Where Does the Money Go Across Long-Running Coding Agents?
The cost of control The post Where Does the Money Go Across Long-Running Coding Agents? appeared first on Towards Data Science.
Towards Data Science11 min read
retrieval augmented generation
499 stories
EmbeddingGemma 2: Text, Code, Images, Video and Audio in One Vector Space
EmbeddingGemma 2 launched on October 6, 2026 under Apache 2.0. It is a sub-1B model built on Gemma 4 that maps text, code, images, video and audio into one 768-dimensional space. This article covers the architecture, the benchmarks, and runnable scripts to provide measured results.
Analytics Vidhya15 min read
10 Free AI Tools That Replace Expensive Software for Data Scientists
Build a production-grade data science toolkit without spending a dollar, using open-source AI tools that match, and sometimes exceed, their paid alternatives.
KDnuggets11 min read
How to Fine-Tune Llama 3 for Custom Tool Calling with Unsloth in Python
Llama 3 is a capable generalist, but that's exactly the problem when you need an agent that reliably outputs structured JSON for a specific API.
Machine Learning Mastery Blog8 min read
Why AI Support Agents Make Things Up - and What Actually Reduces It
Hallucination isn’t fixed by one feature or by a vendor saying “we use RAG.” The layers that actually make AI support answers trustworthy - grounding, citations, freshness, permissions, and knowing when to stop.
ify Blog9 min read
Semantic Caching for RAG
Build a Semantic Cache for a RAG Pipeline Time: 30 min Level: Intermediate What’s a Semantic Cache Traditional caches operate on an exact match basis, while semantic caches search for the meaning of the key rather than an exact match.
Qdrant21 min read
🟢 turbopuffer: Resolved — Elevated rate of 5xx in gcp-us-central1
🟢 Resolved · lasted 7h 27m The issue upstream in Google Cloud Storage is resolved and us-central1 operations have returned to normal.
AIWatch Blog3 min readHow Large Language Models Actually Work — Daily AI Post
The conversation has drifted from mortgage rates to whether sourdough starters qualify as pets, when someone across the table leans forward and asks the question everyone’s been dodging for three years:
Towards AI21 min readLandingAI ADE vs Google Pinpoint
Compare LandingAI ADE and Google Pinpoint by document types, accuracy evidence, source traceability, deployment, pricing, access, and best-fit workflows.
Agentic Document Extraction Blog8 min readProduction Grade Retrieval Pipeline That Admits "I Don't Know" [P]
If you're moving a RAG prototype to production, this is the checklist I wish I'd had.
Reddit - r/ML1 min read
6 AI Projects That Actually Get You Hired
Projects, datasets, tool stacks, and the prompt from the video: https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/youtube/ai-engineer-projects.md If you’re applying for AI engineering roles, listing RAG, agents, and MCP on your resume and building a few starter projects isn’t…
Aish Reganti
7 Best Resources to Learn About Self-Evolving AI Agents
The next step for AI agents? Self-improvement. Here are 7 resources to get started.
KDnuggets5 min read
Evaluating Graph-RAG vs. Standard RAG: A Hallucination Benchmark on Fact-Dense Queries
In this article, you will learn how to benchmark a deterministic 3-Tiered Graph-RAG system against a standard vector RAG pipeline on fact-dense queries, and what...
Machine Learning Mastery Blog5 min read
Nano Banana 2.1 Review
Have an idea for a lesson illustration, a project chart, or a comic for your next presentation? Nano Banana 2.1 lets you explore these formats with text prompts, making it easier to try different visual styles without switching between tools.
Analytics Vidhya7 min read
Complete AI Engineering Roadmap
Check out Vidya AI: https://www.krishnaik.in/ai-tutorials Join our AI FDE Bootcamp Enrollment link: https://www.krishnaik.in/liveclass2/Forward_Deployed_Engineer?id=14 Reach out to Krish Naik's counselling team on 📞 +919111533440 or +918484837781 in case of any queries we are there to help you…
Krish NaikBEACON-SP: Ontology-Grounded GraphRAG Framework for Clinical Suicide Risk Assessment
We present BEACON-SP, an ontology-grounded Graph Retrieval-Augmented Generation (GraphRAG) framework for clinician-facing decision support in behavioral health settings such as suicide prevention, where effective assessment requires integrating heterogeneous clinical, behavioral, social, and…
arXiv - cs.AI2 min read
HPE Unveils The First Of The Next Generation of ProLiants for the AI Era
It is impossible to miss the impact that the rapid adoption of AI continues to have on the datacente ...
Next Platform8 min read
How to Build Multimodal RAG with Google's EmbeddingGemma 2
A practical guide to building cross-modal photo, video, audio, and document search with Google's EmbeddingGemma 2 in a free Colab notebook.
MindStudio Blog8 min read
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