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Distributed Causality in the SDG Network: Evidence from Panel VAR and Conditional Independence Analysis

arXiv.org Machine Learning

The achievement of the 2030 Sustainable Development Goals (SDGs) is dependent upon strategic resource distribution. We propose a causal discovery framework using Panel Vector Autoregression, along with both country-specific fixed effects and PCMCI+ conditional independence testing on 168 countries (2000-2025) to develop the first complete causal architecture of SDG dependencies. Utilizing 8 strategically chosen SDGs, we identify a distributed causal network (i.e., no single 'hub' SDG), with 10 statistically significant Granger-causal relationships identified as 11 unique direct effects. Education to Inequality is identified as the most statistically significant direct relationship (r = -0.599; p < 0.05), while effect magnitude significantly varies depending on income levels (e.g., high-income: r = -0.65; lower-middle-income: r = -0.06; non-significant). We also reject the idea that there exists a single 'keystone' SDG. Additionally, we offer a proposed tiered priority framework for the SDGs namely, identifying upstream drivers (Education, Growth), enabling goals (Institutions, Energy), and downstream outcomes (Poverty, Health). Therefore, we conclude that effective SDG acceleration can be accomplished through coordinated multi-dimensional intervention(s), and that single-goal sequential strategies are insufficient.


A Decomposable Forward Process in Diffusion Models for Time-Series Forecasting

arXiv.org Machine Learning

We introduce a model-agnostic forward diffusion process for time-series forecasting that decomposes signals into spectral components, preserving structured temporal patterns such as seasonality more effectively than standard diffusion. Unlike prior work that modifies the network architecture or diffuses directly in the frequency domain, our proposed method alters only the diffusion process itself, making it compatible with existing diffusion backbones (e.g., DiffWave, TimeGrad, CSDI). By staging noise injection according to component energy, it maintains high signal-to-noise ratios for dominant frequencies throughout the diffusion trajectory, thereby improving the recoverability of long-term patterns. This strategy enables the model to maintain the signal structure for a longer period in the forward process, leading to improved forecast quality. Across standard forecasting benchmarks, we show that applying spectral decomposition strategies, such as the Fourier or Wavelet transform, consistently improves upon diffusion models using the baseline forward process, with negligible computational overhead. The code for this paper is available at https://anonymous.4open.science/r/D-FDP-4A29.


The Download: inside the Vitalism movement, and why AI's "memory" is a privacy problem

MIT Technology Review

The Download: inside the Vitalism movement, and why AI's "memory" is a privacy problem Meet the Vitalists: the hardcore longevity enthusiasts who believe death is "wrong" Last April, an excited crowd gathered at a compound in Berkeley, California, for a three-day event called the Vitalist Bay Summit. It was part of a longer, two-month residency that hosted various events to explore tools--from drug regulation to cryonics--that might be deployed in the fight against death. One of the main goals, though, was to spread the word of Vitalism, a somewhat radical movement established by Nathan Cheng and his colleague Adam Gries a few years ago. Consider it longevity for the most hardcore adherents--a sweeping mission to which nothing short of total devotion will do. Although interest in longevity has certainly taken off in recent years, not everyone in the broader longevity space shares Vitalists' commitment to actually making death obsolete. And the Vitalists feel that momentum is building, not just for the science of aging and the development of lifespan-extending therapies, but for the acceptance of their philosophy that .


The Doomsday Clock Is Now 85 Seconds to Midnight. Here's What That Means

WIRED

The Doomsday Clock Is Now 85 Seconds to Midnight. Catastrophic risks are increasing, cooperation is declining, and swift action is needed from global leaders to correct course. The Doomsday Clock is closer to midnight than ever. The Doomsday Clock has just been set to 85 seconds to midnight. Nearly 80 years after its creation, this time represents the closest the clock has ever been to midnight.


Roundtables: Why AI Companies Are Betting on Next-Gen Nuclear

MIT Technology Review

AI is driving unprecedented investment for massive data centers and an energy supply that can support its huge computational appetite. One potential source of electricity for these facilities is next-generation nuclear power plants, which could be cheaper to construct and safer to operate than their predecessors. Watch a discussion with our editors and reporters on hyperscale AI data centers and next-gen nuclear--two featured technologies on the MIT Technology Review list . China figured out how to sell EVs. Now it has to deal with their aging batteries. Here are our picks for the advances to watch in the years ahead--and why we think they matter right now.


China lags behind US at AI frontier but could quickly catch up, say experts

The Guardian

Since 2021, China has reportedly poured $100bn into support for AI datacentres. Since 2021, China has reportedly poured $100bn into support for AI datacentres. Beijing's AI policy is focused on real-life applications but Chinese companies are beginning to articulate their own grand visions S tanding on stage in the eastern China tech hub of Hangzhou, Alibaba's normally media-shy CEO made an attention-grabbing announcement. "The world today is witnessing the dawn of an AI-driven intelligent revolution," Eddie Wu told a developer conference in September. " Artificial general intelligence (AGI) will not only amplify human intelligence but also unlock human potential, paving the way for the arrival of artificial superintelligence (ASI)."


Symbolic Doomsday Clock moves closer to midnight amid 'catastrophic risks'

Al Jazeera

The world is closer than ever to destruction, scientists have said, as the Doomsday Clock was set at 85 seconds to midnight for 2026, the gloomiest assessment of humanity's prospects since the beginning of the tradition in 1947. The Bulletin of the Atomic Scientists, a not-for-profit organisation founded by Albert Einstein and other scientists, warned in its annual assessment on Tuesday that international cooperation is going backwards on nuclear weapons, climate change and biotechnology, while artificial intelligence poses new threats. "The Doomsday Clock's message cannot be clearer. Catastrophic risks are on the rise, cooperation is on the decline, and we are running out of time," said Alexandra Bell, the president and CEO of the Bulletin of the Atomic Scientists. In a more detailed statement explaining the reasoning for moving the clock closer to midnight, the bulletin expressed concerns that countries including Russia, China, and the United States were becoming "increasingly aggressive, adversarial, and nationalistic".


Russia-Ukraine war: List of key events, day 1,434

Al Jazeera

Could Ukraine hold a presidential election right now? Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? 'Ukraine is running out of men, money and time' At least four people were killed in a Russian drone attack on a passenger train in Ukraine's Kharkiv region, Ukrainian President Volodymyr Zelenskyy said on Telegram. Zelenskyy added that four people were still missing, and that two people were injured in the attack.


The Download: OpenAI's plans for science, and chatbot age verification

MIT Technology Review

In the three years since ChatGPT's explosive debut, OpenAI's technology has upended a remarkable range of everyday activities at home, at work, and in schools. Now OpenAI is making an explicit play for scientists. In October, the firm announced that it had launched a whole new team, called OpenAI for Science, dedicated to exploring how its large language models could help scientists and tweaking its tools to support them. How does a push into science fit with OpenAI's wider mission? And what exactly is the firm hoping to achieve? I put these questions to Kevin Weil, a vice president at OpenAI who leads the new OpenAI for Science team, in an exclusive interview.


'It's 2C in our flat': Inside Kyiv apartment as Russia targets power and heating

BBC News

Russia has been exploiting Ukraine's harshest winter in years to pummel energy infrastructure across the country. Repeated strikes have crippled the power supply to major Ukrainian cities, leaving millions without heating or light as temperatures hover around -15C (5F) for the third week in a row. Electrical companies carry out round-the-clock repairs - only for their work to be undone at night, when Russian drone and missiles again damage power stations. In Kyiv, people were initially able to keep the cold at bay by using electric heaters or wrapping up warm. But the freezing temperatures have lasted weeks now, with no end in sight.