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TR:sources/news/20220413 Razer and Lambda Team Up to Unveil a Linux Laptop for Deep Learning.md
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[#]: subject: "Razer and Lambda Team Up to Unveil a Linux Laptop for Deep Learning"
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[#]: via: "https://news.itsfoss.com/tensorbook-razer-lambda/"
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[#]: author: "Ankush Das https://news.itsfoss.com/author/ankush/"
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[#]: collector: "lujun9972"
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[#]: translator: "wxy"
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[#]: reviewer: " "
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[#]: publisher: " "
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[#]: url: " "
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Razer and Lambda Team Up to Unveil a Linux Laptop for Deep Learning
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======
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Razer is known for its gaming peripherals and hardware.
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On the other hand, Lambda offers workstations, servers, and GPU clusters equipped with their software stack to facilitate deep learning as conveniently as possible.
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They have collaborated to present a sleek-looking modern laptop (powered by Ubuntu 20.04) tailored for deep learning on the go.
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And, it isn’t like any [other Linux laptops][1] available.
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In case you are curious, deep learning is a type of machine learning where you teach a computer to process information similar to how humans do (by example). You can explore [Wikipedia][2] for more details.
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### Tensorbook: The Deep Learning Laptop
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![][3]
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The Tensorbook is a Linux-powered laptop with state-of-the-art specifications to help you efficiently work with deep learning training/development anywhere. And, Lambda’s software stack supports all the tools to conveniently update PyTorch, Tensorflow, CUDA, etc., with just a single command.
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Of course, the name isn’t a surprise, considering tensor cores help speed up the machine learning training/process.
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![][4]
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Razer did not add any of their usual signature patterns with this laptop, like a green accent/color, logo, or RGB elements. Well, for the greater good, this is tailored for deep learning. So, it is only fair that it isn’t too flashy.
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You only find the lambda logo as the primary on the lid and a Razer x Lambda text on the bottom bezel of the screen. And, the purple accent goes all over, Lambda taking the lead on its branding here.
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The specifications for the laptop involve:
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* **GPU**: GeForce RTX 3080 Max-Q 16 GB VRAM
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* **CPU:** Intel i7-11800H
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* **RAM:** 64 GB 3200 MHz DDR4
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* **Storage:** 2 TB NVMe PCIe 4.0
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* **Display:** 165 Hz 1440p 15.6-inch
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In addition to the solid core configuration, the connectivity options include:
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* 3 x USB 3.2 Gen 2 Type-A ports
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* 1 x HDMI 2.1
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* 1 x UHS-III SD Card Reader
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* 3.5 mm Headphone/Microphone jack
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* 2 x Thunderbolt 4 ports
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* Wi-Fi 6E
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* Bluetooth 5.2
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Undoubtedly, the laptop is a sleek powerhouse with all the components packed in it.
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The RTX 3080 GPU should be capable enough to help with your deep learning tasks, whether you are a professional or a beginner.
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Of course, it isn’t pitched for gaming, but with what you have, along with a high refresh rate screen, you can comfortably game on it when you want.
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![][5]
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The machine learning training benchmarks claim that it is way ahead of the M1 Max chip.
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So, you will not have any trouble with training models.
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### Pricing and Availability
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It is a premium offering, so the price tag suits the same, starting at **$3499**. You can customize it for enterprise settings to pack in Windows 10 and Ubuntu.
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An extended warranty and premium support is available if you want to pay the extra.
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You can customize and proceed with the purchase on Lambda’s official website.
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[Tensorbook][6]
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--------------------------------------------------------------------------------
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via: https://news.itsfoss.com/tensorbook-razer-lambda/
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作者：[Ankush Das][a]
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选题：[lujun9972][b]
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译者：[译者ID](https://github.com/译者ID)
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校对：[校对者ID](https://github.com/校对者ID)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]: https://news.itsfoss.com/author/ankush/
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[b]: https://github.com/lujun9972
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[1]: https://itsfoss.com/get-linux-laptops/
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[2]: https://en.wikipedia.org/wiki/Deep_learning
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[3]: https://i.ytimg.com/vi/wMh6Dhq7P_Q/hqdefault.jpg
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[4]: data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjgwMCIgd2lkdGg9IjcyMCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIiB2ZXJzaW9uPSIxLjEiLz4=
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[5]: data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjYwMCIgd2lkdGg9IjgyMCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIiB2ZXJzaW9uPSIxLjEiLz4=
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[6]: https://lambdalabs.com/deep-learning/laptops/tensorbook
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@ -0,0 +1,99 @@
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[#]: subject: "Razer and Lambda Team Up to Unveil a Linux Laptop for Deep Learning"
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[#]: via: "https://news.itsfoss.com/tensorbook-razer-lambda/"
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[#]: author: "Ankush Das https://news.itsfoss.com/author/ankush/"
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[#]: collector: "lujun9972"
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[#]: translator: "wxy"
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[#]: reviewer: " "
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[#]: publisher: " "
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[#]: url: " "
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雷蛇与 Lambda 联手推出用于深度学习的 Linux 笔记本电脑
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======
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> Razer 与一家专注于深度学习的硬件公司合作，以时尚的外形、昂贵的价格提供了最新和最伟大的产品。
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<ruby>雷蛇<rt>Razer</rt></ruby> 以其游戏外设和硬件而闻名。
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另一方面，Lambda 提供配备了他们的软件栈的工作站、服务器和 GPU 集群，以尽可能方便地促进深度学习。
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他们合作推出了一款外观时尚的现代笔记本电脑（由 Ubuntu 20.04 驱动），专为随时随地的深度学习而设计。
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它不同于 [其他 Linux 笔记本电脑][1]。
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顺便说一句，深度学习是一种机器学习，你通过实例教给计算机学会类似人类处理信息的方式。你可以查看 [维基百科][2] 以了解更多细节。
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### Tensorbook：深度学习笔记本电脑
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[![][3]](https://youtu.be/wMh6Dhq7P_Q)
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Tensorbook 是一款由 Linux 驱动的笔记本电脑，具有最先进的规格，可以帮助你在任何地方高效地进行深度学习训练/开发。而且，Lambda 的软件栈支持各种工具，只需一个命令就能方便地更新 PyTorch、Tensorflow、CUDA 等。
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当然，这个名字并不令人意外，因为张量核心有助于加快机器学习训练/过程。
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![][4]
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雷蛇没有在这台笔记本电脑上添加任何他们惯用的标志性图案，比如绿色的点缀/颜色、标志或 RGB 元素。好吧，毕竟这是为深度学习而定制的。所以，它不太浮华是公平的。
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你只能在盖子上找到 lambda 主要标志，在屏幕的底边框上找到 Razer x Lambda 的文字。而且，紫色的风格贯穿始终，Lambda 在这里主导了其品牌宣传。
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这款笔记本电脑的规格涉及：
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* GPU：GeForce RTX 3080 Max-Q 16 GB VRAM
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* CPU：Intel i7-11800H
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* 内存：64 GB 3200 MHz DDR4
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* 存储：2 TB NVMe PCIe 4.0
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* 显示：165 Hz 1440p 15.6 英寸
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除了可靠的核心配置外，连接选项包括：
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* 3 个 USB 3.2 Gen 2 Type-A 端口
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* 1 x HDMI 2.1
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* 1 个 UHS-III SD 卡阅读器
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* 3.5 毫米耳机/麦克风插孔
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* 2 个雷电 4 端口
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* Wi-Fi 6E
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* 蓝牙 5.2
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毋庸置疑，这款笔记本电脑是一个时尚的动力源，将这些组件容纳于其中。
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RTX 3080 GPU 应该有足够的能力来帮助你完成深度学习任务，无论你是专业人士还是初学者。
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当然，它不是为游戏而设计的，但以你所拥有的配置以及高刷新率的屏幕，你可以在需要的时候在上面舒适地玩游戏。
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![][5]
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其机器学习训练基准声称，它远远领先于 M1 Max 芯片。
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因此，你在训练模型方面不会有任何问题。
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### 定价和可用性
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这是一款高端产品，所以价格标签也一样，起价为 **3499 美元**。你可以为企业设置定制它，以便安装上 Windows 10 和 Ubuntu。
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如果你支付额外的费用，还可以获得延长保修和高级支持。
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你可以在 Lambda 的官方网站上定制并进行购买。
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> [Tensorbook][6]
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--------------------------------------------------------------------------------
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via: https://news.itsfoss.com/tensorbook-razer-lambda/
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作者：[Ankush Das][a]
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选题：[lujun9972][b]
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译者：[wxy](https://github.com/wxy)
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校对：[wxy](https://github.com/wxy)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]: https://news.itsfoss.com/author/ankush/
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[b]: https://github.com/lujun9972
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[1]: https://itsfoss.com/get-linux-laptops/
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[2]: https://en.wikipedia.org/wiki/Deep_learning
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[3]: https://i.ytimg.com/vi/wMh6Dhq7P_Q/hqdefault.jpg
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[4]: https://news.itsfoss.com/wp-content/uploads/2022/04/tensorbook-1.jpg
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[5]: https://news.itsfoss.com/wp-content/uploads/2022/04/tensorbook-2.jpg
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[6]: https://lambdalabs.com/deep-learning/laptops/tensorbook
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