MLOps & Infrastructure — The Latent Daily

MLOps & Infrastructure — The Latent DailyServing, cloud, GPUs and the cost of inference.https://thelatentdaily.com/en-usCompute is the new capital: why AI startups raise GPUs, not just cashhttps://thelatentdaily.com/articles/compute-is-the-new-capital-ai-startups/https://thelatentdaily.com/articles/compute-is-the-new-capital-ai-startups/For AI startups, access to GPUs can matter more than money. How cloud deals, credits and chip reservations shape who can build frontier models.Sun, 18 Oct 2026 05:55:00 GMTStartups & Fundingstartups-fundingcomputegpusclouddario_admin@resolvia-crm.techHow to cut your AI API bill: caching, batching and model routinghttps://thelatentdaily.com/articles/how-to-cut-your-ai-api-bill/https://thelatentdaily.com/articles/how-to-cut-your-ai-api-bill/Practical techniques to reduce LLM API costs without hurting quality: prompt caching, batch APIs, smaller models, routing, shorter contexts and output limits.Sun, 18 Oct 2026 05:02:00 GMTPricing & Dealspricingcost-optimizationapisdevelopersdario_admin@resolvia-crm.techVector databases explained: how they work and how to choose onehttps://thelatentdaily.com/guides/vector-databases-explained-how-to-choose/https://thelatentdaily.com/guides/vector-databases-explained-how-to-choose/Embeddings, similarity search, indexes like HNSW and the trade-offs between pgvector, Pinecone, Weaviate, Qdrant, Milvus and Chroma for your RAG project.Sun, 18 Oct 2026 04:50:00 GMTRAG, Search & Vector DBsvector-databasesragembeddingsdevelopersdario_admin@resolvia-crm.techQuantization explained: how big AI models run on small hardwarehttps://thelatentdaily.com/guides/quantization-explained-running-big-models/https://thelatentdaily.com/guides/quantization-explained-running-big-models/Quantization shrinks AI models by storing weights with fewer bits. How 8-bit and 4-bit formats work, GGUF, GPTQ and AWQ, and the quality trade-offs to expect.Sun, 18 Oct 2026 04:46:00 GMTLocal & On-device AIquantizationlocal-aiinferenceexplainerdario_admin@resolvia-crm.techHow LLM inference serving works: batching, KV cache and vLLMhttps://thelatentdaily.com/guides/how-llm-inference-serving-works-vllm/https://thelatentdaily.com/guides/how-llm-inference-serving-works-vllm/What happens when a server answers thousands of LLM requests: prefill and decode, the KV cache, continuous batching, PagedAttention and the metrics that matter.Sun, 18 Oct 2026 04:45:00 GMTMLOps & Infrastructureinferencevllmmlopsgpusdario_admin@resolvia-crm.techHow much GPU memory does an AI model need? A sizing guidehttps://thelatentdaily.com/guides/gpu-memory-sizing-for-llms/https://thelatentdaily.com/guides/gpu-memory-sizing-for-llms/Estimate the GPU memory needed to run or fine-tune a language model: weights, KV cache, activations and overhead, with worked examples for 8B and 70B models.Sun, 18 Oct 2026 04:44:00 GMTMLOps & Infrastructuregpusmlopsinferencesizingdario_admin@resolvia-crm.techHow AI is used in telecom networkshttps://thelatentdaily.com/articles/how-ai-is-used-in-telecom-networks/https://thelatentdaily.com/articles/how-ai-is-used-in-telecom-networks/Self-optimizing networks, energy savings, predictive maintenance, fraud and spam detection, customer care and AI-RAN: how telecom operators use AI, and what 6G may bring.Sun, 18 Oct 2026 03:16:00 GMTTelecomtelecom5gnetworksinfrastructuredario_admin@resolvia-crm.tech