Dontopedia

M

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-20.)

M is Number of subquantizers.

60 facts·26 predicates·20 sources·7 in dispute

Mostly:rdf:type(14), description(4), has value(4)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Inbound mentions (27)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

hasParameterHas Parameter(7)

assignedToAssigned to(2)

affectedByAffected by(1)

appliedToApplied to(1)

balancedByBalanced by(1)

constructedWithConstructed With(1)

createdWithParametersCreated With Parameters(1)

describedForDescribed for(1)

describesDescribes(1)

equalsEquals(1)

hasHypothesisOnHas Hypothesis on(1)

hasMHas M(1)

hasModuleHas Module(1)

hasMParameterHas M Parameter(1)

hasNumAnchorsHas Num Anchors(1)

involvesParameterInvolves Parameter(1)

isSumOverIs Sum Over(1)

parametersParameters(1)

sentBySent by(1)

usesParameterUses Parameter(1)

Other facts (39)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

39 facts
PredicateValueRef
DescriptionNumber of subquantizers[7]
DescriptionNumber of subquantizers[8]
Descriptionnumber-of-sub-quantizers[12]
DescriptionParameter to balance memory usage and query speed[16]
Has Value8[8]
Has Value8[9]
Has Value8[13]
Has Value8[15]
AffectsSubquantizer Count[14]
AffectsMemory Usage[16]
AffectsQuery Speed[16]
Affectssubquantizer-count[17]
Donated toMaryborough Benevolent Institution[1]
Donated toMaryborough Benevolent Institution[2]
Is Parameter ofIndex Ivfpq[6]
Is Parameter ofIndexIVFPQ[14]
ControlsSubquantizer Count[8]
Controlssubquantizer_count[14]
Representsnumber of subquantizers[13]
Representsnumber of subquantizers[14]
Equals8[17]
Equalsnbytes[17]
Donation Amount£2[1]
OffersFrench Music Needlework Lessons[3]
Has AddressBox 9 Office This Paper[3]
Stands forMinute[4]
Rolenumber of subquantizers[5]
Typical Value8[5]
Parameter Value8[7]
Value8[12]
Commentnumber of subquantizers[15]
Used inFaiss.index Ivfpq[15]
PurposeBalance Memory and Speed[16]
Controlled byCreate Ivfpq Index[16]
Default8[17]
DescribesNumber of subquantizers[17]
Assigned Value8[18]
HaspublicationdateChristmas 1894[20]
Haspagerange97–100[20]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

donatedTotrove-cooktown/beche-de-mer
ex:maryborough-benevolent-institution
donationAmounttrove-cooktown/beche-de-mer
£2
donatedTobrackenridge-cairns-1880-1900/trove-new/146785816_Saturday-7-May-1887_LOCAL-NEWS
ex:maryborough-benevolent-institution
offersrosie-reynolds-massacre-connection/trove-hartley-sykes-oconnor-cape-bedford-289344095
ex:french-music-needlework-lessons
hasAddressrosie-reynolds-massacre-connection/trove-hartley-sykes-oconnor-cape-bedford-289344095
ex:box-9-office-this-paper
standsForblucher-uhr/sqlite--qsa-32042220--qsa847166-1885-telegram-from-reginald-uhr-to-under-colonial-secretary-27-august,-colonial-
Minute
typebeam/aaea2d5a-2786-4bf1-840d-700a9d6307af
ex:Parameter
rolebeam/aaea2d5a-2786-4bf1-840d-700a9d6307af
number of subquantizers
typicalValuebeam/aaea2d5a-2786-4bf1-840d-700a9d6307af
8
typebeam/2923b0ab-4ec2-4f48-9528-ef9982bfeed5
ex:SubquantizerCountParameter
typebeam/2923b0ab-4ec2-4f48-9528-ef9982bfeed5
ex:SubquantizerCount
typebeam/2923b0ab-4ec2-4f48-9528-ef9982bfeed5
ex:Parameter
isParameterOfbeam/2923b0ab-4ec2-4f48-9528-ef9982bfeed5
ex:IndexIVFPQ
typebeam/01d47e70-2678-4424-bb6e-17ebfb57cf51
ex:Parameter
parameterValuebeam/01d47e70-2678-4424-bb6e-17ebfb57cf51
8
descriptionbeam/01d47e70-2678-4424-bb6e-17ebfb57cf51
Number of subquantizers
hasValuebeam/9c3d6c77-2b58-4a3b-9618-59e705c00dfd
8
descriptionbeam/9c3d6c77-2b58-4a3b-9618-59e705c00dfd
Number of subquantizers
controlsbeam/9c3d6c77-2b58-4a3b-9618-59e705c00dfd
ex:subquantizer-count
hasValuebeam/ea1c880d-666a-428b-9f18-ae4bdd751abe
8
typeblah/atlas-ai/2
ex:Subdomain
labelblah/atlas-ai/2
mobile subdomain
typebeam/b296f27d-a550-49c1-ae24-6118c21f96b1
ex:Variable
labelbeam/b296f27d-a550-49c1-ae24-6118c21f96b1
Number of usage patterns
typebeam/49101dfd-4fc4-460c-9cd9-8e0457730c83
ex:Parameter
labelbeam/49101dfd-4fc4-460c-9cd9-8e0457730c83
M
valuebeam/49101dfd-4fc4-460c-9cd9-8e0457730c83
8
descriptionbeam/49101dfd-4fc4-460c-9cd9-8e0457730c83
number-of-sub-quantizers
typebeam/c987e07c-dc22-48c0-aadb-1075131743e6
ex:variable
representsbeam/c987e07c-dc22-48c0-aadb-1075131743e6
number of subquantizers
hasValuebeam/c987e07c-dc22-48c0-aadb-1075131743e6
8
representsbeam/4efeeb64-8572-49af-812f-e5accd46c4ad
number of subquantizers
typebeam/4efeeb64-8572-49af-812f-e5accd46c4ad
ex:IndexParameter
labelbeam/4efeeb64-8572-49af-812f-e5accd46c4ad
m
isParameterOfbeam/4efeeb64-8572-49af-812f-e5accd46c4ad
IndexIVFPQ
affectsbeam/4efeeb64-8572-49af-812f-e5accd46c4ad
ex:subquantizer_count
controlsbeam/4efeeb64-8572-49af-812f-e5accd46c4ad
subquantizer_count
hasValuebeam/c5e65b2e-6289-4399-808e-64fe4e0eddce
8
typebeam/c5e65b2e-6289-4399-808e-64fe4e0eddce
ex:Variable
labelbeam/c5e65b2e-6289-4399-808e-64fe4e0eddce
m
commentbeam/c5e65b2e-6289-4399-808e-64fe4e0eddce
number of subquantizers
usedInbeam/c5e65b2e-6289-4399-808e-64fe4e0eddce
ex:faiss.IndexIVFPQ
typebeam/16e72a23-0e74-4398-83f0-1a6963cbc18d
ex:Parameter
labelbeam/16e72a23-0e74-4398-83f0-1a6963cbc18d
m
descriptionbeam/16e72a23-0e74-4398-83f0-1a6963cbc18d
Parameter to balance memory usage and query speed
purposebeam/16e72a23-0e74-4398-83f0-1a6963cbc18d
ex:balanceMemoryAndSpeed
affectsbeam/16e72a23-0e74-4398-83f0-1a6963cbc18d
ex:memory-usage
affectsbeam/16e72a23-0e74-4398-83f0-1a6963cbc18d
ex:query-speed
controlledBybeam/16e72a23-0e74-4398-83f0-1a6963cbc18d
ex:create_ivfpq_index
typebeam/3aa97b5d-2401-4a53-a5d0-4cd1d9b8e042
ex:Parameter
defaultbeam/3aa97b5d-2401-4a53-a5d0-4cd1d9b8e042
8
describesbeam/3aa97b5d-2401-4a53-a5d0-4cd1d9b8e042
Number of subquantizers
equalsbeam/3aa97b5d-2401-4a53-a5d0-4cd1d9b8e042
8
affectsbeam/3aa97b5d-2401-4a53-a5d0-4cd1d9b8e042
subquantizer-count
equalsbeam/3aa97b5d-2401-4a53-a5d0-4cd1d9b8e042
nbytes
assignedValuebeam/9170f193-72c4-43d3-9c09-87f869d91b8b
8
typebeam/a5fc8118-22f9-47dc-ab75-3a5765c02306
ex:Variable
labelbeam/a5fc8118-22f9-47dc-ab75-3a5765c02306
number of stages
haspublicationdatemoore-making-mala-ch3
Christmas 1894
haspagerangemoore-making-mala-ch3
97–100

References (20)

20 references
  1. [1]Beche De Mer2 facts
    ctx:genes/trove-cooktown/beche-de-mer
  2. ctx:genes/brackenridge-cairns-1880-1900/trove-new/146785816_Saturday-7-May-1887_LOCAL-NEWS
  3. ctx:genes/rosie-reynolds-massacre-connection/trove-hartley-sykes-oconnor-cape-bedford-289344095
  4. ctx:research/blucher-uhr/sqlite--qsa-32042220--qsa847166-1885-telegram-from-reginald-uhr-to-under-colonial-secretary-27-august,-colonial-
  5. ctx:claims/beam/aaea2d5a-2786-4bf1-840d-700a9d6307af
  6. ctx:claims/beam/2923b0ab-4ec2-4f48-9528-ef9982bfeed5
  7. ctx:claims/beam/01d47e70-2678-4424-bb6e-17ebfb57cf51
  8. ctx:claims/beam/9c3d6c77-2b58-4a3b-9618-59e705c00dfd
    • full textbeam-chunk
      text/plain1 KBdoc:beam/9c3d6c77-2b58-4a3b-9618-59e705c00dfd
      Show excerpt
      # Normalize the vectors for cosine similarity faiss.normalize_L2(vectors) # Create an IVFPQ index nlist = 100 # Number of clusters m = 8 # Number of subquantizers index = faiss.IndexIVFPQ(faiss.IndexFlatL2(128), 128, nlist, m, 8) # 8 is
  9. ctx:claims/beam/ea1c880d-666a-428b-9f18-ae4bdd751abe
    • full textbeam-chunk
      text/plain1 KBdoc:beam/ea1c880d-666a-428b-9f18-ae4bdd751abe
      Show excerpt
      index = faiss.IndexHNSWFlat(128, M) index.hnsw.efConstruction = efConstruction index.hnsw.efSearch = efSearch index.add(vectors) # Measure initial performance start_time = time.time() distances, indices = search_similar_vectors(query_vecto
  10. [10]22 facts
    ctx:discord/blah/atlas-ai/2
    • full textctx:discord/blah/atlas-ai/2
      text/plain3 KBdoc:discord/blah/atlas-ai/2
      Show excerpt
      [2025-04-04 05:23] lisamegawatts: I had a polisci professor that worked on this, he used to say theory is fine but no match for data https://correlatesofwar.org/ [2025-04-04 05:23] lisamegawatts: Trying to catalog and predict all factors th
    • full textatlas-ai-2
      text/plain3 KBdoc:agent/atlas-ai-2/3a79ad11-fcb3-4da8-b38e-c15390bfab94
      Show excerpt
      [2025-04-04 05:23] lisamegawatts: I had a polisci professor that worked on this, he used to say theory is fine but no match for data https://correlatesofwar.org/ [2025-04-04 05:23] lisamegawatts: Trying to catalog and predict all factors th
  11. ctx:claims/beam/b296f27d-a550-49c1-ae24-6118c21f96b1
  12. ctx:claims/beam/49101dfd-4fc4-460c-9cd9-8e0457730c83
    • full textbeam-chunk
      text/plain1 KBdoc:beam/49101dfd-4fc4-460c-9cd9-8e0457730c83
      Show excerpt
      - Adjust the search parameters like `efSearch` for `IndexHNSW` to balance between speed and accuracy. ### Example Implementation Here's an optimized version of your code using `IndexIVFPQ` and enabling multi-threading: ```python impor
  13. ctx:claims/beam/c987e07c-dc22-48c0-aadb-1075131743e6
    • full textbeam-chunk
      text/plain1 KBdoc:beam/c987e07c-dc22-48c0-aadb-1075131743e6
      Show excerpt
      1. **Create an Index**: Choose an appropriate index type that balances speed and accuracy. 2. **Add Embeddings**: Add your embeddings to the index. 3. **Search for Nearest Neighbors**: Perform the search and optimize the parameters for bett
  14. ctx:claims/beam/4efeeb64-8572-49af-812f-e5accd46c4ad
    • full textbeam-chunk
      text/plain1 KBdoc:beam/4efeeb64-8572-49af-812f-e5accd46c4ad
      Show excerpt
      query_vector = np.random.rand(1, 128).astype("float32") # Search for nearest neighbors k = 10 # number of nearest neighbors to retrieve D, I = index.search(query_vector, k) # Print the results print("Distances:", D) print("Indices:", I)
  15. ctx:claims/beam/c5e65b2e-6289-4399-808e-64fe4e0eddce
    • full textbeam-chunk
      text/plain1 KBdoc:beam/c5e65b2e-6289-4399-808e-64fe4e0eddce
      Show excerpt
      m = 8 # number of subquantizers index = faiss.IndexIVFPQ(faiss.MetricType.L2, d, nlist, m, 8) # Train the index index.train(embeddings) # Add the embeddings to the index index.add(embeddings) # Generate a query embedding in a different
  16. ctx:claims/beam/16e72a23-0e74-4398-83f0-1a6963cbc18d
    • full textbeam-chunk
      text/plain1 KBdoc:beam/16e72a23-0e74-4398-83f0-1a6963cbc18d
      Show excerpt
      - `nprobe`: Number of clusters to probe during the search. 2. **Training the Index**: - The `train` method is used to train the index on the dataset. 3. **Adding Vectors**: - The `add` method adds the vectors to the index. 4. **
  17. ctx:claims/beam/3aa97b5d-2401-4a53-a5d0-4cd1d9b8e042
  18. ctx:claims/beam/9170f193-72c4-43d3-9c09-87f869d91b8b
    • full textbeam-chunk
      text/plain1 KBdoc:beam/9170f193-72c4-43d3-9c09-87f869d91b8b
      Show excerpt
      index.nprobe = nprobe return index # Example usage: vectors = np.random.rand(10000, 128).astype(np.float32) index = create_ivfpq_index(vectors, nlist=200, m=8, nprobe=15) print(index.ntotal) # Test the index query_vectors = np.ran
  19. ctx:claims/beam/a5fc8118-22f9-47dc-ab75-3a5765c02306
  20. customctx:src/moore-making-mala-ch3
    • text/plain89 KBdoc:research/rosie-research/south-sea-islander/moore-making-mala-ch3
      Show excerpt
      Previous Making Mala 3 Malaitan Christians Overseas, 1880s–1910s It is easy to understand why labourers in Queensland should have become Christians. They were cut off from all home influences, separated from their relatives, and i

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