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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
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.
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.
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.
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.
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 Run the Full DeepSeek-R1-0528 Model Locally Running the quantized version DeepSeek-R1-0528 Model locally using Ollama and WebUI.
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 Run the Full DeepSeek-R1-0528 Model Locally Running the quantized version DeepSeek-R1-0528 Model locally using Ollama and WebUI.
San Sebastian, Spain – June 12, 2025: 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. The company today also announced a €189 million ($215 million) investment round.
Landing a data science role isn’t just about coding and modeling anymore. Interviewers increasingly focus on behavioral questions to assess your problem-solving, communication, and teamworking skills. In this article, we’ll explore what these questions are, why they matter, and how to answer them using proven techniques. I’ll also provide you with 20 sample behavioral questions […] The post 20 Behavioral Questions to Ace Your Next Data Science Interview appeared first on Analyt
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 How to Learn Math for Data Science: A Roadmap for Beginners Confused about where to start with data science math?
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
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.
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.
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.
The world of AI has just taken a gigantic leap forward by Edge Gallery Google. Just in the last week, Google quietly launched AI Edge Gallery, a democratizing application for AI. Google Edge AI enables the execution of powerful language models directly on our smartphones, eliminating dependency on the cloud and offering no subscription fees. […] The post Run LLMs Locally for Free Using Google’s Latest App!
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.
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
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.
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 Building a Custom PDF Parser with PyPDF and LangChain PDFs look simple — until you try to parse one.
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.
A rather brutal truth has emerged in the AI industry, redefining what we consider the true capabilities of AI. A research paper titled “The Illusion of Thinking” has sent ripples across the tech world, exposing reasoning flaws in prominent AI ‘so-called reasoning’ models – Claude 3.7 Sonnet (thinking), DeepSeek-R1, and OpenAI’s o3-mini (high).
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.
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 AI Agents in Analytics Workflows: Too Early or Already Behind? A look at how AI agents are reshaping the data analytics workflow and whether you’re ahead or behind the curve.
We’re excited to announce Lakeflow Designer, an AI-powered, no-code pipeline builder that is fully integrated with the Databricks Data Intelligence Platform.
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.
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.
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?
Nowadays, machine learning has become an integral part of various industries such as finance, healthcare, software, and data science. However, to develop a good and working ML model, setting up the necessary environments and tools is essential, and sometimes it may create many problems as well. Now, imagine training models like XGBoost directly in your […] The post Browser-Based XGBoost: Train Models Without Jupyter or IDEs appeared first on Analytics Vidhya.
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.
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
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!
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!
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.
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
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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