A Coding Guide to Implement a pgvector-Powered Semantic, Hybrid, Sparse, and Quantized Vector Search System
In this tutorial, we build a complete pgvector playground inside Google Colab and explore how PostgreSQL can work as a powerful vector database for modern AI applications. We start by installing PostgreSQL, compiling the pgvector extension, connecting through Psycopg, and registering vector types for smooth Python integration. Then, we create embeddings with SentenceTransformers, store them […]
Sakana AI Proposes DiffusionBlocks: a Block-wise Training Framework That Converts Residual Networks into Independently Trainable Denoising Modules
Researchers from Sakana AI and the University of Tokyo propose DiffusionBlocks. It trains transformer-based networks one block at a time. Training memory is reduced by a factor of B, where B is the number of blocks. Performance is maintained across diverse architectures. The Memory Problem in Neural Network Training End-to-end backpropagation requires storing intermediate activations […]
MUFG aims to become AI-native with OpenAI
MUFG is one of Japan’s largest financial groups, with Mitsubishi UFJ Bank at its core. Through banking, trust banking, securities, cards, leasing, and other financial services, MUFG supports individuals and businesses in Japan and around the world. For MUFG, AI is more than an efficiency tool. The company sees it as a way to extend […]
NVIDIA Releases Polar, a Token-Faithful Rollout Framework for GRPO Training Across Codex, Claude Code, and Qwen Code
Reinforcement learning for language agents is growing more complex. Agents now manage multi-turn tool use, long-running contexts, and multi-agent orchestration. The main engineering challenge is connecting existing agent software to training pipelines without breaking how those tools work. NVIDIA’s research team introduced Polar, a rollout framework that lets researchers run reinforcement learning over any agent […]
How to Effectively Run Many Claude Code Sessions in Parallel
coding agents sequentially and not in multiple runs in parallel, you’re losing out. One of the key benefits of coding agents is that you can start completing work in parallel, something that was never really possible before when working on software engineering tasks. However, when I start running a lot of parallel coding sessions, it’s […]
Learning From Pairwise Preferences: An Introduction to the Bradley Terry Model
assumes the availability of absolute labels. For example, an instance belongs to a class, a document receives a score, an observation is assigned a probability, a product is rated on a fixed scale. In practice, however, human judgment often appears in a more local and comparative form. People may not know whether an answer deserves […]
Most AI Agents Fail in Production Because They’re Built Backwards
agent system seriously fail in production, it wasn’t dramatic. There was no crash. No error message. The system just kept running and producing outputs that looked reasonable until someone actually read them carefully enough to notice something was off. When we decided to look into it, it took us two days’ worth of debugging to […]
Google folds Display Ads into AI-first Demand Gen platform
Google is folding Display Ads into its AI-powered Demand Gen platform, marking the end of a long-standing digital advertising model. The Google Display Network (GDN) has been a staple of the open internet for almost twenty years. Marketers previously relied on its predictable framework to target placements, bid on audiences, and A/B test static creative […]
Exploring the Benefits of AI Bots for Forex Trading in Forex Markets
The foreign exchange market is really moving away from pure intuition and toward a space shaped by speed, data and precision. By using automated systems in your routine, you can approach volatility with a level of discipline that manual trading often struggles to maintain. Every entry and exit can be based on clear rules, not […]
They Requested It. I Built It. Nobody Ever Used It.
to us asking for a model. We built a proof of concept. Got the green light. Delivered the model. Weeks of work…all to hear nothing. It’s a tale as old as time, and one that plagues data professionals everywhere, from analysts to ML engineers. So, what happened? Your Model is a Mystery Our profession is […]