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🎯 Welcome to DataPro 134
This week’s issue is packed with powerful breakthroughs that are turning developer workflows smarter, sharper, and way more fun to build with. Whether you're wrangling multimodal models, benchmarking LLMs, or debugging AWS workflows inside your IDE, this issue's for you.

Also, two new books just dropped from the Packt Data Science team, and they’re worth your attention:

📘 Architecting Power BI Solutions in Microsoft Fabric
If you're building anything serious with Power BI, this is your 2025 playbook. It's all about scaling, governance, and doing BI right.

📗 Tableau Cookbook for Experienced Professionals
Already know Tableau? This helps you scale it. Real-world recipes for performance, security, and smarter dashboards.

🔧 Top Tools

🔸 Dia-1.6B – Lifelike voice generation with tone & real-time control

🔸 BitNet-1bit – Efficient, low-latency language model from Microsoft

🔸 MAGI-1 – Chunk-based high-quality video generation

🔸 DeepMath-103K – New benchmark for math-savvy models

🔸 OpenAI’s o3 and o4-mini - What They Mean for Data, Tech, and Research Workflows

🔥 What’s Trending

🔸 Build APIs with FastAPI

🔸 Physics meets Finance via PINNs

🔸 Benchmark DeepSeek-R1 with Ollama

🔸 Export MLflow from HPC systems

🚀 Fresh Launches

🔸 NVIDIA's Describe Anything 3B – Region-specific image/video captions

🔸 Meta’s Llama Stack – A full-stack AI dev platform

🔸 Amazon SWE-PolyBench – Real-world coding agent benchmark

🔸 Serverless MCP – AI-assisted AWS debugging in IDEs

🔸 Atla MCP Server – Purpose-built model critique engine

Buckle up. This issue is packed with fresh tools, smarter protocols, and insights from the bleeding edge of DS, ML & Gen AI. Ready to build what’s next? Let’s dive in. 👇

📢 Want to follow along with #100DaysOfMathematicsOfML?

We’re sharing one powerful concept a day from our upcoming book, Mathematics of Machine Learning by Tivadar Danka -covering 100 essential topics that connect math to real-world machine learning.

If you're on LinkedIn and want to stay in the loop, follow our page [Packt DataPro]. You'll get daily insights straight from the book -explained simply, shared practically.

👉 Follow us on LinkedIn and join the journey: Packt DataPro | LinkedIn

#100DaysOfMathematicsOfML | 1 topic a day, 100 days straight

Cheers,

Merlyn Shelley

Growth Lead, Packt

Author Nagaraj Venkatesan

Architecting Power BI Solutions in Microsoft Fabric written by Nagaraj Venkatesan is your roadmap to mastering the platform shift from dashboards to data architecture. Packed with real-world patterns, decisions, and strategies, this book helps BI pros, engineers, and architects build scalable, governed, future-ready solutions in the new world of Microsoft Fabric.

👉 Buy now at Packt

Author Pablo Sáenz de Tejada

Author Daria Kirilenko

Tableau Cookbook for Experienced Professionals written by Pablo Sáenz de Tejada and Daria Kirilenko is for those who've outgrown the basics and need real-world strategies for performance, scale, and governance. With 60+ advanced recipes, it helps analysts and developers turn fragile dashboards into enterprise-ready solutions. Built for those ready to go from good to great in Tableau.

👉 Buy now at Packt

⭕ New developer products provide a glimpse into the future of app building on HubSpot, including deeper extensibility, flexible UI, modern development tools, and more: HubSpot’s AI-powered ecosystem presents a global opportunity projected to reach $10.2 billion by 2028. To fuel that growth potential, we are opening up our platform more –introducing an expanded set of APIs, customizable app UI, and tools that better support a unified data strategy. Learn more.

⭕ [Rubrik Guided Lab] AWS Cloud Native Protection: IBM reports that 82% of breaches involve cloud data. Join Virtual Camp Rubrik: AWS Cloud Protection on April 23 at 10:00 AM PST to learn how to protect and recover AWS workloads like EC2, RDS, and EBS, and explore today’s cloud threat landscape.

⭕nari-labs/Dia-1.6B · Dia is a 1.6B parameter text-to-speech model by Nari Labs that creates lifelike English dialogue from transcripts. It supports tone control, nonverbal cues, voice cloning, and real-time generation, with open-source code and demos available for testing and research.

⭕microsoft/bitnet-b1.58-2B-4T · BitNet b1.58 2B4T is Microsoft’s 2B-parameter native 1-bit language model. It matches full-precision models in accuracy while using less memory, energy, and latency. Optimized for research, it’s best run with specialized C++ code.

⭕sand-ai/MAGI-1 · MAGI-1 is a large-scale autoregressive video generation model that creates high-fidelity, controllable videos chunk-by-chunk. It supports text/image/video inputs, excels in temporal consistency, and runs efficiently via parallel denoising and optimized diffusion-based architecture.

⭕DeepSite - a Hugging Face Space by enzostvs: DeepSite is an AI-powered coding platform by DeepSeek AI, built for developers, data scientists, and engineers. It integrates generative AI into coding workflows to boost creativity, streamline tasks, and accelerate development.

⭕zwhe99/DeepMath-103K · DeepMath-103K is a high-difficulty math dataset designed to advance language models' reasoning skills. It features diverse topics, rich annotations, and decontaminated benchmarks, supporting training of models like DeepMath-Zero-7B and DeepMath-1.5B.

⭕Exporting MLflow Experiments from Restricted HPC Systems: This article outlines a workaround for exporting MLflow experiments from HPC systems with restricted outbound communication. It uses a local MLflow server to log experiments, then transfers and imports the data into a remote MLflow server for tracking.

⭕How to Benchmark DeepSeek-R1 Distilled Models on GPQA Using Ollama and OpenAI’s simple-evals: This article explains how to locally benchmark DeepSeek-R1 distilled models using the GPQA-Diamond reasoning benchmark with Ollama and OpenAI’s simple-evals. It includes setup, evaluation scripts, and analysis of results.

⭕MapReduce: How It Powers Scalable Data Processing: This article explains MapReduce, a distributed computing model for large-scale data processing. It covers its core principles, execution flow, code examples, and evolution into modern frameworks like Spark, emphasizing its impact on scalable computing.

⭕Inside OpenAI’s o3 and o4-mini: What They Mean for Data, Tech, and Research Workflows: OpenAI’s o3 and o4-mini models mark a leap in AI reasoning, combining strategic tool use, multimodal understanding, and autonomous decision-making. Ideal for research, analytics, coding, and business tasks, they enable faster, smarter, and more adaptive workflows.

⭕Building a Personal API for Your Data Projects with FastAPI: This article demonstrates how to build a personal API using FastAPI to expose data or models. It promotes modularity, reusability, and collaboration, making it easier to access and share data logic across notebooks, dashboards, or applications with minimal setup.

⭕When Physics Meets Finance: Using AI to Solve Black-Scholes: This article explores how Physics-Informed Neural Networks (PINNs) can be used to solve the Black-Scholes financial model. It blends physics, finance, and AI, demonstrating a neural network that respects both market data and mathematical theory.

⭕Causal Reasoning and Large Language Models: Opening a New Frontier for Causality. This article shows how large language models, like GPT-3.5 and 4, excel at causal reasoning tasks, outperforming traditional methods. They bridge natural language and formal causal analysis, offering new ways to support decision-making in high-stakes domains like medicine, law, and policy.

⭕MCP Toolbox for Databases (formerly Gen AI Toolbox for Databases) now supports Model Context Protocol (MCP): This post introduces Google Cloud’s MCP Toolbox for Databases, an open-source tool that enables secure, standardized access for AI agents to enterprise databases. It supports multi-agent systems, simplifies development, and integrates with Vertex AI, ADK, and LangGraph for production-ready deployments.

⭕Amazon introduces SWE-PolyBench, a multilingual benchmark for AI Coding Agents: This blog introduces SWE-PolyBench, Amazon’s new multi-language benchmark for evaluating AI coding agents on real-world programming tasks. It improves upon previous benchmarks by expanding to four languages, diversifying task types, and introducing new metrics to assess agents' understanding of complex codebases beyond simple pass/fail accuracy.

⭕Optimizing cost for using foundational models with Amazon Bedrock: This blog outlines cost optimization strategies for using foundation models on Amazon Bedrock. It covers flexible pricing options, efficient model selection, use of Knowledge Bases, prompt caching, model distillation, and automated reasoning, all aimed at helping developers balance performance with affordability in generative AI applications.

⭕10 Awesome MCP Servers: This blog highlights 10 standout Model Context Protocol (MCP) servers that enable AI models like Claude to interact with various systems, from local files and Slack to Google Drive, Spotify, Notion, and even Windows controls, unlocking powerful, real-world functionality for personal, professional, and creative applications.

⭕NVIDIA AI Releases Describe Anything 3B: A Multimodal LLM for Fine-Grained Image and Video Captioning: NVIDIA's Describe Anything 3B (DAM-3B) is a multimodal large language model designed for fine-grained image and video captioning. Using focal prompts and a localized vision backbone, it generates detailed region-specific descriptions, outperforming leading models across seven benchmarks and enabling new capabilities in vision-language tasks.

⭕Meta AI Releases the First Stable Version of Llama Stack: A Unified Platform Transforming Generative AI Development with Backward Compatibility, Safety, and Seamless Multi-Environment Deployment: Meta AI’s Llama Stack 0.1.0 is a unified platform for generative AI development, offering backward compatibility, safety features, and multi-environment deployment. It simplifies building production-ready applications with modular tools for inference, RAG, agents, and monitoring, eliminating vendor lock-in while supporting local, cloud, and edge deployments.

⭕Atla AI Introduces the Atla MCP Server: A Local Interface of Purpose-Built LLM Judges via Model Context Protocol (MCP): Atla AI’s new MCP Server offers a local, standards-based interface to its Selene evaluation models, designed to score and critique LLM outputs. Built on the Model Context Protocol (MCP), it enables seamless integration into tools like Claude Desktop and OpenAI Agents SDK, supporting reproducible, multi-criteria model assessments.

⭕Serverless MCP Brings AI-Assisted Debugging to AWS Workflows Within Modern IDEs: Serverless MCP integrates AI-assisted debugging directly into IDEs like Cursor, streamlining the development of AWS serverless applications. By surfacing logs, metrics, and infrastructure insights contextually, it helps developers debug Lambda, API Gateway, DynamoDB, and IAM issues without leaving their code, improving speed, clarity, and workflow efficiency.