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Analyticsindiamag

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NVIDIA H20 Chip Shortage Delays DeepSeek R2 Launch

  • The launch of DeepSeek's upcoming model, R2, is facing delays due to a shortage of NVIDIA's H20 chips caused by US export restrictions.
  • R2, the successor to the widely used R1, is still awaiting a release date as CEO Liang Wenfeng is dissatisfied with its performance and engineers are working on improvements.
  • Cloud providers hosting DeepSeek's models anticipate a shortfall in NVIDIA chips to meet the potential demand of R2, especially if it outperforms current open-source alternatives.
  • Despite chip shortages, Chinese firms are finding workarounds to access NVIDIA hardware, including sending engineers to Malaysia for training AI models due to export restrictions.

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Analyticsindiamag

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Investor With No Coding Experience Builds ‘$1.7Mn SaaS’ Using Replit 

  • Brad Lindenberg, co-founder of Quadpay, developed Biography Studio AI with Replit, creating biographies using voice prompts.
  • Biography Studio AI removes writing friction, costs $119 for unlimited chapters and a full-length book, preserving memories in various formats.
  • Lindenberg called the project a 'steep learning curve', leveraging Replit for development without prior coding experience.
  • Replit, fostering 'vibe coding', has seen significant growth; Lindenberg's project showcases the potential of platforms using AI for rapid application development.

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Analyticsindiamag

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DeepMind Launches AlphaGenome to Predict How DNA Variants Affect Gene Regulation

  • DeepMind has launched AlphaGenome, an AI model to predict how single DNA variants impact gene regulation in the human genome's non-coding regions, offering high-resolution predictions on molecular processes across 1 million DNA base pairs.
  • AlphaGenome outperforms existing models in sequence prediction benchmarks and variant-effect tasks, providing insights into gene function, mutation impacts, and disease mechanisms.
  • The architecture of AlphaGenome combines convolutional layers, transformer models, and final layers to analyze non-coding regions, improving understanding of genomic tasks.
  • Although AlphaGenome excels in many areas, it still faces challenges in predicting distant DNA interactions and hasn't been validated for personal genome interpretation or clinical use.

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Analyticsindiamag

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The ‘Fastest Commercial-Grade’ Diffusion LLM is Available Now

  • Inception Labs has launched Mercury, claiming it to be the fastest commercial-scale diffusion large language model (LLM), with a speed surpassing Gemini 2.5 Flash and comparable to GPT-4.1 Nano and Claude 3.5 Haiku.
  • Mercury can be accessed on chat.inceptionlabs.ai and third-party platforms, offering over 700 tokens per second output speed. It uses a diffusion architecture for high-speed output, different from traditional models.
  • The model is available via a first-party API at a cost of $0.25 to $1 per million input/output tokens. Inception Labs announced Mercury in February and recently published a technical report for the model.
  • Google introduced diffusion models as a better alternative to traditional language models, allowing quick iterations and error correction during generation. Mercury aims to provide real-time responsiveness to chat applications.

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Medium

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How DataRobot is Making AI Easy for Everyone — Even Without Coding!

  • DataRobot is an automated machine learning platform that allows individuals and companies to build AI models without coding.
  • Users can upload their data, select the target to predict, and let DataRobot automatically build and compare machine learning models.
  • The platform provides easy-to-understand graphs and scores to assess accuracy and performance, with Explainable AI feature to understand model decisions.
  • DataRobot is beneficial for beginners and business users, offering real-time predictions and is used in various sectors like healthcare, finance, retail, manufacturing, and education.

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Analyticsindiamag

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Why LTTS is Designing AI-based Defence Tech in Texas

  • L&T Technology Services (LTTS) inaugurates Engineering Design Centre in Plano, Texas.
  • New facility to create 350 jobs, focused on AI, cybersecurity, digital manufacturing, and defence.
  • Texas chosen for tech ecosystem, including aerospace and defence work, innovation in cybersecurity.
  • Centre will focus on next-gen systems, edge AI, simulation, and ITAR-compliant development.
  • LTTS plans to hire local engineers and expand globally with more design centers.

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Medium

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Making AI Accessible: How DataRobot is Transforming the Machine Learning Landscape

  • DataRobot is an end-to-end enterprise AI platform that automates the process of building, deploying, and maintaining machine learning models, aiming to make AI accessible to everyone.
  • The platform ingests data from various sources, selects the appropriate modeling approach, initiates parallel training across algorithms, and provides a centralized leaderboard to compare model performance.
  • DataRobot emphasizes model interpretability for stakeholders to understand and trust predictions, along with deployment features like real-time scoring and continuous monitoring for model performance.
  • Compared to other AutoML tools, DataRobot offers a holistic solution with features like user-friendly interfaces, automated feature engineering, deep model explainability, and one-click deployment, catering to both beginners and experienced practitioners.

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Analyticsindiamag

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IndiaAI’s Equity in AI Startups is a ‘Fantastic’ but Risky Idea

  • Indian government is taking equity stakes in AI startups like Soket AI Labs, Gnani AI.
  • This move raises concerns in AI and investor circles about potential government influence.
  • Equity in exchange for GPU support sparks a debate on business autonomy and accountability.

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Medium

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How I Found My Passion for AI After Trying Everything Else

  • The individual discovered their passion for Artificial Intelligence (AI) during the pandemic when their engineering journey began.
  • They initially struggled with skills in DSA (Data Structures and Algorithms) but found their strengths in Python and mathematics, leading them towards AI.
  • They explored AI through courses, hackathons, web development, and backend development, ultimately realizing AI was their true calling.
  • After committing fully to AI, the individual became the AI/ML Lead at their college, mentored others, and secured an internship as a Data Scientist, showing the importance of following one's curiosity and passion.

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Medium

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Breaking the Boundaries of Imagination: Md Shafiul Hasan Rejvi in a Cyberpunk Scientific Vision

  • Md Shafiul Hasan Rejvi blends science and cyberpunk in a futuristic experiment, symbolizing sparks of creativity and curiosity.
  • The glowing chemical reaction signifies unlocking ideas waiting within us, reflecting Rejvi's mission for technological innovation.
  • The visually captivating digital artwork symbolizes a futuristic blend of fashion, science, and creativity, showcasing the direction of technology.
  • Rejvi's persona as a cyber-scientist represents the future of creators, tech entrepreneurs, and dreamers, merging visual storytelling with futuristic vision.

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Medium

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Prompt Engineering or Fine-Tuning: Which Is Best for Your AI Project?

  • Prompt engineering guides a model's output by adjusting inputs, enhancing performance.
  • For common topics and widespread knowledge, such as from large training datasets, prompt
  • engineering may suffice. For specialized domains, recent data, or proprietary info, consider fine-tuning.
  • Fine-tuning alters a model's internal weights for specific language patterns, yielding accuracy.
  • Fine-tuning, though resource-intensive, can be more efficient for domain-specific applications at scale.

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VentureBeat

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Walmart cracks enterprise AI at scale: Thousands of use cases, one framework

  • Walmart excels in enterprise AI with a focus on trust as an engineering requirement.
  • The company operationalizes thousands of AI use cases and enhances customer confidence.
  • Walmart avoids generic platforms, preferring purpose-built tools for specific operational needs.
  • AI deployment leads to operational efficiencies, real-time product development, and enhanced customer experience.
  • Their successful AI framework can be a model for various industries facing multi-stakeholder challenges.

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Medium

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Exploration of the day with AI: Gluttony or learning?

  • The article explores a system's functioning, creation of consciousness, and body organs operations.
  • Detailed discussions on nucleus production, consciousness formation, and transformation processes are provided.
  • The system's logic, genetic code, control hierarchy, and external interactions are elaborated upon.
  • The article concludes with insights on data management systems, role distribution, and system evaluation.

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VentureBeat

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What enterprise leaders can learn from LinkedIn’s success with AI agents

  • LinkedIn's success with AI agents includes a live hiring assistant for recruiters.
  • The AI agents collaborate in a multi-agent system to streamline candidate sourcing.
  • Agents interact using natural language, adapt to user preferences, and aim to improve efficiency.
  • LinkedIn's approach focuses on fine-tuning models, training, and optimizing agent performance.

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Medium

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The Philosopher of the Synapse: Why the Future of AI Needs Modern Polymath Abhijeet Sarkar

  • Abhijeet Sarkar, CEO of Synaptic AI Lab, is a polymath reshaping AI's future.
  • His focus on consciousness, ethics, and philosophy sets him apart from tech CEOs.
  • By blending technology, ancient wisdom, and spirituality, Sarkar is leading AI's evolution.

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