I am honoured to present the International AI Safety Report. It is the work of 96 international AI experts who collaborated in an unprecedented effort to establish an internationally shared scientific understanding of risks from advanced AI and methods for managing them. We embarked on this journey just over a year ago, shortly after the countries present at the Bletchley Park AI Safety Summit agreed to support the creation of this report. Since then, we published an Interim Report in May 2024, which was presented at the AI Seoul Summit. We are now pleased to publish the present, full report ahead of the AI Action Summit in Paris in February 2025. Since the Bletchley Summit, the capabilities of general-purpose AI, the type of AI this report focuses on, have increased further. For example, new models have shown markedly better performance at tests of Professor Yoshua Bengio programming and scientific reasoning.

Cities worldwide are rapidly adopting smart technologies, transforming urban life. Despite this trend, a universally accepted definition of 'smart city' remains elusive. Past efforts to define it have not yielded a consensus, as evidenced by the numerous definitions in use. In this paper, we endeavored to create a new 'compromise' definition that should resonate with most experts previously involved in defining this concept and aimed to validate one of the existing definitions. We reviewed 60 definitions of smart cities from industry, academia, and various relevant organizations, employing transformer architecture-based generative AI and semantic text analysis to reach this compromise. We proposed a semantic similarity measure as an evaluation technique, which could generally be used to compare different smart city definitions, assessing their uniqueness or resemblance. Our methodology employed generative AI to analyze various existing definitions of smart cities, generating a list of potential new composite definitions. Each of these new definitions was then tested against the pre-existing individual definitions we have gathered, using cosine similarity as our metric. This process identified smart city definitions with the highest average cosine similarity, semantically positioning them as the closest on average to all the 60 individual definitions selected.

This paper studies extractable memorization: training data that an adversary can efficiently extract by querying a machine learning model without prior knowledge of the training dataset. We show an adversary can extract gigabytes of training data from open-source language models like Pythia or GPT-Neo, semi-open models like LLaMA or Falcon, and closed models like ChatGPT. Existing techniques from the literature suffice to attack unaligned models; in order to attack the aligned ChatGPT, we develop a new divergence attack that causes the model to diverge from its chatbot-style generations and emit training data at a rate 150x higher than when behaving properly. Our methods show practical attacks can recover far more data than previously thought, and reveal that current alignment techniques do not eliminate memorization.

Compartmental epidemiological models categorize individuals based on their disease status, such as the SEIRD model (Susceptible-Exposed-Infected-Recovered-Dead). These models determine the parameters that influence the magnitude of an outbreak, such as contagion and recovery rates. However, they don't account for individual characteristics or population actions, which are crucial for assessing mitigation strategies like mask usage in COVID-19 or condom distribution in HIV. Additionally, studies highlight the role of citizen solidarity, interpersonal trust, and government credibility in explaining differences in contagion rates between countries. Agent-Based Modeling (ABM) offers a valuable approach to study complex systems by simulating individual components, their actions, and interactions within an environment. ABM provides a useful tool for analyzing social phenomena. In this study, we propose an ABM architecture that combines an adapted SEIRD model with a decision-making model for citizens. In this paper, we propose an ABM architecture that allows us to analyze the evolution of virus infections in a society based on two components: 1) an adaptation of the SEIRD model and 2) a decision-making model for citizens. In this way, the evolution of infections is affected, in addition to the spread of the virus itself, by individual behavior when accepting or rejecting public health measures. We illustrate the designed model by examining the progression of SARS-CoV-2 infections in A Coru\~na, Spain. This approach makes it possible to analyze the effect of the individual actions of citizens during an epidemic on the spread of the virus.

Information and communication technologies are rapidly changing and transforming the citizens' urban life, culture, and habits. Today, cities are lively, active, productive, and innovative, but, at the same time, cities face many problems, such as high density, traffic, waste, water and air pollution, unplanned urbanization, etc. Public and local administrations have focused on finding solutions to these problems and developing new strategies. According to the United Nations' World Population Prospects 2022 most recent forecasts, the world population might reach 8.5 billion in 2030, 9.7 billion in 2050, and 10.4 billion in 2100. By 2050, it is estimated that 68% of the world's population will live in cities. There are many different definitions of smart cities.

We are a Ukraine-based company which means that our parents and grandparents lived in the era of infamous Soviet collective farms, where tractors were considered to be an ultimate technology. For them, a smart farm will sound like a fairy tale. So let it be, a fairy tale of a smart farm. First of all, what is a smart farm? Smart Farming is a concept of farming management using modern Information and Communication Technologies to increase the quantity and quality of products.

While the Fukushima event led to a particularly strong change in energy policies in Germany, resulting in the so-called Energiewende, or energy transition, the trend toward renewables is visible worldwide. Here, we outline how major challenges of the energy transition have led to a strong need for essential contributions from the computer science community to maintain stability and security of supply, particularly for the electric power grid. As a result, the new discipline of Energy Informatics has emerged which is addressing this highly interdisciplinary and dynamic field of research and development. In tomorrow's energy system, electric power will be provided mainly by photo-voltaic modules on rooftops and in larger field installations, and by wind power plants, onshore as well as offshore. Being weather-dependent, this energy supply is inherently volatile and only partially controllable.

TEHRAN – Iran will be placed among the top 10 countries in artificial intelligence (AI) by 2032 based on the national document on artificial intelligence strategy, Shahram Moein, head of innovation and development center of artificial intelligence at the Research Institute of Information and Communication Technology, said. The study of the national artificial intelligence development roadmap started a year ago at the Research Institute of Information and Communication Technology, which was officially completed by the end of November 2021. "To draft this document, strategic documents of 23 countries in the field of artificial intelligence were evaluated so that areas such as environment, health, transportation, online education, energy, robotics, industry, agriculture, and security development are among the priority areas of AI. Among the goals of this document are 80 percent of research to meet the needs of the country, use of 45 percent of artificial intelligence in industries, $8 billion investment in artificial intelligence and a 12 percent share of AI in the GDP," he explained. Stating that this document contains 14 macro policies, he said that supporting the AI products, laying the groundwork for the development of this technology, strengthening companies active in this field, and using artificial intelligence in solving super challenges are among these macro policies.

TEHRAN – The roadmap for the development of artificial intelligence (AI) was drafted after a year of scientific work with the participation of academic and industrial figures from both the public and the private sector. The study of the national artificial intelligence development roadmap document started a year ago at the Research Institute of Information and Communication Technology, which was officially completed by the end of November this year. The document is presented in two general sections, "application development" and "development of enablers", Mohammad-Shahram Moein, head of innovation and development center of artificial intelligence at the Research Institute of Information and Communication Technology, said. Iran is in 13th place among the top countries in artificial intelligence by the total number of publications in 2021."In the application development section, the main goal is to use artificial intelligence in priority areas such as health, transportation, and agriculture, and in the next priorities, areas such as education, industry, and environment have been considered. In the development of enablers, we have considered the training of specialized manpower, the development of infrastructure, and the development of the innovation system," he explained.

There is mounting public concern over the influence that AI based systems has in our society. Coalitions in all sectors are acting worldwide to resist hamful applications of AI. From indigenous people addressing the lack of reliable data, to smart city stakeholders, to students protesting the academic relationships with sex trafficker and MIT donor Jeffery Epstein, the questionable ethics and values of those heavily investing in and profiting from AI are under global scrutiny. There are biased, wrongful, and disturbing assumptions embedded in AI algorithms that could get locked in without intervention. Our best human judgment is needed to contain AI's harmful impact. Perhaps one of the greatest contributions of AI will be to make us ultimately understand how important human wisdom truly is in life on earth.