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Netflix’s Wednesday season 2 cast clicks into gear with Westworld star addition as Apple’s Neuromancer series finds its lead

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There’s good news for fans of William Gibson’s fictional AI Neuromancer and Wednesday, the ongoing tales of Charles Addams’ creepy and kooky family. Both shows’ already impressive casts have just announced some equally impressive new additions. 

First up, BAFTA award-nominated Callum Turner from Masters of the Air and The Boys in the Boat is going to be appearing in Neuromancer. Based on Gibson’s book of the same name, it’s a 10-part Apple TV Plus series following a largely broken top-tier hacker called Case (Turner). Case stumbles into a tangled web of electronic espionage and corporate skulduggery with suitably thrilling results, and the source novel won stacks of literary awards and helped define what would come to be known as cyberpunk. 

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BlackBerry-Like ‘Clicks’ Keyboard Shipping for More iPhone Models Soon

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The company behind the new “Clicks” physical keyboard accessory for the iPhone says it will soon start shipping for a few more models.

Clicks Keyboard iPhone Yellow
In an email shared by Parker Ortolani on Threads this week, the company said the iPhone 15 Pro version of the keyboard will begin shipping to customers worldwide by April 15. And on the Clicks website, the iPhone 15 Pro Max and iPhone 14 Pro Max versions of the keyboard are estimated to ship by April 30 and in May, respectively.

Clicks started shipping the iPhone 14 Pro version of the keyboard in February, and this is the only model that has arrived to customers so far. The keyboard was first announced in early January, ahead of the annual CES tech conference.

Inspired by the once-popular BlackBerry smartphone, Clicks is both a physical keyboard and a case for the iPhone. The keyboard connects to the iPhone’s USB-C or Lightning port, and it features dedicated keys for emoji and dictation, backlit keys, and a pass-through charging port. Wireless charging is still supported through the case.

Clicks Keyboard iPhoneClicks Keyboard iPhone
One advantage of using a physical keyboard with an iPhone is a full-screen experience, as the on-screen keyboard does not appear. There are also keyboard shortcuts, such as CMD-H to return to the Home Screen and CMD-Space to open Spotlight.

The obvious downsides of the keyboard are the added size and weight, but there is a niche market of physical keyboard fans who are willing to put up with these compromises to have an old-school BlackBerry-like typing experience.

Clicks was co-founded by well-known tech personalities “MrMobile” and “CrackBerry Kevin.” The keyboard starts at $139 in the U.S., and it is offered in London Sky and BumbleBee color options. It has silicone on the front, and vegan leather on the back. The keyboard is currently sold out, with the company accepting reservations for future availability.

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Keychron K8 mechanical keyboard clicks with Mac Studio setup

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Some people love peace and quiet. Others love mechanical keyboards. That clackety-clacking noise is the very sound of productivity, isn’t it? The feel of the keys. The way you can practically make a lifelong hobby out of customizing a “hot swappable” model with different keycaps, switches and more. Today’s Mac Studio and Studio Display setup relies on a Keychron K8 mechanical keyboard. 

The user swears by it, having chosen it over a couple of well-regarded Razer keebs. He’s still got the Razer wrist rest, though. 

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Keychron K8 mechanical keyboard click with Mac Studio and Studio Display setup

Redditor bucketofmonkeys (“Monk”) showcased the setup in a post entitled, “New Mac Studio M2 Max setup.” On Monday we covered his refurbished M2 Max Mac Studio and Studio Display. Now we’ll focus on his mechanical keyboard. 

So the Keychron K8 mechanical keyboard is a compact, tenkeyless model. That means it lacks a 10-key numeric key pad. It sports a total of 87 keys. It’s not tiny, but it’s not full-sized, either. 

It features a Mac layout’s multimedia and function keys, but works fine with Windows. And it comes with extra keycaps for both OS and a simple switch to flip between the OS. It includes white backlighting, Bluetooth 5.1 or USB-C cable connections and a 4000mAh battery that lasts 200 hours without backlighting, according to the company. 

“I used Razer keyboards for a long time, first the Black Widow and later the Huntsman TKL,” Monk said. “They are not bad, but I wasn’t super happy with the feel. I like the feel of the Keychron better. I also tried the K4, which is a 96% layout, but I’m used to tenkeyless now, so switched to the K8.” 

And he added that he likes the Keychron K8 mechanical keyboard so much that he actually has two K8 keebs. The second one is for his work setup (Windows).

And along with that keyboard, by the way, Monk uses a mouse so popular we see it as much if not more than Apple’s Magic Mouse. That would be the seemingly ubiquitious Logitech MX Master 3S wireless mouse. You can find it and the other gear, including that great keyboard, in the gear list below. 

Mac Studio and Studio Display refurbs in setup
This user said it’s hard to tell his Mac Studio and Studio Display aren’t new.
Photo: [email protected]

Shop these items now:

Mechanical keyboard and mouse:

Computer:

Display and accessories:

Connectivity:

Other:

If you would like to see your setup featured on Cult of Mac, send some high-res pictures to [email protected]. Please provide a detailed list of your equipment. Tell us what you like or dislike about your setup, and fill us in on any special touches, challenges and plans for new additions.



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How to deploy a Llama 2 70B API in just 5 clicks

How to deploy a Llama 2 70B API in just 5 clicks

Trelis Research has recently released a comprehensive guide on how to set up an API for the Llama 70B using RunPod, a cloud computing platform primarily designed for AI and machine learning applications. This guide provides a step-by-step process on how to optimize the performance of the Llama 70B API using RunPod’s key offerings, including GPU Instances, Serverless GPUs, and AI Endpoints.

RunPod’s GPU Instances allow users to deploy container-based GPU instances that spin up in seconds using both public and private repositories. These instances are available in two different types: Secure Cloud and Community Cloud. The Secure Cloud operates in T3/T4 data centers, ensuring high reliability and security, while the Community Cloud connects individual compute providers to consumers through a vetted, secure peer-to-peer system.

The Serverless GPU service, part of RunPod’s Secure Cloud offering, provides pay-per-second serverless GPU computing, bringing autoscaling to your production environment. This service guarantees low cold-start times and stringent security measures. AI Endpoints, on the other hand, are fully managed and scaled to handle any workload. They are designed for a variety of applications including Dreambooth, Stable Diffusion, Whisper, and more.

Deploying a Llama 2 70B API on RunPod

To automate workflows and manage compute jobs effectively, RunPod provides a CLI / GraphQL API. Users can access multiple points for coding, optimizing, and running AI/ML jobs, including SSH, TCP Ports, and HTTP Ports. RunPod also offers OnDemand and Spot GPUs to suit different compute needs, and Persistent Volumes to ensure the safety of your data even when your pods are stopped. The Cloud Sync feature allows seamless data transfer to any cloud storage.

Other articles you may find of interest on the subject of Meta’s Llama 2 large language model.

Setting up RunPod

 

To set up an API for Llama 70B, users first need to create an account on RunPod. After logging in, users should navigate to the Secure Cloud section and choose a pricing structure that suits their needs. Users can then deploy a template and find a Trellis Research Lab Llama 2 70B. Once the model is loaded, the API endpoint will be ready for use.

To increase the inference speed, users can run multiple GPUs in parallel. Users can also run a long context model by searching for a different template by trellis research. The inference software allows users to make multiple requests to the API at the same time. Sending in large batches can make the approach as economic as using the open AIA API. Larger GPUs are needed for more batches or longer context length.

One of the key use cases for doing inference on a GPU is for data preparation. Users can also run their own model by swapping out the model name on hugging face. Access to the Llama 2 Enterprise Installation and Inference Guide server setup repo can be purchased for €49.99 for more detailed information on setting up a server and maximizing throughput for models.

Deploying a Meta’s Llama 2 70B API using RunPod is a straightforward process that can be accomplished in just a few steps. With the right tools and guidance, users can optimize the performance of their API and achieve their AI and machine learning objectives.

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