of a series about distributed AI across multiple GPUs: ContentsIntroductionThe Memory Problem in DDPZeRO-1: Optimizer State PartitioningZeRO-2: Gradient PartitioningZeRO-3: Parameter PartitioningUsing ZeRO in PyTorchConclusionReferences Introduction In the previous post, we saw how Distributed Data Parallelism (DDP) speeds up training by splitting batches across GPUs. DDP solves the throughput problem, but it introduces a new challenge: memory …
Image by Editor Contents# Introduction# Getting Started With Kedro# Exploring the Core Elements of Kedro# Wrapping Up # Introduction Data science projects usually begin as exploratory Python notebooks but need to be moved to production settings at some stage, which might be tricky if not planned carefully. QuantumBlack’s framework, Kedro, is an open-source tool that bridges the gap between …
A Guide to Kedro: Your Production-Ready Data Science Toolbox Read More »
Today, we’re introducing Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model. Built for high-volume developer workloads at scale, 3.1 Flash-Lite delivers high quality for its price and model tier. Starting today, 3.1 Flash-Lite is rolling out in preview to developers via the Gemini API in Google AI Studio and for enterprises …
to be the state-of-the-art object detection algorithm, looked to become obsolete thanks to the appearance of other methods like SSD (Single Shot Multibox Detector), DSSD (Deconvolutional Single Shot Detector), and RetinaNet. Finally, after two years since the introduction of YOLOv2, the authors decided to improve the algorithm where they eventually came up with the next …
YOLOv3 Paper Walkthrough: Even Better, But Not That Much Read More »
Image by Editor Contents# The Value of Docker# 1. Docker Model Runner: Your Local Gateway# 2. Defining AI Models in Docker Compose# 3. Docker Offload: Cloud Power, Local Experience# 4. Model Context Protocol Servers: Agent Tools# 5. GPU-Optimized Base Images for Custom Work# Putting It All Together # The Value of Docker Building autonomous AI systems is no longer just about prompting …
Docker AI for Agent Builders: Models, Tools, and Cloud Offload Read More »
In August of last year, our Gemini Image model, Nano Banana, became a viral sensation, redefining image generation and editing. Then in November, we released Nano Banana Pro, offering users advanced intelligence and studio-quality creative control. Today, we’re bringing the best of both worlds to users across Google. Introducing Nano Banana 2 (Gemini 3.1 Flash …
is one of the earliest and most iconic games in the history of digital entertainment. In its classic form, the game simulates a table tennis match with two paddles that move vertically across the screen to hit a bouncing ball. Each of the player controls a paddle and has to bounce the ball back to …
Image by Author Contents# Introduction# 1. Analyzing Missing Data# 2. Validating Data Types# 3. Detecting Duplicate Records# 4. Detecting Outliers# 5. Checking Cross-Field Consistency# Wrapping Up # Introduction Data quality problems are everywhere. Missing values where there shouldn’t be any. Dates in the wrong format. Duplicate records that slip through. Outliers that skew your analysis. Text fields with inconsistent capitalization and spelling …
5 Useful Python Scripts for Automated Data Quality Checks Read More »
Introducing our National Partnerships for AI and collaboration in India We believe AI will be the most transformative technology in human history and that it should be deployed in ways that benefit all of humanity. This requires deep, strategic collaboration between frontier AI labs, governments, academia, and civil society. To fully realise AI’s potential, Google …
scaling AI in science and education — Google DeepMind Read More »
that have pervaded nearly every facet of our daily lives are autoregressive decoder models. These models apply compute-heavy kernel operations to churn out tokens one by one in a manner that, at first glance, seems extremely inefficient. Given the enormous demand for generative AI, it is no surprise that extraordinary engineering effort is being invested …
Optimizing Token Generation in PyTorch Decoder Models Read More »
