Activists sailed to Gaza to deliver aid, but were met with drone attacks and imprisonment. "All of this preparation, all of this work--it's actually come together and we're sailing east, finally," said Dane Hunter. Get your news from a source that's not owned and controlled by oligarchs. Earlier this fall, hundreds of activists from all over the world crowded onto several dozen boats and set sail for Gaza. They thought that by sharing their journey through social media, they could capture the world's attention.

Large language models (LLMs) demonstrate impressive performance but lack the flexibility to adapt to human preferences quickly without retraining. In this work, we introduce Test-time Preference Optimization (TPO), a framework that aligns LLM outputs with human preferences during inference, removing the need to update model parameters. Rather than relying on purely numerical rewards, TPO translates reward signals into textual critiques and uses them as textual rewards to iteratively refine its response. Evaluations on benchmarks covering instruction following, preference alignment, safety, and mathematics reveal that TPO progressively improves alignment with human preferences. Notably, after only a few TPO steps, the initially unaligned Llama-3.1-70B-SFT model can surpass the aligned counterpart, Llama-3.1-70B-Instruct. Furthermore, TPO scales efficiently with both the search width and depth during inference. Through case studies, we illustrate how TPO exploits the innate capacity of LLM to interpret and act upon reward signals. Our findings establish TPO as a practical, lightweight alternative for test-time preference optimization, achieving alignment on the fly. Our code is publicly available at https://github.com/yafuly/TPO.

Tehran, Iran – Iran's use of hundreds of drones and missiles to directly target Israel on Saturday night and Sunday morning set a number of major political and military precedents. It was the single largest drone attack ever carried out by any country, and it was the first time Iran directly attacked Israel after almost a half-century of being archenemies. Here's a look at what political, military and economic considerations Tehran might have factored in while deciding on the attack that has amplified fears of a larger regional war and that could also affect the direction of Israel's war on Gaza. The Islamic Revolutionary Guard Corps (IRGC) dubbed the operation "True Promise" to show that top leaders in Tehran, including Supreme Leader Ayatollah Ali Khamenei, intend to make good on their vows of "punishment" for attacks by Israel and others. The attack was a direct retaliation for an Israeli strike on the Iranian consulate in Damascus on April 1 that killed seven IRGC members, including two generals in charge of leading operations in Syria and Lebanon, along with six other people.

The troubling rise of hallucination presents perhaps the most significant impediment to the advancement of responsible AI. In recent times, considerable research has focused on detecting and mitigating hallucination in Large Language Models (LLMs). However, it's worth noting that hallucination is also quite prevalent in Vision-Language models (VLMs). In this paper, we offer a fine-grained discourse on profiling VLM hallucination based on two tasks: i) image captioning, and ii) Visual Question Answering (VQA). We delineate eight fine-grained orientations of visual hallucination: i) Contextual Guessing, ii) Identity Incongruity, iii) Geographical Erratum, iv) Visual Illusion, v) Gender Anomaly, vi) VLM as Classifier, vii) Wrong Reading, and viii) Numeric Discrepancy. We curate Visual HallucInation eLiciTation (VHILT), a publicly available dataset comprising 2,000 samples generated using eight VLMs across two tasks of captioning and VQA along with human annotations for the categories as mentioned earlier.

Google has been accused of censoring Israel-Palestine responses after its AI refused to call Hamas a terrorist organization. But the tech giant's rival, OpenAI's ChatGPT, had no issue condemning the ruling part of Gaza, saying ''Hamas is designated as a terrorist organization by several countries.' It comes as Israel has launched more than 700 airstrikes on Gaza this week in retaliation for Palestine carrying out an unprecedented attack on festival goers on October 7. The same queries were fed to OpenAI's ChatGPT, which returned with detailed information and answered that'Hamas is designated as a terrorist organization by several countries.' A Google spokesperson told DailyMail.com:

Naqab, Israel – In 1992, Mohamed Abu Qwaider watched his mother's home bulldozed by the Israeli army in the unrecognised Bedouin village of az-Zarnug in the Naqab Desert. The then-10-year-old helped his family rebuild the house using stone and concrete, sturdier than the previous metal shack. A few days after completing their new home, the family got another demolition order stating the structure was built illegally and had to watch it flattened to the ground. "I was too young so I didn't know the regulations," Abu Qwaider, now 41, said. "All I knew is that we had the right – anybody has the right to upgrade their house and live peacefully," he told Al Jazeera.

For real-world applications, autonomous mobile robotic platforms must be capable of navigating safely in a multitude of different and dynamic environments with accurate and robust localization being a key prerequisite. To support further research in this domain, we present the INSANE data sets - a collection of versatile Micro Aerial Vehicle (MAV) data sets for cross-environment localization. The data sets provide various scenarios with multiple stages of difficulty for localization methods. These scenarios range from trajectories in the controlled environment of an indoor motion capture facility, to experiments where the vehicle performs an outdoor maneuver and transitions into a building, requiring changes of sensor modalities, up to purely outdoor flight maneuvers in a challenging Mars analog environment to simulate scenarios which current and future Mars helicopters would need to perform. The presented work aims to provide data that reflects real-world scenarios and sensor effects. The extensive sensor suite includes various sensor categories, including multiple Inertial Measurement Units (IMUs) and cameras. Sensor data is made available as raw measurements and each data set provides highly accurate ground truth, including the outdoor experiments where a dual Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) setup provides sub-degree and centimeter accuracy (1-sigma). The sensor suite also includes a dedicated high-rate IMU to capture all the vibration dynamics of the vehicle during flight to support research on novel machine learning-based sensor signal enhancement methods for improved localization. The data sets and post-processing tools are available at: https://sst.aau.at/cns/datasets

NIR Calibration-Model Services Services for Professional Development of NIRS Calibrations NIR Near-Infrared-Spectroscopy QA QC QAQC Laboratory LINK Spectroscopy and Chemometrics News Weekly 35, 2022 NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK Near-Infrared Spectroscopy (NIRS) "Comparing Calibration Algorithms for the Rapid Characterization of Pretreated Corn Stover Using Near-Infrared Spectroscopy" LINK "Indirect Measurement of -Glucan Content in Barley Grain with Near-Infrared Reflectance Spectroscopy" LINK "Foods: Markov Transition Field Combined with Convolutional Neural Network Improved the Predictive Performance of Near-Infrared Spectroscopy Models for Determination of Aflatoxin B1 in Maize" LINK "Determination of Fruit Freshness Using Near-Infrared Spectroscopy and Machine Learning Techniques" LINK "Extensive evaluation of prediction ...

Israel is holding its largest-ever air force exercise this week with the participation of several countries including the United Arab Emirates, with whom it normalised ties last year. Amir Lazar, chief of Israeli air force operations, told reporters at the southern Ovda airbase the drills "don't focus on Iran", but army officials have said Iran remains Israel's top strategic threat and at the centre of much of its military planning. Israel has held the so-called "Blue Flag" exercises every two years since 2013 in the Negev desert to synchronise different types of aircraft, piloted by different countries to counter armed drones and other threats. With more than 70 fighter jets and some 1,500 personnel participating, this year's drills are the largest-ever held in Israel, Lazar said. Among the nations taking part are France, the United States and Germany, as well as the United Kingdom, whose aircraft flew over Israeli territory for the first time since the Jewish state's creation in 1948.

We've found crowdsourcing (i.e., the gathering of ideas, thoughts, and concepts from a widespread variety of interested individuals) to be a very effective tool in enabling us to diversify our thoughts and challenge our assumptions. Dr. Buras' post takes the results from one such crowdsourcing exercise and extrapolates three future urban scenarios. Given The Army Vision's clarion call to "Focus training on high-intensity conflict, with emphasis on operating in dense urban terrain," our readers would do well to consider how the Army would operate in each of Dr. Buras' posited future scenarios…] The challenges of the 21st century have been forecast and are well-known. In many ways we are already experiencing the future now. But predictions are hard to validate. A way around that is turning to slightly older predictions to illuminate the magnitude of the issues and the reality of their propositions.1