construct a polar code of length 2048 with code rate 0.5, without the CRC-aid, tailored to plain successive cancellation list (SCL) decoding, achieving the same error-rate performance as the CRC-aided SCL decoding, and leading to a coding gain of 1 dB at BER of $10^{-6}$. Further, a belief propagation (BP)-tailored polar code approaches the SCL error-rate performance without any modifications in the decoding algorithm itself.

The global shipping industry has changed more in the past few years than the previous half of a decade. Artificial intelligence is one of the biggest factors that is spearheading the evolution of this timeless industry. Mike Konstantinidis, The CEO of METIS Cybertechnology provided an especially insightful critique of the impact AI has had on the industry. Konstantinidis points out that the shipping industry was reluctant to invest in new communication technologies during the late 1990s and early 21st century. Artificial intelligence has made it easier for these companies to seamlessly integrate new shipping logistics and communication technology into their business models.