Engineering posts about Tensorflow
Curated summaries and key learnings for engineers working with Tensorflow.
A Smarter Google AI Edge Gallery: MCP integration, notifications, and session continuity
The Google AI Edge Gallery has introduced significant enhancements, including support for the Model Context Protocol (MCP), which allows for dynamic tool integration and improved interaction with...
Blazing fast on-device GenAI with LiteRT-LM
The article provides an in-depth exploration of LiteRT-LM, an advanced framework for deploying the Gemma 4 model across various platforms, including Android, iOS, and web environments. It highlights...
Google Tensor SDK Beta with LiteRT
The Google Tensor ML SDK has transitioned from an Experimental Access Program to Beta, enabling developers to leverage the capabilities of the Google Tensor System-on-Chip (SoC) and its dedicated...
Accelerating on-device AI: A look at Arm and Google AI Edge optimization
The article explores advancements in on-device AI through the integration of Arm's Scalable Matrix Extension 2 (SME2) and Google's AI Edge framework. It highlights how SME2 enhances CPU performance...
Announcing Genkit Middleware: Intercept, extend, and harden your agentic apps
The article introduces Genkit, an open-source framework designed for building full-stack, AI-powered applications across multiple programming languages, including TypeScript, Go, Dart, and Python. It...
How we built the most performant DeepSeek V3.2, MiniMax-M2.5 and Qwen 3.5 397B on DigitalOcean Serverless Inference
The article discusses the launch of DeepSeek V3.2, MiniMax-M2.5, and Qwen 3.5 397B on DigitalOcean's Serverless Inference platform, highlighting their performance benchmarks and the engineering...
Building real-world on-device AI with LiteRT and NPU
The article presents LiteRT, a cross-platform framework designed for on-device AI, which leverages Neural Processing Units (NPUs) to enhance performance while maintaining battery efficiency. It...
Mastering the 600B+ Frontier: Optimizing Large Model Deployments on the Inference Cloud
The article explores the challenges and solutions associated with deploying large AI models, particularly those exceeding 600 billion parameters, in cloud environments. It highlights the importance...
Expanding Agent Governance with Unity AI Gateway
The article introduces significant enhancements to the Unity AI Gateway, which is now integrated with Unity Catalog to provide comprehensive governance for AI agents. It emphasizes the importance of...
Bring state-of-the-art agentic skills to the edge with Gemma 4
Google DeepMind has introduced Gemma 4, a cutting-edge framework designed for on-device AI development, enabling developers to create agents and autonomous AI applications without the need for...
ADK Go 1.0 Arrives!
ADK Go 1.0 introduces significant enhancements for developing AI agents, emphasizing observability, security, and extensibility. Key features include native integration with OpenTelemetry for tracing...
Databricks recognized as a Gartner® Peer Insights™ Customers’ Choice for Analytics and BI
Databricks has been recognized as a Customers’ Choice in the Gartner Peer Insights Voice of the Customer for Analytics and Business Intelligence Platforms, achieving a high customer rating of 4.8 out...
Powering the agents: Workers AI now runs large models, starting with Kimi K2.5
The article introduces Cloudflare's Workers AI platform, which now supports the Kimi K2.5 model, a large language model (LLM) designed for agentic tasks. It highlights the importance of a robust...
Announcing the Colab MCP Server: Connect Any AI Agent to Google Colab
The article introduces the Colab MCP Server, an open-source tool designed to enhance the integration of AI agents with Google Colab. By allowing any MCP-compatible agent to access Colab's cloud...
DigitalOcean at NVIDIA GTC 2026: Building the AI Factory for the Agentic Era
DigitalOcean is positioning itself as a leader in AI infrastructure by launching an AI Factory designed for dynamic, long-running agentic workflows. The partnership with NVIDIA aims to enhance...
Building the Spatial Interaction and Interface Frameworks for Specs
The article provides an in-depth exploration of the Spectacles Interaction Kit (SIK) and Spectacles UI Kit (UIKit), two frameworks designed for building spatial interactions and interfaces in...
A Declarative Standard for AI Agents
The article outlines the development of a declarative standard for AI agents, inspired by Kubernetes, to address the fragmentation and inefficiencies in agent implementation across different...
What's new in TensorFlow 2.21
TensorFlow 2.21 introduces significant enhancements, particularly with the LiteRT stack, which is designed for high-performance on-device inference. This new runtime offers improved GPU performance,...
Supercharge your AI agents: The New ADK Integrations Ecosystem
The article introduces significant enhancements to the Agent Development Kit (ADK), an open-source framework designed for building and deploying AI agents. It highlights new integrations with various...
DigitalOcean Gradient™ AI GPU Droplets Optimized for Inference: Increasing Throughput at Lower the Cost
The article discusses the development of DigitalOcean's Inference Optimized Image for GPU Droplets, specifically designed to enhance the performance of large language model (LLM) inference. It...