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Technology#Artificial Intelligence, Data Centers, Energy📝 BlogAnalyzed: Jan 16, 2026 01:53

Meta strikes nuclear power deals in support of its AI data centers

Published:Jan 16, 2026 01:53
1 min read

Analysis

The article focuses on Meta's agreements for nuclear power to support its AI data centers. This suggests a strategic move towards sustainable energy sources for high-demand computational infrastructure. The implications could include reduced carbon footprint and potentially lower energy costs. The lack of detailed information necessitates further investigation to understand the specifics of the deals and their long-term impact.

Key Takeaways

Reference

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Permalink
business#carbon🔬 ResearchAnalyzed: Jan 6, 2026 07:22

AI Trends of 2025 and Kenya's Carbon Capture Initiative

Published:Jan 5, 2026 13:10
1 min read
MIT Tech Review

Analysis

The article previews future AI trends alongside a specific carbon capture project in Kenya. The juxtaposition highlights the potential for AI to contribute to climate solutions, but lacks specific details on the AI technologies involved in either the carbon capture or the broader 2025 trends.

Key Takeaways

Reference

“In June last year, startup Octavia Carbon began running a high-stakes test in the small town of Gilgil in…”

PermalinkMIT Tech Review
research#llm🔬 ResearchAnalyzed: Jan 5, 2026 08:34

MetaJuLS: Meta-RL for Scalable, Green Structured Inference in LLMs

Published:Jan 5, 2026 05:00
1 min read
ArXiv NLP

Analysis

This paper presents a compelling approach to address the computational bottleneck of structured inference in LLMs. The use of meta-reinforcement learning to learn universal constraint propagation policies is a significant step towards efficient and generalizable solutions. The reported speedups and cross-domain adaptation capabilities are promising for real-world deployment.
Reference

“By reducing propagation steps in LLM deployments, MetaJuLS contributes to Green AI by directly reducing inference carbon footprint.”

PermalinkArXiv NLP
Research Paper#Materials Science, Nanotechnology, Carbon Nanotubes🔬 ResearchAnalyzed: Jan 3, 2026 17:01

Vapor-Solid-Solid Growth of Carbon Nanotubes: A Molecular Dynamics Study

Published:Dec 31, 2025 05:35
1 min read
ArXiv

Analysis

This paper investigates the vapor-solid-solid growth mechanism of single-walled carbon nanotubes (SWCNTs) using molecular dynamics simulations. It focuses on the role of rhenium nanoparticles as catalysts, exploring carbon transport, edge structure formation, and the influence of temperature on growth. The study provides insights into the kinetics and interface structure of this growth method, which is crucial for controlling the chirality and properties of SWCNTs. The use of a neuroevolution machine-learning interatomic potential allows for microsecond-scale simulations, providing detailed information about the growth process.
Reference

“Carbon transport is dominated by facet-dependent surface diffusion, bounding sustainable supply on a 2.0 nm particle to ~44 carbon atoms per μs on the slow (10̄11) facet.”

PermalinkArXiv
research#climate change economics🔬 ResearchAnalyzed: Jan 4, 2026 06:48

Optimal Carbon Prices in an Unequal World: The Role of Regional Welfare Weights

Published:Dec 30, 2025 23:46
1 min read
ArXiv

Analysis

This article, sourced from ArXiv, likely presents research on the economic implications of carbon pricing, specifically considering how regional welfare disparities impact the optimal carbon price. The focus is on the role of different welfare weights assigned to various regions, suggesting an analysis of fairness and efficiency in climate policy.
Reference

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PermalinkArXiv
Research Paper#Decarbonization, Material Flow Analysis, China, Vehicle Fleet🔬 ResearchAnalyzed: Jan 3, 2026 17:15

Decarbonizing China's Private Vehicles: A Material Flow Analysis

Published:Dec 30, 2025 16:36
1 min read
ArXiv

Analysis

This paper is significant because it provides a comprehensive, dynamic material flow analysis of China's private passenger vehicle fleet, projecting metal demands, embodied emissions, and the impact of various decarbonization strategies. It highlights the importance of both demand-side and technology-side measures for effective emission reduction, offering a transferable framework for other emerging economies. The study's findings underscore the need for integrated strategies to manage demand growth and leverage technological advancements for a circular economy.
Reference

“Unmanaged demand growth can substantially offset technological mitigation gains, highlighting the necessity of integrated demand- and technology-oriented strategies.”

PermalinkArXiv
Research Paper#Positron Emission Tomography (PET), Positronium Lifetime Imaging (PLI), Radionuclides, Medical Imaging🔬 ResearchAnalyzed: Jan 3, 2026 15:52

First Positronium Lifetime Imaging with Mn-52 and Co-55

Published:Dec 30, 2025 14:36
1 min read
ArXiv

Analysis

This paper presents the first application of Positronium Lifetime Imaging (PLI) using the radionuclides Mn-52 and Co-55 with a plastic-based PET scanner (J-PET). The study validates the PLI method by comparing results with certified reference materials and explores its application in human tissues. The work is significant because it expands the capabilities of PET imaging by providing information about tissue molecular architecture, potentially leading to new diagnostic tools. The comparison of different isotopes and the analysis of their performance is also valuable for future PLI studies.
Reference

“The measured values of $τ_{ ext{oPs}}$ in polycarbonate using both isotopes matches well with the certified reference values.”

PermalinkArXiv
Research Paper#Phase Transitions, Non-equilibrium Thermodynamics, ZGB Model🔬 ResearchAnalyzed: Jan 3, 2026 18:27

Finite-time Effects on Irreversible Phase Transition

Published:Dec 29, 2025 19:56
1 min read
ArXiv

Analysis

This paper investigates the dynamics of a first-order irreversible phase transition (FOIPT) in the ZGB model, focusing on finite-time effects. The study uses numerical simulations with a time-dependent parameter (carbon monoxide pressure) to observe the transition and compare the results with existing literature. The significance lies in understanding how the system behaves near the transition point under non-equilibrium conditions and how the transition location is affected by the time-dependent parameter.
Reference

“The study observes finite-time effects close to the FOIPT, as well as evidence that a dynamic phase transition occurs. The location of this transition is measured very precisely and compared with previous results in the literature.”

PermalinkArXiv
Research Paper#Control Systems, Machine Learning, Optimization🔬 ResearchAnalyzed: Jan 3, 2026 19:08

Data-Driven Economic Predictive Control for Nonlinear Systems

Published:Dec 29, 2025 03:25
1 min read
ArXiv

Analysis

This paper presents a novel data-driven control approach for optimizing economic performance in nonlinear systems, addressing the challenges of nonlinearity and constraints. The use of neural networks for lifting and convex optimization for control is a promising combination. The application to industrial case studies strengthens the practical relevance of the work.
Reference

“The online control problem is formulated as a convex optimization problem, despite the nonlinearity of the system dynamics and the original economic cost function.”

PermalinkArXiv
Environment#Renewable Energy📝 BlogAnalyzed: Dec 29, 2025 01:43

Good News on Green Energy in 2025

Published:Dec 28, 2025 23:40
1 min read
Slashdot

Analysis

The article highlights positive developments in the green energy sector in 2025, despite continued increases in greenhouse gas emissions. It emphasizes that the world is decarbonizing faster than anticipated, with record investments in clean energy technologies like wind, solar, and batteries. Global investment in clean tech significantly outpaced investment in fossil fuels, with a ratio of 2:1. While acknowledging that this progress isn't sufficient to avoid catastrophic climate change, the article underscores the remarkable advancements compared to previous projections. The data from various research organizations provides a hopeful outlook for the future of renewable energy.
Reference

“"Is this enough to keep us safe? No it clearly isn't," said Gareth Redmond-King, international lead at the ECIU. "Is it remarkable progress compared to where we were headed? Clearly it is...."”

PermalinkSlashdot
Research Paper#Nuclear Physics, Experimental Techniques🔬 ResearchAnalyzed: Jan 3, 2026 20:02

Quantifying Impurities in Calcium Targets for Nuclear Reaction Studies

Published:Dec 27, 2025 02:22
1 min read
ArXiv

Analysis

This paper addresses a crucial experimental challenge in nuclear physics: accurately accounting for impurities in target materials. The authors develop a data-driven method to correct for oxygen and carbon contamination in calcium targets, which is essential for obtaining reliable cross-section measurements of the Ca(p,pα) reaction. The significance lies in its ability to improve the accuracy of nuclear reaction data, which is vital for understanding nuclear structure and reaction mechanisms. The method's strength is its independence from model assumptions, making the results more robust.
Reference

“The method does not rely on assumptions about absolute contamination levels or reaction-model calculations, and enables a consistent and reliable determination of Ca$(p,pα)$ yields across the calcium isotopic chain.”

PermalinkArXiv
Research#Hydrate🔬 ResearchAnalyzed: Jan 10, 2026 07:10

Computational Study Reveals CO2 Hydrate Phase Diagram Details

Published:Dec 26, 2025 21:27
1 min read
ArXiv

Analysis

This research provides valuable insights into the behavior of CO2 hydrates, crucial for carbon capture and storage applications. The accurate determination of the phase diagram contributes to safer and more efficient designs in related technologies.
Reference

“The study focuses on locating the Hydrate-Liquid-Vapor Coexistence and its Upper Quadruple Point.”

PermalinkArXiv
Research#Catalysis🔬 ResearchAnalyzed: Jan 10, 2026 07:14

Investigating CO2 Dissociation on Copper: A Surface Science Analysis

Published:Dec 26, 2025 11:36
1 min read
ArXiv

Analysis

The article focuses on a fundamental study of CO2 dissociation on a copper surface, a process relevant to catalysis and carbon capture. Understanding the reaction mechanisms is crucial for developing efficient and sustainable technologies.
Reference

“The study examines CO2 dissociative sticking on Cu(110).”

PermalinkArXiv
Technology#AI Infrastructure📝 BlogAnalyzed: Dec 28, 2025 21:57

Texas Developer Proposes Using Recycled Navy Nuclear Reactors for AI Data Centers

Published:Dec 25, 2025 23:26
1 min read
SiliconANGLE

Analysis

The article highlights a novel proposal from a Texas power developer, HGP Intelligent Energy LLC, to utilize decommissioned U.S. Navy nuclear reactors to power large-scale AI data centers. This is a significant development because it addresses the increasing energy demands of AI infrastructure, which are substantial and growing rapidly. The proposal, if successful, could offer a continuous and potentially carbon-neutral power source, addressing concerns about the environmental impact of AI. The article's brevity, however, leaves several questions unanswered, such as the feasibility of repurposing the reactors, the associated costs, and the regulatory hurdles involved. Further investigation into these aspects is crucial to assess the viability of this innovative approach.
Reference

“The article does not contain a direct quote.”

PermalinkSiliconANGLE
Astrophysics#Galactic Dust, Hydrocarbon Emission, AKARI🔬 ResearchAnalyzed: Jan 4, 2026 00:18

Hydrocarbon Emission in Galaxies: A Systematic Study

Published:Dec 25, 2025 13:35
1 min read
ArXiv

Analysis

This paper investigates the processing of hydrocarbon dust in galaxies, focusing on the ratio of aliphatic to aromatic hydrocarbon emission. It uses AKARI near-infrared spectra to analyze a large sample of galaxies, including (U)LIRGs, IRGs, and sub-IRGs, and compares them to Galactic HII regions. The study aims to understand how factors like UV radiation and galactic nuclei influence the observed emission features.
Reference

“The luminosity ratios of aliphatic to aromatic hydrocarbons ($L_{ali}/L_{aro}$) in the sample galaxies show considerably large variations, systematically decreasing with $L_{IR}$ and $L_{Brα}$.”

PermalinkArXiv
Research#Materials Science🔬 ResearchAnalyzed: Jan 10, 2026 07:28

Unveiling Metastable Structures in Metal Dichalcogenides: A Carbon-Analog Approach

Published:Dec 25, 2025 02:30
1 min read
ArXiv

Analysis

This ArXiv article likely presents novel findings in materials science, potentially offering insights into new material properties and applications. The study's focus on metal dichalcogenides and their carbon-analog behavior suggests a focus on innovative material design.
Reference

“The research explores hidden layered structures in metal dichalcogenides.”

PermalinkArXiv
Research#Nuclear Physics🔬 ResearchAnalyzed: Jan 10, 2026 07:36

Fragmentation of Neutron-Rich Carbon Isotopes: Insights from Nuclear Physics Research

Published:Dec 24, 2025 15:16
1 min read
ArXiv

Analysis

This article, sourced from ArXiv, likely presents novel research findings in nuclear physics. The study focuses on the fragmentation of neutron-rich carbon isotopes, a topic crucial for understanding nuclear structure and reactions.
Reference

“The study investigates fragmentation on light targets at 27.5 MeV/nucleon.”

PermalinkArXiv
Research#Planetary Science🔬 ResearchAnalyzed: Jan 4, 2026 07:29

Quantum scattering of hot H/D on CO$_2$: Cross sections and rate coefficients for planetary atmospheres and their evolution

Published:Dec 24, 2025 08:20
1 min read
ArXiv

Analysis

This article reports on research into quantum scattering of hydrogen and deuterium on carbon dioxide, focusing on its relevance to planetary atmospheres. The study likely calculates cross sections and rate coefficients, which are crucial for understanding atmospheric processes and evolution. The use of 'hot' H/D suggests the study considers high-energy collisions, potentially simulating conditions in specific atmospheric layers or during planetary formation. The title clearly indicates the research's focus and its potential applications.
Reference

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PermalinkArXiv
Research#Nuclear Physics🔬 ResearchAnalyzed: Jan 10, 2026 08:15

Glauber Theory Applied to Carbon-12 Nuclear Reactions: A Variational Monte Carlo Analysis

Published:Dec 23, 2025 06:51
1 min read
ArXiv

Analysis

This research applies theoretical physics concepts to analyze nuclear reactions, a highly specialized field. The use of Glauber theory and variational Monte Carlo methods suggests a focus on improving the understanding of nuclear interactions.
Reference

“The research analyzes nuclear reactions on a 12C target.”

PermalinkArXiv
Research#llm🔬 ResearchAnalyzed: Dec 25, 2025 16:13

Welcome to Kenya’s Great Carbon Valley: A Bold New Gamble to Fight Climate Change

Published:Dec 22, 2025 10:00
1 min read
MIT Tech Review

Analysis

This article from MIT Technology Review explores Kenya's ambitious plan to establish a "Great Carbon Valley" near Lake Naivasha. The initiative aims to leverage geothermal energy and carbon capture technologies to create a sustainable industrial hub. The article highlights the potential benefits, including economic growth and reduced carbon emissions, but also acknowledges the challenges, such as the high costs of implementation and the potential environmental impacts of large-scale industrial development. It provides a balanced perspective, showcasing both the promise and the risks associated with this innovative approach to climate change mitigation. The success of this project could serve as a model for other developing nations seeking to transition to a low-carbon economy.
Reference

“The earth around Lake Naivasha, a shallow freshwater basin in south-central Kenya, does not seem to want to lie still.”

PermalinkMIT Tech Review
Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 07:46

Locational Marginal Emissions for Carbon-Aware Data Center Operations in Large-Scale Power Grids

Published:Dec 21, 2025 17:16
1 min read
ArXiv

Analysis

This article likely discusses the application of Locational Marginal Emissions (LME) to optimize data center operations for reduced carbon footprint. It suggests a research focus on how data centers can adapt their energy consumption based on the carbon intensity of the local power grid. The use of LME allows for a more granular and accurate assessment of carbon emissions compared to simpler methods. The scale of the power grids mentioned implies a focus on practical, large-scale implementations.

Key Takeaways

    Reference

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    PermalinkArXiv
    Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 09:34

    Assessing Long-Term Electricity Market Design for Ambitious Decarbonization Targets using Multi-Agent Reinforcement Learning

    Published:Dec 19, 2025 10:56
    1 min read
    ArXiv

    Analysis

    This article focuses on using Multi-Agent Reinforcement Learning (MARL) to design electricity markets that can achieve ambitious decarbonization goals. The use of MARL suggests a complex system modeling approach, likely simulating various market participants and their interactions. The research likely explores different market designs and their effectiveness in reducing carbon emissions while maintaining grid stability and economic efficiency. The source, ArXiv, indicates this is a pre-print or research paper, suggesting a focus on novel methodologies and findings.
    Reference

    “The article likely explores different market designs and their effectiveness in reducing carbon emissions while maintaining grid stability and economic efficiency.”

    PermalinkArXiv
    Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 10:46

    Artificial Intelligence-Enabled Holistic Design of Catalysts Tailored for Semiconducting Carbon Nanotube Growth

    Published:Dec 18, 2025 04:14
    1 min read
    ArXiv

    Analysis

    This article reports on the use of AI to design catalysts for the growth of semiconducting carbon nanotubes. The focus is on a holistic design approach, suggesting a comprehensive and potentially more efficient method compared to traditional catalyst design. The source, ArXiv, indicates this is a pre-print or research paper, implying the findings are preliminary and subject to peer review.
    Reference

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    PermalinkArXiv
    Research#Nanomaterials🔬 ResearchAnalyzed: Jan 10, 2026 10:34

    Multiscale Modeling Reveals Impact of Interlayer Bonds on Carbon Nanostructure Behavior

    Published:Dec 17, 2025 02:58
    1 min read
    ArXiv

    Analysis

    This article discusses cutting-edge research in materials science and computational modeling. The focus on interlayer bonds and their effect on carbon nanostructure deformation and fracture provides valuable insights.

    Key Takeaways

    Reference

    “The research focuses on the influence of interlayer sp3 bonds on the nonlinear large-deformation and fracture behaviors.”

    PermalinkArXiv
    Research#sustainability🔬 ResearchAnalyzed: Jan 4, 2026 07:03

    On the Complementarity of Shared Electric Mobility and Renewable Energy Communities

    Published:Dec 15, 2025 08:56
    1 min read
    ArXiv

    Analysis

    This article, sourced from ArXiv, likely explores the synergistic relationship between shared electric vehicle (EV) systems and communities that utilize renewable energy sources. The focus is on how these two elements can work together to enhance sustainability and efficiency. The analysis would likely delve into the benefits of integrating these systems, such as reduced carbon emissions, lower energy costs, and improved grid stability. The research likely uses data analysis, simulations, or case studies to support its claims.
    Reference

    “The article likely contains specific findings or arguments regarding the benefits of integrating shared electric mobility with renewable energy communities. A specific quote would highlight a key conclusion or a significant finding from the research.”

    PermalinkArXiv
    Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 07:06

    Probabilistic Predictions of Process-Induced Deformation in Carbon/Epoxy Composites Using a Deep Operator Network

    Published:Dec 15, 2025 03:04
    1 min read
    ArXiv

    Analysis

    This article describes a research paper focusing on using a Deep Operator Network to predict deformation in carbon/epoxy composites. The probabilistic nature of the predictions suggests an attempt to account for uncertainties in the manufacturing process. The use of a Deep Operator Network is a key aspect, indicating the application of advanced machine learning techniques to solve a complex engineering problem.
    Reference

    “The article likely details the methodology, results, and implications of using a Deep Operator Network for this specific application.”

    PermalinkArXiv
    Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 08:06

    LLM-Upgraded Graph Reinforcement Learning for Carbon-Aware Job Scheduling in Smart Manufacturing

    Published:Dec 6, 2025 08:53
    1 min read
    ArXiv

    Analysis

    This article presents a research paper exploring the application of Large Language Models (LLMs) to enhance graph reinforcement learning for carbon-aware job scheduling in smart manufacturing. The focus is on optimizing job scheduling to minimize carbon footprint. The use of LLMs suggests an attempt to incorporate more sophisticated reasoning and contextual understanding into the scheduling process, potentially leading to more efficient and environmentally friendly manufacturing operations. The paper likely details the methodology, experimental setup, results, and implications of this approach.
    Reference

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    PermalinkArXiv
    Research#physics🔬 ResearchAnalyzed: Jan 4, 2026 11:58

    Guest metal-driven quantum anharmonic effects on stability and two-gap superconductivity in carbon-boron clathrates

    Published:Dec 5, 2025 07:44
    1 min read
    ArXiv

    Analysis

    This article, sourced from ArXiv, likely presents original research on the effects of guest metals on the stability and superconductivity of carbon-boron clathrates. The title suggests a focus on quantum anharmonic effects, which are deviations from ideal harmonic behavior in quantum systems. The research likely explores how the presence of guest metals influences these effects and, consequently, the material's superconducting properties.

    Key Takeaways

      Reference

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      PermalinkArXiv
      Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 08:08

      From FLOPs to Footprints: The Resource Cost of Artificial Intelligence

      Published:Dec 3, 2025 17:01
      1 min read
      ArXiv

      Analysis

      The article likely discusses the environmental and economic costs associated with training and running large AI models. It probably moves beyond just computational power (FLOPs) to consider energy consumption, carbon emissions, and other resource demands (footprints). The source, ArXiv, suggests a focus on research and a potentially technical analysis.
      Reference

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      PermalinkArXiv
      Research#LLMs👥 CommunityAnalyzed: Jan 10, 2026 15:01

      Mistral AI Releases Environmental Impact Report on LLMs

      Published:Jul 22, 2025 19:09
      1 min read
      Hacker News

      Analysis

      The article likely discusses Mistral's assessment of the carbon footprint and resource consumption associated with training and using their large language models. A critical review should evaluate the methodology, transparency, and the potential for actionable insights leading to more sustainable practices.
      Reference

      “The article reports on Mistral's findings regarding the environmental impact of its LLMs.”

      PermalinkHacker News
      Environmental Science#Artificial Intelligence, Climate Change, Materials Science📝 BlogAnalyzed: Jan 3, 2026 06:26

      AI-Powered Cement Recipe Optimization

      Published:Jun 19, 2025 07:55
      1 min read
      ScienceDaily AI

      Analysis

      This article highlights a promising application of AI in addressing climate change. The core innovation lies in the AI's ability to rapidly simulate and identify cement recipes with reduced carbon emissions. The brevity of the article suggests a focus on the core achievement rather than a detailed explanation of the methodology. The use of 'dramatically cut' and 'far less CO2' indicates a significant impact, making the research newsworthy.
      Reference

      “The article doesn't contain a direct quote.”

      PermalinkScienceDaily AI
      Research#llm📝 BlogAnalyzed: Dec 29, 2025 08:59

      CO² Emissions and Model Performance: Insights from the Open LLM Leaderboard

      Published:Jan 9, 2025 00:00
      1 min read
      Hugging Face

      Analysis

      This article likely discusses the relationship between the carbon footprint of large language models (LLMs) and their performance, as evaluated by the Open LLM Leaderboard. It probably analyzes the energy consumption of training and running these models, and how that translates into CO² emissions. The analysis would likely compare different LLMs, potentially highlighting models that achieve high performance with lower environmental impact. The Hugging Face source suggests a focus on open-source models and community-driven evaluation.
      Reference

      “Further details on specific models and their emissions are expected to be included in the article.”

      PermalinkHugging Face
      Research#llm📝 BlogAnalyzed: Dec 29, 2025 08:11

      Environmental Impact of Large-Scale NLP Model Training with Emma Strubell - TWIML Talk #286

      Published:Jul 29, 2019 18:26
      1 min read
      Practical AI

      Analysis

      This article discusses the environmental impact of training large-scale NLP models, focusing on carbon emissions. It highlights Emma Strubell's research, which examines the energy consumption of deep learning in NLP. The article explores how companies are responding to environmental concerns related to model training. The focus is on the trade-off between model accuracy and environmental impact, and the potential for more efficient and sustainable machine learning practices. The article suggests a growing awareness of the environmental cost of AI development.
      Reference

      “The article doesn't contain a direct quote, but it references Emma Strubell's research on carbon emissions.”

      PermalinkPractical AI
      Environmental Science#Machine Learning for Climate Change📝 BlogAnalyzed: Dec 29, 2025 08:12

      Tracking CO2 Emissions with Machine Learning with Laurence Watson - TWIML Talk #277

      Published:Jun 24, 2019 19:29
      1 min read
      Practical AI

      Analysis

      This article discusses the use of machine learning, specifically computer vision, to track CO2 emissions. It focuses on a conversation with Laurence Watson, CTO of Plentiful Energy and former data scientist at Carbon Tracker. The core of the discussion revolves around Carbon Tracker's goals and their report on using satellite imagery to estimate fossil fuel power plant utilization. The article highlights the application of computer vision to process satellite images of coal plants, including the labeling process, and addresses the challenges associated with the project's scope and scale. This suggests a practical application of AI in environmental monitoring.
      Reference

      “The article doesn't contain a direct quote, but it summarizes the discussion topics.”

      PermalinkPractical AI