1. 22 Sep 2026

    onPanda paper reports 52% cut in LLM alignment annotation time | AI Weekly

    If the 52% speed-up survives outside a small controlled study, labeling-vendor economics for RLHF and SFT shift; alignment leads should pilot ...

    aiweekly.co ↗
  2. 21 Sep 2026

    The Post-training Process OpenAI Used for ChatGPT - O'Reilly

    Supervised fine-tuning (SFT) on human demonstrations; Training a reward model on human preference comparisons; Reinforcement learning with human ...

    www.oreilly.com ↗
  3. 17 Sep 2026

    Salesforce Launches Koa - Destination CRM

    The Koa reasoning model and training ... To post-train the model, Salesforce applied Supervised Fine-Tuning (SFT) and reinforcement learning ...

    www.destinationcrm.com ↗
  4. 15 Sep 2026

    Salesforce, NVIDIA unveil CRM domain-specific reasoning model - CIO

    ... training corpus was designed to reflect ... Salesforce post-trained the model by applying Supervised Fine-Tuning (SFT) and reinforcement learning ...

    www.cio.com ↗
  5. 15 Sep 2026

    Build an AI-powered product tagging system with Amazon SageMaker serverless model ...

    In this walkthrough, we customize Qwen3-8B with supervised fine-tuning (SFT), then optimize it with reinforcement learning with verifiable rewards ...

    aws.amazon.com ↗
  6. 15 Sep 2026

    Build an AI-powered product tagging system with Amazon SageMaker serverless model ...

    In this walkthrough, we customize Qwen3-8B with supervised fine-tuning (SFT), then optimize it with reinforcement learning with verifiable rewards ( ...

    aws.amazon.com ↗
  7. 14 Aug 2026

    How LLMs Are Trained After Pretraining: SFT, Reward Models, and RL Without the Alphabet Soup

    After that it turned into soup. RLHF, PPO, DPO, RLVR, GRPO, reward model, value function. A pile of three- and four-letter acronyms all orbiting "fine ...

    hackernoon.com ↗
Sources

Where this comes from

Artificial Intelligence — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1990879549…

401 items Polled 22 Sep, 21:25 UTC 200

Agentic AI — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4849751788…

401 items Polled 22 Sep, 21:25 UTC 200

AI Agents — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4849751788…

401 items Polled 22 Sep, 21:25 UTC 200

Data Science — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4836803184…

401 items Polled 22 Sep, 21:25 UTC 200

Large Language Model — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/8510459957…

401 items Polled 22 Sep, 21:25 UTC 200

Machine Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4836803184…

401 items Polled 22 Sep, 21:25 UTC 200

Deep Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1643871049…

401 items Polled 22 Sep, 21:25 UTC 200

LLMs Alignment — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/5121641697…

45 items Polled 22 Sep, 21:25 UTC 200

AI Alignment — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1764885284…

401 items Polled 22 Sep, 21:25 UTC 200

Representation Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1758013403…

146 items Polled 22 Sep, 21:25 UTC 200

Reinforcement Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1720175169…

401 items Polled 22 Sep, 21:25 UTC 200

Generative AI — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/7811591585…

401 items Polled 22 Sep, 21:25 UTC 200

Multimodal AI — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/9568555102…

401 items Polled 22 Sep, 21:25 UTC 200

Mechanistic Interpretability — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/8541059511…

34 items Polled 22 Sep, 21:25 UTC 200

RLHF — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/7811591585…

36 items Polled 22 Sep, 21:25 UTC 200

Feeds are configured through the LEARN_FEEDS environment variable, so new sources can be added without a code change. Each poll sends the stored ETag and Last-Modified headers, so an unchanged feed answers 304 and costs the publisher nothing.