Razer Blade 14 (2023) review: powerful chips in a thin body, a 16:10 QHD+ 240Hz screen, and an RGB keyboard, but $2.4K+ is absurd and the speakers are just okay 拆封筆電

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Lambda, an AI infrastructure company, this week announced it raised $15 million in a venture funding round from 1517, Gradient Ventures, 拆封筆電razer, Bloomberg Beta, Georges Harik, and others, plus a $9.5 million debt facility. The $24.5 million investment brings the company’s total raised to $28.5 million, following an earlier $4 million seed tranche.

In 2013, San Francisco, California-based Lambda controversially launched a facial recognition API for developers working on apps for Google Glass, Google’s ill-fated heads-up augmented reality display. The API — which soon expanded to other platforms — enabled apps to do things like “remember this face” and “find your friends in a crowd,” Lambda CEO Stephen Balaban told TechCrunch at the time. The API has been used by thousands of developers and was, at least at one point, seeing over 5 million API calls per month.

Since then, however, Lambda has pivoted to selling hardware systems designed for AI, machine learning, and deep learning applications. Among these are the TensorBook, a laptop with a dedicated GPU, and a workstation product with up to four desktop-class GPUs for AI training. Lambda also offers servers, including one designed to be shared between teams and a server cluster, called Echelon, that Balaban describes as “datacenter-scale.”

(Lambda’s Balaban presented at VB Transform this week, as part of the event’s innovation showcase of cool, emerging technologies. See Balaban’s presentation above.)

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“We initially created a facial recognition API, a deep learning-powered image editor called Dreamscope, and, because of the experience of running our own GPU infrastructure, decided to offer preconfigured workstations and servers,” Balaban told VentureBeat via email. “We provide the infrastructure — laptops, workstations, and servers — so that our customers can focus on training models and building value for their customers. Most companies get distracted by building huge infrastructure teams when they should be building huge machine learning teams to use infrastructure that’s easier to manage.”

Above: One of Lambda workstations.

A number of startups offer preconfigured hardware for AI development, including Graphcore. But Balaban says Lambda’s major differentiator is its software tools.

Every Lambda machine comes preinstalled with Lambda Stack, a collection of machine learning software development frameworks, including Google’s TensorFlow and Facebook’s PyTorch. Developers can update the frameworks with a single console command, and if they’ve trained the model on a local machine, they can copy it up to a Lambda server running in the cloud.

“Our customers include Apple, Intel, Microsoft, Amazon Research, Tencent, Kaiser Permanente, MIT, Stanford, Harvard, Caltech, and the Department of Defense,” Balaban said. “We have [thousands] of users, [and] most of the Fortune 500 and almost every major research university in the U.S. — as well as [many of] the research labs at the Department of Transportation and Department of Energy — use Lambda hardware and Lambda Stack.”

Balaban also claims that the over-40-employee company, which was founded in 2012, has been GAAP (generally accepted accounting principles) profitable since 2019. It’s on a $60 million revenue run rate for 2021 and plans to have around 60 employees by the end of the year.

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華碩在Twitter再度劇透ROG Phone 6具備IPX4防潑濺。（圖／Twitter）

華碩新一代電競手機ROG Phone 6預計7月5日發表，為了預熱話題，官方自爆不斷，最新又在Twitter上透露，ROG Phone 6會是全球首款具備IPX4防潑濺的電競手機。

根據國際標準，IPX4的防水能力，是能承受從任何角度潑濺10分鐘，華碩號稱是歷代首度加入，亦是業界首款。不過華碩被網友吐槽，拆封筆電razer Phone 2早就支援IP67防水，中興旗下的Nubia紅魔系列也擁有IPX5。

請繼續往下閱讀…

總結而言，加上華碩先前的自行破梗，等於ROG Phone 6共擁有4大亮點，除了IPX4防潑濺，還有採高通Snapdragon 8+ Gen 1處理器、6.78吋的165Hz螢幕，以及更強的散熱，液態均溫板加大30%、石墨片加大85% 。

其他規格傳聞則配置6,000mAh電池、65Ｗ快充、最大18GB記憶體，以及6,400萬畫素後三鏡頭。

華碩ROG Phone 6出現在中國工信部網站，外型被揭露。（圖／網站）

此外，中國工信部也已經曝光ROG Phone 6的外型，整體延續既有風格，不過機背設計還是會有一些不同，例如線條切割的圖型等。

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