Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

AtScale Introduces Industry-First Public Leaderboard for Text-to-SQL Solutions, Setting Transparent Standards for Natural Language Query (NLQ) Evaluation

AtScale, a leader in semantic layer technology, has launched an open, public leaderboard for Text-to-SQL (T2SQL) solutions, addressing a critical need for transparency and standardization in evaluating natural language data query capabilities. This resource enables academia, vendors, and developers to measure and compare T2SQL performance on a consistent, replicable benchmark using an industry standard open dataset, schema, and evaluation methods.

Also Read: Segmind Adds Recraft-V3-SVG, Bringing Scalable Vector Graphics to Its Creative Platform

“Enable Natural Language Prompting with AtScale’s Semantic Layer & Generative AI”

The surge in interest for T2SQL solutions, fueled by Generative AI advancements, enables non-technical users to ask complex questions of proprietary data without SQL skills. However, inconsistent and proprietary evaluation methods make it challenging to validate or compare these solutions. AtScale’s public benchmark solves this issue, providing an objective framework inspired by canonical benchmarks, like TPC-DS, and metrics that account for query and schema complexity.

Related Posts
1 of 41,260

“AtScale’s leaderboard sets a new standard for transparency in Text-to-SQL evaluation,” said John Langton, Head of Engineering at AtScale. “By creating an open, objective framework, we’re enabling the industry to validate and improve solutions that make natural language data queries more accessible and reliable for everyone.”

Also Read:Segmind Adds Recraft-V3-SVG, Bringing Scalable Vector Graphics to Its Creative Platform

The AtScale Text-to-SQL Leaderboard includes:

  • Open Benchmarking Environment: A public GitHub repository with detailed download instructions for the TPC-DS dataset, evaluation questions, KPI definitions, and scoring methods that serve as a replicable standard for T2SQL evaluations.
  • Objective Complexity Metrics: Evaluation metrics that consider question and schema complexity, with scores across two dimensions:
    • Question Complexity: Measures the complexity of KPIs required to answer a question, from simple selections to complex aggregations.
    • Schema Complexity: Captures the number of tables needed to answer a question accurately, with questions requiring five or more tables rated as high complexity.
  • Real-Time Public Leaderboard: An industry-first live performance tracker that displays the scores of T2SQL solutions, fostering transparency and competition.
  • Community Collaboration: As a community resource, the leaderboard encourages participation, feedback, and collaborative improvement, allowing the industry to continuously refine the evaluation framework.

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

Comments are closed.