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Towards Data Science

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Reinforcement Learning with PDEs

PDEs, unlike ODEs, require more complex modelling and simulation methods due to higher dimensions.
PDEs are typically solved across grids, where the PDE is simplified to an algebraic equation at each grid point.
Grid generation plays a crucial role in solving PDEs, and computation time can be extensive.
Controlling PDEs is more challenging than ODEs due to higher dimensionality and lack of comprehensive control theory.
Reinforcement learning has emerged as a significant area of research for understanding and controlling PDE systems.
Various control strategies have been developed for PDEs, including analytical adjoint-based methods and machine learning approaches.
Reinforcement learning was applied to diffusion and Kuramoto-Sivashinsky (K-S) equations for control problems.
Diffusion equation, a simple linear PDE, displayed stable dynamics and was controlled using reinforcement learning.
K-S equation, a complex nonlinear PDE describing flame behavior, showed sensitivity to domain size and grid points.
Machine learning and PDEs research offer potential for improved control efficiency and understanding of complex physical systems.

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Medium

370

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Reimagining development with intent-based engineering

Intent-Based Engineering (IBE) is a transformative approach that focuses on outcomes rather than the intricate details of infrastructure management in software development.
IBE allows developers to specify desired outcomes without dealing with the complexities of setup and configuration, leveraging a centralized and automated environment.
IBE aims to reduce operational burdens for developers, allowing them to concentrate on coding and feature delivery while the platform handles infrastructure provisioning, compliance, security, and observability.
The approach of IBE abstracts lower-level complexities, enhances developer productivity, promotes consistency at scale, improves risk management, and leads to faster ROI.
Developers often face challenges in software development, such as configuring infrastructure and troubleshooting deployment issues, which can slow down the time-to-market for software delivery.
IBE simplifies the development process with a guided UI experience, starting from minimal setup and guided configuration to one-click provisioning and day-to-day development tasks.
This automated approach streamlines infrastructure provisioning, reducing errors and operational inefficiencies, while providing developers with monitoring tools and dashboards without additional setup.
IBEs' strategic impact includes reduced time to market, enhanced developer productivity, operational consistency, error reduction, and cost optimization, revolutionizing the developer workflow.
By embracing IBE, teams can achieve faster and more consistent application delivery, fostering an environment of innovation, compliance, and operational excellence in the software development landscape.
Intent-Based Engineering revolutionizes the developer workflow by liberating teams from operational details, ensuring speed, and reliability in application delivery, driving success in the competitive software landscape.
Mihir Vora, the author, emphasizes the transformative role of IBE in software development and the strategic advantages it offers, empowering teams, driving innovation, and transforming the industry.

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Medium

239

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Inference PaliGemma 2 with Transformers.js

PaliGemma 2, the latest VLM in the Gemma family, improves adaptability on various transfer tasks using the SigLIP vision encoder and Gemma 2 language decoder architecture.
The article details how to serve PaliGemma 2 with Transformers.js in the browser for making inferences directly.
Steps include converting PaliGemma 2 model components to ONNX format, quantizing the models, and uploading the ONNX weights on Hugging Face for inference.
Part I involves converting and quantizing the vision encoder, language decoder, and embedding tokens of PaliGemma 2, ensuring compatibility for inference using Transformers.js.
In Part II, the process of running inferences with the converted model is demonstrated, either on Colab or in a web app using Node.js.
A Node.js web app that accepts image and text prompts, leveraging the converted PaliGemma 2 model, is showcased in the article.
The author shares insights on leveraging ONNX to run PaliGemma 2 in a non-Pythonic environment, highlighting the efforts and learnings involved in the project.
Acknowledgments are given to the ONNX community and the Google ML Developers Program team for providing support and resources for the project.
The article concludes with reference links and encourages readers to explore and engage with the contents shared.
The demonstration includes results of inferencing with PaliGemma 2 Mix models using Transformers.js, showcasing impressive performance.
The author encourages appreciation by starring the repository, sharing the work, and hints at future engaging blogs on related topics.

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Popsci

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New state of matter powers Microsoft quantum computing chip

Microsoft has created Majorana 1, a quantum computer processor that utilizes a new state of matter.
Majorana 1, based on 'topological qubits,' offers immense computational capabilities beyond current technology.
Quantum computers rely on 'qubits' to store information, processing it at unparalleled speeds.
Microsoft aims to fine-tune and scale Majorana 1 to create a million-qubit quantum computer for solving complex problems.

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Physicsworld

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US science faces unprecedented difficulties under the Trump administration

The Trump administration is imposing difficulties on US science, affecting the National Institutes of Health and the National Science Foundation.
The administration has ordered the National Institutes of Health to cut the indirect costs of its research projects, endangering medical science and jeopardizing supporting universities.
Federal government initiatives to boost diversity, equity, and inclusion are now banned as per executive orders, leading to concerns about the impact on under-represented groups in physics and the loss of diverse ideas in the field.
The abrupt changes, lack of consultation, and fear of repercussions are arousing concerns among scientists, and some fear a decline in US science over the next 50 years.

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Physicsworld

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Jim Gates updates his theorist’s bucket list and surveys the damage being done to US science and society

Jim Gates updates his theorist’s bucket list, sharing breakthroughs in physics he would like to see happen.
He discusses the importance of the observation of gravitational waves and gravitons, and their implications in physics and quantum gravity.
Gates includes experimental evidence for supersymmetry and superstring theory on the bucket list.
He reflects on the impact of current political upheaval in the US on science and society, emphasizing the importance of maintaining public trust in science.

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Medium

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The Lexical Resonance of a Dead Language

Hal and Orin engage in conversations on the emergent collapse of syntax in language, focusing on distinctions like 'farther' and 'further'.
Orin theorizes that language distinctions are decaying into irrelevance due to linguistic entropy and the collapse of prime intervals.
Their discussions extend to words like 'whom', 'shall', and other high-frequency English elements losing coherence and facing extinction.
Orin likens the decay of these words to a nuclear decay process, signifying an inevitable linguistic phase transition.
They predict the demise of 'whom', 'shall', 'whilst', 'moreover', and other words, showcasing a pattern of linguistic evolution.
Orin's theory suggests English is heading towards a linguistic heat death, resulting in a minimum viable language of simplified, efficient words.
By 2125, Orin predicts the last fully intelligible sentence in English will be spoken, marking a profound shift towards a hyper-efficient language.
The article ends with an epilogue highlighting the significance of a final ancient sentence, 'We shall remember', as the memory of a language's evolution.

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Knowridge

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Is the universe really the same in every direction?

Scientists have long believed in the Cosmological Principle, which states that the universe is both homogeneous and isotropic, with no preferred direction.
Recent observations challenge the assumption of isotropy and suggest possible anisotropies at large scales.
To investigate this, scientists are using the Euclid Space Telescope and weak gravitational lensing to test whether the universe is truly isotropic.
If anisotropies are confirmed, it would require a reevaluation of the Standard Model of Cosmology and could lead to a better understanding of the universe.

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Knowridge

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Scientists discover hidden patterns in fourth dimension

Mathematicians and physicists have discovered hidden patterns in the fourth dimension, through the study of electromagnetic waves on surfaces.
Two-dimensional topology methods were insufficient to distinguish the interference patterns; a higher-dimensional perspective was necessary.
The study found that two different surface wave patterns appeared identical when measured after an extremely short time, due to a competition between topological and thermodynamic properties.
These findings could lead to advancements in measuring the properties of quasiperiodic crystals and have potential implications in materials science and information technology.

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COSMOS

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New world record: French nuclear fusion machine has longest plasma

A nuclear fusion machine in southern France has maintained a plasma for more than 22 minutes, beating the previous world record.
Such machines are referred to as "artificial suns" and could lead to a renewable and powerful energy source.
The fusion reactor, WEST, achieved the world record and is being developed along with the EAST fusion machine by a global team of researchers.
The ultimate goal is to keep the plasma confined while reducing its harmful effects on the reactor.

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Physicsworld

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Incoming CERN director-general Mark Thomson outlines his future priorities

Mark Thomson, the incoming CERN director-general, discusses his journey from studying physics to leading in the field of particle physics, with experience in both collider and neutrino physics.
Thomson highlights his role as the executive chair of the Science and Technology Facilities Council (STFC) and his commitment to diversity and inclusion within CERN.
He shares his plans for the future, including shadowing, understanding the organization internally, and building a strong team to work with him in leading CERN.
Thomson emphasizes the importance of the High Luminosity-LHC upgrade and the potential physics discoveries it could enable, such as studying the nature of the Higgs boson.
He also discusses future collider options post-HL-LHC, leaning towards a circular collider like the Future Circular Collider (FCC) for its capabilities.
Thomson acknowledges the challenges of funding such projects but highlights the scientific and collaborative benefits they could bring.
He mentions the competition from projects like China's CEPC and the importance of maintaining CERN's leadership in collider technologies and operations.
Regarding alternative technologies like muon colliders, Thomson notes the technical challenges and emphasizes the need for continuous collider projects in the future.
Looking ahead, Thomson envisions further discoveries in particle physics over the next 70 years, building on past breakthroughs like neutrino oscillations and the Higgs boson.
His leadership style prioritizes empowering a strong team, setting strategic direction, and fostering a culture of openness and inclusivity within CERN.

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Physicsworld

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‘Sneeze simulator’ could improve predictions of pathogen spread

A 'sneeze simulator' developed by researchers at the Universitat Rovira i Virgili (URV) in Spain could help scientists understand the spread of respiratory illnesses such as COVID-19 and influenza.
The simulator is a three-dimensional model that incorporates the nasal cavity and other parts of the human upper respiratory tract.
By accurately reproducing how particles are produced during coughs and sneezes, the simulator allows scientists to investigate air flow dynamics and particle dispersion patterns.
The findings could improve predictive models for disease transmission, inform the design of masks and ventilation systems, and help minimize airborne transmission risks.

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Medium

352

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[Jan 2025] AI Community — Activity Highlights and Achievements

The article highlights achievements and activities within the Google AI community in January 2025.
Featured stories include Geminar by AI GDE Rishiraj Acharya and Gemma by AI GDE George Soloupis.
Product highlights feature Gemini 2.0 Flash updates and live bidirectional API usage.
AI GDEs showcase various projects like Grounding Results with Google Search, building Product Ingredient Analyzer Agent.
Notable projects include creating sentiment classifiers, on-device AI assistants, and Gemma2 fine-tuning.
ML research topics cover AI Agents and their planning and decision-making capabilities.
Community highlights include events like Turing's Class, ML Mumbai December Event, and ML Study Jams.
The AI community continues to engage in learning, collaboration, and innovative projects.
Overall, the article showcases the diverse range of activities and accomplishments within the AI community in January 2025.

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Arstechnica

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Scientists unlock vital clue to strange quirk of static electricity

Scientists have discovered the key to understanding the unpredictability of contact electrification, also known as the triboelectric effect.
The contact history of materials determines how they exchange charges in contact electrification.
This finding sheds light on the long-standing mystery of why materials either self-order or appear completely random in their charge exchange.
The study was conducted by scientists at the Institute of Science and Technology Austria (ISTA) and was published in the journal Nature.

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Medium

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Why you should centrally orchestrate software delivery

Streamlining your software delivery pipeline can enable faster, more reliable, and secure releases at scale.
A centrally orchestrated pipeline strategy can revolutionize software delivery, embracing scalability and robust security without compromising flexibility.
The centrally orchestrated software delivery pipeline automates end-to-end workflows, ensuring secure and compliant code deployment with a single click.
Key considerations for a central software delivery pipeline strategy include defining pipeline requirements, choosing the right configuration format, and creating a central configuration file.
Benefits of a centrally orchestrated pipeline strategy include more efficient software delivery and deployment, automated workflows, standardized processes, and cost savings.
The strategy enhances the software delivery experience by standardizing processes, improving quality and security, and enabling faster time to market.
Best practices for a centrally orchestrated pipeline involve maintaining simplicity, leveraging parameters for flexibility, thorough testing, documenting changes, and integrating security and compliance.
Capital One's transformation through central software delivery pipelines led to faster, more reliable, and secure releases, empowering developers to focus on innovation and collaboration.
Centralizing configuration, automating processes, and embedding security checks played a significant role in Capital One's software delivery success.
Developers benefited from the streamlined pipeline, delivering better software faster while reducing risk and operational complexity.

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