How many total unique AI systems will Baidu and Alibaba submit for the next round of the MLPerf benchmarking suite?
The MLPerf Benchmarking suite measures how fast systems can train models to a target quality metric. MLPerf has emerged as an industry standard for companies to publicly show how fast their hardware has become for solving machine learning problems. Here is a short summary of the current benchmarks and metrics with a detailed description of the motivation and guiding principles behind the benchmark suite.
This question will resolve using results reported on the MLCommons website for the December 2022 round. We expect results for the next submission round to be available in early December 2022. All results to date are available here. Results from previous rounds can be viewed by selecting them from the “Other Rounds” dropdown box. To count the total number of AI models submitted by Baidu and Alibaba:
This question will resolve using results reported on the MLCommons website for the December 2022 round. We expect results for the next submission round to be available in early December 2022. All results to date are available here. Results from previous rounds can be viewed by selecting them from the “Other Rounds” dropdown box. To count the total number of AI models submitted by Baidu and Alibaba:
- First, under the “Closed” tab of the spreadsheet, look for the rows where Alibaba or Baidu is listed under the “Submitter” column.
- Each row represents an AI system with a unique number in the “ID” column.
- The total number of unique AI systems is equal to the total number of rows where either Baidu or Alibaba is listed under the “Submitter” column.
Baidu made 4 submissions in v2.0 (Jun 2022) and 2 in v1.1 (Dec 2021). Alibaba made 4 submissions in v0.7 (Jul 2020) and 1 in v0.6 (Jun 2019).
Outcome
| Answer | Final crowd forecast | Resolution |
|---|---|---|
| Less than or equal to 4 | 34% | Happened |
| Between 5 and 9, inclusive | 57% | Did not happen |
| More than or equal to 10 | 9% | Did not happen |
“Final crowd forecast” is the last aggregate crowd probability computed before the question closed – the right-hand end of the chart below, which this table is the accessible equivalent of.
Crowd forecast over time
Between 5 and 9, inclusive
Less than or equal to 4
More than or equal to 10