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Salesforce Research Releases SFR-AutoR&D Agent Framework

Official accountSalesforce AI Research@SFResearch
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Why we picked it

The notable part is that the agents handle infrastructure-level tasks like 1T-parameter training runs, not just code snippets, meaning automated research could compress engineering cycles that currently take teams weeks. ML engineers and platform teams can benchmark the reported gains against their own pipelines. Compared with single-task coding assistants, this targets end-to-end experiment design and validation.

Salesforce Research introduced SFR-AutoR&D, a system of AI agents designed to automate the full R&D loop from selecting experiments to verifying results.

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The framework includes AutoR&D-Engineer, which speeds up optimized code by up to 1.84x on pandas reductions, 3.

14x on generation in the RL stack, and +17.5% QPS on USearch.

A second component, TrainForge, produced gains of +11 to +14 percentage points on held-out math, code, and research benchmarks by inventing new training methods.

A third component, AutoInfra, orchestrates the work, including full-parameter training of 1T-parameter models at 1M-token context.

Original · Salesforce AI Research

1/5 🔬What if AI agents could run the entire R&D loop, from choosing what to try to proving it works?

🚨 Meet SFR-AutoR&D 🧵 https://t.co/cPiJDQDWN6

Highlights:

→ AutoR&D-Engineer makes heavily optimized code faster: up to 1.84× on pandas reductions, +17.5% QPS on USearch, and 3.14× faster generation in our RL stack → TrainForge invents new training methods: +11 to +14pp on held-out math, code, and research benchmarks → AutoInfra runs it all, including full-parameter training of 1T models at 1M-token context

Full Technical🧵👇

Industry Coordinates & Source Verification

This report is categorized under AITOP's "Models" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows and US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include Salesforce, SFR-AutoR&D, agents, AI infrastructure.

Source attribution: curated from Salesforce AI Research (@SFResearch).

#Salesforce#SFR-AutoR&D#agents#AI infrastructure

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