Email: Ghost launches AI PC 👻, SpaceX seeks Nvidia chips 🚀, Synopsys and OpenAI team up 🤝

Subject:
Ghost launches AI PC 👻, SpaceX seeks Nvidia chips 🚀, Synopsys and OpenAI team up 🤝
Received:
10/7/2026, 1:14:28 PM
From:
"TLDR Hardware" <dan@tldrnewsletter.com>
To:
silk.theater.56@fwdnl.com
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&lt;div style="display: none; max-height: 0px; overflow: hidden;"&gt;Ghost opened pre-orders for Core, a $3,499 screenless computer with an Nvidia RTX Pro 4000 SFF Blackwell GPU. The device runs preinstalled AI&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%2Frunware.ai%2Fsonic-pods%3Futm_source=tldrhardware%26utm_medium=newsletter%26utm_campaign=Primary10072026%26utm_content=header_1_mw_ai%26utm_term=2026-10-07_hardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/ZDPwkAfBiFRwk4tZRueNQtiInyJi8EmG7RNMS-T_V6Q=452"&gt;&lt;img src="https://images.tldr.tech/runware.png" valign="middle" style="vertical-align: middle !important; height: 100%;" alt="runware.ai"&gt;&lt;/a&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;


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&lt;h1&gt;&lt;strong&gt;TLDR Hardware &lt;span id="date"&gt;2026-10-07&lt;/span&gt;&lt;/strong&gt;&lt;/h1&gt;
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                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Frunware.ai%2Fsonic-pods%3Futm_source=tldrhardware%26utm_medium=newsletter%26utm_campaign=Primary10072026%26utm_content=header_1_mw_ai%26utm_term=2026-10-07_hardware/2/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/MpsOZiLxv2HU5d9uFE8q8BEL2dO_0doi7P_20ATCOT4=452"&gt;
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                                        &lt;strong&gt;A 1 MW AI data center in a shipping container, live in days (Sponsor)&lt;/strong&gt;
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                                    Building a data center takes 3–5 years, and about a third of the power goes to cooling and building systems instead of compute. &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Frunware.ai%2Fsonic-pods%3Futm_source=tldrhardware%26utm_medium=newsletter%26utm_campaign=Primary10072026%26utm_content=Body_runwares_sonic_pods%26utm_term=2026-10-07/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/z5IrsE1rr4tpTO8_OFt85V_0n-fO8SM3WKy1fhMpg3s=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;Runware's Sonic Pods &lt;/span&gt;&lt;/a&gt;skip all of it.

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

&lt;p&gt;Each pod is a complete &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Frunware.ai%2Fsonic-pods%3Futm_source=tldrhardware%26utm_medium=newsletter%26utm_campaign=Primary10072026%26utm_content=Body_ai_inference_data_center%26utm_term=2026-10-07/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/PVWSexNe_PFeUWrhSzF5cJMD3CaPM7V1dq4RV271ZRY=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;AI inference data center in a 20 ft shipping container&lt;/span&gt;&lt;/a&gt;, trucked in and live in days:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;Up to 1,200 GPUs and 1 MW of compute, any GPU architecture&lt;/li&gt;
&lt;li&gt;Closed-loop liquid cooling on every GPU: 1.5 m³ of water, recirculated, none consumed&lt;/li&gt;
&lt;li&gt;Europe is live, US rollout underway&lt;/li&gt;
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&lt;p&gt;Capacity is filling up. &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Frunware.ai%2Fsonic-pods%3Futm_source=tldrhardware%26utm_medium=newsletter%26utm_campaign=Primary10072026%26utm_content=Body_reserve_pod%26utm_term=2026-10-07/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/DdHBoZeu4cMD5XhUqbLticglkPGllSGxhmNQIsDEdo8=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;Reserve a pod&lt;/span&gt;&lt;/a&gt; or &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Frunware.ai%2Fsonic-pods%3Futm_source=tldrhardware%26utm_medium=newsletter%26utm_campaign=Primary10072026%26utm_content=cta_serverless%26utm_term=2026-10-07/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/lCEnfIJieLIRPYPPSux_43aLNQgnBdTeOVKnt5wHdmw=452" rel="noopener noreferrer nofollow" target="_blank"&gt;&lt;span&gt;start on Serverless&lt;/span&gt;&lt;/a&gt;, billed by the second.


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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;Headlines and Launches&lt;/strong&gt;&lt;/h1&gt;
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&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ftechcrunch.com%2F2026%2F10%2F05%2Fat-19-ghost-founder-raises-11-million-to-build-a-3499-computer-for-your-personal-ai%2F%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/e7P9QOP4raRq6ijxu7fkg4pSVVc7DsSdmvti483stBk=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Ghost launches a personal AI computer (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;
                                    Ghost opened pre-orders for Core, a $3,499 screenless computer with an Nvidia RTX Pro 4000 SFF Blackwell GPU. The device runs preinstalled AI models locally and gives users access through a phone app. Ghost raised an $11 million seed round and plans to ship the first batch in late October.
                                &lt;/span&gt;
&lt;/span&gt;
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&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2F0G2W5n/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/Xn7uDunD3T4SNDM-FpRprLc_T8JyvkAL8kT5PrwICGQ=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;SpaceX seeks $40B Apollo-led debt financing to buy Nvidia chips (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;
                                    The FT reports SpaceX is raising about $10 billion in bank loans and $30 billion in investment-grade debt to fund an Nvidia chip order, with Apollo leading and helping sell the debt to a broad investor base, and bond fund Pimco among lenders in talks. The deal is expected to close in 2027. It fits the pattern Nvidia flagged in August, when it disclosed its own SpaceX stake and a $500 billion Wall Street financing push, with chip purchases increasingly funded by debt and equity ties to the buyer. Reuters could not independently verify the report, and SpaceX, Apollo, Nvidia, and Pimco haven't commented.
                                &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 and Applications&lt;/strong&gt;&lt;/h1&gt;
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&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.eetimes.com%2Fgpt-synopsys-combines-ic-design-eda-with-agentic-ai%2F%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/Xf0m0drjWgt9dricnFETPavyQbNcMdx2XQiApySCTgE=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Synopsys and OpenAI team up on GPT-Synopsys, a frontier model that runs EDA tools like an engineer (4 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;
                                    GPT-Synopsys is an OpenAI frontier model trained and tuned to operate Synopsys' EDA tools directly, covering PPA optimization, timing closure, and verification. Engineers hand it an objective, and agents run the tools, interpret the results, make changes, and loop until there's a verified outcome to review. It runs on OpenAI-hosted infrastructure and plugs into Synopsys.ai and the Autopilot agentic platform. OpenAI licenses Synopsys' tools to train the model, paying a training subscription fee, and the two companies then share revenue based on how well the model improves chip designs, an unusual structure that ties both to the results. Synopsys says customer design data stays protected and won't be used to train the frontier model, and the bundled service covers compute, the model, and EDA licenses.
                                &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%2Fsemiengineering.com%2Fextreme-environments-push-chips-to-their-breaking-point%2F%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/dgsw6ygAx5IbPUuRT_2kT1BByi1sDgp08jTOpvhFc4c=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Designing chips for extreme environments (12 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;
                                    Engineers must test chips against combined radiation, thermal shock, vibration, and other stresses rather than qualify each condition alone. Arizona State University pairs a radiation source with a cryostat to test devices at 77 Kelvin. Digital twins can model package and system behavior, but physical tests still check whether those predictions hold.
                                &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;Research and Prototypes&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%2Finterestingengineering.com%2Fai-robotics%2Frobopartys-rp1-open-source-humanoid-robotics%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/qoXK3U5H4dwUXxMr-LweLhpr-x2udtKf_HghUMkPDJQ=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;RoboParty demonstrates the RP1 humanoid (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;
                                    RoboParty demonstrated RP1 recovering its balance after visitors pushed or kicked it at IROS. The platform combines actuator modules, robot hardware, and reinforcement-learning motion control, with peak joint torque up to 160 Nm. RoboParty plans to release more control software, simulation tools, and hardware details, so its full open-source roadmap remains in progress.
                                &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%2Fdynamic.robots.ox.ac.uk%2Fprojects%2Fscarf-slam%2F%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/9rSf70vzWGfiVgOUb9A-3Hlw19Jvr5_-XbFjcfDfJyA=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;ScaRF-SLAM: Scale-Consistent Reconstruction with Feed-Forward Models and Classical Visual SLAM (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;
                                    ScaRF-SLAM is a dense visual mapping system that pairs the reliability of classical visual SLAM with modern feed-forward geometric foundation models for 3D scene reconstruction. By decoupling camera tracking from dense depth estimation and optimizing scale consistency across submaps, it achieves globally accurate 3D maps across diverse sensor configurations. For perception engineers and autonomy developers, this framework provides a practical way to produce metric-scale environmental maps in real time without sacrificing tracking stability.
                                &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%2Fwww.tomshardware.com%2Ftech-industry%2Fdata-centers%2Fgoogle-ai-data-center-project-investigated-after-420-football-fields-of-finnish-forest-razed-trees-were-removed-before-a-mandatory-environmental-impact-assessment-say-reports%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/rLD8HmaOfD5Nc8-WuLQ8jQR34OfoA1KZA8J7qxN3ITM=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Google faces scrutiny over Finnish data-center clearing (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;
                                    Finnish authorities are investigating allegations that Google's local operator cleared over 300 hectares of forest before a required environmental assessment. A conservation group has requested a suspension of work near Muhos. Google says the tree felling complied with forestry requirements and that it protected high-value nature zones.
                                &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%2Fgithub.com%2FFeSens%2FopenTPU%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/toWH0ShpO7dqlFI-sAfyqZrVaAUOn4aaPxcDRsCnPnM=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;OpenTPU Full-Stack Open-Source AI Accelerator  (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;
                                    OpenTPU is a complete, open-source AI accelerator project that packages custom SystemVerilog RTL, instruction set architecture, a bit-exact simulator, and a compiler into a single accessible repository. The design runs modern quantized language models directly on cost-effective Kintex-7 FPGA PCIe cards, matching simulation results bit for bit. This architecture provides embedded systems designers and compute engineers an invaluable end-to-end reference for deploying and tailoring custom neural network hardware without relying on proprietary black-box tooling.
                                &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;

&lt;table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td class="container" style="padding-top: 0px; padding-bottom: 0px;"&gt;
&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;div class="text-block"&gt;
&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.theverge.com%2Ftech%2F1005397%2Famd-intends-to-substantially-increase-its-chip-supply-next-year%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/BoS_DnLbKDPt-zycG7PZTs5qiL-Uh1etqDDW7grob4w=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;AMD says it will substantially increase chip supply in 2027 (1 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;
                                    Lisa Su said supply grew through 2026.
                                &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.phoronix.com%2Fnews%2FLinux-CRAM-Compressed-RAM%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/DmbTvpMCoZIqYM_zJA3-C7-EuFo4ykZwJG_kHgtYcMA=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Meta develops compressed RAM "CRAM" for Linux (4 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;
                                    Meta's Gregory Price presented hardware-offloaded compression at Linux Plumbers.
                                &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;
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&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.washingtonpost.com%2Ftechnology%2F2026%2F10%2F06%2Ftrump-steers-nearly-7b-shipbuilding-deal-with-weapons-maker-anduril%2F%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/3QgeQCerW8J4xlZWXq6GTrZldWOrTXWqj2a5Y6MLDhw=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Trump announces nearly $7B Anduril submarine shipyard deal in Baltimore (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;
                                    Anduril will invest $3.7 billion to build a two-million-square-foot "software-defined" shipyard at Sparrows Point, the former Bethlehem Steel site near Baltimore, and the Navy separately awarded it a $2.9 billion "Arsenal 2" contract with payments tied to production outcomes, bringing the package to roughly $6.6 billion.
                                &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;
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&lt;span&gt;
                                &lt;a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fgithub.com%2FManufacturedMotion%2FHex%3Futm_source=tldrhardware/1/010001a11680490a-c59c3c55-c021-41f6-88c3-86cfde39d11d-000000/okU1wxqeokv7iTdtFEMXSPbiRd4hklasdtRv1PH6TYo=452"&gt;
                                    &lt;span&gt;
                                        &lt;strong&gt;Hex Open-Source Hexapod Robot Platform (1 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;
                                    Hex is an open-source, six-legged robot platform designed to give makers and developers an accessible foundation for building and testing legged locomotion.
                                &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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