Cabo Verde, an archipelagic nation of just 5.25 lakh citizens, holds European champions Spain to a draw in the FIFA World Cup. What is India doing wrong in football?

Under Khruschev people ate adequate amounts of food and there was way less ethnic cleansing. What's the issue?

in case this wasnt enough, zcash has upcoming: - 3 parallel formal verifications in progress - ironwood pool supply verification - quantum proofing - tachyon pool with formal verification and simpler arithmetic - 10x higher scale - 10x miners coming all within *this* year

My interpretation of this: Right now, Anthropic and OpenAI are making a killing by selling enterprise FDE services to F500s, building workflows for them on top of proprietary models, then using the traces and context from this to build RL envs to improve the models. This is crazy amounts of leverage - instead of buying this data they're getting paid gigantic consulting fees to extract it. This also goes way beyond typical consulting in scope - organizations are effectively outsourcing key learning curves and domain knowledge to the AI labs. Despite that, it's so far been worth it for them because the value of skilled FDE is so high and the ROI so fast, and orgs are willing to pay a premium for competent AI implementation. But in the long run, one of two things happens: either orgs are gonna get hooked on this and end up paying for the model training that replaces their business, or they find a way to build and own their own model ecosystem. What that looks like is developing some combination of AI models, evals, RL envs, and workflows. Initially probably the model will still be an off-the-shelf frontier model from a top lab. But as firms build out more sophisticated eval / RL env (increasingly the same thing) infra, it starts to become viable to post-train an custom model on top of an OSS base. Cursor have done this successfully with their Composer model RL'd on top of Kimi. Sidenote, this is the same conversation that a lot of national governments in Europe are having in the past week. When we look at what the rhetoric about 'sovereign AI' in the UK actually boils down to, it's doing custom post-training on top of an OSS model, and then running it on local GPUs. Ultimately, the current feeding frenzy for AI services in all of its guises - FDE, AI consulting, etc - should raise questions about long-term sustainability. If consulting services are truly a value add and competitive advantage, then in the long term you want to in-house.