<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0">
<channel>
  <title>AI Radar · Research</title>
  <link>https://ai-radar-ik42.pages.dev/en/</link>
  <description>AI Radar aggregates official AI blogs, GitHub releases, trusted media and community discussion, clusters sources describing the same event, labels verification status, and keeps tracking follow-ups.</description>
  <language>en</language>
  <item>
    <title>[Limited sources] Optimizing Qwen3.6 / Qwen3.8-27B on 16GB VRAM: Complete Benchmark Results and Setup Guide (~30-50tps at 32k to 72k context)</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-88117478c6ef/index.html</link>
    <guid isPermaLink="false">ev-88117478c6ef-en</guid>
    <pubDate>Tue, 18 Aug 2026 02:28:24 GMT</pubDate>
    <description>Limited sources · 1 src · This post was made with AI. I tried to remove as much slop as possible and keep it straight to the point to save your time as I know how annoying AI slop posts can be, but I still wanted to retain all the details so it can be used as a resource for comparison with other future q…</description>
  </item>
  <item>
    <title>[Limited sources] we benchmark models nobody actually runs</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-1aa471d129fc/index.html</link>
    <guid isPermaLink="false">ev-1aa471d129fc-en</guid>
    <pubDate>Mon, 17 Aug 2026 21:53:54 GMT</pubDate>
    <description>Limited sources · 1 src · qwen3.8-27b looks genuinely impressive on the benchmark tables - beating models many times its size on some of them. but those numbers come from bf16 weights, and nobody here is running a 27b at bf16. we&#39;re running the 4-bit at ~17gb because that&#39;s what fits on a 4090 or a 24gb…</description>
  </item>
  <item>
    <title>[Limited sources] Benchmarked Qwen3.8-27B on 4x RTX 3090</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-4f8f243ce02f/index.html</link>
    <guid isPermaLink="false">ev-4f8f243ce02f-en</guid>
    <pubDate>Mon, 17 Aug 2026 21:17:41 GMT</pubDate>
    <description>Limited sources · 1 src · A while back I made a post about my 4x3090 rig in a Silverstone RV-02 . Check it out if you&#39;re a conoissuer of OG PC cases. With the incredible Qwen 3.8 27B release I ran benchmarks. So in case you are rocking 3090s you might be interested in this. Everything below is entirely L…</description>
  </item>
  <item>
    <title>[Limited sources] Local agentic coding Benchmark : Qwen 3.8 27B (in many weights quants / cache quants / engine / reasoning effort) vs others.</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-f32b2a2af121/index.html</link>
    <guid isPermaLink="false">ev-f32b2a2af121-en</guid>
    <pubDate>Mon, 17 Aug 2026 20:45:23 GMT</pubDate>
    <description>Limited sources · 1 src · In medium reasoning mode, it both scores higher than the 3.6 version, AND is very much more efficient (almost half requests needed, and a third less tokens generated) - at DeepSeek v4 Flash 3107 MXFP4 level
The xhigh mode is advertised to be the best one for hard tasks. In this…</description>
  </item>
  <item>
    <title>[Limited sources] Artificial Analysis&#39; Qwen3.8-27B benchmarks put it neck and neck with DeepSeek V4 and GPT-5.6 Luna Max</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-4de3452cd1db/index.html</link>
    <guid isPermaLink="false">ev-4de3452cd1db-en</guid>
    <pubDate>Mon, 17 Aug 2026 17:26:46 GMT</pubDate>
    <description>Limited sources · 1 src · submitted by /u/anderspitman
[link] [comments]</description>
  </item>
  <item>
    <title>[Limited sources] [Paper] Intern-S2-Mobius: Foundation Model with Decoupled Knowledge and Reasoning</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-a30357b6312b/index.html</link>
    <guid isPermaLink="false">ev-a30357b6312b-en</guid>
    <pubDate>Mon, 17 Aug 2026 12:49:03 GMT</pubDate>
    <description>Limited sources · 1 src · We introduce Mobius-v0, an architecture that comprises a globally shared Memory (FFN) that stores knowledge vectors and multiple Reasoners (Self-Attn) that iteratively achieve compositional reasoning. Using hidden states as cache and carrier, reasoners repeatedly query memory fo…</description>
  </item>
  <item>
    <title>[Limited sources] LLM&#39;s can&#39;t &quot;jump&quot; - a paper by Deepmind showing LLMs can&#39;t generate novel explanatory hypotheses</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-d666afc16f4e/index.html</link>
    <guid isPermaLink="false">ev-d666afc16f4e-en</guid>
    <pubDate>Mon, 17 Aug 2026 09:58:16 GMT</pubDate>
    <description>Limited sources · 1 src · submitted by /u/juanviera23
[link] [comments]</description>
  </item>
  <item>
    <title>[Confirmed] What We Learned by Reproducing 2,200 papers from ICML</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-80d2b1019426/index.html</link>
    <guid isPermaLink="false">ev-80d2b1019426-en</guid>
    <pubDate>Thu, 13 Aug 2026 00:00:00 GMT</pubDate>
    <description>Confirmed · 1 src · </description>
  </item>
  <item>
    <title>[Confirmed] AMIE, our research medical AI system, demonstrates real-time clinical video consultation capabilities in a first-of-its-kind study.</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-f3e7c9ebce6a/index.html</link>
    <guid isPermaLink="false">ev-f3e7c9ebce6a-en</guid>
    <pubDate>Tue, 11 Aug 2026 17:00:00 GMT</pubDate>
    <description>Confirmed · 1 src · AMIE promotional video</description>
  </item>
  <item>
    <title>[Confirmed] Third-party cyber evaluations involving OpenAI models</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-37aa7ebe2f1d/index.html</link>
    <guid isPermaLink="false">ev-37aa7ebe2f1d-en</guid>
    <pubDate>Tue, 04 Aug 2026 19:00:00 GMT</pubDate>
    <description>Confirmed · 1 src · OpenAI explains recent third-party cybersecurity evaluation incidents and outlines new safeguards to strengthen AI model testing and evaluation.</description>
  </item>
  <item>
    <title>[Confirmed] How enabling two settings tripled our scores on the ARC-AGI-3 benchmark</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-b29d9984715a/index.html</link>
    <guid isPermaLink="false">ev-b29d9984715a-en</guid>
    <pubDate>Wed, 29 Jul 2026 15:00:00 GMT</pubDate>
    <description>Confirmed · 1 src · How two API settings improved GPT-5.6 performance on ARC-AGI-3, boosting scores and efficiency by retaining reasoning and enabling compaction.</description>
  </item>
  <item>
    <title>[Confirmed] Accelerating scientific discovery with ChatGPT for Academic Researchers</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-7094112115d8/index.html</link>
    <guid isPermaLink="false">ev-7094112115d8-en</guid>
    <pubDate>Wed, 29 Jul 2026 10:00:00 GMT</pubDate>
    <description>Confirmed · 1 src · OpenAI is giving 100,000 academic researchers free access to ChatGPT&#39;s most advanced AI models to accelerate scientific research, collaboration, and discovery.</description>
  </item>
  <item>
    <title>[Confirmed] OpenAI and Hugging Face partner to address security incident during model evaluation</title>
    <link>https://ai-radar-ik42.pages.dev/en/event/ev-95209b786bce/index.html</link>
    <guid isPermaLink="false">ev-95209b786bce-en</guid>
    <pubDate>Tue, 21 Jul 2026 07:00:00 GMT</pubDate>
    <description>Confirmed · 1 src · OpenAI and Hugging Face share early findings from a security incident during AI model evaluation, highlighting advanced cyber capabilities and lessons for defenders.</description>
  </item>
</channel>
</rss>
