Image by Editor   Contents# Introduction# 1. In-memory Caching# 2. Caching On Persistent Disk# 3. Network-resilient Apps# 4. Client-side Throttling# 5. Structured Output Binding# Wrapping Up # Introduction  Python decorators are tailor-made solutions that are designed to help simplify complex software logic in a variety of applications, including LLM-based ones. Dealing with LLMs often involves coping with unpredictable, slow—and frequently expensive—third-party APIs, and …

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Embracing the opportunity ahead, responsibly We believe the promise of AI in education can only be achieved by developing it responsibly. One essential facet of this is doing so in close partnership with the entire education ecosystem. When my team and I met with Damian Harvey, Interim Head of C2k, he emphasized this point. He …

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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 …

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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 …

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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 …

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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 …

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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 …

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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 …

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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 …

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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 …

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