1. 22 Sep 2026

    Local start-ups are loving Chinese AI (just don't ask them about it) - AFR

    ... large language models, shows just how ubiquitous Chinese models have become. DeepSeek was the most used model provider globally last week, based ...

    www.afr.com ↗
  2. 22 Sep 2026

    Machine learning algorithm sets Intel (INTC) stock price for October 1, 2026 - Finbold

    Using predictions from DeepSeek Chat, Gemini 3.5 Flash, and GPT-5.7 Luna, the machine learning model projects Intel stock to trade at an average price ...

    finbold.com ↗
  3. 19 Sep 2026

    DeepSeek publishes V4.1-Flash: 552B MoE, 890-byte KV cache/token | AI Weekly

    TL;DR · DeepSeek-V4.1-Flash is a 552B-parameter multimodal Mixture-of-Experts model with support for contexts of up to one million tokens. · Global KV ...

    aiweekly.co ↗
  4. 16 Sep 2026

    Understanding DeepSeek V4.1 Flash, DeepMind's AlphaGenome Atlas and Muse

    The Sequence Learning ... There is another useful detail: DeepSeek reports that post-training retains supervised fine-tuning, reinforcement learning and ...

    thesequence.substack.com ↗
  5. 12 Sep 2026

    DeepSeek planned to retire V4-Pro for V4.1-Flash. They backed down in 45 hours - Medium

    The engineers used supervised fine-tuning, reinforcement learning and on-policy distillation, with no algorithmic changes. The training pipeline ...

    medium.com ↗
  6. 11 Sep 2026

    US agencies accuse six Chinese AI firms - Jon Peddie Research

    ... reinforcement learning, software engineering, and math capability. The advisory challenges DeepSeek's widely-cited $5.6 million training cost ...

    www.jonpeddie.com ↗
  7. 11 Sep 2026

    DeepSeek has released V4.1 Flash with 552 billion parameters and a KV cache four times smaller

    DeepSeek claims that, thanks to new pre-training methods and larger-scale reinforcement learning, V4.1 Flash outperforms V4 Pro in internal benchmarks ...

    mezha.ua ↗
  8. 11 Sep 2026

    DeepSeek has released V4.1 Flash with 552 billion parameters and a KV cache four times smaller

    The new multimodal AI model activates only a fraction of its parameters whilst running and requires significantly less memory to store context.

    mezha.ua ↗
  9. 11 Sep 2026

    DeepSeek-V4.1-Flash officially launches on B.AI, with the native multimodal MoE large ...

    The B.AI platform announced that DeepSeek's newly released native multimodal MoE large model, DeepSeek-V4.1-Flash, is now officially available.

    m.techflowpost.com ↗
  10. 11 Sep 2026

    Magic Matched DeepSeek V4 Pro Base Quality for $500K, Using 50 Times Less Compute

    For base models that have not yet undergone reinforcement learning or supervised fine-tuning, bpb loss is particularly important. Before RL training ...

    www.techtimes.com ↗
  11. 10 Sep 2026

    B.AI announced the launch of the DeepSeek-V4.1-Flash multimodal model

    The B.AI platform announces the official launch of the DeepSeek native multimodal MoE large model DeepSeekV4.1Flash. This model uses a backbone ...

    www.chaincatcher.com ↗
  12. 10 Sep 2026

    DeepSeek Rolls Out V4.1-Flash, Betting Native Multimodal Design Can Slash AI Agent Costs

    DeepSeek has opened community testing for an interim version of V4.1-Flash, its first natively multimodal model, which the company says delivers…

    finance.biggo.com ↗
  13. 10 Sep 2026

    DeepSeek rolls out V4.1-Flash as it targets faster, lower-cost AI

    The company said new pre-training methods and larger-scale reinforcement learning post-training have delivered benchmark results ahead of its flagship ...

    enterpriseai.economictimes.indiatimes.com ↗
  14. 10 Sep 2026

    DeepSeek rolls out V4.1-Flash as it targets faster, lower-cost AI

    Making AI Work: Chinese AI startup DeepSeek has introduced ... multimodal capabilities, as they prepare for an IPO to fund future developments.

    enterpriseai.economictimes.indiatimes.com ↗
  15. 10 Sep 2026

    DeepSeek posts V4.1-Flash: 552B MoE, 8B active, 1M context | AI Weekly

    DeepSeek posted a new model card on Hugging Face for DeepSeek-V4.1-Flash, a 552B-parameter multimodal Mixture-of-Experts release under an MIT ...

    aiweekly.co ↗
  16. 10 Sep 2026

    DeepSeek Launches V4.1-Flash to Make Large-Scale AI Inference Cheaper | AIM

    The company has made V4.1-Flash available through its API with native multimodal support. DeepSeek has retired V4-Flash and V4-Flash-Vision-Exp ...

    analyticsindiamag.com ↗
  17. 10 Sep 2026

    China's DeepSeek Launches Smaller, Faster AI Model - Caixin Global

    The new DeepSeek-V4.1-Flash is a 552-billion-parameter mixture-of-experts model with native multimodal visual understanding. DeepSeek said the model ...

    www.caixinglobal.com ↗
  18. 08 Sep 2026

    DeepSeek Launches Two-Day Limited Beta for V4.1 Flash - BigGo Finance

    ... Multimodal Capabilities. 2026-09-08 02 ... How does that affect the pricing strategies of other Chinese AI companies like Zhipu and Moonshot AI?

    finance.biggo.com ↗
Sources

Where this comes from

Artificial Intelligence — Google

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

401 items Polled 22 Sep, 18:24 UTC 200

Agentic AI — Google

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

401 items Polled 22 Sep, 18:24 UTC 200

AI Agents — Google

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

401 items Polled 22 Sep, 18:24 UTC 200

Data Science — Google

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

401 items Polled 22 Sep, 18:24 UTC 200

Large Language Model — Google

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

401 items Polled 22 Sep, 18:24 UTC 200

Machine Learning — Google

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

401 items Polled 22 Sep, 18:24 UTC 200

Deep Learning — Google

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

401 items Polled 22 Sep, 18:24 UTC 200

LLMs Alignment — Google

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

45 items Polled 22 Sep, 18:24 UTC 200

AI Alignment — Google

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

401 items Polled 22 Sep, 18:24 UTC 200

Representation Learning — Google

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

146 items Polled 22 Sep, 18:25 UTC 200

Reinforcement Learning — Google

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

401 items Polled 22 Sep, 18:25 UTC 200

Generative AI — Google

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

401 items Polled 22 Sep, 18:25 UTC 200

Multimodal AI — Google

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

401 items Polled 22 Sep, 18:25 UTC 200

Mechanistic Interpretability — Google

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

33 items Polled 22 Sep, 18:25 UTC 200

RLHF — Google

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

32 items Polled 22 Sep, 18:25 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.