Email: Navier-Stokes breakthrough 🧮, Meta Muse 🤖, nondeterministic inference 💻

Subject:
Navier-Stokes breakthrough 🧮, Meta Muse 🤖, nondeterministic inference 💻
Received:
9/9/2026, 11:15:13 AM
From:
"TLDR Dev" <dan@tldrnewsletter.com>
To:
silk.theater.56@fwdnl.com
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&lt;div style="display: none; max-height: 0px; overflow: hidden;"&gt;OpenAI published a claimed solution to the Navier-Stokes existence and smoothness problem, produced by a system of roughly 10,000 agents&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;‌&nbsp;&lt;/div&gt;
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                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.anaconda.com%2Fblog%2Fopenai-astra-ai-security%3Futm_source=tldrdev/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/q66Thkoi80hqluvDGhVPwh55Vkv33AXbP43weaQMDXY=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;What OpenAI's Astra Means for AI Security Teams (5 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Astra's ability to discover and chain zero-day exploits makes periodic pentests inadequate as a sole defense. Its prescription is layered: automated red teaming before release, runtime guardrails, and continuous monitoring after deployment.
                                &lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
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&lt;div class="text-block"&gt;
&lt;div style="text-align: center;"&gt;&lt;span style="font-size: 36px;"&gt;🚀&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;
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&lt;div class="text-block"&gt;
&lt;div style="text-align: center;"&gt;

&lt;h1&gt;&lt;strong&gt;Launches &amp; Tools&lt;/strong&gt;&lt;/h1&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

&lt;table style="table-layout: fixed; width: 100%;" width="100%"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td style="padding:0;border-collapse:collapse;border-spacing:0;margin:0;" valign="top"&gt;

&lt;table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td class="container" style="padding: 15px 15px;"&gt;
&lt;div class="text-block"&gt;
&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.ory.com%2Fory-agent-plugins%3Futm_campaign=478444734-ADV-2026-Q3-TLDR%2520PLACEMENT-2026-09-09%26utm_source=tldr%26utm_medium=dev-newsletter/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/mtfgE9BGzxcS2DPdCd7XoZu1kwqGtMCMs2yBv6qFH68=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Between shadow AI and blind permissions: Navigating agent accountability (Sponsor)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Ory Agent Security &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.ory.com%2Fory-agent-plugins%3Futm_campaign=478444734-ADV-2026-Q3-TLDR%2520PLACEMENT-2026-09-09%26utm_source=tldr%26utm_medium=dev-newsletter/2/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/q_Q-r8T1qK8jDV73tFd2ORMbCO2LA1DfJ9b3f3jgBIU=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;closes the accountability gap&lt;/span&gt;&lt;/a&gt; with a dual-principal identity model. Every action requires explicit, distinct authentication for both the human (via OAuth 2.0 with PKCE) and the AI process itself (as a registered OAuth client). That way audit trails reflect real-time delegation: agents and users, together. &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.ory.com%2Fory-agent-plugins%3Futm_campaign=478444734-ADV-2026-Q3-TLDR%2520PLACEMENT-2026-09-09%26utm_source=tldr%26utm_medium=dev-newsletter/3/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/WCOvlnzvwPpKwkwxRkqRY4GNIGWnxfM9wgdrLcoz2dQ=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;See how&lt;/span&gt;&lt;/a&gt;
&lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

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&lt;div class="text-block"&gt;
&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.inceptionlabs.ai%2Fblog%2Fintroducing-mercury-2-5%3Futm_source=tldrdev/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/JIwFWdrAqFHVdKSKSfScw2hQdmItgTx3Ae3s3nmLHQg=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Introducing Mercury 2.5 (7 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Inception's latest diffusion LLM runs at a claimed 1,107 tokens per second, with a 260K-token context window and a 40% intelligence gain over Mercury 2. It also adds parallel tool calls and structured JSON, while previews of Mercury Voice and Mercury Router target latency-sensitive agents.
                                &lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

&lt;table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td class="container" style="padding: 15px 15px;"&gt;
&lt;div class="text-block"&gt;
&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fai.meta.com%2Fmuse%2F%3Futm_source=tldrdev/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/bUQ1PtJzzSaf9QPOQ8XUuymX89tjMws-srikZBIXDkw=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Introducing Muse (5 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Muse is Meta's personal AI agent designed to automate everyday tasks, fill out forms, and navigate the web via a dedicated, secure virtual machine. Accessible through everyday apps like WhatsApp, it proactively organizes goals and builds custom tools while requiring direct user approval for sensitive actions like making purchases or sending emails.
                                &lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

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&lt;div class="text-block"&gt;
&lt;div style="text-align: center;"&gt;&lt;span style="font-size: 36px;"&gt;🎁&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

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&lt;div class="text-block"&gt;
&lt;div style="text-align: center;"&gt;&lt;strong&gt;&lt;h1&gt;Miscellaneous&lt;/h1&gt;&lt;/strong&gt;&lt;/div&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

&lt;table bgcolor="" style="table-layout: fixed; width: 100%;" width="100%"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td style="padding:0;border-collapse:collapse;border-spacing:0;margin:0;" valign="top"&gt;

&lt;table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td class="container" style="padding: 15px 15px;"&gt;
&lt;div class="text-block"&gt;
&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2FJ6TISt/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/U2KwfY-xNCtB8ssE_fDng7TPEWY2uyKjJF5HE5ezw1k=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;OpenAI's Agents Claim a Navier-Stokes Breakthrough (8 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    OpenAI published a claimed solution to the Navier-Stokes existence and smoothness problem, produced by a system of roughly 10,000 agents and accompanied by a Lean-formalized proof. The company says the effort used about 130 billion output tokens, with GPT-6 Astra handling the final formalization and verification.
                                &lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

&lt;table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td class="container" style="padding: 15px 15px;"&gt;
&lt;div class="text-block"&gt;
&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.dwarkesh.com%2Fp%2Fpretraining-progress-is-mostly-data%3Futm_source=tldrdev/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/Y8jrG1CbrNpOAOt7mTDUqzMojPEdu9m7gfL848Mycu4=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Pretraining Progress Is Mostly Coming From Data (18 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    A controlled study of open model recipes and datasets from 2019 to 2025 found that data improvements produced a 12x compute-efficiency gain at a 10^19 FLOPs budget, versus 3.7x from model improvements. The authors stress that the experiment covers small models and pretraining only, while architecture work still makes larger-scale training possible.
                                &lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;



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&lt;div class="text-block"&gt;
&lt;div style="text-align: center;"&gt;&lt;span style="font-size: 36px;"&gt;⚡&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

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&lt;div class="text-block"&gt;
&lt;div style="text-align: center;"&gt;

&lt;h1&gt;&lt;strong&gt;Quick Links&lt;/strong&gt;&lt;/h1&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

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&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fluma.com%2Fkwdnwg1g%2F%3Futm_campaign=Quicklink09092026%26utm_source=tldrdev%26utm_medium=newsletter/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/XQMkSfbBxQ1d1MkosClkEyV2lQMeH_qe-wN-kqDP0M4=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Ready to take your AI agent beyond the GUI? (Sponsor)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Join Twilio Assemble SF on Sep 23 to network with local builders, learn how to build omni-channel, context-aware AI agents, and grab exclusive swag and hardware prizes! &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fluma.com%2Fkwdnwg1g%2F%3Futm_campaign=Quicklink09092026%26utm_source=tldrdev%26utm_medium=newsletter/2/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/0D0iVm28zAwVxsMNKOTrqhStl0Kn6O6ypio44mMzJ2s=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;&lt;strong&gt;[Save your spot]&lt;/strong&gt;&lt;/span&gt;&lt;/a&gt;
&lt;/span&gt;
&lt;/span&gt;
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&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

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&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fishamf.dev%2Fp%2Fllm-attention-visualizer%2F%3Futm_source=tldrdev/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/XmW3A_Pw1SWHBjC89UD0upeaXuHCrX2FXlu5sjSE1TI=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;LLM Attention Visualization (3 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    This interactive explainer lets you hover over generated tokens to see which earlier tokens contributed most to them.
                                &lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

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&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fmg-crea.com%2Fblog%2Fthe-late-software-developer%2F%3Futm_source=tldrdev/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/1xRshFxikt2czkVamhmamu-hh8A4G_BILhO8PaMcMAE=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;The Late Software Developer (2 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    A developer describes the strange shift from flow-state coding to orchestrating 20-plus agents, and why the software factory itself is becoming the product.
                                &lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

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&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.blackmagicdesign.com%2Fmedia%2Frelease%2F20260908-03%3Futm_source=tldrdev/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/arsyswjM1Ww2WfnXkCpEURZ2sk05FO4W2uxUyOJubVY=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;DaVinci Resolve 21.1 (9 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    DaVinci Resolve 21.1 has been released, featuring AI assistant integration, expanded camera support, enhanced multi-cam workflows, and over 25 new Krokodove graphics tools to improve editing and color grading efficiency.
                                &lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

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&lt;div class="text-block"&gt;
&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fblog.sshh.io%2Fp%2Fi-asked-100-agents-to-hack-me%3Futm_source=tldrdev/1/010001a085e10d2b-41da4614-fd34-4573-9d01-31c510001192-000000/FbgQKGRM60QjYwsXgxlPvJ28O5DDCqME8NMtptm0BOk=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;I Asked 100 Agents to Hack Me (10 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
&lt;/a&gt;
&lt;br&gt;
&lt;br&gt;
&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Shrivu Shankar gave roughly 100 self-hosted, guardrail-removed agents five hours to compromise his online accounts, and they broke into five lower-tier accounts through old software flaws and password attacks, attempted social engineering 16 times, and assembled sensitive personal data for about $210 in GPU time.
                                &lt;/span&gt;
&lt;/span&gt;
&lt;/div&gt;
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&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;


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