2025

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F1 Score: A Key Metric in LLM Evaluation

Data Science Dojo

Evaluating the performance of Large Language Models (LLMs) is an important and necessary step in refining it. LLMs are used in solving many different problems ranging from text classification and information extraction. Choosing the correct metrics to measure the performance of an LLM can greatly increase the effectiveness of the model. In this blog, we will explore one such crucial metric the F1 score.

AI 418
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$200M HPC Data Center for AI in Wisconsin Launched by DPO and Billerud

insideBIGDATA

NEW YORK,Jan. 23, 2025 — Digital Power Optimization, Inc. (“DPO”), a developer and operator of power-dense data centers, today announced it has secured land and a power supply to develop a $200 millionhigh-performance computing facility inWisconsin Rapids, WI. This project will enable up to 20 megawatts of AI computing.

AI 459
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Inductive biases of neural network modularity in spatial navigation

ML @ CMU

TL;DR: The brain may have evolved a modular architecture for daily tasks, with circuits featuring functionally specialized modules that match the task structure. We hypothesize that this architecture enables better learning and generalization than architectures with less specialized modules. To test this, we trained reinforcement learning agents with various neural architectures on a naturalistic navigation task.

AI 340
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Serve Machine Learning Models via REST APIs in Under 10 Minutes

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Serve Machine Learning Models via REST APIs in Under 10 Minutes Stop leaving your models on your laptop.

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Precision in Motion: Why Process Optimization Is the Future of Manufacturing

Speaker: Jason Chester, Director, Product Management

In today’s manufacturing landscape, staying competitive means moving beyond reactive quality checks and toward real-time, data-driven process control. But what does true manufacturing process optimization look like—and why is it more urgent now than ever? Join Jason Chester in this new, thought-provoking session on how modern manufacturers are rethinking quality operations from the ground up.

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Introducing Agent Bricks: Auto-Optimized Agents Using Your Data

databricks

Skip to main content Login Why Databricks Discover For Executives For Startups Lakehouse Architecture Mosaic Research Customers Customer Stories Partners Cloud Providers Databricks on AWS, Azure, GCP, and SAP Consulting & System Integrators Experts to build, deploy and migrate to Databricks Technology Partners Connect your existing tools to your Lakehouse C&SI Partner Program Build, deploy or migrate to the Lakehouse Data Partners Access the ecosystem of data consumers Partner Solutions

Analytics 348
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Normalizing Flows are Capable Generative Models

Machine Learning Research at Apple

Normalizing Flows (NFs) are likelihood-based models for continuous inputs. They have demonstrated promising results on both density estimation and generative modeling tasks, but have received relatively little attention in recent years. In this work, we demonstrate that NFs are more powerful than previously believed. We present TarFlow: a simple and scalable architecture that enables highly performant NF models.

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New Threads Needed To Weave Stronger Integration Layer For AI Data

Adrian Bridgwater for Forbes

Data integration at a deep iPaaS level can help feed AI services with the right data, the correct langauge models and the most relevant information sources.

AI 351
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Evaluating Long-Context Question & Answer Systems

Eugene Yan

eugeneyan Start Here Writing Speaking Prototyping About Evaluating Long-Context Question & Answer Systems [ llm eval survey ] · 28 min read While evaluating Q&A systems is straightforward with short paragraphs, complexity increases as documents grow larger. For example, lengthy research papers, novels and movies, as well as multi-document scenarios.

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Building a Medical Chatbot with Gemini 2.0, Flask and Vector Embedding

Analytics Vidhya

In the era of AI, chatbots have revolutionized how we interact with technology. Perhaps one of the most impactful uses is in the healthcare industry. Chatbots are able to deliver fast, accurate information, and help individuals more effectively manage their health. In this article, we’ll learn how to develop a medical chatbot using Gemini 2.0, […] The post Building a Medical Chatbot with Gemini 2.0, Flask and Vector Embedding appeared first on Analytics Vidhya.

Analytics 291
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Inside the LLM system that reads emails like a cybersecurity analyst

Dataconomy

Phishing emails, those deceptive messages designed to steal sensitive information, remain a significant cybersecurity threat. As attackers devise increasingly sophisticated tactics, traditional detection methods often fall short. Researchers from the University of Auckland, have introduced a novel approach to combat this issue. Their paper, titled “ MultiPhishGuard: An LLM-based Multi-Agent System for Phishing Email Detection ,” authored by Yinuo Xue, Eric Spero, Yun Sing Koh, and Gi

AI 186
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Airflow Best Practices for ETL/ELT Pipelines

Speaker: Kenten Danas, Senior Manager, Developer Relations

ETL and ELT are some of the most common data engineering use cases, but can come with challenges like scaling, connectivity to other systems, and dynamically adapting to changing data sources. Airflow is specifically designed for moving and transforming data in ETL/ELT pipelines, and new features in Airflow 3.0 like assets, backfills, and event-driven scheduling make orchestrating ETL/ELT pipelines easier than ever!

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What Is Agentic AI? A Gateway to Building Smarter and Autonomous Agents

Data Science Dojo

It is easy to forget how much our devices do for us until your smart assistant dims the lights, adjusts the thermostat, and reminds you to drink water, all on its own. That seamless experience is not just about convenience, but a glimpse into the growing world of agentic AI. Whether it is a self-driving car navigating rush hour or a warehouse robot dodging obstacles while organizing inventory, agentic AI is quietly revolutionizing how things get done.

AI 343
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Multiverse Says It Compresses Llama Models by 80%

insideBIGDATA

Donostia, Spain April 8, 2025 Multiverse Computing today released two new AI models compressed by CompactifAI, Multiverse’s AI compressor: 80 percent compressed versions of Llama 3.1-8B and Llama 3.3-70B.

AI 433
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Muvera: Making multi-vector retrieval as fast as single-vector search

Hacker News

Jump to Content Research Research Who we are Back to Who we are menu Defining the technology of today and tomorrow. Philosophy We strive to create an environment conducive to many different types of research across many different time scales and levels of risk. Learn more about our Philosophy Learn more Philosophy People Our researchers drive advancements in computer science through both fundamental and applied research.

Algorithm 179
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10 GitHub Repositories for Mastering Agents and MCPs

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 10 GitHub Repositories for Mastering Agents and MCPs Learn how to build your own agentic AI application with free tutorials, guides, courses, projects, example code, research papers, and more.

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Whats New in Apache Airflow 3.0 –– And How Will It Reshape Your Data Workflows?

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

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Announcing Lakeflow Designer: No-Code ETL, Powered by the Databricks Intelligence Platform

databricks

We’re excited to announce Lakeflow Designer, an AI-powered, no-code pipeline builder that is fully integrated with the Databricks Data Intelligence Platform.

ETL 309
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Understanding Aggregate Trends for Apple Intelligence Using Differential Privacy

Machine Learning Research at Apple

At Apple, we believe privacy is a fundamental human right. And we believe in giving our users a great experience while protecting their privacy. For years, weve used techniques like differential privacy as part of our opt-in device analytics program. This lets us gain insights into how our products are used, so we can improve them, while protecting user privacy by preventing Apple from seeing individual-level data from those users.

Analytics 353
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5 Common Mistakes to Avoid When Training LLMs

Machine Learning Mastery

Introduction Training large language models (LLMs) is an involved process that requires planning, computational resources, and domain expertise. Data scientists, machine learning practitioners, and AI engineers alike can fall into common training or fine-tuning patterns that could compromise a model’s performance or scalability.

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10 GitHub Awesome Lists for Data Science

Flipboard

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 10 GitHub Awesome Lists for Data Science Most popular educational resource list on GitHub for Python, R, SQL, analytics, machine learning, datasets, and more.

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

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The Democratization Of Graph Data For Business Users

Adrian Bridgwater for Forbes

Newsletters Games Share a News Tip Featured Featured Breaking News White House Watch Daily Cover Stories The Capital of Quantum | Paid Program The New Industrial Identity: The Power Of Digitalization And Automation In America | Paid Program Presented by Invesco QQQ: The Three Ps Of Success Purpose, Persistence And Passion | Paid Program AI’s Nuanced Impact And A Quest To Quantify It DNA of Success Embracing And Bracing For AI Facing A Volatile Market, C-Suites Look To The CFO For Strategic Guida

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Accelerate Machine Learning Model Serving With FastAPI and Redis Caching

Analytics Vidhya

Ever waited too long for a model to return predictions? We have all been there. Machine learning models, especially the large, complex ones, can be painfully slow to serve in real time. Users, on the other hand, expect instant feedback. That’s where latency becomes a real problem. Technically speaking, one of the biggest problems is […] The post Accelerate Machine Learning Model Serving With FastAPI and Redis Caching appeared first on Analytics Vidhya.

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Windows 11 just got a big fix but you have to manually update

Dataconomy

Microsoft has released a new preview update, KB5050094 , for Windows 11 24H2 on Tuesday, which aims to fix multiple bugs affecting the operating system, including issues arising from the January Patch Tuesday update. Microsoft releases preview update KB5050094 for Windows 11 24H2 KB5050094 addresses audio issues where USB headphones, as well as other devices connected through a digital-to-analog converter (DAC), failed to produce sound, displaying the error message: “Insufficient system re

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10 AI Conferences in the USA (2025): Connect with Top AI and Data Minds

Data Science Dojo

Artificial intelligence is evolving rapidly, reshaping industries from healthcare to finance, and even creative arts. If you want to stay ahead of the curve, networking with top AI minds, exploring cutting-edge innovations, and attending AI conferences is a must. According to Statista, the AI industry is expected to grow at an annual rate of 27.67% , reaching a market size of US$826.70bn by 2030.

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Automation, Evolved: Your New Playbook for Smarter Knowledge Work

Speaker: Frank Taliano

Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.

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AI Inference: NVIDIA Reports Blackwell Surpasses 1000 TPS/User Barrier with Llama 4 Maverick

insideBIGDATA

NVIDIA said it has achieved a record large language model (LLM) inference speed, announcing that an NVIDIA DGX B200 node with eight NVIDIA Blackwell GPUs achieved more than 1,000tokens per second (TPS) per user on the 400-billion-parameter Llama 4 Maverick model.

AI 389
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Fault Tolerant Llama training

Hacker News

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AI-First Google Colab is All You Need

KDnuggets

Let's take a closer look at Google Colab's new AI features, and find out how you can use them to increase your daily data workflow productivity.

AI 318
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Introducing Apache Spark 4.0

databricks

Apache Spark 4.0 marks a major milestone in the evolution of the Spark analytics engine.

SQL 342
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The 2nd Generation of Innovation Management: A Survival Guide

Speaker: Chris Townsend, VP of Product Marketing, Wellspring

Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?

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Apple Machine Learning Research at ICML 2025

Machine Learning Research at Apple

Apple researchers are advancing AI and ML through fundamental research, and to support the broader research community and help accelerate progress in this field, we share much of this research through publications and engagement at conferences. Next week, the International Conference on Machine Learning (ICML) will be held in Vancouver, Canada, and Apple is proud to once again participate in this important event for the research community and to be an industry sponsor.

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Mixture of Experts Architecture in Transformer Models

Machine Learning Mastery

This post covers three main areas: • Why Mixture of Experts is Needed in Transformers • How Mixture of Experts Works • Implementation of MoE in Transformer Models The Mixture of Experts (MoE) concept was first introduced in 1991 by

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'Quantum AI' algorithms already outpace the fastest supercomputers, study says

Flipboard

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Algorithm 181
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Google Cloud Creates 3-Levels Of Agentic Software Coding

Adrian Bridgwater for Forbes

Newsletters Amazon Prime Day Share a News Tip Featured Featured Breaking News White House Watch Daily Cover Stories The Capital of Quantum | Paid Program AI’s Nuanced Impact And A Quest To Quantify It DNA of Success Embracing And Bracing For AI Facing A Volatile Market, C-Suites Look To The CFO For Strategic Guidance Forbes Research: 2023 Small Business Survey Your Four-Part Blueprint To Unlock AI Value In 2025 | Paid Program Forbes Insights: Your Five-Step Strategy To Unleash AI’s Value In Mark

AI 194
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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.