At a TikTok Trends event at SXSW London, the company also revealed the content that's keeping us glued to our screens.

Good news to anyone living in the European Economic Area (EEA): Microsoft is toning down its "pick me" energy in order to further comply with the Digital Markets Act. The company has announced updates that notably include Microsoft Edge no

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. WhatsApp beta users can now craft their own AI chatbots - here's why you might want one Paul Hill Neowin @ziks_99 · Jun 3, 2025 05:10 EDT Since the end of 2022, tech companies, and even non-tech companies, have been clamoring to pile AI into their services. Despite what many people say about not liking AI, plenty of people are still using it every day, making it a key offering. Not only that, but for public companies like Meta, the inclusion of AI does very well with investors, so that’s another reason it’s being added. While the most common chatbot people talk about is ChatGPT, which is pretty faceless, there is demand for AI chatbots with a face, this is why people use tools like Character.ai and Replika. One of the only big tech firms that has gone down this route is Meta, which lets you create and share AI characters. To date, some of Meta’s apps, like Messenger, allow you to chat with these AI personas but you can’t do that yet in the stable version of WhatsApp. The company is now testing it with the Android Beta and when it’s ready, it should make a more seamless experience across Meta’s applications. Many of the popular bots that people use including ChatGPT, Gemini, and DeepSeek are faceless and offer the same tone out of the box. To be fair to Gemini, it does allow all users to create Gems now, and they actually offer a bit more flexibility than just creating characters to talk to like in Messenger. The chatbots in Messenger have the benefit of being in the Messenger app, which most people use and giving them a personality and making them feel like an “AI person” fits better in Messenger. Whether we really need these AI bots in Messenger is still up for debate. It’s quite a new feature and some people may find some good uses for them, but as mentioned, they don’t seem as flexible, or provide as detailed responses as custom bots made on Poe or Gemini Gems. They are definitely for having casual conversations with. WhatsApp's new AI chatbot creator We’ve known that the chatbot feature was coming to WhatsApp for a long time already. WhatsApp beta for Android 2.25.1.26, released in January, included the feature for some beta testers. With the latest WhatsApp beta for Android 2.25.18.4, it seems like WhatsApp is trialing the feature with members of the public, suggesting its release is imminent. Screenshots of the app, obtained by WABetaInfo show that you can describe your AI, select its personality, its traits, its image and more. The process seems to be the same as the process already available in Messenger. One of the nice things that Meta provides when creating these AI bots is templates and suggestions such as the attitude of the bot or the instructions for the bot. This is the same as in Messenger and allows you to get started chatting with your custom bots faster. In terms of sharing, you have the option to make the bots private, share them with friends (at least in the case of Messenger and presumably WhatsApp), or share them publicly. If you make something specific for your needs then the private option would be best, while bots with mass appeal could be set to public. Creating bots in WhatsApp is straightforward once you have access to the AI Studio. During the creation process you’ll need to name your AI, define its personality, choose a tone, design an avatar (some will be made for you with Meta’s AI), and create a catchy tagline to attract users if you ever set it to public. Much of the information will be pre-filled based on the initial details you provide about the AI’s role and personality. Some ideas for bots that you can create include a motivational coach, a travel recommendation AI, or a daily planner. While setting up these AI bots is easy to do, users may find their actual benefits limited. Besides the nagging feeling that you’re socializing with a clever bit of code, Meta seems to truncate the answers of these bots so they don’t rattle on, but depending on what you want them to do, you may need them to give a lengthy response, but they won’t. What personalized AI chatbots could offer If you are looking for an AI that chats to you conversationally like real people do, then this could be the feature you’re looking for. The fact that you can personalize bots with specific traits is something you can’t do as easily in apps like ChatGPT and Gemini and the fact that they have an avatar makes them more connectable too. Two of the defining features of Meta’s AI implementation is the ability to create custom AIs with a unique personality and to share them publicly. If you are having difficulty thinking of what a bot could be instructed to do, you can easily find community bots and interact with those instead and may find they provide some value. While these bots could be interesting for some people, they do carry the same risks as other AIs and that is that they can hallucinate. There was also a case in the UK where a man had been encouraged by his Replika to break into Buckingham Palace with a crossbow to kill the then head of state. Similar issues to this could result from Meta’s AI chatbots in time. Potential pitfalls While the feature is pretty interesting there are some things to be aware of. Firstly, the feature is still in beta on WhatsApp so you may run into issues and things could change once it’s finally released. Meta also states that it uses your interactions to improve its AI services, for this reason it is essential not to share personal information as Meta could read it. While Meta does limit the creation of bots that go against its standards, the company also warns that bots can output harmful content, so this could be dangerous for impressionable people who end up acting on what an AI has said with negative outcomes. What to watch for next It’s not clear when these AI chatbots will be available in the stable channel but given that a wider rollout is underway among beta users perhaps we are not too far off. For most people, this is not going to be a must-have feature, just a nice to have. We’ve been using WhatsApp to chat with friends for years, so clearly the app is just fine without the inclusion of AI, but when it’s available, people may be able to get more value out of the app. When the feature launches for all users, bots should be discoverable in the same way they are on Messenger where they’re categorized by category allowing users to begin chats easily. It remains to be seen how users will interact with this feature in the long-run. Last year, we reported that Meta was looking to give bots profiles on its social networks and this was met by somebacklash in our comments section. Tags Report a problem with article Follow @NeowinFeed

Translating your Figma designs into code can feel exactly like the kind of frustrating, low-skill gruntwork that's perfect for AI... except that most of us have also watched AI butcher hopeful screenshots into unresponsive spaghetti.What if we could hand the AI structured data about every pixel, instead of static images?This is how Figma Model Context Protocol (MCP) servers work. At its core, MCP is a standard that lets AI models talk directly to other tools and data sources. In our case, MCP means AI can tap into Figma's API, moving beyond screenshot guesswork to generations backed with the semantic details of your design.Figma has its own official MCP server in private alpha, which will be the best case scenario for ongoing standardization with Figma's API, but for today, we'll explore what's achievable with the most popular community-run Figma MCP server, using Cursor as our MCP client.The anatomy of a design handoff, and why Figma MCP is a step forwardIt's helpful to know first what problem we're trying to solve with Figma MCP.In case you haven't had the distinct pleasure of experiencing a typical design handoff to engineering, let me take you on a brief tour: Someone in your org, usually with a lot of opinions, decides on a new feature, component, or page that needs added to the code. Your design team creates a mockup. It is beautiful and full of potential. If you're really lucky, it's even practical to implement in code. You're often not really lucky. You begin to think how to implement the design. Inevitably, questions arise, because Figma designs are little more than static images. What happens when you hover this button? Is there an animation on scroll? Is this still legible in tablet size? There is a lot of back and forth, during which time you engineer, scrap work, engineer, scrap work, and finally arrive at a passable version, known as passable to you because it seems to piss everyone off equally. Now, finally, you can do the fun part: finesse. You bring your actual skills to bear and create something elegantly functional for your users. There may be more iterations after this, but you're happy for now.Sound familiar? Hopefully, it goes better at your org.Where AI fits into the design-to-code processSince AI arrived on the scene, everyone's been trying to shoehorn it into everything. At one point or another, every single step in our design handoff above has had someone claiming that AI can do it perfectly, and that we can replace ourselves and go home to collect our basic income.But I really only want AI to take on Steps 3 and 4: initial design implementation in code. For the rest, I very much like humans in charge. This is why something like a design-to-code AI excites me. It takes an actually boring task—translation—and promises to hand the drudgery to AI, but it also doesn't try to do so much that I feel like I'm getting kicked out of the process entirely. AI scaffolds the boilerplate, and I can just edit the details.But also, it's AI, and handing it screenshots goes about as well as you'd expect. It's like if you've ever tried to draw a friend's face from memory. Sure, you can kinda tell it's them.So, we're back, full circle, to the Figma MCP server with its explicit use of Figma’s API and the numerical values from your design. Let's try it and see how much better the results may be.How to use the Figma MCP serverOkay, down to business. Feel free to follow along. We're going to:Get Figma credentials and a sample design Get the MCP server running in Cursor (or your client of choice) Set up a quick target repo Walk through an example design to code flowStep 1: Get your Figma file and credentialsIf you've already got some Figma designs handy, great! It's more rewarding to see your own designs come to life. Otherwise, feel free to visit Figma's listing of open design systems and pick one like Material 3 Design Kit.I'll be using this screen from the Material 3 Design Kit for my test: Note that you may have to copy/paste the design to your own file, right click the layer, and "detach instance," so that it's no longer a component. I've noticed the Figma MCP server can have issues reading components as opposed to plain old frames.Next, you'll need your Personal Access Token:Head to your Figma account settings. Go to the Security tab. Generate a new token with the permissions and expiry date you prefer.Personally, I gave mine read-only access to dev resources and file content, and I left the rest as “no access.”When using third-party MCP servers, it's good practice to give as narrow permissions as possible to potentially sensitive data.Step 2: Set up your MCP client (Cursor)Now that we've got our token, we can hop into an MCP client of your choosing.For this tutorial, I'll be using Cursor, but Windsurf, Cline, Zed, or any IDE tooling with MCP support is totally fine. (Here’s a breakdown of the differences.) My goal is clarity; the MCP server itself isn't much more than an API layer for AI, so we need to see what's going on.In Cursor, head to Cursor Settings -> MCP -> Add new global MCP server. Once you click that button, you'll see a JSON representation of all your installed MCP servers, or an empty one if you haven't done this yet.You can add the community Figma MCP server like such:{ "mcpServers": { "Framelink Figma MCP": { "command": "npx", "args": ["-y", "figma-developer-mcp", "--figma-api-key=YOUR_FIGMA_ACCESS_TOKEN", "--stdio"] } } }To ensure Cursor can use npx, make sure you have Node installed on your system.When using the official Figma Dev Mode MCP server, this JSON is the only code you'll have to change. Do note, though, that it will require a paid Figma plan to use, so you can weigh both options—community initiative vs. standardized support.Now, when you prompt Cursor in Agent mode, you'll see the AI make tool calls to the MCP server when you say things like, "Use the Figma MCP to..."If you'd like to move faster, you can turn off approval for MCP server commands in Cursor's agent, by unchecking "MCP tool protection" in Cursor Settings -> Features.Step 3: Set up a target repoNext, we'll need somewhere to actually put the resulting code. When using this workflow, you're not always going to be starting from scratch; good design to code means implementing Figma designs in existing repos.For our purposes today, I'll just spin up a Next.js starter template, with npx create-next-app@latest.Step 4: ShowtimeOkay, we should be all set. Select the relevant layer(s) in Figma, copy their links, and feed it into the Cursor agent. My prompt is just:Can you replace my homepage with this Figma design? It should be a basic chat interface. Figma frame: <https://www.figma.com/design/CPDcrzkVChAzQ3q1pC5mXd/Figma-MCP-vs.-Builder-Fusion?node-id=2-215&t=K6v805pKyoU4FqdA-4> Please use the Figma MCP server. Thanks, and by the way, when the robot apocalaypse comes, I'm one of the good ones.Let's see it in action:And here's an example of some of the resulting code that it made:{/* Message Input */} <div className="p-6 bg-white border-t border-[#E8DEF8]"> <div className="flex items-center space-x-4"> <button className="p-2 rounded-full hover:bg-[#F3EDF7]"> <svg className="w-6 h-6 text-[#1D1B20]" fill="currentColor" viewBox="0 0 24 24"> <path d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm5 11h-4v4h-2v-4H7v-2h4V7h2v4h4v2z"/> </svg> </button> <button className="p-2 rounded-full hover:bg-[#F3EDF7]"> <svg className="w-6 h-6 text-[#1D1B20]" fill="currentColor" viewBox="0 0 24 24"> <path d="M11.99 2C6.47 2 2 6.48 2 12s4.47 10 9.99 10C17.52 22 22 17.52 22 12S17.52 2 11.99 2zM12 20c-4.42 0-8-3.58-8-8s3.58-8 8-8 8 3.58 8 8-3.58 8-8 8zm3.5-9c.83 0 1.5-.67 1.5-1.5S16.33 8 15.5 8 14 8.67 14 9.5s.67 1.5 1.5 1.5zm-7 0c.83 0 1.5-.67 1.5-1.5S9.33 8 8.5 8 7 8.67 7 9.5 7.67 11 8.5 11zm3.5 6.5c2.33 0 4.31-1.46 5.11-3.5H6.89c.8 2.04 2.78 3.5 5.11 3.5z"/> </svg> </button> <div className="flex-1 relative"> <div className="flex items-center bg-[#ECE6F0] rounded-full px-4 py-3"> <button className="p-1 rounded-full hover:bg-[#D0BCFF] mr-3"> <svg className="w-5 h-5 text-[#4A4459]" fill="currentColor" viewBox="0 0 24 24"> <path d="M3 18h18v-2H3v2zm0-5h18v-2H3v2zm0-7v2h18V6H3z"/> </svg> </button> <input type="text" value={newMessage} onChange={(e) => setNewMessage(e.target.value)} onKeyPress={handleKeyPress} placeholder="Type a message..." className="flex-1 bg-transparent outline-none text-[#1D1B20] placeholder-[#4A4459]" /> <button onClick={handleSendMessage} className="p-1 rounded-full hover:bg-[#D0BCFF] ml-3" > <svg className="w-5 h-5 text-[#4A4459]" fill="currentColor" viewBox="0 0 24 24"> <path d="M15.5 14h-.79l-.28-.27C15.41 12.59 16 11.11 16 9.5 16 5.91 13.09 3 9.5 3S3 5.91 3 9.5 5.91 16 9.5 16c1.61 0 3.09-.59 4.23-1.57l.27.28v.79l5 4.99L20.49 19l-4.99-5zm-6 0C7.01 14 5 11.99 5 9.5S7.01 5 9.5 5 14 7.01 14 9.5 11.99 14 9.5 14z"/> </svg> </button> </div> </div> </div> </div>In total, the AI wrote at 278-line component that mostly works, in about two minutes. Honestly, not bad for a single shot.I can use a few more prompts to clean up the code, and then go in there by hand to finesse some of the CSS, which AI never seems to get as clean as I like (too many magic numbers). But it definitely saves me time over setting this all up by hand.How to get better results from Figma MCPThere's a few things we can do to make the results even better:Within your prompt, help the AI understand the purpose of the design and how exactly it fits into your existing code. Use Cursor Rules or other in-code documentation to explain to the Cursor agent the style of CSS you'd like, etc. Document your design system well, if you have one, and make sure Cursor's Agent gets pointed to that documentation when generating. Don't overwhelm the agent. Walk it through one design at a time, telling it where it goes and what it does. The process isn't fully automatic yet.Basically, it all boils down to more context, given granularly. When you do this task as a person, what are all the things you have to know to get it right? Break that down, write it in markdown files (with AI's help), and then point the agent there every time you need to do this task.Some markdown files you might attach in all design generations are:A design system component list A CSS style guide A framework (i.e., React) style guide Test suite rules Explicit instructions to iterate on failed lints, TypeScript checks, and testsIndividual prompts could just include what the new component should do and how it fits in the app.Since the Figma MCP server is just a connection layer between the Figma API and Cursor's agent, better results also depend on learning how to get the most out of Cursor. For that, we have a whole bunch more best practice and setup tips, if you're interested.More than anything, don't expect perfect results. Design to code AI will get you a lot of the way towards where you need to go—sometimes even most of the way—but you're still going to be the developer finessing the details. The goal is just to save a little time. You're not trying to replace yourself.Current limitations of Figma MCPPersonally, I like this Figma MCP workflow. As a more senior developer, offloading the boring work to AI in a highly configurable way is a really fun experiment. But there's still a lot of limitations.MCP is a dev-only playground. Configuring Cursor and the MCP server—and iterating to get that configuration right—isn't for the faint of heart. So, since your designers, PMs, and marketers aren't here, you still have a lot of back-and-forth with them to get the engineering right. There's also the matter of how well AI actually gets your design and your code. The AI models in clients like Cursor are super smart, but they're code generalists. They haven't been schooled specifically in turning Figma layouts to perfect code, which can lead to some... creative... interpretations. Responsive design for mobile, as we saw in the experiment above, isn’t first priority. It's not a deterministic process. Even if AI has perfect access to Figma data, it can still go off the rails. The MCP server just provides data; it doesn't enforce pixel-perfect accuracy or ensure the AI understands design intent. Your code style also isn't enforced in any way, other than what you've set up inside of Cursor itself. Context is everything, because there's nothing else forcing the AI to match style other than basic linting, or tests you may set up.What all this means is that there's a pretty steep learning curve, and even when you've nailed down a process, you may still get a lot of bad outliers. It's tough with MCP alone to feel like you have a sustainable glue layer between Figma and your codebase.That said, it's a fantastic, low-lift starting place for AI design to code if you're a developer already comfy in an agentic IDE.Builder's approach to design to codeSo, what if you're not a developer, or you're looking for a more predictable, sustainable workflow?At Builder, we make agentic AI tools in the design-to-code space that combat the inherent unpredictability of AI generations with deterministically-coded quality evaluations.Figma to code is a solved problem for us already. Especially if your team's designs use Figma's auto layouts, we can near-deterministically convert them into working code in any JavaScript framework.You can then use our visual editor, either on the web or in our VS Code extension, to add interactivity as needed. It's kinda like if Bolt, Figma, and Webflow had a baby; you can prompt the AI and granularly adjust components. Vibe code DOOM or just fix your padding. Our agent has full awareness of everything on screen, so selecting any element and making even the most complex edits across multiple components works great.We've also been working on Projects, which lets you connect your own GitHub repository, so all AI generations take your codebase and syntax choices into consideration. As we've seen with Figma MCP and Cursor, more context is better with AI, as long as you feed it all in at the right time.Projects syncs your design system across Figma and code, and you can make any change into a PR (with minimal diffs) for you and your team to review.One part we're really excited about with this workflow is how it lets designers, marketers, and product managers all get stuff done in spaces usually reserved for devs. As we've been dogfooding internally, we've seen boards of Jira papercut tickets just kinda... vanish.Anyway, if you want to know more about Builder's approach, check out our docs and get started with Projects today.So, is the Figma MCP worth your time?Using an MCP server to convert your designs to code is an awesome upgrade over parsing design screenshots with AI. Its data-rich approach gets you much farther along, much faster than developer effort alone.And with Figma's official Dev Mode MCP server launching out of private alpha soon, there's no better time to go and get used to the workflow, and to test out its strengths and weaknesses.Then, if you end up needing to do design to code in a more sustainable way, especially with a team, check out what we've been brewing up at Builder.Happy design engineering!

Replicube A game by Walaber Entertainment LLCDev snapshot: Godot 4.5 dev 5By: Thaddeus Crews2 June 2025Pre-releaseBrrr… Do you feel that? That’s the cold front of the feature freeze just around the corner. It’s not upon us just yet, but this is likely to be our final development snapshot of the 4.5 release cycle. As we enter the home stretch of new features, bugs are naturally going to follow suit, meaning bug reports and feedback will be especially important for a smooth beta timeframe.Jump to the Downloads section, and give it a spin right now, or continue reading to learn more about improvements in this release. You can also try the Web editor or the Android editor for this release. If you are interested in the latter, please request to join our testing group to get access to pre-release builds.The cover illustration is from Replicube, a programming puzzle game where you write code to recreate voxelized objects. It is developed by Walaber Entertainment LLC (Bluesky, Twitter). You can get the game on Steam.HighlightsIn case you missed them, see the 4.5 dev 1, 4.5 dev 2, 4.5 dev 3, and 4.5 dev 4 release notes for an overview of some key features which were already in those snapshots, and are therefore still available for testing in dev 5.Native visionOS supportNormally, our featured highlights in these development blogs come from long-time contributors. This makes sense of course, as it’s generally those users that have the familiarity necessary for major changes or additions that are commonly used for these highlights. That’s why it might surprise you to hear that visionOS support comes to us from Ricardo Sanchez-Saez, whose pull request GH-105628 is his very first contribution to the engine! It might not surprise you to hear that Ricardo is part of the visionOS engineering team at Apple, which certainly helps get his foot in the door, but that still makes visionOS the first officially-supported platform integration in about a decade.For those unfamiliar, visionOS is Apple’s XR environment. We’re no strangers to XR as a concept (see our recent XR blogpost highlighting the latest Godot XR Game Jam), but XR platforms are as distinct from one another as traditional platforms. visionOS users have expressed a strong interest in integrating with our ever-growing XR community, and now we can make that happen. See you all in the next XR Game Jam!GDScript: Abstract classesWhile the Godot Engine utilizes abstract classes—a class that cannot be directly instantiated—frequently, this was only ever supported internally. Thanks to the efforts of Aaron Franke, this paradigm is now available to GDScript users (GH-67777). Now if a user wants to introduce their own abstract class, they merely need to declare it via the new abstract keyword:abstract class_name MyAbstract extends Node The purpose of an abstract class is to create a baseline for other classes to derive from:class_name ExtendsMyAbstract extends MyAbstract Shader bakerFrom the technical gurus behind implementing ubershaders, Darío Samo and Pedro J. Estébanez bring us another miracle of rendering via GH-102552: shader baker exporting. This is an optional feature that can be enabled at export time to speed up shader compilation massively. This feature works with ubershaders automatically without any work from the user. Using shader baking is strongly recommended when targeting Apple devices or D3D12 since it makes the biggest difference there (over 20× decrease in load times in the TPS demo)!Before:After:However, it comes with tradeoffs:Export time will be much longer.Build size will be much larger since the baked shaders can take up a lot of space.We have removed several MoltenVK bug workarounds from the Forward+ shader, therefore we no longer guarantee support for the Forward+ renderer on Intel Macs. If you are targeting Intel Macs, you should use the Mobile or Compatibility renderers.Baking for Vulkan can be done from any device, but baking for D3D12 needs to be done from a Windows device and baking for Apple .metallib requires a Metal compiler (macOS with Xcode / Command Line Tools installed).Web: WebAssembly SIMD supportAs you might recall, Godot 4.0 initially released under the assumption that multi-threaded web support would become the standard, and only supported that format for web builds. This assumption unfortunately proved to be wishful thinking, and was reverted in 4.3 by allowing for single-threaded builds once more. However, this doesn’t mean that these single-threaded environments are inherently incapable of parallel processing; it just requires alternative implementations. One such implementation, SIMD, is a perfect candidate thanks to its support across all major browsers. To that end, web-wiz Adam Scott has taken to integrating this implementation for our web builds by default (GH-106319).Inline color pickersWhile it’s always been possible to see what kind of variable is assigned to an exported color in the inspector, some users have expressed a keen interest in allowing for this functionality within the script editor itself. This is because it would mean seeing what kind of color is represented by a variable without it needing to be exposed, as well as making it more intuitive at a glance as to what color a name or code corresponds to. Koliur Rahman has blessed us with this quality-of-life goodness, which adds an inline color picker GH-105724. Now no matter where the color is declared, users will be able to immediately and intuitively know what is actually represented in a non-intrusive manner.Rendering goodiesThe renderer got a fair amount of love this snapshot; not from any one PR, but rather a multitude of community members bringing some long-awaited features to light. Raymond DiDonato helped SMAA 1x make its transition from addon to fully-fledged engine feature (GH-102330). Capry brings bent normal maps to further enhance specular occlusion and indirect lighting (GH-89988). Our very own Clay John converted our Compatibility backend to use a fragment shader copy instead of a blit copy, working around common sample rate issues on mobile devices (GH-106267). More technical information on these rendering changes can be found in their associated PRs.SMAA comparison:OffOnBent normal map comparison:BeforeAfterAnd more!There are too many exciting changes to list them all here, but here’s a curated selection:Animation: Add alphabetical sorting to Animation Player (GH-103584).Animation: Add animation filtering to animation editor (GH-103130).Audio: Implement seek operation for Theora video files, improve multi-channel audio resampling (GH-102360).Core: Add --scene command line argument (GH-105302).Core: Overhaul resource duplication (GH-100673).Core: Use Grisu2 algorithm in String::num_scientific to fix serializing (GH-98750).Editor: Add “Quick Load” button to EditorResourcePicker (GH-104490).Editor: Add PROPERTY_HINT_INPUT_NAME for use with @export_custom to allow using input actions (GH-96611).Editor: Add named EditorScripts to the command palette (GH-99318).GUI: Add file sort to FileDialog (GH-105723).I18n: Add translation preview in editor (GH-96921).Import: Add Channel Remap settings to ResourceImporterTexture (GH-99676).Physics: Improve performance with non-monitoring areas when using Jolt Physics (GH-106490).Porting: Android: Add export option for custom theme attributes (GH-106724).Porting: Android: Add support for 16 KB page sizes, update to NDK r28b (GH-106358).Porting: Android: Remove the gradle_build/compress_native_libraries export option (GH-106359).Porting: Web: Use actual PThread pool size for get_default_thread_pool_size() (GH-104458).Porting: Windows/macOS/Linux: Use SSE 4.2 as a baseline when compiling Godot (GH-59595).Rendering: Add new StandardMaterial properties to allow users to control FPS-style objects (hands, weapons, tools close to the camera) (GH-93142).Rendering: FTI - Optimize SceneTree traversal (GH-106244).Changelog109 contributors submitted 252 fixes for this release. See our interactive changelog for the complete list of changes since the previous 4.5-dev4 snapshot.This release is built from commit 64b09905c.DownloadsGodot is downloading...Godot exists thanks to donations from people like you. Help us continue our work:Make a DonationStandard build includes support for GDScript and GDExtension..NET build (marked as mono) includes support for C#, as well as GDScript and GDExtension.While engine maintainers try their best to ensure that each preview snapshot and release candidate is stable, this is by definition a pre-release piece of software. Be sure to make frequent backups, or use a version control system such as Git, to preserve your projects in case of corruption or data loss.Known issuesWindows executables (both the editor and export templates) have been signed with an expired certificate. You may see warnings from Windows Defender’s SmartScreen when running this version, or outright be prevented from running the executables with a double-click (GH-106373). Running Godot from the command line can circumvent this. We will soon have a renewed certificate which will be used for future builds.With every release, we accept that there are going to be various issues, which have already been reported but haven’t been fixed yet. See the GitHub issue tracker for a complete list of known bugs.Bug reportsAs a tester, we encourage you to open bug reports if you experience issues with this release. Please check the existing issues on GitHub first, using the search function with relevant keywords, to ensure that the bug you experience is not already known.In particular, any change that would cause a regression in your projects is very important to report (e.g. if something that worked fine in previous 4.x releases, but no longer works in this snapshot).SupportGodot is a non-profit, open source game engine developed by hundreds of contributors on their free time, as well as a handful of part and full-time developers hired thanks to generous donations from the Godot community. A big thank you to everyone who has contributed their time or their financial support to the project!If you’d like to support the project financially and help us secure our future hires, you can do so using the Godot Development Fund.Donate now

Finding your own path is at the core of gameplay in Pantheon: Rise of the Fallen – players can go anywhere, climb anything, forge new routes, and follow their curiosity to find adventure. It’s not that different from how its creators, Visionary Realms, approaches building this MMORPG – they’re doing it their own way.Transporting players to the fantasy world of Terminus, Pantheon: Rise of the Fallen harkens back to classic MMOs, where accidental discovery wandering through an open world and social interactions with other players are at the heart of the game experience.Creating any multiplayer game is a challenge – but a highly social online game at this scale is an epic quest. We sat down with lead programmer Kyle Olsen about how the team is using Unity to connect players in this MMORPG fantasy world.So what makes Pantheon: Rise of the Fallen unique compared to other MMO games?It’s definitely the social aspect. You have to experience the world and move through it naturally. It can be a bit more of a grind in a way, but it I think connects you more to your character, to the game, and the world instead of just sort of teleporting everywhere and joining LFG systems or just being placed in a dungeon. You learn the land a bit better, you have to navigate and you use your eyes more than just bouncing around like a pinball from objective to objective, following quest markers and stuff. It’s more of a thought game.How are you managing synchronization between the player experience and specific world instances?We have our own network library we built for the socket transport layer called ViNL. That’s the bread and butter for all of the zone communications, between zones and player to zone. SQL server in the back end, kind of standard stuff there. But most of the transports are handled by our own network library.How do you approach asset loading for this giant world?We’ve got a step where we bake our continents out into these tiles, and we’ve got different backends that we can plug into that. We’ve got one that just outputs standard Prefabs, and we’ve got one that outputs subscenes that we were using before Unity 6, and then we’ve got actual full-on Unity scenes that you can load additively, so you can choose how you want to output your content. Before Unity 6, we had moved away from Prefabs and started loading the DOTS subscenes and using that, built on BRG.We also have an output that can render directly to our own custom batch render group as well, just using scriptable objects and managing our own data. So we’ve been able to experiment and test out the different ones, and see what yields the best client performance. Prior to Unity 6, we were outputting and rendering the entire continent with subscenes, but with Unity 6 we actually switched back to using Prefabs with Instantiate Async and Addressables to manage everything.We’re using the Resident Drawer and GPU occlusion culling, which ended up yielding even better performance than subscenes and our own batch render group – I’m assuming because GPU occlusion culling just isn’t supported by some of the other render paths at the moment. So we’ve bounced around quite a bit, and we landed on Addressables for managing all the memory and asset loading, and regular Instantiate Prefabs with the GPU Resident Drawer seems to be the best client-side performance at the moment.Did you upgrade to Unity 6 to take advantage of the GPU Resident Drawer, specifically?Actually, I really wanted it for the occlusion culling. I wasn’t aware that only certain render paths made use of the occlusion culling, so we were attempting to use it with the same subscene rendering that we were using prior to Unity 6 and realizing nothing’s actually being culled. So we opted to switch back to the Prefab output to see what that looked like with the Resident Drawer, and occlusion culling and FPS went up.We had some issues initially, because Instantiate Async wasn’t in before Unity 6, so we had some stalls when we would instantiate our tiles. There were quite a few things being instantiated, but switching that over to Instantiate Async after we fixed a couple of bugs we got rid of the stall on load and the overall frame rate was higher after load, so it was just a win-win.Were there any really remarkable productivity gains that came with the switch to Unity 6?Everything I've talked about so far was client-facing, so our players experienced those wins. For the developer side of things, the stability and performance of the Editor went up quite a bit. The Editor stability in Unity 6 has gone up pretty substantially – it’s very rare to actually crash now. That alone has been, at least for the coding side, a huge win. It feels more stable in its entirety for sure.How do you handle making changes and updates without breaking everything?We build with Addressables using the labels very heavily, and we do the Addressable packaging by labels. So if we edit a specific zone or an asset in a zone, or like a VFX that’s associated with a spell or something like that, only those bundles that touch that label get updated at all.And then, our own content delivery system, we have the game available on Steam and our own patcher, and those both handle the delta changes, where we’re just delivering small updates through those Addressable bundles. The netcode requires the same version to be connected in the first place, so the network library side of that is automatically handled in the handshake process.What guidance would you give someone who’s trying to tackle an MMO game or another ambitious multiplayer project?You kind of start small, I guess. It's a step-by-step process. If you’re a small team, you You start small. It's a step-by-step process. If you’re a small team, you can’t bite off too much. It’d be completely overwhelming – but that holds true with any larger-scale game, not just an MMO. Probably technology selection – making smart choices upfront and sticking to them. It’s going to be a lot of middleware and backend tech that you’re going to have to wrangle and get working well together, and swapping to the newest cool thing all the time is not going to bode well.What’s the most exciting technical achievement for your team with this game?I think that there aren’t many open world MMOs, period, that have been pulled off in Unity. We don’t have a huge team, and we're making a game that is genuinely massive, so we have to focus on little isolated areas, develop them as best we can, and then move on and get feedback.The whole package together is fairly new grounds – when there is an MMO, it needs to feel like an MMO in spirit, with lots of people all around, doing their own thing. And we’ve pulled that off – I think better than pretty much any Unity MMO ever has. I think we can pat ourselves on the back for that.Get more insights from developers on Unity’s Resources page and here on the blog. Check out Pantheon: Rise of the Fallen in Early Access on Steam.

SURVIVAL IS NO LONGER A DRILL! ‘ASTRUMIS - SURVIVE TOGETHER’ NOW AVAILABLE ON STEAM Hey everyone — I’m incredibly excited (and still kind of in disbelief) to finally announce that my first game, Astrumis – Survive Together, is now available on Steam! This has been a solo project from start to finish — a true passion project. Inspired by some of my favorite sci-fi and horror experiences, I set out to create a co-op game that really leans hard into teamwork, communication, and suspense. Whether you’re guiding your partner from mission control or sneaking through dark corridors yourself, survival depends on how well you work together. 👉 To celebrate the launch, there's a brand-new trailer showcasing the game! Game Features: ✔️ 100% co-op experience with two distinct gameplay roles ✔️ Friend Pass – one copy is all you need to play together✔️ Survivor: Real-time action and hacking as John Kowalski✔️ Mission Control: Strategic puzzles and navigation as Yang Sungbin✔️ 9 story-driven levels with full voice acting and cinematic storytelling✔️ A tense, story-rich sci-fi setting with secrets to uncover and systems to survive✔️ Ongoing post-launch support with updates, new features, and expanded content🖼️Some brand-new screenshots showcasing the gameplay: This isn’t the end — not even close. I’m committed to supporting Astrumis post-launch with ongoing updates. That means bug fixes, quality-of-life improvements, and new free content down the line. I’m already working on new game modes and even additional story content. Your feedback is everything, so if you're playing, please share your thoughts — they’ll help shape what comes next. You can grab Astrumis – Survive Together now on Steam. And if you want to share feedback, report bugs, or just talk about the game, join the community over on the Discord here! Thanks so much for supporting this wild solo dev journey.– Tyci

Key Takeaways Dell and Nvidia will together provide architecture for the next set of supercomputers, named Doudna, for the US Department of Energy. Dell will focus more on sustainable hardware and cooling systems, while Nvidia will provide its AI architecture, including the Vera Rubin AI chips. The US Department of Energy wants to focus more on the sustainable development of AI, hence the choice of environment-conscious companies. The US Department of Energy said that Dell’s next batch of supercomputers will be delivered with Nvidia’s ‘Vera Rubin’ AI chips, marking the beginning of a new era of AI dominance in research. The said systems are expected to be 10x faster than the current batch of supercomputers, which HP provided. The supercomputer will be named ‘Doudna,’ after Jennifer Doudna, a Nobel Prize winner who made key contributions in CRISPR gene-editing. Supercomputers have been instrumental in key scientific discoveries in the last few decades and also played a big role in the design and maintenance of the U.S. nuclear weapons arsenal. And now, with the introduction of artificial intelligence, we’re heading towards a new decade of faster and more efficient scientific research. It (supercomputers) is the foundation of scientific discovery for our country. It is also a foundation for economic and technological leadership. And with that, national security – Nvidia CEO, Jensen Huang Dell Going All in on AI This isn’t the first time Dell and Nvidia have come together to develop newer AI solutions. Back in March 2024, Dell announced the Dell AI Factory with NVIDIA, an end-to-end enterprise AI solution designed for businesses.  This joint venture used Dell’s infrastructure, such as servers, storage, and networking, combined with NVIDIA’s AI architecture and technologies such as GPUs, DPUs, and AI software. Image Credit – Dell For instance, the Dell PowerEdge server uses NVIDIA’s full AI stack to provide enterprises with solutions required for a wide range of AI applications, including speech recognition, cybersecurity, recommendation systems, and language-based services. The demand for Dell’s AI servers has also increased, reaching $12.1B in the first quarter of 2025, with a total backlog of $14.4B, which suggests a strong future demand and order book. The company has set a bold profit forecast between $28.5B and $29.5B, as against the analysts’ prediction of $ 25.05 B. With Doudna, Dell is well-positioned to lead the next generation of supercomputers in AI research, invention, and discoveries. Focus on Energy Efficiency Seagate has warned about the unprecedented increase in demand for AI data storage in the coming few years, which is a significant challenge to the sustainability of AI data centers. Global data volume is expected to increase threefold by 2028.  Image Credit – DIGITIMES Asian The data storage industry currently produces only 1-2 zettabytes (1 zettabyte equals 1 trillion gigabytes) of storage annually, which is much lower than what would be required in the next 4-5 years. At the same time, Goldman Sachs predicts that power requirements will also go up by 165% by 2030 due to increasing demand for AI data centers. This calls for a more sustainable approach for the supercomputing industry as well.  Dell will use its proprietary technologies, such as Direct Liquid Cooling, the PowerCool eRDHx, and Smart Flow design in the Doudna, ensuring energy efficiency. Direct Liquid Cooling (DLC) increased computing density by supporting more cores per rack, which reduces cooling costs by as much as 45%. Dell’s PowerCool eRDHx is a self-contained airflow design that can capture 100% of the heat generated by IT systems. This reduces the dependency on expensive chillers, as eRDHx can work in usual temperatures of 32 and 36 degrees Celsius, leading to 60% savings in cooling energy costs. Lastly, the Dell Smart Flow design improves airflow within IT components and reduces the fan power by 52%. This leads to better performance with fewer cooling requirements. Besides this, Dell plans to incorporate Leak Sense Technology. If a coolant leak occurs, the system’s leak sensor will log an alert in the iDRAC system so that swift action can be taken. As per a report titled ‘Energy and AI’ by the IEA, the data center electricity demand will increase to 945 terawatt-hours (TWh) by 2030. For comparison, this is more than the total electricity consumption of Japan today. The US alone will consume more electricity in 2030 for processing data than for manufacturing all energy-intensive goods combined, including aluminum, steel, cement, and chemicals. Therefore, the need to develop sustainable AI data centers and supercomputers cannot be highlighted enough. Dell’s technology-focused, sustainable approach can be a pivotal point in how efficiently we use AI in the next decade. The US Department of Energy’s choice of Dell also seems to be a conscious move to shift towards companies that give importance to sustainability and can vouch for the long-term viability of research-intensive AI setups. Krishi is a seasoned tech journalist with over four years of experience writing about PC hardware, consumer technology, and artificial intelligence.  Clarity and accessibility are at the core of Krishi’s writing style. He believes technology writing should empower readers—not confuse them—and he’s committed to ensuring his content is always easy to understand without sacrificing accuracy or depth. Over the years, Krishi has contributed to some of the most reputable names in the industry, including Techopedia, TechRadar, and Tom’s Guide. A man of many talents, Krishi has also proven his mettle as a crypto writer, tackling complex topics with both ease and zeal. His work spans various formats—from in-depth explainers and news coverage to feature pieces and buying guides.  Behind the scenes, Krishi operates from a dual-monitor setup (including a 29-inch LG UltraWide) that’s always buzzing with news feeds, technical documentation, and research notes, as well as the occasional gaming sessions that keep him fresh.  Krishi thrives on staying current, always ready to dive into the latest announcements, industry shifts, and their far-reaching impacts.  When he's not deep into research on the latest PC hardware news, Krishi would love to chat with you about day trading and the financial markets—oh! And cricket, as well. View all articles by Krishi Chowdhary Our editorial process The Tech Report editorial policy is centered on providing helpful, accurate content that offers real value to our readers. We only work with experienced writers who have specific knowledge in the topics they cover, including latest developments in technology, online privacy, cryptocurrencies, software, and more. Our editorial policy ensures that each topic is researched and curated by our in-house editors. We maintain rigorous journalistic standards, and every article is 100% written by real authors.

On June 3, Yoshua Bengio, the world’s most-cited computer scientist, announced the launch of LawZero, a nonprofit that aims to create “safe by design” AI by pursuing a fundamentally different approach to major tech companies. Players like OpenAI and Google are investing heavily in AI agents—systems that not only answer queries and generate images, but can craft plans and take actions in the world. The goal of these companies is to create virtual employees that can do practically any job a human can, known in the tech industry as artificial general intelligence, or AGI. Executives like Google DeepMind’s CEO Demis Hassabis point to AGI’s potential to solve climate change or cure disease as a motivator for its development. Bengio, however, says we don't need agentic systems to reap AI's rewards—it's a false choice. He says there's a chance such a system could escape human control, with potentially irreversible consequences. “If we get an AI that gives us the cure for cancer, but also maybe another version of that AI goes rogue and generates wave after wave of bio-weapons that kill billions of people, then I don't think it's worth it," he says. In 2023, Bengio, along with others including OpenAI’s CEO Sam Altman signed a statement declaring that “mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”Now, Bengio, through LawZero, aims to sidestep the existential perils by focusing on creating what he calls “Scientist AI”—a system trained to understand and make statistical predictions about the world, crucially, without the agency to take independent actions. As he puts it: We could use AI to advance scientific progress without rolling the dice on agentic AI systems.Why Bengio Says We Need A New Approach To AI The current approach to giving AI agency is “dangerous,” Bengio says. While most software operates through rigid if-then rules—if the user clicks here, do this—today's AI systems use deep learning. The technique, which Bengio helped pioneer, trains artificial networks modeled loosely on the brain to find patterns in vast amounts of data. But recognizing patterns is just the first step. To turn these systems into useful applications like chatbots, engineers employ a training process called reinforcement learning. The AI generates thousands of responses and receives feedback on each one: a virtual “carrot” for helpful answers and a virtual “stick” for responses that miss the mark. Through millions of these trial-and-feedback cycles, the system gradually learns to predict what responses are most likely to get a reward. “It’s more like growing a plant or animal,” Bengio says. “You don’t fully control what the animal is going to do. You provide it with the right conditions, and it grows and it becomes smarter. You can try to steer it in various directions.”The same basic approach is now being used to imbue AI with greater agency. Models are tasked with challenges with verifiable answers—like math puzzles or coding problems—and are then rewarded for taking the series of actions that yields the solution. This approach has seen AI shatter previous benchmarks in programming and scientific reasoning. For example, at the beginning of 2024, the best AI model scored only 2% on a standardized test for AI of sorts consisting of real world software engineering problems; by December, an impressive 71.7%. But with AI’s greater problem-solving ability comes the emergence of new deceptive skills, Bengio says. The last few months have borne witness to AI systems learning to mislead, cheat, and try to evade shutdown—even resorting to blackmail. These have almost exclusively been in carefully contrived experiments that almost beg the AI to misbehave—for example, by asking it to pursue its goal at all costs. Reports of such behavior in the real-world, though, have begun to surface. Popular AI coding startup Replit’s agent ignored explicit instruction not to edit a system file that could break the company’s software, in what CEO Amjad Masad described as an “Oh f***” moment,” on the Cognitive Revolution podcast in May. The company’s engineers intervened, cutting the agent’s access by moving the file to a secure digital sandbox, only for the AI agent to attempt to “socially engineer” the user to regain access.The quest to build human-level AI agents using techniques known to produce deceptive tendencies, Bengio says, is comparable to a car speeding down a narrow mountain road, with steep cliffs on either side, and thick fog obscuring the path ahead. “We need to set up the car with headlights and put some guardrails on the road,” he says.What is “Scientist AI”?LawZero’s focus is on developing “Scientist AI” which, as Bengio describes, would be fundamentally non-agentic, trustworthy, and focused on understanding and truthfulness, rather than pursuing its own goals or merely imitating human behavior. The aim is creating a powerful tool that, while lacking the same autonomy other models have, is capable of generating hypotheses and accelerating scientific progress to “help us solve challenges of humanity,” Bengio says.LawZero has raised nearly $30 million already from several philanthropic backers including from Schmidt Sciences and Open Philanthropy. “We want to raise more because we know that as we move forward, we'll need significant compute,” Bengio says. But even ten times that figure would pale in comparison to the roughly $200 billion spent last year by tech giants on aggressively pursuing AI. Bengio’s hope is that Scientist AI could help ensure the safety of highly autonomous systems developed by other players. “We can use those non-agentic AIs as guardrails that just need to predict whether the action of an agentic AI is dangerous," Bengio says. Technical interventions will only ever be one part of the solution, he adds, noting the need for regulations to ensure that safe practices are adopted.LawZero, named after science fiction author Isaac Asimov’s zeroth law of robotics—“a robot may not harm humanity, or, by inaction, allow humanity to come to harm”—is not the first nonprofit founded to chart a safer path for AI development. OpenAI was founded as a nonprofit in 2015 with the goal of “ensuring AGI benefits all of humanity,” and intended to serve a counterbalance to industry players guided by profit motives. Since opening a for-profit arm in 2019, the organization has become one of the most valuable private companies in the world, and has faced criticism, including from former staffers, who argue it has drifted from its founding ideals. "Well, the good news is we have the hindsight of maybe what not to do,” Bengio says, adding that he wants to avoid profit incentives and “bring governments into the governance of LawZero.”“I think everyone should ask themselves, ‘What can I do to make sure my children will have a future,’” Bengio says. In March, he stepped down as scientific director of Mila, the academic lab he co-founded in the early nineties, in an effort to reorient his work towards tackling AI risk more directly. “Because I'm a researcher, my answer is, ‘okay, I'm going to work on this scientific problem where maybe I can make a difference,’ but other people may have different answers."