{"slug": "ep222-what-is-googles-tpu", "title": "EP222: What is Google’s TPU?", "summary": "Google unveiled its 8th-generation Tensor Processing Unit (TPU) at Cloud Next '26, shipping in two variants for the first time: TPU 8t for training and TPU 8i for inference, both sharing Axion CPUs, liquid cooling, and the same software stack. The custom AI chip is designed specifically for deep learning matrix multiplications, distinguishing it from GPUs built for graphics.", "body_md": "# EP222: What is Google’s TPU?\n\n[Architect the Future at AWS re:Invent (Sponsored)](https://go.bytebytego.com/AWS_081526)\n\nThis isn’t a conference you sit through. AWS re:Invent includes 2,200+ sessions, and 70% are interactive; workshops, code talks, AWS Jams, GameDays, and the Architecture Rodeo, built for engineers who’d rather work through a problem than watch a slidedeck.\n\nBetween November 30 and December 4, you’ll have the opportunity to:\n\nRun demos against real workloads with sandbox access in small groups\n\nTest newly launched AWS services in the AWS Village before your team adopts them\n\nWork through architecture decisions directly with service engineers\n\nThis week’s system design refresher:\n\nHTTP vs HTTPS Explained (Youtube video)\n\nWhat is Google’s TPU?\n\n9 Types of API Testing\n\nCommon types of AI Agents guardrails on production\n\nForward Proxy, Reverse Proxy, and API Gateway Explained\n\n## HTTP vs HTTPS Explained\n\n## What is Google’s TPU?\n\nA TPU (Tensor Processing Unit) is Google’s custom AI chip, designed from scratch for the giant matrix multiplications that modern models live on. GPUs were built for graphics first.\n\nTPUs were built for deep learning from day one.\n\nAt Cloud Next ’26, Google unveiled its 8th generation, and for the first time it ships in two flavors. TPU 8t is built for training, where raw throughput wins. TPU 8i is built for inference, where latency and chip-to-chip speed matter most.\n\nBoth still share the same Axion CPUs, liquid cooling, and software stack, so code written for one runs on the other.\n\nThe diagram is a quick study guide to what’s the same, what’s different, and why, based on our understanding of published Google articles.\n\n[What Makes an FDE Role Credible? (Sponsored)](https://go.bytebytego.com/Ontologize_081526)\n\nStrong candidates are skeptical of vague forward deployed engineer postings, and the title alone won’t earn their trust.\n\nThe ** free State of FDE Jobs 2026 Report** explains what candidates look for, how the market is evolving, and how employers can make these roles easier to understand.\n\nHiring? You can also bring your openings to [forwarddeployedengineer.com](https://go.bytebytego.com/Ontologize_081526), the focused jobs board for forward-deployed engineers.\n\n## 9 Types of API Testing\n\nHere are the 9 most common API tests used to catch different kinds of failures.\n\nSmoke tests run right after a deploy to confirm the critical endpoints still respond, especially things like login, checkout, or health checks.\n\nFunctional testing checks whether an endpoint does what the business expects or just returns a clean 200 with the wrong number inside.\n\nContract testing protects the agreement between services. If a consumer depends on a field, a type, or a status code, the provider should not change it without warning.\n\nIntegration testing covers the full workflow across systems. An order endpoint may also use inventory, payment, and notifications, and a- ny of those dependencies can fail.\n\nRegression testing protects existing behavior when new changes are added. A change in discount logic should not break checkout totals or order history.\n\nLoad testing asks how things hold up under expected traffic.\n\nStress testing keeps pushing until something breaks.\n\nSecurity testing covers auth, access control, unsanitized input, and what your errors leak.\n\nFuzz testing sends unexpected or invalid inputs to the API to find bugs that normal test cases may miss.\n\nOver to you: Which of these do you rely on most in practice?\n\n## Common types of AI Agents guardrails on production\n\nInput Screening: Every user request is scanned for prompt injection, sensitive data, and off-scope topics before the model sees it. Unsafe inputs return a fallback message.\n\nContext Verification: Every user request is scanned for prompt injection, sensitive data, and off-scope topics before the model sees it. Unsafe inputs return a fallback message.\n\nResponse Generation: The LLM reasons only over verified context.\n\nOutput Validation: Every response is checked for groundedness, format, and safety before it leaves the system. Failures trigger up to two retries, then a safe fallback.\n\nOperational Controls: A final layer enforces limits, logs every call, and routes low-confidence or high-risk actions to humans.\n\nReliable agents aren't built on better prompts. They're built on the guardrails wrapped around them.\n\nOver to you: Which guardrail layer catches the most issues in your setup?\n\n## Forward Proxy, Reverse Proxy, and API Gateway Explained\n\nPeople mix these up all the time, since they all sit between a client and a server. The real difference is which side they represent and what problem they solve.\n\nA forward proxy sits next to the client. Your laptop sends a request, the proxy forwards it out, and the destination never sees your real IP. Corporate networks use this to enforce policy, block sites, and cache traffic.\n\nA reverse proxy sits next to the server. The client has no idea how many machines are behind it. The proxy decides who handles the request, terminates TLS, and keeps your backend off the public internet. NGINX and HAProxy are commonly used here, typically paired with a load balancer in front.\n\nAn API gateway is a reverse proxy that does more than route traffic. It also handles auth, rate limits, API keys, versioning, and request shaping. Without it, each microservice has to implement its own version of validation, throttling logic, and request logging.\n\nA forward proxy represents the client, a reverse proxy represents the server, and an API gateway is what you add when ten services need the same authentication and rate limiting rules applied consistently.\n\nIn most real systems, all three are running at different layers. The forward proxy filters outbound traffic, the reverse proxy fronts the application servers, and the API gateway sits in front of your APIs to enforce policies before requests reach them.\n\nOver to you: What's your proxy + gateway combo? Always interesting to see what teams pair together.", "url": "https://wpnews.pro/news/ep222-what-is-googles-tpu", "canonical_source": "https://blog.bytebytego.com/p/ep222-what-is-googles-tpu", "published_at": "2026-08-15 15:30:49+00:00", "updated_at": "2026-08-15 15:41:37.717214+00:00", "lang": "en", "topics": ["ai-chips", "artificial-intelligence", "machine-learning"], "entities": ["Google", "TPU 8t", "TPU 8i", "Axion CPUs", "Cloud Next '26"], "alternates": {"html": "https://wpnews.pro/news/ep222-what-is-googles-tpu", "markdown": "https://wpnews.pro/news/ep222-what-is-googles-tpu.md", "text": "https://wpnews.pro/news/ep222-what-is-googles-tpu.txt", "jsonld": "https://wpnews.pro/news/ep222-what-is-googles-tpu.jsonld"}}