Email: Instinct group chats 💬, Reflection’s 501B model 🧠, OpenAI text watermarks 🏷️

Subject:
Instinct group chats 💬, Reflection’s 501B model 🧠, OpenAI text watermarks 🏷️
Received:
10/6/2026, 1:25:47 PM
From:
"TLDR AI" <dan@tldrnewsletter.com>
To:
silk.theater.56@fwdnl.com
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		&lt;div style="display: none; max-height: 0px; overflow: hidden;"&gt;Instinct now lets early-access users add a shared agent to group chats for planning trips, tickets, carpools, and events. Personal Instincts&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;td align="center" height="20" style="vertical-align:middle !important;" valign="middle" width="100%"&gt;&lt;strong style="vertical-align:middle !important; height: 100%;"&gt;Together With &lt;/strong&gt;
																										&lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ffireworks.ai%2Fnexus%3Futm_source=tldr%26utm_medium=newsletter%26utm_campaign=nexus/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/fKbLVrvbDMcQMs_rqlJGvpxZnWkD7dHg2VO2Plb8MR0=452"&gt;&lt;img src="https://images.tldr.tech/fireworks.png" valign="middle" style="vertical-align: middle !important; height: 100%;" alt="Fireworks"&gt;&lt;/a&gt;&lt;/td&gt;
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																											&lt;h1&gt;&lt;strong&gt;TLDR AI &lt;span id="date"&gt;2026-10-06&lt;/span&gt;&lt;/strong&gt;&lt;/h1&gt;
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                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ffireworks.ai%2Fnexus%3Futm_source=tldr%26utm_medium=newsletter%26utm_campaign=nexus/2/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/5rRGVgkGEHqSExHiVLIimPrkDRX-qziO5oMDVgii7tk=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Frontier intelligence. Half the bill. (Sponsor)&lt;/strong&gt;
                                    &lt;/span&gt;
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																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    AI coding spend is growing fast. But teams shouldn't have to choose between giving developers access to frontier intelligence and keeping token costs under control.&lt;p&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Fireworks Nexus gives developers access to frontier open models in the harnesses they already use. With &lt;/em&gt;&lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fapp.fireworks.ai%2Ffire-router%3Futm_source=tldr%26utm_medium=newsletter%26utm_campaign=nexus/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/2x0PRGqNCr0ZzubZcXUd5BAwgXDKBrKcxyT1ajU8jao=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;&lt;em&gt;FireRouter,&lt;/em&gt;&lt;/span&gt;&lt;/a&gt;&lt;em&gt; each request is scored and routed to the optimal model for the task, while difficult tasks can pass through to your closed provider.&lt;/em&gt;&lt;/p&gt;

																											&lt;p&gt;Set up in minutes. Keep your existing workflow. Get more control over your AI spend.&lt;/p&gt;

																											&lt;p&gt;👉&lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ffireworks.ai%2Fnexus%3Futm_source=tldr%26utm_medium=newsletter%26utm_campaign=nexus/3/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/rtJpJZ8jnBu-ylAmbQuS4jKS2HdAhwHj8oxYgKqfyzY=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt; Explore Fireworks Nexus&lt;/span&gt;&lt;/a&gt;


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																							&lt;div style="text-align: center;"&gt;&lt;span style="font-size: 36px;"&gt;&lt;span style="font-size:36px;"&gt;🚀&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;
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																								&lt;h1&gt;&lt;strong&gt;Headlines &amp; Launches&lt;/strong&gt;&lt;/h1&gt;
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                                    &lt;span&gt;
                                        &lt;strong&gt;OpenAI in $30 Billion Round Talks With UAE Funds, BlackRock (3 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
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																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    OpenAI is in talks with multiple investment funds from the United Arab Emirates to help anchor a $30 billion round of financing. The UAE funds have discussed forming a syndicate to invest as much as $10 billion in the round. The University of California's endowment fund, BlackRock, Thrive Capital, and Andreessen Horowitz may also participate in the round alongside that syndicate. The fundraise is ongoing, and the details could change.
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                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2F0K4IIf/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/_0rrn8lh0ZnZtWz1HhZ_uERQRBlzCvyjax4--dk398E=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;OpenAI to Add Text Watermarks (7 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
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																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    OpenAI said it would add invisible text watermarks to eligible ChatGPT and Codex outputs in the EU to meet AI Act transparency requirements. Its textGrain method subtly alters word selection so generated text can be detected, though editing, translation, and short passages can weaken detection.
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                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2FTpZLHX/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/3viCjmWPptKnzjlv74e5yN7p8la4MEUhJlvBhCcecEg=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Instinct in group chats (1 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
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																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Instinct now lets early-access users add a shared agent to group chats for planning trips, tickets, carpools, and events. Personal Instincts enforce permissions, keep account access separate, and pause sharing when new members join.
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																							&lt;div style="text-align: center;"&gt;&lt;span style="font-size: 36px;"&gt;🧠&lt;/span&gt;&lt;/div&gt;
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																								&lt;h1&gt;&lt;strong&gt;Deep Dives &amp; Analysis&lt;/strong&gt;&lt;/h1&gt;
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																											&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.akashbajwa.co%2Fp%2Fopenais-b2b-marketplace-the-hyperscaler%3Futm_source=tldrai/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/AQxgjyVb9_3Y4wz2PRINWnRibqiCP76ACE4dxtq29eQ=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;OpenAI's B2B Marketplace: The Hyperscaler Of AI Apps (6 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;
                                    The OpenAI B2B marketplace opened on September 29 with 32 partners. OpenAI wants to position itself as the platform that the wider AI ecosystem is built on and relies on for distribution. This will consolidate AI sprawl and make it easier for customers to budget. If the marketplace gains traction, we may see an evolution similar to the cloud ecosystem where labs and AI apps co-sell, apps get charged a listing fee, and buyers receive one invoice for their spend.
                                &lt;/span&gt;
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																											&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fdevin.ai%2Fblog%2Fmemory-and-dreaming%3Futm_source=tldrai/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/iL8F3qwwJEve9jEP6hZna5Lkq2CtAMYgrEUP6BHxcko=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;How Devin's Memory and Dreaming Work (4 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
																											&lt;/a&gt;
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																											&lt;br&gt;
																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Devin's new Memory system carries preferences, corrections, and project learnings across sessions, while Dreaming periodically reorganizes and connects that information. The process deduplicates memories, links them to past sessions and artifacts, and can derive new knowledge from accumulated work.
                                &lt;/span&gt;
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                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.theaithinker.com%2Fp%2Fhow-to-build-an-ai-native-software%3Futm_source=tldrai/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/mMiToM-SG8ySsF0F7Nks46reZm5CRJTYFFXfEqq4ZZg=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;How to Build an AI-Native Software Factory (19 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
																											&lt;/a&gt;
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																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    A practical look at the infrastructure companies need around coding agents once usage scales beyond individual developers. Using Uber's software factory as the main case study, it covers cloud execution, model gateways, agent identity, testing, migrations, code review, and measuring economics such as cost per merged pull request.
                                &lt;/span&gt;
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																							&lt;div style="text-align: center;"&gt;&lt;span style="font-size: 36px;"&gt;🧑‍💻&lt;/span&gt;&lt;/div&gt;
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																								&lt;h1&gt;&lt;strong&gt;Engineering &amp; Research&lt;/strong&gt;&lt;/h1&gt;
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																											&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ffandf.co%2F3TKlfLb/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/pVKFQvCUZUXeMtg5Jwukv46YjZjOBNb1hupv8kS4cmk=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Zero Trust must extend to cover AI agents (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;
                                    AI agents act autonomously at speed and scale that challenges security frameworks. Zero Trust is insufficient to control or contain AI agents as it's currently conceived. &nbsp;“&lt;em&gt;From Zero Trust to Agent Trust&lt;/em&gt;,” from &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ffandf.co%2F3TKlfLb/2/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/Schh9bx0vPLsJxk5raeNVWfTJk6VIGalo0KYfdiTtRk=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;Teleport&lt;/span&gt;&lt;/a&gt;, explains how to extend&nbsp;from Zero Trust to new Agentic Trust Principles.&nbsp;

																											&lt;p&gt;&lt;/p&gt;

																											&lt;p&gt;&lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ffandf.co%2F3TKlfLb/3/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/Urovlic1lQJiGCzvH40Q_h97Dl2foxTMhBedQMVLlRM=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;Read the paper →&lt;/span&gt;&lt;/a&gt;


																											&lt;/p&gt;
																											&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
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																											&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Freflection.ai%2Fblog%2Fintroducing-beam%3Futm_source=tldrai/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/1x1sKsaLOyHy45Qg07-RjES8G6098e0mmWmwZkmp7FU=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Reflection Introduces Beam Model (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;
                                    Beam is a 501B-parameter sparse Mixture-of-Experts model with 23B active parameters trained for coding, reasoning, and agentic workloads. The model used 23.8T pretraining tokens and more than 100M reinforcement-learning rollouts, with open weights and developer artifacts planned for release later in October.
                                &lt;/span&gt;
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																											&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2FDilGg3/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/e4aLuxyT5QisCI-nI8puZTB23ilIreZ0QastcDDkfLg=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Announcing d1 with vision (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;
                                    d1, a decision model from Liquid AI, now supports images, text, or both as inputs. The model costs 19x to 200x less than GPT-6.1 Sol and Claude Opus 5.5 and answers significantly faster on every task. It outputs probabilities for yes/no, choice, or score questions in one forward pass without generating tokens. Text decisions are made in 200 to 300 milliseconds.
                                &lt;/span&gt;
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																											&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fgithub.com%2Fgatewai-dev%2Fframefields%3Futm_source=tldrai/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/ZQBoHqoBXyktdlEuIIrxGxTU4VvuYnWxnJGZ8dJ1jpM=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Framefields (GitHub Repo)&lt;/strong&gt;
                                    &lt;/span&gt;
																											&lt;/a&gt;
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																											&lt;br&gt;
																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Framefields is an npm package built for coding agents. It enables agents to create Photoshop-inspired compositing and VFX, After Effects-style motion, typography, and keyframing, and Blender-style 3D scenes, cameras, and models. The agent writes a TypeScript composition, checks frames, and renders an MP4. Framefields renders directly on GPU hardware in Node.js and modern WebGPU browsers.
                                &lt;/span&gt;
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																							&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 style="text-align: center;"&gt;&lt;strong&gt;&lt;h1&gt;Miscellaneous&lt;/h1&gt;&lt;/strong&gt;&lt;/div&gt;
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																											&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.vals.ai%2Fblogs%2Froom-temperature-magnetic-semiconductors%3Futm_source=tldrai/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/LZYyhmMu2ZxLuk4wcKSnMXW7l5-l0zsJn2znmNdgOJE=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Two Room-Temperature Antiferromagnetic Semiconductor Candidates (11 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
																											&lt;/a&gt;
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																											&lt;br&gt;
																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    Ferromagnets' atomic magnets all point the same way, adding their magnetic effects. Antiferromagnets have neighboring atomic magnets that point opposite ways and exactly cancel out magnetically. There is an intense drive in computer memory research to create materials in between these two extremes. This post details how a team of AI agents designed a candidate magnet for next-generation computer memory that has zero net magnetism yet still sorts electrons by spin.
                                &lt;/span&gt;
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                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2FaHiUC5/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/WLX7Mz1b3u2Y_NRVephnBA_d794E2SehZuFcEzRWXTk=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;OpenAI Expands Ads in ChatGPT (5 minute read)&lt;/strong&gt;
                                    &lt;/span&gt;
																											&lt;/a&gt;
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																											&lt;br&gt;
																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
                                    OpenAI introduced a new visual ad format in ChatGPT alongside expanded measurement tools, partnerships, and brand-suitability work. The company positioned advertising as a way to support broader access to ChatGPT while giving businesses another channel to reach users during product discovery and decision-making.
                                &lt;/span&gt;
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																							&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;h1&gt;&lt;strong&gt;Quick Links&lt;/strong&gt;&lt;/h1&gt;
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																											&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fserpapi.com%2Ftldr-ai/1/010001a1116449cf-af9d1e7e-7eed-49f9-b6c8-9132c9bb1502-000000/wOBx9Ei3VVYMC6qyZTwk7Bit9LOCcBUTmdFc-Kxotsk=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Power your AI agents with a real-time web search API (Sponsor)&lt;/strong&gt;
                                    &lt;/span&gt;
																											&lt;/a&gt;
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																											&lt;br&gt;
																											&lt;span style="font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, Verdana, sans-serif;"&gt;
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                                        &lt;strong&gt;Nvidia's $20 billion Groq deal faces lawsuit alleging startup's stockholders were shortchanged (3 minute read)&lt;/strong&gt;
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                                    The deal was allegedly made without the stockholder vote that Delaware law requires and without any process designed to test or maximize the value of what Nvidia bought.
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                                    OpenAI's Tibo Sottiaux expects agents to take most internet actions, model pickers to disappear, and models to improve roughly 10x within a year.
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                                    While it seems like a fast timetable to raise another mega round (Etched raised $700 million at a $21 billion valuation a couple of months ago), the company is pursuing a particularly expensive segment of the AI industry: building full AI hardware systems powered by proprietary chips.
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