About this Dataset

Parameter, Compute And Data Trends In Machine Learning (Epoch, 2023)

The affiliation of the research team building a particular notable AI system was classified according to the following:
— Academia: 100% of researchers affiliated with academia
— Collaboration, Academia-majority: 71–99% affiliated with academia
— Collaboration: 30–70% affiliated with academia
— Collaboration, Industry-majority: 71–99% affiliated with industry
— Industry: 100% of researchers affiliated with industry

This data corresponds to the "Organization Categorization" and "Domain" columns in the primary source data spreadsheet.

The authors selected the AI systems for inclusion based on the following necessary criteria:
— Have an explicit learning component
— Showcase experimental results
— Advance the state of the art

In addition, the systems had to meet at least one of the following notability criteria:
— Paper has more than 1000 citations
— Historical importance
— Important state-of-the-art advance
— Deployed in a notable context

The authors note that: "For new models (from 2020 onward) it is harder to assess these criteria, so we fall back to a subjective selection. We refer to models meeting our selection criteria as 'milestone models.'"
In cases where the model name was unavailable, OWID uses the institution name that published the model for identification.

Tables

Epoch 1

@owid.epoch.owid_epoch_1

33.08 kB
393 rows
11 columns

CREATE TABLE owid_epoch_1 (
  "index" BIGINT,
  "system" VARCHAR,
  "days_since_1949" INTEGER,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "publication_date" TIMESTAMP,
  "parameters" BIGINT,
  "training_compute_flop" FLOAT  -- Training Compute, Flop,
  "training_dataset_size_datapoints" VARCHAR  -- Training Dataset Size, Datapoints,
  "training_time_hours" FLOAT  -- Training Time, Hours,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_10

40.17 kB
890 rows
8 columns

CREATE TABLE owid_epoch_10 (
  "days_since_1949" INTEGER,
  "model" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" BIGINT,
  "training_dataset_size_datapoints" BIGINT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_11

41.59 kB
926 rows
8 columns

CREATE TABLE owid_epoch_11 (
  "days_since_1949" INTEGER,
  "model" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" BIGINT,
  "training_dataset_size_datapoints" BIGINT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_12

35.93 kB
805 rows
9 columns

CREATE TABLE owid_epoch_12 (
  "days_since_1949" INTEGER,
  "system" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" FLOAT,
  "training_dataset_size_datapoints" FLOAT  -- Training Dataset Size, Datapoints,
  "approach" VARCHAR,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_2

36.46 kB
837 rows
8 columns

CREATE TABLE owid_epoch_2 (
  "days_since_1949" INTEGER,
  "system" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" FLOAT,
  "training_dataset_size_datapoints" FLOAT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_3

37.65 kB
865 rows
8 columns

CREATE TABLE owid_epoch_3 (
  "days_since_1949" INTEGER,
  "system" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" FLOAT,
  "training_dataset_size_datapoints" FLOAT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_4

36.37 kB
825 rows
8 columns

CREATE TABLE owid_epoch_4 (
  "days_since_1949" INTEGER,
  "system" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" FLOAT,
  "training_dataset_size_datapoints" FLOAT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_5

36.51 kB
828 rows
8 columns

CREATE TABLE owid_epoch_5 (
  "days_since_1949" INTEGER,
  "system" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" FLOAT,
  "training_dataset_size_datapoints" FLOAT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_6

37.84 kB
867 rows
8 columns

CREATE TABLE owid_epoch_6 (
  "days_since_1949" INTEGER,
  "system" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" FLOAT,
  "training_dataset_size_datapoints" FLOAT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_7

39.2 kB
862 rows
8 columns

CREATE TABLE owid_epoch_7 (
  "days_since_1949" INTEGER,
  "system" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" BIGINT,
  "training_dataset_size_datapoints" BIGINT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_8

39.47 kB
869 rows
8 columns

CREATE TABLE owid_epoch_8 (
  "days_since_1949" INTEGER,
  "model" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" BIGINT,
  "training_dataset_size_datapoints" BIGINT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);

Parameter, Compute And Data Trends In Machine Learning

@owid.epoch.owid_epoch_9

40.08 kB
889 rows
8 columns

CREATE TABLE owid_epoch_9 (
  "days_since_1949" INTEGER,
  "model" VARCHAR,
  "publication_date" TIMESTAMP,
  "domain" VARCHAR,
  "organization_categorization" VARCHAR,
  "parameters" BIGINT,
  "training_dataset_size_datapoints" BIGINT  -- Training Dataset Size, Datapoints,
  "training_computation_petaflop" FLOAT
);