Do you like really cool wallpapers for your phone? Of course you do. Everyone does. That’s why it seems like such an easy market to provide for, and why it was such a shock when Marques Brownlee — MKBHD — tripped over himself with the launch of the Panels app. Despite the YouTuber’s popularity, much of the internet quickly turned on him when he released his wallpaper app Panels and it asked for an unnecessary number of permissions alongside an absurdly high subscription cost.

Brownlee made the right move by responding calmly to the criticism and listening to what fans had to say. He released a 15-minute long video detailing what he planned to change and improve to address those concerns.

Brownlee says that the app should have always been free, and he’s right. There are far too many places to download wallpapers to count and next to none of them charge much. Panels might have attractive wallpapers, but they need to be more than aesthetically pleasing to ask such a high price point. Now the free tier of Panels will be loaded with 1080p wallpapers, but with none of the annoying advertisements from before. And if you want a higher-resolution version of a wallpaper you see there, you can unlock it by watching an ad.

Of course, if you want to avoid any ads at all (like most of us do), you can sign up for Panel’s new subscription tier: a mere $2 per month. You’ll also be able to purchase individual collections of wallpapers from artists for a one-time payment, or you can unlock all of them for your use if you sign up for the original $12 monthly/$50 annually plan.

Now, about the permissions — those are reportedly being fixed, and the initially broad scope was due to Brownlee and the Panels team providing incorrect information to the App Store.

The biggest takeaway from this whole debacle is that Brownlee geniunely does listen to his fans. In a time when the dollar drives every decision, that’s a nice thing to know.

TikTok has announced layoffs affecting hundreds of employees worldwide, with a significant impact on its workforce in Malaysia. The social media giant confirmed the cuts on Friday, citing a strategic move to enhance using artificial intelligence (AI) in its content moderation processes. The decision aligns with TikTok’s goal to streamline operations and increase efficiency in managing its vast user-generated content.

Impact in Malaysia: Hundreds of Jobs Affected to enhance the use of AI

Sources familiar with the situation told Reuters that TikTok initially planned to lay off more than 700 employees in Malaysia. However, the company later clarified that fewer than 500 workers in the country were actually affected by the decision. Most of those losing their jobs were part of the firm’s content moderation team.

TikTok informed the affected employees of the layoffs through email late Wednesday. The job cuts align with the company’s broader plan to enhance its global moderation efforts using AI technology.

The company uses both automated systems and human moderators to review its content. The company aims to increase AI’s role in moderation. It believes this shift will improve its efficiency and effectiveness in handling content.

A TikTok spokesperson said the company is committed to strengthening its content moderation model globally. “We’re making these changes as part of our ongoing efforts to further strengthen our global operating model for content moderation,” the spokesperson said. The shift will allow TikTok to handle the growing volume of content more effectively, with the help of advanced AI technologies.

Investment in Trust and Safety

Despite the layoffs, TikTok has indicated its continued investment in trust and safety initiatives. The popular social media app plans to allocate $2 billion globally this year to enhance its content moderation and ensure a safer user experience. According to TikTok, around 80% of content that violates guidelines is already being flagged and removed through automated technologies.

ByteDance, TikTok’s parent company, currently employs over 110,000 people in more than 200 cities worldwide. This restructuring move, however, is expected to lead to further job cuts as TikTok consolidates some of its regional operations.

The company’s efforts to bolster AI-based content moderation come amid increasing pressure from governments around the world, including Malaysia. In the first half of 2023, TikTok and Meta faced a record number of content restriction requests from the Malaysian government. These requests often targeted posts related to sensitive topics, such as race, religion, and royalty.

October Prime Day may have come and gone, but you can still save on Lego sets at the moment. While you may think it’s early to think about holiday shopping, these kits make amazing presents — for the young and full-grown adults alike. At Engadget, we’re most interested in specific sets from lines like Super Mario, Star Wars and Harry Potter, and some of these are still on sale for up to 41 percent off. These are the best Prime Day Lego deals you can still get today.

Prime Day Lego deals still available

On the Star Wars side of things, this Spider Tank set is 36 percent off and down to only $32, which is the lowest it’s ever been. It includes 526 pieces that replicate the spider tank from season three of The Mandalorian, plus three minifigures: Din Djarin, Bo-Katan Kryze and Grogu. Once built, the spider tank has grabbing claws, flexible legs and a little cockpit in which one of the figures can sit. Also on sale is this Boarding The Tantive IV set in which you recreate the iconic scene from Star Wars: A New Hope. That will set you back $44, which represents a 20-percent discount.

The Star Wars Lego Advent calendar (complete with Luke and Leia in holiday sweaters) is down to $36, after a 20 percent discount, and we don’t expect this one to last long.

In the Mario space, this Dixie Kong’s Jungle Jam expansion set has the biggest discount: 41 percent off and down to $16. It has 174 pieces along with buildable Dixie Kong and Squawks figures that both come with musical accessories. Mario fans who are old enough to have a work-from-home setup might appreciate this displayable Piranha Plant set that would look great in the background of any video conference call. It’s 20 percent off and down to $48.

Rounding things out with Harry Potter sets, this Hogwarts Castle and Grounds set is down to $136 and has never been cheaper. It includes 2,660 pieces that create a final product that’s over eight inches high, 13 inches wide and 10 inches deep. Plus, it comes with a cute, golden Hogwarts architect statue minifigure.

If you’re looking for more general Lego sets, the best deal we found was on the Classic Medium Creative Brick Box, down to $21. The box includes 484 pieces in all different sizes and colors, and would make a great gift for anyone who just likes to build with Lego without following a set of instructions.

Follow @EngadgetDeals on Twitter for the latest tech deals and buying advice, and stay tuned to Engadget.com for all of the best tech deals coming out of October Prime Day 2024.

The number of AI video generation models continues to grow with a new one, Pyramid Flow, launching this week and offering high quality video clips up to 10 seconds in length — quickly, and all open source.

Developed by a collaboration of researchers from Peking University, Beijing University of Posts and Telecommunications, and Kuaishou Technology — the latter the creator of the well-reviewed proprietary Kling AI video generator — Pyramid Flow leverages a new technique wherein a single AI model generates video in stages, most of them low resolution, saving only a full-res version for the end of its generation process.

It’s available as raw code for download on Hugging Face and Github, and can be run in an inference shell here but requires the user to download and run the model code on their own machine.

At inference, the model can generate a 5-second, 384p video in just 56 seconds—on par with or faster than many full-sequence diffusion counterparts — though Runway’s Gen 3-Alpha Turbo still takes cake in terms of speed of AI video generation, coming in at under one minute and often times 10-20 seconds in our tests.

We haven’t had a chance to test Pyramid Flow yet, but the videos posted by the model creators appear to be incredibly lifelike, high enough resolution, and compelling — analogous to those of proprietary offerings. You can see various examples here on its Github project page.

Indeed, Pyramid Flow is available designed now to download and use — even for commercial/enterprise purposes — and is designed to compete directly with paid proprietary offerings such as Runway’s Gen-3 Alpha, Luma’s Dream Machine, Kling, and Haulio, which can cost hundreds of even thousands of dollars a year for users on unlimited generation subscriptions.

As the race between various AI video providers to gain users continues, Pyramid Flow aims to bring more efficiency and flexibility to developers, artists, and creators seeking advanced video generation capabilities.

A new technique for high-quality AI videos: ‘pyramidal flow matching’

AI video generation is a computationally intensive task that typically involves modeling large spatiotemporal spaces. Traditional methods often require separate models for different stages of the process, which limits flexibility and increases the complexity of training.

Pyramid Flow is built on the concept of pyramidal flow matching, a method that drastically cuts down the computational cost of video generation while maintaining high visual quality, completing the video generation process as a series of “pyramid” stages, with only the final stage operating at full resolution.

It’s described in a pre-reviewed paper, “Pyramidal Flow Matching for Efficient Video Generative Modeling,” submitted to open access science journal arXiv on October 8, 2024.

The authors include Yang Jin, Zhicheng Sun, Ningyuan Li, Kun Xu, Hao Jiang, Nan Zhuang, Quzhe Huang, Yang Song, Yadong Mu, and Zhouchen Lin. Most of these researchers are affiliated with Peking University, while others are from Kuaishou Technology.

As they write, the ability to compress and optimize video generation at different stages leads to faster convergence during training, allowing Pyramid Flow to generate more samples per training batch.

For example, the proposed pyramidal flow reduces the token count by a factor of four compared to traditional diffusion models, which results in more efficient training.

The model can produce 5- to 10-second videos at 768p resolution and 24 frames per second, all while being trained on open-source datasets. Specifically, the paper states that Pyramid Flow was trained on trained on:

• LAION-5B, a large dataset for multimodal AI research.
• CC-12M, a dataset of web-crawled image-text pairs.
• SA-1B, which features high-quality, non-blurred images.
• WebVid-10M and OpenVid-1M, which are video datasets widely used for text-to-video generation.

In total, the authors curated approximately 10 million single-shot videos.

However, many of these “public” or “open source” datasets have in recent years come under fire from critics for including copyrighted material without permission or informed consent of the copyright holders, and LAION-5B in particular accused of hosting child sexual abuse material.

Separately, Runway is among the companies being sued by artists in a class action lawsuit for training on materials without permission, compensation, or consent — allegedly in violation of U.S. copyright. The case remains being argued in court, for now.

Permissively licensed, open source for commercial usage

Pyramid Flow is released under the MIT License, allowing for a wide range of uses, including commercial applications, modifications, and redistribution, provided the copyright notice is preserved.

This makes Pyramid Flow an attractive option for developers and companies looking to integrate the model into proprietary systems, and could challenge Luma AI and Runway as both look to offer paid application programming interfaces for developers seeking to integrate their proprietary AI video generation technology into customer or employee-facing apps.

Yet those proprietary models already exist as inferences suitable for developers, while Pyramid Flow has a demo inference on Hugging Face, it is not suitable for building full applications atop it and users would need to host their own version of an inference, which could also be costly, despite the model itself being “free.”

In addition, Pyramid Flow may prove to be enticing to film studios looking to leverage AI to gain efficiencies, cut costs, and explore new creative tools. One major film studio, Lionsgate — owner of the John Wick and Twilight films franchises, among many other tiles — recently inked a deal for an unspecified sum with Runway to train a custom AI video generation model. Furthermore, Titanic and Terminator director James Cameron joined the board of AI video and image model provider Stability (the latter also subject to the same class-action lawsuit from artists as Runway).

Using Pyramid Flow, Lionsgate or any other film studio could fine-tune the open source version without paying a third party company. However, they would still need to have on hand or contract out the developer talent and computing resources necessary to do so, which may make partnering with established AI providers such as Runway more appealing, since that company and others like it already have the AI engineering talent at their disposal in house.

The research team behind Pyramidal Flow Matching has also made a commitment to openness and accessibility. All code and model weights will be made freely available to the public through their official project page, ensuring that researchers and developers around the world can utilize and build upon this work.

Despite its strengths, Pyramid Flow does have some limitations. For now, it lacks some of the advanced fine-tuning capabilities found in models like Runway Gen-3 Alpha, which offers precise control over cinematic elements like camera angles, keyframes, and human gestures. Similarly, Luma’s Dream Machine provides advanced camera control options that Pyramid Flow is still catching up to.

Moreover, the relatively recent launch of Pyramid Flow means its ecosystem—while robust—isn’t as mature as those of its competitors.

Looking ahead: AI video race shows no signs of slowing

As the AI video generation market continues to evolve, Pyramid Flow’s launch signals a shift toward more accessible, open-source solutions that can compete with proprietary offerings such as Runway and Luma.

For now, it offers a solid alternative for those looking to avoid the cost and limitations of closed models, while providing impressive video quality on par with its more commercial counterparts.

In the coming months, developers and creators will likely keep a close eye on Pyramid Flow’s growth. With the potential for further improvements and optimizations, it could very well become a go-to tool in the arsenal of video content creators everywhere. All the companies and researchers are currently battling both for technological supremacy and users.

Meanwhile, OpenAI’s Sora, first shown off in February 2024, remains nowhere to be seen — outside of its collaborations with a handful of small early alpha users.

How to preorder the standard PlayStation 5 Pro

$699

The “pro” version of Sony’s PlayStation 5 has a bigger GPU, new PSSR AI-based upscaling, advanced ray tracing, and 2TB SSD (with expandable storage). The new features allow for better graphics at higher frame rates, allowing for the blending of “fidelity” and “performance” modes in some games.

Where to order a PS5 Pro disc drive

$80

Sony’s official disc drive for PS5 Digital Edition consoles allows you to retrofit both the PS5 Digital Edition and PS5 Pro with a bay for inserting physical games.

Huawei has announced the seventh generation of its all-flash OceanStor Dorado array, claiming it will meet enterprise data storage needs for the AI era.

The new storage solution is specifically designed for mission-critical applications, delivering what the company describes as “extreme performance and resilience” for complex AI workloads.