AI has the potential to help solve some of the world’s biggest challenges — not just in the digital realm, but in the physical world, too. Robotics is one of the most exciting frontiers of AI, where advances in language, vision and action models can help create intelligent machines that interact with the real world …
says “this customer’s probability of leaving is 0.4” and your code does predict(X) >= 0.5, you have just made a pricing decision: you decided that the cost of sending a retention offer to a customer who would have stayed is exactly equal to the cost of losing one who would have left, and on the …
Contents# Introduction# Step 1: Building the Foundation# Step 2: Designing Prompts and Building Tool-Calling Systems# Step 3: Building Retrieval Systems Beyond the Basics# Step 4: Fine-Tuning and Aligning Models# Step 5: Serving and Operating LLM Applications# Recommended Learning Resources# Final Thoughts # Introduction An LLM engineer is not the same thing as a general machine learning engineer. Where a machine learning engineer might …
Today, we are introducing Gemma 4 12B, our latest model designed to bring agentic multimodal intelligence directly to laptops. Bridging the gap between our edge-friendly E4B and our more advanced 26B Mixture of Experts (MoE), Gemma 4 12B packages powerful capabilities inside a reduced memory footprint. It is also our first mid-sized model to feature …
I was asked to do something new at work: Given a data dump of unstructured text data, give us a detailed PDF report of insights about what customers are saying about our products this quarter. So I wrote a clear prompt. Gave Claude a detailed set of instructions. Fed it the dataset. It gave me …
Contents# Introduction# How Claude Code Connects to Any Local Model# Backend 1: Ollama# Backend 2: LM Studio# Backend 3: llama.cpp# The Complete settings.json# Best Local Models for Claude Code in 2026# Troubleshooting Common Issues# Conclusion # Introduction Agentic coding sessions are expensive. A single Claude Code session — reading files, writing code, running tests, iterating — can burn 10–50x more tokens than a …
ContentsWhy diffusion for text?The trade-off with traditional models Why diffusion for text? While the AI research community has explored diffusion-based text generation for years, applying it to large models has remained a challenge. DiffusionGemma changes this by shifting how models use hardware. The trade-off with traditional models Most language models act like a typewriter, generating …
The true bottleneck was never the analysis. The post BI Is Dead, Long Live BI appeared first on Towards Data Science.
Contents# Introduction# Why Gemma 4?# The Modelfile# Wiring Claude Code to the Local Model# Agentic Task Walkthrough# Wrapping Up # Introduction Visualize this: a multi-agent workflow that reads files, writes patches, runs tests, and iterates across four services, making 400 API calls in a single afternoon. The notification arrives. You have crossed the soft limit again. Every token costs money, every …
Local Agentic Programming on the Cheap: Claude Code + Ollama + Gemma4 Read More »
Twenty years ago, translation at Google began as one of our pioneering machine learning experiments to turn the science of language into the magic of human connection. That experiment has come a long way with over a trillion words being translated for billions of users across our products every month. Today, we’re taking our next …
