MongoDB said on March 20, 2026 that Heidi’s AI scribe has scaled to 81 million clinical consultations across 190+ countries in 18 months. The linked case study argues Atlas and Atlas Vector Search let Heidi consolidate heterogeneous medical data, run RAG, and scale without downtime in healthcare settings.
Google Cloud Tech highlighted BigQuery’s autonomous embedding generation preview on April 10, 2026, positioning it as a way to keep vector data in sync without separate ETL glue. The documentation shows automatically maintained embedding columns backed by Vertex AI models, plus a preview built-in model path inside BigQuery.
A March 2026 r/singularity post shared Google Research’s TurboQuant work and drew 114 points with 18 comments. Google says the method can shrink KV cache memory by at least 6x on needle tasks, quantize caches to 3 bits without training, and deliver up to 8x attention-logit speedups on H100 GPUs.
Hacker News picked up a DuckDB community extension that fixes filtered HNSW search and adds aggressive vector compression, making retrieval workloads more predictable under real SQL filters.
Hacker News picked up Google Research's TurboQuant because it promises 3-bit KV-cache compression without fine-tuning while targeting both vector search and long-context inference.