标签：#m

TL;DR: An API gateway manages HTTP traffic between services — auth, routing, rate limiting, load balancing for REST and gRPC. An AI gateway manages LLM workloads — token-based rate limiting, model routing, cost attribution, semantic caching, guardrails. Use an API gateway for your microservices. Use an AI gateway for your LLM traffic. Most production teams eventually need both, sitting at different layers. This post walks through exactly where each one fits. When we started adding LLM features to our platform, we already had Kong running for our microservices. The instinct was natural: route the LLM traffic through Kong too. Same auth, same rate limiting, same observability stack. One gateway to rule them all. It worked — for about six months, and only in the sense that requests got through. What it didn't give us was anything useful for actually managing AI workloads. We had no idea what each team was spending on tokens. We had no way to set a budget cap that would fire before the bill arrived. Our rate limits were based on requests per minute, which meant a single request with a 50k token prompt counted the same as one with a 200 token prompt. And when OpenAI had a partial outage, Kong had no concept of "try Anthropic instead" — we just served errors. None of that is a criticism of Kong. It's doing exactly what it was designed to do. The problem was us expecting an API gateway to handle a fundamentally different category of infrastructure problem. Here's the precise distinction, and why it matters architecturally. What an API gateway actually does An API gateway is a reverse proxy that sits between client applications and backend services. It handles the cross-cutting concerns of service-to-service HTTP communication: authentication, authorization, rate limiting, load balancing, SSL termination, request transformation, and routing based on URL paths or headers. A typical request flow through an API gateway: Client sends a request to the gateway endpoint Gateway ve

I couldn't find many resources online that showed how to see cache misses on macOS. I thought I'd learn a bit about Instruments, throw some toy problems at it, and write about the experience in a blog post. These toy examples - iterating sequentially then randomly, summing elements in a matrix, naive vs tiled matmul and iterating AoS vs SoA - are great to see some real numbers from L1 data cache misses, but they're far away from real programming problems. What's your experience using tools like Instruments/perf/cachegrind to actually optimize an algorithm? Is it ever needed to measure this at the hardware counter level or can you get away with intuition about the size of your data structure, how it's been accessed and using basic timers? submitted by /u/markuzo1 [link] [留言]

Modular, one of the most promising chip software startups of the AI era, heads for a multibillion-dollar exit.

Looking for family fun this summer? You need these WIRED-recommended Prime Day board game deals.

Every generation gets a new interface: ⌨️ Keyboard 🖱️ Mouse 📱 Touchscreen What's next? submitted by /u/goto-con [link] [留言]

submitted by /u/cekrem [link] [留言]

I spent some time reading Grafana Alloy’s source code to understand how it loads configuration, builds a dependency graph, evaluates components, and runs them. I wrote a short breakdown of what I learned, mainly focused on the runtime/controller, loader, scheduler, services, and component lifecycle. It is not a complete deep dive into the whole project, but more of a source-code reading note from exploring a real production Go codebase. Feedback is welcome, especially from people familiar with observability systems or large Go codebases. submitted by /u/am0123 [link] [留言]

The US government is reportedly asking Meta to share its AI models for review, in the midst of growing security and safety concerns over the technology.

The biggest Switch 2 exclusives so far have largely been about scale. Mario Kart World introduced a wide open continent to race across, Donkey Kong Bananza let you smash basically everything around you, and Pokopia brought an expansive Minecraft-style creative experience to the Pokémon universe. Star Fox is different. A remake of a Nintendo 64 […]

The common cold comes for us all—often more than once a year. And there is no way to prevent it. The best you can do is take vitamin C and stay away from people with the sniffles. Now, the payment company Stripe, founded by brothers Patrick and John Collison, says it will fund a new…

submitted by /u/sommukhopadhyay [link] [留言]

Grand Theft Auto 6 will cost $80 when pre-orders open on June 25th at midnight.

Dyson’s PencilWash cordless hard floor cleaner is on sale for $199.99 ($150 off) at Amazon. This is the lowest price yet for the powered wet mop that’s a cousin to the silly-sounding-but-awesome Dyson PencilVac Fluffycones vacuum. The PencilWash basically takes the sleek styling and design of the PencilVac and simplifies it into a single-purpose electric […]

Prime Day is still rolling, and so is our live blog. We'll bring you deals, trends, and commentary during the second day of Amazon's annual summer sale.

Naomi Saphra discusses 5 rules governing language model behavior, breaking down why LLMs act like populations rather than individuals. She explains how tokenization creates strange semantic blind spots and highlights the mechanics of sycophancy, showing how models leverage subtle data associations to match user biases and demographics - even guessing political views based on favorite sports teams. By Naomi Saphra

Welcome to Walmart deals for folks who’d rather not shop at Amazon. These are the best gadget deals at Walmart this Prime Day.

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At least one malware developer is adding text about nuclear and biological weapons to their spyware, in an effort to stop automatic AI analysis. Details : The _index.js payload begins with a large JavaScript block comment containing fake system instructions and policy-triggering content. Because it is inside a comment, it does not affect JavaScript execution. The runtime skips it. The real malware begins after the comment with a try{eval(…)} wrapper around a large character-code array and a ROT-style substitution function. This header appears designed for AI-mediated analysis, not for Node, Bun, or Python. It attempts to derail scanners or analyst copilots that feed the beginning of a file to a language model without clearly isolating the content as untrusted data. In weak pipelines, this can cause refusal behavior, prompt confusion, context pollution, or premature classification before the scanner reaches the actual malware...

These goggles have an excellent display, solid metric tracking, and an open-water “SwimStraight” feature. But the real smart tech requires a subscription.

Welcome to day two of Amazon’s four-day Prime Day event, which, if we’re being honest, looks a lot like day one. That’s actually good news, though, because many of the best deals are still around, and some new ones have joined them. If you’ve got a Prime subscription, whether through a free trial or a […]