Amazon OpenSearch Service needs about 1.3 TB of resident RAM for 100 million 1,536-dimension FP32 vectors with one replica, a dev.to sizing post calculates. Raw vector values are about 98% of each entry, so the encoding picked before ingestion decides most of that memory and the node count behind it.
Reality
- Evidence58
- Adoption
- Insufficient
- Hype gap+5
- Incentives
- Insufficient
- Confidence62
The first VDPU samples are back from fab and go into system evaluation in the fourth quarter. Everything Dnotitia has published so far, including the 5.77x throughput claim, was measured on a four-card FPGA rig.
Reality
- Evidence38
- Adoption12
- Hype gap+22
- Incentives78
- Confidence52
A three-engine evaluation of filtered vector search on a purpose-built relational dataset credits Milvus's hybrid approximate/exact execution with stable recall, and puts pgvector's plan choice ahead of its index choice as the thing that loses it.
Reality
- Evidence52
- Adoption
- Insufficient
- Hype gap+10
- Incentives32
- Confidence55
A dev.to post lists six LLM integration mistakes with a code fix for each. Read the snippets and almost all of the failure sits in contracts the developer wrote, including a retry ceiling four attempts never reach.
Reality
- Evidence45
- Adoption
- Insufficient
- Hype gap+20
- Incentives75
- Confidence60
A systematic review grades LLM work in building automation by deployment readiness, and the pattern that clears the bar translates raw point names into a canonical schema while a human signs off on the table.
Reality
- Evidence38
- Adoption8
- Hype gap+10
- Incentives
- Insufficient
- Confidence42
The corpus is 24.47 TB. The ground truth cost more than a quadrillion distance computations. What actually changes a procurement conversation is the YAML-configured harness, which also runs against two competing engines.
Reality
- Evidence54
- Adoption18
- Hype gap+14
- Incentives80
- Confidence56
MX1 puts 3,072 in-order RISC-V cores and up to 2TB of DDR5 behind a CXL 3.2 link, betting that bandwidth-bound inference work is cheaper to run on the card than to drag across 128GB per second of host interface.
Reality
- Evidence52
- Adoption12
- Hype gap+18
- Incentives72
- Confidence50
The FAISS-plus-BM25 retrieval in this writeup does address vocabulary mismatch, but the agent loop around it ran at over 213 seconds a step on CPU, and that figure decided the deployment, not the retrieval design.
Reality
- Evidence34
- Adoption14
- Hype gap+42
- Incentives38
- Confidence56
A founder's FAISS writeup at roughly a billion face vectors argues that memory and bandwidth rank your options, which leaves the choice of what you embed as the only term you can cut without paying for it in recall.
Reality
- Evidence22
- Adoption18
- Hype gap+38
- Incentives74
- Confidence46
A build report claims 87.3% root-cause accuracy across 2,400 incident scenarios and a 59% cut in mean diagnosis time. The miss rate and the denominators deserve as much attention as the headline.
Reality
- Evidence30
- Adoption15
- Hype gap+38
- Incentives62
- Confidence52
A dev.to writeup drops vector stores for a SQLite table with tag and timestamp columns. Its own numbers put the practical ceiling at a million rows, not a hundred million.
Reality
- Evidence24
- Adoption
- Insufficient
- Hype gap+42
- Incentives
- Insufficient
- Confidence33
PixelRAG now ships as a single pip package with a Claude Code plugin. The rendering half is cheap and local; the retrieval half still wants a Linux box with a GPU.
Reality
- Evidence42
- Adoption12
- Hype gap+20
- Incentives35
- Confidence38