OpenAI launches the Partner Network, investing $150M to help global partners accelerate enterprise AI adoption, deployment, and transformation.

Startups are trying to "ride that SpaceX IPO wave."

FTX held a diluted 7.84% stake in Anthropic, according to Reuters. Anthropic’s latest reported valuation is around $965B. That implies the former FTX stake would be worth about $75B before further dilution. FTX’s customer shortfall was roughly $8B to $9B. The estate sold the Anthropic stake during bankruptcy to repay creditors. Sources: https://www.reuters.com/technology/crypto-exchange-ftx-sell-shares-ai-startup-anthropic-2024-02-22/ https://www.reuters.com/technology/openai-files-us-ipo-after-

I have this vivid memory of walking to pick up my oldest from school in June of 2022. For a variety of reasons, I was in a very bad place mentally. And to make matters worse, it was brutally hot. I was depressed, angry with the world, sunburned, and soaked through with sweat. But as […]

Customers can order new joysticks, batteries, screens and more.

This is a current list of where and when I am scheduled to speak: I’m giving a keynote at Cybernation 2026 in Berlin, Germany, on June 24, 2026. I’m speaking at the Potsdam Conference on National Cybersecurity at the Hasso Plattner Institut in Potsdam, Germany. The event runs June 24–25, 2026, and my talk will be the evening of June 24. I’m participating in a panel discussion at the Austrian Institute for International Affairs in Vienna on Thursday, June 25, 2026. I’m speaking at the Digital Humanism Conference in Vienna, Austria, on Friday, June 26, 2026...

What are you working on? Any new ideas that you're thinking about?

Welcome back to TechCrunch Mobility, your hub for the future of transportation and now, more than ever, how AI is playing a part.

University of Leicester historian thinks Eilmer of Malmesbury saw two different comets: in 1018 and 1066

Hoping to catch some World Cup matches while spending as little money as possible? You have a few options for finding a few days of free streaming, although you may choose to eventually pony up some money. That, or get creative by combining multiple offers to make it through the whole tournament. We found a […]

So you built your stack on a hosted frontier model. Good throughput, clean API, your foreign-national engineers hit the same endpoint as everyone else. Then on June 12 the US government pulled Claude Fable 5 and Mythos 5 offline for the entire planet, three days after launch, and the reason is a compliance gap baked into how these things actually serve traffic. Here's the thing worth understanding as an engineer: the bug was narrow. The takedown wasn't. The gap between those two facts is where every team running a hosted model should be paying attention. What actually triggered it Commerce hit Anthropic with an order barring access to both models by any foreign national, anywhere, inside or outside the US, including Anthropic's own foreign-national staff. The stated trigger was a jailbreak: point the model at a codebase, ask it to find flaws. That's it. Anthropic reviewed the demo and watched it surface a handful of already-known minor vulns, the kind GPT-5.5 and other public models hand you with no bypass at all. So the capability wasn't exotic. It was automated code review on a Tuesday. The reason it went nuclear is the legal layer sitting on top, not the finding itself. The architecture problem: you can't gate on a passport you can't see Walk it through like any other access-control question. The restriction names a class of users: foreign nationals. Every one of them, globally. Now look at what a model API knows about a session at request time. restriction: deny any foreign national, anywhere session metadata: auth token, IP, usage tier NOT in session: verified nationality isolatable set: ∅ only compliant state: serve nobody An API session doesn't carry a verified passport. IP geolocation is trivially defeated by a VPN and tells you location, not citizenship anyway. There's no field in the request that maps to the restricted class. When you can't isolate the users you're forbidden to serve, the only provably-compliant state is serving no one. Off switch. Global.

Rust promises memory safety without garbage collection. That's why many of us dream of writing a kernel in it. After several years of building a from‑scratch operating system in Rust, I've collected the real — not theoretical — challenges that will make you question your life choices. Here are the five hardest problems, and the pragmatic solutions that actually work. 1. The unsafe Infection: Your Core is Not Safe The kernel's job is to manage memory, poke hardware registers, and handle interrupts. That means unsafe is not an exception — it's the norm. The problem : A single unsafe block can corrupt state that safe code depends on. In userspace, you isolate unsafe behind a small API. In the kernel, the entire bottom layer is unsafe . A bug in the page fault handler trashes everything. What doesn't work : Pretending that "only 5% of the code is unsafe ". In practice, the scheduler, the memory allocator, the interrupt handlers — they all need unsafe . You can't push it to the edges. What works : Treat unsafe as a capability . Every unsafe function must have a // SAFETY: comment explaining why it's sound. Use static assertions ( const_assert! ) to validate invariants at compile time. Isolate hardware access behind a hal crate where unsafe is contained, but don't cheat — the rest of the kernel still needs unsafe for core operations. Example — writing to a memory-mapped register: /// SAFETY: addr must be a valid MMIO address for this device, /// aligned to 4 bytes, and the caller must hold the device lock. pub unsafe fn mmio_write(addr: *mut u32, value: u32) { addr.write_volatile(value); } The comment doesn't make it safe — it documents the contract so the caller knows what they must guarantee. Memory Allocation Before alloc You want Vec, Box, Arc. But alloc requires a global allocator. The allocator requires a lock. The lock requires a working scheduler. The scheduler requires memory allocation. Classic chicken‑and‑egg. The problem: You can't allocate memory to create th

Six months ago I moved my RAG pipeline from Pinecone to self-hosted Qdrant. My vector search bill went from $210/month to $6.50/month. Same latency. Same recall. Here's exactly how. The Setup My app does document Q&A for legal contracts. The numbers: 5.2 million vectors (1536-dim, OpenAI embeddings) ~800K queries/month P99 latency requirement: < 50ms On Pinecone Serverless, this cost me roughly $210/month — storage plus read units plus write units for daily ingestion of new documents. What I Moved To A single Hetzner CX32 server: 4 vCPU, 8 GB RAM, 80 GB SSD €8.50/month (about $9.20) Qdrant running in Docker Automated daily backups to S3-compatible storage ($0.50/month) Total: ~$10/month. That's a 95% cost reduction. The Migration Was Easier Than Expected bash# Export from Pinecone (I used their scroll API) python export_pinecone.py --index legal-docs --output vectors.jsonl Start Qdrant docker run -d -p 6333:6333 -v ./storage:/qdrant/storage qdrant/qdrant Import python import_qdrant.py --input vectors.jsonl --collection legal-docs The whole migration took an afternoon. The Qdrant Python client is straightforward, and the API is surprisingly similar to Pinecone's. Performance Comparison I ran the same 10,000 test queries against both setups: MetricPinecone ServerlessQdrant Self-HostedP50 latency23ms4msP99 latency89ms12msRecall@100.970.97Monthly cost$210$10 The self-hosted Qdrant is actually faster because the data sits in memory on the same machine. Pinecone Serverless loads data from object storage on demand, which adds cold-start latency. When Self-Hosting Is a Bad Idea I want to be honest about the trade-offs: Don't self-host if: You have zero DevOps experience and no one on the team does You need 99.99% uptime SLA for enterprise customers Your vector count is growing unpredictably (10M one month, 100M the next) You're a team of 1-2 and every hour on infra is an hour not building product Do self-host if: Your scale is predictable (you know roughly how many vectors

The global economic architecture that governs how resources flow, how capital accumulates, and how power consolidates was not built with African flourishing as an objective. It was built with African extraction as a feature. There is a difference between a system that failed Africa and a system that is working exactly as designed. Understanding that distinction is the first act of an uncommon mind. At houseofchrys.com efforts are made to make you understand that distinction. The common African response to this reality is one of two things. Outrage that leads nowhere productive. Or hope — the expensive, professionally peddled variety that keeps people emotionally invested in a collective salvation that is always arriving and never quite here. The uncommon African response is neither. It is the cold, clear recognition that the terrain is what it is — and then the immediate pivot to the only question worth spending energy on. Given the terrain, how do I govern myself? The AI Access Gap Is the New Wealth Gap Naval Ravikant framed it cleanly. The new competition is not humans versus AI. It is humans with AI versus everyone else. The third order consequence of that framing is worth sitting with longer than most people do. If the competition is between humans with AI and everyone else then the specific question that determines where you land in that competition is not whether you use AI. It is which AI you have access to, how deeply you understand it, and how early you started building with it. Access to the most capable AI models is not evenly distributed. The most powerful systems available to a developer in San Francisco are not equally available, equally affordable, or equally optimized for the contexts and problems of someone in Lagos or Nairobi or Accra. The infrastructure gap, the payment barrier, the language and cultural gap in how these systems are trained — all of it means that the AI revolution is not arriving in Africa on equal terms with anywhere else. This i

submitted by /u/swe129 [link] [留言]