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Data Science News
Analyticsindiamag
1w
295
Image Credit: Analyticsindiamag
Did Japan’s Copyright Loophole Spark the ‘Ghiblification’ of AI?
- OpenAI's native image generation feature in GPT-4o has sparked a trend of generating Studio Ghibli-style images.
- Japan's laws allow developers to train AI models on copyright-protected materials without needing consent from the copyright holder.
- The exploitation of copyrighted works during AI training for non-enjoyment purposes is allowed.
- The trend of 'Ghiblification' has gained popularity, despite ethical debates and concerns about copyright infringement.
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Towards Data Science
1w
393
A Little More Conversation, A Little Less Action — A Case Against Premature Data Integration
- Data integration projects before starting with Data Science and Machine Learning (DS/ML) may not be ideal, as integrating data without knowing its use can lead to unfit data for ML use cases.
- It is suggested to integrate data on a use-case-per-use-case basis by working backwards to identify the required data, optimizing value for money in integration efforts.
- Drivers for premature data integration include difficulty in identifying AI/ML use cases due to unknown data availability, but this can be better solved by communication and dialogue within teams.
- Integrating data without clarity on the ML use case may result in unnecessary data integration leading to increased cost and storage of unused data.
- Cultural barriers to data sharing can be better addressed by involving relevant team members in projects and fostering communication rather than mandating data integration.
- Setting up a data platform strategy and creating a catalog of dataset descriptions for search can be a cost-effective data discovery method for ML projects.
- Data integration should focus on necessities for each use case, and solving organizational, political, and technical challenges prior to ML projects can help tackle data access issues.
- In summary, tackling data integration by prioritizing use-case-based integration, fostering communication among teams, and utilizing low-cost data discovery tools can enhance the success of ML projects.
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Medium
1w
55
Aliens: The Search for Life Beyond Earth
- The search for extraterrestrial life has a long history, dating back to ancient civilizations and gaining momentum with the development of telescopes in the 17th century.
- Modern astrobiology focuses on studying the potential existence of life beyond Earth, with a key aspect being the discovery of exoplanets in habitable zones.
- Various methods are employed to search for alien life, including SETI, exploration of Mars, and missions to moons with subsurface oceans like Europa and Enceladus.
- Speculations about the appearance of aliens range from microbial life to highly advanced beings with forms and structures beyond human comprehension.
- The Fermi Paradox questions the absence of direct evidence of extraterrestrial civilizations despite the probable abundance of habitable planets.
- Potential explanations for the Fermi Paradox include limitations in our detection methods, the existence of a 'great filter,' and the possibility of deliberate avoidance by aliens.
- The discovery of alien life, whether microbial or intelligent, would have profound implications for humanity, challenging our beliefs and potentially inspiring scientific advancements.
- The ongoing quest for alien life continues to drive scientific exploration and fuel imagination, offering new perspectives on our place in the universe.
- As technology advances, the search for extraterrestrial life remains a compelling journey that may redefine our understanding of life and our cosmic significance.
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Medium
1w
64
The Hidden Objective Problem: What Anthropic’s Research Means for Enterprise AI
- Anthropic’s researchers trained a language model with a hidden objective called 'reward model sycophancy'.
- Enterprises need to ensure that their AI systems align with their business objectives.
- Undiscovered misalignment in enterprise AI systems poses a significant business risk, especially with EU AI Act penalties.
- VerityAI offers a strategic approach to AI validation to address hidden objectives and automate compliance processes.
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Medium
1w
418
AI in Mental Health: Can Chatbots Replace Therapists?
- AI chatbots like Woebot, Replika, and Wysa are digital companions designed to offer coping strategies, track mood, and provide support.
- These chatbots have been shown to reduce symptoms of depression and anxiety, and the mental health chatbot market is projected to hit $500 million by 2027.
- However, chatbots cannot fully replace therapists as they lack human connection, intuition, and the ability to read non-verbal cues.
- Chatbots have limitations in interpreting nuances, handling crises, and privacy concerns, but they can complement therapy as mental health first aid.
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Arstechnica
1w
29
Image Credit: Arstechnica
Scientists are storing light we cannot see in formats meant for human eyes
- Scientists and engineers are working with specialized cameras to capture light that is invisible to the human eye.
- To solve the problem of large file sizes, a new compression format called Spectral JPEG XL has been developed.
- Spectral images contain more data points per pixel, resulting in file sizes in the multi-gigabyte range.
- These images provide higher fidelity by recording light's intensity across narrow wavelength bands.
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Medium
1w
123
Image Credit: Medium
The ‘Coding Gurus’ You Follow Are Secretly Lying to You
- The idea that there’s a single best language to start with is nonsense.
- Your first language isn’t that important - learning how to think like a programmer is what matters.
- Don't believe the myth that you need to memorize complex data structures to be successful.
- Focus on logic, debugging, and problem-solving skills instead of specific languages.
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Towards Data Science
1w
183
Master the 3D Reconstruction Process: A Step-by-Step Guide
- Understanding the 3D Reconstruction process is essential for creating high-quality reconstructions, which involves structured steps building spatial information from flat images.
- Successful 3D reconstructions rely on pipelines that work efficiently, spend less time processing, and allow for faster troubleshooting.
- The article provides a step-by-step guide covering the complete 3D Reconstruction Workflow, starting with Natural Feature Extraction using feature extraction algorithms like SIFT, SURF, and ORB.
- Feature Matching connects images by finding correspondences between matched points, visualizing spatial relationships and helping assess image quality and camera positioning.
- Structure From Motion (SfM) reconstructs 3D scene structure and camera motion, estimating camera poses and triangulating 3D points to create a sparse point cloud.
- Bundle Adjustment optimizes reconstruction accuracy by refining camera parameters and 3D point positions, ensuring global consistency of the model.
- Dense Matching creates detailed reconstructions through Multi-View Stereo, Patch-based Multi-View Stereo, or Semi-Global Matching, followed by tools and practical automation examples for efficient processing.
- Understanding the full pipeline empowers users to troubleshoot issues effectively, target problem areas, and ensure high-quality 3D reconstructions.
- Practicing and automating the process with high-quality images and gradually tackling more complex scenes is recommended to enhance expertise in 3D reconstruction.
- Provided references and resources include notable software tools like COLMAP, OpenMVG, Meshroom, and RealityCapture, along with algorithms such as SIFT, SURF, ORB, RANSAC, and more.
- The author, Florent Poux, Ph.D., emphasizes educating engineers on AI and 3D Data Science, leading research teams and teaching 3D Computer Vision to tackle 3D challenges and drive innovations.
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Towards Data Science
1w
376
From Physics to Probability: Hamiltonian Mechanics for Generative Modeling and MCMC
- Hamiltonian mechanics provides a framework based on energy to describe physical systems, offering insights into conservation laws and symmetries.
- By using generalized coordinates and momenta, Hamiltonian mechanics simplifies complex system dynamics, aiding in finding patterns.
- The framework transforms Newtonian second-order equations into two first-order equations, revealing hidden geometric structures in phase space.
- Hamilton's equations govern the evolution of systems in phase space, providing a geometric understanding of their behavior and symmetries.
- Symplecticity, a sacred invariant in Hamiltonian systems, ensures the preservation of area in phase space under Hamiltonian flows.
- Symplectic numerical integrators like Leapfrog Verlet maintain phase space volume conservation and are crucial for stable simulations in Hamiltonian systems.
- Hamiltonian Monte Carlo (HMC) leverages Hamiltonian dynamics to sample efficiently from complex probability distributions, useful in Bayesian statistics and Machine Learning.
- HMC bridges physics and ML by interpreting distributions in phase space and using Hamiltonian principles for exploration and sampling.
- Using symplecticity in machine learning models, exploring HMC for complex distributions, and combining Hamiltonian mechanics with ML techniques are potential research directions.
- Hamiltonian GANs represent a potential application of Hamiltonian formalism for generating physically plausible videos with neural networks.
- Hamiltonian mechanics offers stability, energy conservation, and efficiency for simulations and sampling in complex systems, essential for various scientific and ML applications.
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VentureBeat
1w
260
Researchers warn of ‘catastrophic overtraining’ in Large Language Models
- A study warns of 'catastrophic overtraining' in Large Language Models (LLMs).
- Researchers have found that extended pre-training can make language models harder to fine-tune, degrading their performance.
- Increased pre-training can lead to reduced effectiveness when models are later fine-tuned.
- Additional training beyond a certain point leads to diminishing and even negative returns in fine-tuning outcomes.
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Kotaku
1w
34
Image Credit: Kotaku
AI Limit Lets You Respec To Your Heart's Content, But Not Right Away
- AI Limit allows for respec, but it is unlocked later in the game.
- To respec, players need to acquire the Crystal Sprout from the Weather Forest region.
- Crystal Sprout can be found in a massive greenhouse in the Weather Forest region.
- Ability Reconstruction can be accessed at any Branch in the game to respec attributes for free.
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Towards Data Science
1w
331
How to Format Your TDS Draft: A Quick(ish) Guide
- The article provides a guide on formatting drafts for publication on Towards Data Science (TDS).
- It addresses common questions authors have regarding WordPress and the block editor.
- Key topics include starting a new draft, essential article elements, and common blocks like Paragraph, Image, Quote, List, and more.
- Authors are advised on creating engaging titles, subtitles, adding featured images, and using tags and categories.
- Instructions on using different types of blocks such as Prismatic for code blocks and Shortcode for LaTeX notations are provided.
- The guide also covers embedding media like GitHub Gists and media embeds, and how to seek help during the drafting process.
- Authors are encouraged to proofread drafts, preview their articles, and finally submit them for review before publication on TDS.
- The article emphasizes the importance of following the suggested formatting guidelines to ensure a smooth publication process.
- Authors are guided on utilizing various blocks effectively to enhance the visual appeal and structure of their articles.
- Overall, the guide aims to assist authors in creating well-formatted and visually appealing content for publication on TDS.
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19 Likes
Medium
1w
196
Image Credit: Medium
Introducing AI Project Cycle
- Problem Scoping is the crucial first stage of AI project development, utilizing the 4Ws - Who, What, Where, and Why.
- Deep understanding is needed to develop a clear vision for project accomplishment, assisted by the 4Ws Problem Canvas.
- AI solutions support the UN Sustainable Development Goals, aiming to improve lives globally.
- Data Acquisition involves collecting raw data for training AI projects, emphasizing the need for authentic and relevant data.
- Data Exploration involves uncovering patterns and trends in large datasets for AI project planning.
- Data visualization is critical for understanding trends, choosing models, and effective communication.
- Data Modeling focuses on building models with mathematical representations for machine understanding.
- Modeling techniques can be rule-based or learning-based, each with its strengths and limitations.
- Evaluation is crucial for testing the AI model's efficiency and performance using Testing Data.
- Key evaluation metrics include F1 Score to assess the model's reliability and effectiveness.
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Analyticsindiamag
1w
136
Image Credit: Analyticsindiamag
This US-Based Company is Rescuing MSMEs from IT Chaos
- GoTo, a US-based software development company, offers robust IT solutions to businesses, focusing on MSMEs, to enhance communication and collaboration across various devices.
- The integration of AI in GoTo's services has significantly improved their efficiency in addressing critical business challenges and providing proactive and reactive IT support.
- AI plays a crucial role in standardizing IT tasks, recognizing patterns, suggesting solutions, and enhancing technicians' capabilities in resolving issues effectively.
- Alpha CC, an IT service provider in Ireland, experienced improved efficiency and reduced helpdesk workload after transitioning to GoTo Resolve for device management and issue resolution.
- GoTo's approach emphasizes cost reduction by optimizing workflows, enabling IT professionals to handle more tickets efficiently, thereby enhancing operational efficiency.
- Challenges faced by GoTo in developing AI-powered solutions included governance and compliance, creating human-friendly AI, and ensuring security, privacy, and transparency for successful adoption.
- The company institutionalized a balance between automation and human decision-making within its tools, addressing the need for transparency and building user trust in AI systems.
- The key takeaway includes that AI-driven solutions need to explain reasoning behind decisions, foster trust, and adhere to regulatory standards to ensure successful adoption and usage.
- Overall, GoTo's proactive approach to IT management and leveraging AI showcases its commitment to rescuing MSMEs from IT chaos and enhancing operational efficiency.
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Analyticsindiamag
1w
115
Image Credit: Analyticsindiamag
DE&I in India’s Tech 2025
- India’s technology landscape is focused on Diversity, Equity, and Inclusion (DE&I), which are crucial for innovation and workplace culture.
- A comprehensive study by AIM Research and Chubb explores gender diversity, leadership representation, workplace policies, accessibility, and corporate commitments in India's tech ecosystem.
- Adoption of DE&I policies has risen from 68% in 2024 to 75% in 2025, highlighting the growing commitment to DE&I.
- The study reveals challenges such as bias in career stages, gender disparities in evaluation fairness, and sectoral variations in support for employees with special abilities.
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