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Bridging the Gap: New Datasets Push Recommender Research Toward Real-World Scale

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 Bridging the Gap: New Datasets Push Recommender Research Toward Real-World Scale Publicly available datasets in recommender research currently shaping the field.

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News Bytes 20250609: AI Defying Human Control, Huawei’s 5nm Chips, WSTS Semiconductor Forecast

insideBIGDATA

A rare day in June to you! As the ISC 2025 supercomputing conference, we reflect on interesting recent news in the world of HPC-AI, including: – French government to acquire Eviden from Atos – Made-in-China 5nm chips from Huawei – World Semiconductor Trade Statistics (WSTS) market forecast – AI eerily defies human control.

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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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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

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What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

Speaker: Tamara Fingerlin, Developer Advocate

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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Updates to Apple's On-Device and Server Foundation Language Models

Machine Learning Research at Apple

With Apple Intelligence, we're integrating powerful generative AI right into the apps and experiences people use every day, all while protecting their privacy. At the 2025 Worldwide Developers Conference we introduced a new generation of language foundation models specifically developed to enhance the Apple Intelligence features in our latest software releases.

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Integrating DuckDB & Python: An Analytics Guide

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 Integrating DuckDB & Python: An Analytics Guide Learn how to run lightning-fast SQL queries on local files with ease.

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Nvidia CEO: You now program AI the same way you talk to people

Dataconomy

Nvidia CEO Jensen Huang stated at London Tech Week on Monday that artificial intelligence serves as an “equalizer,” enabling users to program with natural language. Huang addressed the challenges of traditional computing, noting the necessity for specialized programming languages and complex computer architecture. He said, “We had to learn programming languages.

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What Is a Lakebase?

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

Database 200
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Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents

Hacker News

Today's AI systems have human-designed, fixed architectures and cannot autonomously and continuously improve themselves. The advance of AI could itself be automated. If done safely, that would accelerate AI development and allow us to reap its benefits much sooner. Meta-learning can automate the discovery of novel algorithms, but is limited by first-order improvements and the human design of a suitable search space.

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Why You Need RAG to Stay Relevant as a Data Scientist

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 Why You Need RAG to Stay Relevant as a Data Scientist How retrieval-augmented generation (RAG) reduces LLM costs, minimises hallucinations, and keeps you employable in the age of AI.

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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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Multiverse Computing Raises $215M for LLM Compression

insideBIGDATA

Multiverse Computing has developed CompactifAI, a compression technology capable of reducing the size of LLMs (Large Language Models) by up to 95 percent while maintaining model performance, according to the company.

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Implementing Vector Search from Scratch: A Step-by-Step Tutorial

Machine Learning Mastery

There’s no doubt that search is one of the most fundamental problems in computing.

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MLflow 3.0: Unified AI Experimentation, Observability, and Governance

databricks

MLflow has become the foundation for MLOps at scale, with over 30 million monthly downloads and contributions from over 850 developers worldwide powering ML and

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Superblocks CEO: How to find a unicorn idea by studying AI system prompts

Flipboard

Brad Menezes, CEO of enterprise vibe coding startup Superblocks, believes the next crop of billion-dollar startup ideas are hiding in almost plain sight: the system prompts used by existing unicorn AI startups.

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How to Modernize Manufacturing Without Losing Control

Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives

Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri

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7 Python Errors That Are Actually Features

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 7 Python Errors That Are Actually Features You never expected these Python errors to help your work, but they do!

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Translating the Internet in 18 Days: DeepL to Deploy NVIDIA DGX SuperPOD

insideBIGDATA

Language AI company DeepL announced the deployment of an NVIDIA DGX SuperPOD with DGX Grace Blackwell 200 systems. The company said the system will enable DeepL to translate the entire internet – which currently takes 194 days of nonstop processing – in just over 18 days.

AI 195
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Build a Conversational AI Agent with Rasa

Analytics Vidhya

Customer-facing conversational AI assistants don’t operate in a vacuum. They are embedded within well-defined business processes. That’s why these systems are expected to reliably and consistently guide users through each step of a predetermined workflow. However, existing agentic frameworks that leverage a concept of tool calling or function calling to interact with systems (such as […] The post Build a Conversational AI Agent with Rasa appeared first on Analytics Vidhya.

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Mosaic AI Announcements at Data + AI Summit 2025

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

AI 152
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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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The Tech Industry Said It Was "Impossible" to Create AI Based Entirely on Ethically-Sourced Data, So These Scientists Proved Them Wrong in Spectacular Fashion

Flipboard

Well, look at that.

AI 173
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Selling Your Side Project? 10 Marketplaces Data Scientists Need to Know

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 Selling Your Side Project? 10 Marketplaces Data Scientists Need to Know That app collecting dust on your GitHub?

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MOSTLY AI Launches $100K Synthetic Data Prize  

insideBIGDATA

Austrian synthetic data firm MOSTLY AI has launched a $100,000 prize challenge to raise awareness of how synthetic data can be used to create open-access datasets for businesses, AI developers and other organizations.

AI 195
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5 Ways to Market Yourself as a Data Professional on LinkedIn

Analytics Vidhya

LinkedIn is the de facto social networking site for professionals. With over a billion users on the platform and 7 people getting hired each minute, it has positioned itself as the mainstream career market. A survey shows, LinkedIn candidates are given higher precedence than candidates from the other channels, and over 72% of recruiters prefer […] The post 5 Ways to Market Yourself as a Data Professional on LinkedIn appeared first on Analytics Vidhya.

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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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Announcing Lakebase Public Preview

databricks

At the Data and AI Summit, we introduced a new category of operational databases called lakebases for building intelligent applications.

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Mistral’s first reasoning model, Magistral, launches with large and small Apache 2.0 version

Flipboard

European AI powerhouse Mistral today launched Magistral, a new family of large language models (LLMs) that marks the first from the company to enter the increasingly competitive space of “reasoning,” or models that take time to reflect on their thinking to catch errors and solve more complex tasks …

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Top 7 MCP Clients for AI Tooling

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 Top 7 MCP Clients for AI Tooling The most popular clients that seamlessly and reliably work with MCP servers ranging from IDEs to chatbots and plugins.

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Lenovo to Deliver AI System for the European Institute of Oncology

insideBIGDATA

Milan, 09 June 2025 – Lenovo will provide the IEO Monzino Group with a high performance computing system to accelerate scientific research in oncology and cardiology at the European Institute of Oncology and the Monzino Cardiology Center.

AI 195
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Apache Airflow® Best Practices: DAG Writing

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!

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Log-Linear Attention

Hacker News

The attention mechanism in Transformers is an important primitive for accurate and scalable sequence modeling. Its quadratic-compute and linear-memory complexity however remain significant bottlenecks. Linear attention and state-space models enable linear-time, constant-memory sequence modeling and can moreover be trained efficiently through matmul-rich parallelization across sequence length.

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Introducing Databricks Free Edition

databricks

Today, we are excited to announce the availability of Databricks Free Edition, a product for learning and exploring the latest data and AI technologies for free.

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Why most enterprise AI agents never reach production and how Databricks plans to fix it

Flipboard

Many enterprise AI agent development efforts never make it to production and it’s not because the technology isn’t ready. The problem, according to Databricks, is that companies are still relying on manual evaluations with a process that’s slow, inconsistent and difficult to scale.

AI 154
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10 Awesome OCR Models for 2025

KDnuggets

Stay ahead in 2025 with the latest OCR models optimized for speed, accuracy, and versatility in handling everything from scanned documents to complex layouts.

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

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Controlling Language and Diffusion Models by Transporting Activations

Machine Learning Research at Apple

Large generative models are becoming increasingly capable and more widely deployed to power production applications, but getting these models to produce exactly what's desired can still be challenging. Fine-grained control over these models' outputs is important to meet user expectations and to mitigate potential misuses, ensuring the models' reliability and safety.