# Apr 10, 2025

## Ironwood: The first Google TPU for the age of inference
- **Ironwood is Google’s seventh-generation TPU**, engineered specifically for the **age of inference**, enabling advanced AI models to generate insights proactively rather than merely responding to queries.

## The Agent2Agent Protocol (A2A)
- **Agent2Agent (A2A) Protocol** enables AI agents to communicate and collaborate across diverse platforms, enhancing productivity and reducing costs through interoperability among over **50 technology partners** including Atlassian and Salesforce.

## Colossus for Rapid Storage
- **Rapid Storage** leverages the **Colossus stateful protocol** to achieve **sub-millisecond read/write latency** and support for **unlimited appends**, enhancing performance for data-intensive workloads like AI and ML.

## [D] Yann LeCun Auto-Regressive LLMs are Doomed
- **Yann LeCun argues that auto-regressive LLMs are fundamentally flawed**, suggesting that their reliance on sequential data processing limits their potential for true understanding and reasoning.

## Visual Reasoning Is Coming Soon
- **OpenAI's GPT-4o model revolutionizes image manipulation** by integrating full conversational context into image generation, allowing for more accurate and consistent results, such as dressing a specific cat in a detective hat.

## The next generation of Bazel builds
- **Bonanza represents a radical shift in build systems**, leveraging cloud capabilities to handle all aspects of builds, including dependency management and graph construction, thus eliminating local execution complexities inherent in Bazel.

## The 2025 AI Index Report
- The **2025 AI Index Report** reveals significant advancements in AI research, highlighting a **50% increase** in published papers compared to the previous year, indicating a robust growth in the field.

## Controlling Language and Diffusion Models by Transporting Activations
- **Activation Transport (AcT)** is a novel framework that enables **fine-grained control** over generative models' outputs with minimal computational overhead, addressing challenges in reliability and safety without altering model parameters.

## TVMC: Time-Varying Mesh Compression
- **TVMC** introduces a novel approach for **time-varying mesh compression** using volume-tracked reference meshes, enhancing efficiency in 3D data representation.

## [P] B200 vs H100 Benchmarks: Early Tests Show Up to 57% Faster Training Throughput & Self-Hosting Cost Analysis
- **B200 GPUs** demonstrate up to **57% higher training throughput** than H100s in computer vision tasks, indicating a significant performance leap for model training workloads.

## Trustworthy AI Without Trusted Data
- **EPFL researchers have developed ByzFL**, a tool that enhances federated learning by benchmarking models against adversarial threats, ensuring AI systems can be built without trusting individual data sources.

## EGPU: Extending eBPF Programmability and Observability to GPUs
- **eGPU** introduces a groundbreaking framework that dynamically offloads **eBPF bytecode** onto GPUs via **PTX injection**, enhancing observability and programmability for AI and HPC applications without significant overhead.

## Self-Steering Language Models
- The paper introduces **DisCIPL**, a method for **self-steering** language models that allows a Planner model to create task-specific inference programs executed by Follower models, enhancing reasoning capabilities. [Link to article](http://arxiv.org/abs/2504.07081v1)

## Google Cloud Rapid Storage
- **AI Hypercomputer** integrates over a decade of Google’s AI expertise, delivering **24x higher intelligence per dollar** than GPT-4o, thanks to innovations like the **Ironwood TPU**, which offers **5x more peak compute capacity** and **6x the HBM** of its predecessor.

## [P] Reducing Transformer Training Time Without Sacrificing Accuracy — A Dynamic Architecture Update Approach
- A **novel method** for optimizing transformer models enables **dynamic architecture updates during training**, significantly reducing training time while preserving accuracy.