Today, we’re excited to introduce Stack Overflow Internal—the next evolution of our enterprise platform and the future of Stack Overflow for Teams.
Embeddings are a crucial component at the intersection of data and AI. As data structures, they encode the inherent meaning of the data they represent, and their significance becomes apparent when they are compared to one another. Vector search is a technique that uncovers the relative meaning of those embeddings by evaluating the distances between
BigQuery under the hood: How Google brought embeddings to analytics Read More »
Training large video diffusion models at scale isn’t just computationally expensive — it can become impossible when your framework can’t keep pace with your ambitions. JAX has become a popular computational framework across AI applications, now recognized for its capabilities in training large-scale AI models, such as LLMs and life sciences models. Its strength lies
How Lightricks trains video diffusion models at scale with JAX on TPU Read More »
Google and the cloud-native community have consistently strengthened Kubernetes to support modern applications. At KubeCon EU 2025 earlier this year, we announced a series of enhancements to Kubernetes to better support AI inference. Today, at KubeCon NA 2025, we’re focused on making Kubernetes the most open and scalable platform for AI agents, with the introduction
Introducing Agent Sandbox: Strong guardrails for agentic AI on Kubernetes and GKE Read More »
The past decade of cloud native infrastructure has been defined by relentless change — from containerization and microservices to the rise of generative AI. Through every shift, Kubernetes has been the constant, delivering stability and a uniform, scalable operational model for both applications and infrastructure. As Google Kubernetes Engine (GKE) celebrates its 10th anniversary, its
GKE: From containers to agents, the unified platform for every modern workload Read More »
Ryan is joined by Secure Code Warrior’s co-founder and CTO Matias Madou to discuss the implications of LLMs’ variability on code security, the future of developer training as AI coding assistants become more popular, and the importance of critical thinking—especially for junior developers—in the age of AI.
AI code means more critical thinking, not less Read More »
India’s developer community, vibrant startup ecosystem, and leading enterprises are embracing AI with incredible speed. To meet this moment for India, we are investing in powerful, locally-available tools in India that can help foster a diverse ecosystem, and ensure our platform delivers the controls you need for compliance and AI sovereignty. Today, we’re announcing a
Supporting Viksit Bharat: Announcing our newest AI investments in India Read More »
In today’s fast-paced, data-driven landscape, the ability to process, analyze, and act on vast amounts of data in real time is paramount. For businesses aiming to deliver personalized customer experiences and optimize operations, the choice of database technology is a critical decision. At Zeotap — a leading Customer Data Platform (CDP) — we empower enterprises
Zeotap’s big win: 46% TCO reduction and enhanced real-time performance with Bigtable Read More »
As Large Language Models (LLMs) evolve, Reinforcement Learning (RL) is becoming the crucial technique for aligning powerful models with human preferences and complex task objectives. However, enterprises that need to implement and scale RL for LLMs are facing infrastructure challenges. The primary hurdles include the memory contention from concurrently hosting multiple large models (such as
Running high-scale reinforcement learning (RL) for LLMs on GKE Read More »
The best feedback during a code review is specific, consistent, and understands the history of a project. However, AI code review agents today are often stateless; they have no memory of past interactions. This means you might find the same feedback on new pull requests that you’ve rejected before, because the agent can’t learn from
