Think tap to pay — but smarter and safer. Visa is tapping into AI to enhance services for its global network of customers, focused on fraud prevention, personalization and agentic commerce. Sarah Laszlo, senior director of Visa’s machine learning platform, joined the AI Podcast to discuss how artificial intelligence is powering the next generation of payment experiences. Visa processes hundreds of billions of transactions each year, so even small technological enhancements can have a large impact. The company prevents $40 billion in fraud annually. “There’s so much attempted fraud that, even though we’re very good at preventing it, marginal improvements save large dollar amounts,” Laszlo said. AI also powers Visa’s personalization systems, delivering smarter, more relevant offers and recommendations to cardholders. The company’s unique dataset presents a huge opportunity to improve transaction predictions — but also brings privacy challenges. “The key to addressing those challenges is building abstract representations of users — embeddings that capture preferences without exposing private data,” Laszlo said. The company is also working toward agentic commerce — where AI agents help customers with payments. For example, AI agents with access to payment credentials can handle transactions on behalf of consumers, like booking travel arrangements, when instructed. Laszlo shared best practices for enterprises adopting generative AI. She also recommended using open-source models when possible and developing strong relationships between governance and technical teams. In one success story, Visa used GPT-4 to convert legacy code to Python, saving $5 million, with just one engineer completing 50 conversion jobs in a quarter. To learn more, watch Laszlo’s GTC session, The Next Era of Payments: How Generative AI is Shaping the Future. Time Stamps 03:28 – Visa’s priorities for AI use. 07:09 – How Visa optimizes resources using virtual GPUs. 14:42 – AI factories and unified pipelines. 18:52 – Best practices for AI in financial services. You Might Also Like…  NVIDIA’s Jacob Liberman on Bringing Agentic AI to Enterprises Agentic AI enables developers to create intelligent multi-agent systems that reason, act and execute complex tasks with a degree of autonomy. Jacob Liberman, director of product management at NVIDIA, explains how agentic AI bridges the gap between powerful AI models and practical enterprise applications. Firsthand’s Jon Heller Shares How AI Agents Enhance Consumer Journeys in Retail Jon Heller, co-CEO and founder of Firsthand, discusses how the company’s Brand Agents are transforming the retail landscape by personalizing customer journeys, converting marketing interactions into valuable research data and enhancing the customer experience with hyper-personalized insights and recommendations. Telenor Builds Norway’s First AI Factory, Offering Sustainable and Sovereign Data Processing Telenor opened Norway’s first AI factory in November 2024, enabling organizations to process sensitive data securely on Norwegian soil while prioritizing environmental responsibility. Telenor’s Chief Innovation Officer and Head of the AI Factory Kaaren Hilsen discusses the AI factory’s rapid development, going from concept to reality in under a year.

html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN" "http://www.w3.org/TR/REC-html40/loose.dtd" We seem to have more video footage and still images than ever before, thanks to smartphones, GoPro cameras and the backlog of older ones collected across a lifetime. Managing all these formats, as well as making sure they look their best, can be a frightening proposition. Thankfully, Winxvideo AI is a powerful all-in-one solution that not only uses advanced Artificial Intelligence software to upgrade the quality of your content but can rescue old photos and footage too. The newly updated version 4.0 also brings huge improvements to speed, plus a special price offer, so you can save both time and money while you upgrade your photo and video library. Grab your discount on Winxvideo AI Winxvideo AI comes with an impressive array of features that can turn tired, old, blurry videos into something far more professional. For example, if you have footage of a significant event that was shot on an old device and only displays in low resolution, then the AI upscaling tool can cleverly convert it to 720p ,1080p or even 4K! It offers dedicated AI models for different video types – whether enhancing fine details, smoothing low-detail footage, refining animations, or upscaling photorealistic content. Digiarty Winxvideo AI significantly improves video quality thanks to its advanced AI models that remove noise, sharpen footage, and clean up compression artifacts caused by low light or poor equipment. This means that the unimpressive video you shot of an important occasion can instantly look better than you thought possible, and play back in glorious 4K with realistic detail, revealing textures like skin, hair, fur, and fabric with impressive clarity. Is a great shot spoiled by the camera shaking? No problem, the AI Stabilization capabilities in Winxvideo AI can fix that in only a few clicks. If you find that your video is jerky and stutters due to a low frame rate, that’s fixable too thanks to the AI frame interpolation that can boost frame rates for smooth footage or allow you to convert it to slo-mo instead. Alongside these tools there’s also a full suite of video editing features so you can put together your own films, remove noise from audio tracks, the option to convert video to and from a wide range of formats, plus the helpful ability to compress file sizes to make them easier to share over email or messaging services. Restore and enhance photos and images  It’s not only video that you can improve with Winxvideo AI, as it also brings serious enhancements to still images. The AI upscaler technology instantly improves low-quality images by up to 10x, removing noise and blurriness to give you pin-sharp results. If you want to enhance portraits, Winxvideo AI’s Face Recovery restores fine details like eyelashes, pupils, and skin texture, while removing blemishes. It works perfectly for both individual portraits and group photos.Digiarty The same thing works on old photographs, which you can scan and then make them look like they were taken yesterday. Should you want to modernize old black and white pictures, then the colorize feature in Winxvideo AI makes this incredibly simple, bringing old images to life with full color versions. Everything is handled by the simple-to-use software that does all the heavy-lifting for you. Winxvideo AI version 4.0 takes things to a new level Thanks to big improvements in two of the AI models used in version 4.0, the latest iteration of Winxvideo AI boasts incredible performance gains, with upscaling speeds increased by up to 80% over version 3.9! Digiarty Not only that, the finished results also come with enhanced quality and details too. All this, while the CPU/GPU usage has been lowered, so your PC won’t be punished while working on the video or images. Grab time-limited special deals for Winxvideo AI This year also marks the 19th anniversary of Winxvideo AI’s creators Digiarty, which is being celebrated by a superb deal on the software where you can buy it for only $29.95, saving you $40 off the normal price. Hurry, though, as this is a time-limited deal to accompany the Digiarty festivities. With so many useful tools to upgrade your video and photo library, there’s never been a better time to buy Winxvideo AI, and thanks to the special deal there’s never been a cheaper time either. View Offer

Proton Mail4.5 ExcellentBottom LineProton Mail is an easy-to-use webmail service that brings zero-access encryption to your local message store and end-to-end encryption for message transmission, along with an impressive posse of related programs.US Street Price$47.88Learn MoreProton Mail ReviewVSPreVeil4.5 ExcellentBottom LineWith PreVeil, you get free end-to-end encrypted secure cloud storage along with secure email that’s tough enough for business but extremely easy to use, all while keeping your existing email address.Learn MorePreVeil Review Table of ContentsPricing and Pricing TiersDo I Need a New Email Address?Authentication and Security OptionsCloud Storage and File SharingEmail Client IntegrationTemporary Email AddressesAdvanced Security FeaturesFeatures Beyond Email Encryption Pricing and Pricing TiersPreVeil’s pricing system is as simple as can be—it’s free. Period.You can use ProtonMail for free, too, but a free Proton Mail account lacks some features and limits others. For example, you can only send 150 messages per day and only manage a single email account. When you pay $47.88 per year for a Proton Mail Plus account, the limit on messages per day vanishes, but there’s still a cap on the number of email addresses you can use.There’s one more option, Proton Mail Ultimate, which costs $119.88 per year and includes the full pantheon of Proton’s products. This one makes sense if you want your email encryption served up along with fully functional instances of Proton Calendar, Proton Drive, Proton VPN, and the Proton Pass password manager. Ultimately, everything’s better when it’s free, so PreVeil wins.Winner: PreVeilDo I Need a New Email Address?I’ve had the same personal email address for more than 20 years, and I’ve grown fond of it. I could sign up for PreVeil and keep that address. But if I wanted to rely on Proton Mail to safeguard my email secrets, I would have to pick a new address and share it with all my contacts.On the flip side, my 20-year-old email address has accumulated quite a collection of spam. It’s been revealed in dozens of data breaches and captured by who knows how many data brokers. If you want to level up your security game by using email encryption, you might prefer switching to a pristine new address, too.Here’s the thing. You can do the same thing with PreVeil. Just set up a new, clean email address before you start using PreVeil. But you simply can’t use Proton Mail with your existing address, except in one rare case. If you own your own domain, and if you host your email on that domain, and if you're up for such domain-management tasks as changing MX records and reconfiguring settings for DNS, DKIM, DMARC, and SPF, then you can use your own email. PreVeil wins on flexibility.Winner: PreVeilAuthentication and Security OptionsIt doesn’t matter how thoroughly your email is encrypted if an evildoer gains access to your encrypted inbox. Proton Mail offers multiple levels of protection, starting with using a strong password and an optional account recovery email. On top of that basic password protection, you can optionally configure it for multi-factor authentication (MFA) using Google Authenticator or a compatible authenticator app. You can advance to expert-tier authentication by configuring Proton Mail to require a hardware security key.(Credit: Proton/PCMag)PreVeil doesn’t use passwords at all, presuming that the security of your email account is sufficient. Yes, an attacker would need access to both your email account and a trusted device, which fits the definition of MFA, barely. But you can only use an authenticator app or hardware key to authenticate your email account, not PreVeil itself. When it comes to actively protecting access to your encrypted email system, Proton Mail takes the prize.Winner: Proton MailCloud Storage and File SharingIf you want to share a file or picture securely with someone, you can add it as an attachment to an encrypted email message. That’s a workable solution, but it’s not always the most convenient. Proton Mail and PreVeil both go beyond simple attachments by allowing you to store files in the cloud and share them securely.Your PreVeil account comes with 5GB of encrypted cloud storage that’s easily accessible from Windows Explorer. You also get the option to securely share folders (but not individual files) and to set each recipient’s permission level, from full Edit & Share permission down to View Only, which merely lets the recipient peek at the file’s content in a browser window.(Credit: PreVeil/PCMag)Proton Mail users at all pricing tiers get access to the separate Proton Drive app for cloud backup. Non-paying customers get a tenth of what PreVeil offers, just 500MB. However, at the commercial Plus level that storage rises to 15GB, and if you go all out with Proton Mail Ultimate, you can store 500GB of files. If you’re keeping score, those storage figures are three times and 100 times what PreVeil gives you.Proton Drive lets you share files directly with other Proton users and control their level of access in much the same way you do with PreVeil. You can also create a public link, optionally setting a password and an expiry date. PreVeil’s similar links only work for someone with whom you’ve already shared the folder.It’s true that PreVeil offers more storage than Proton Mail’s free tier, but there’s no easy path if you want more from PreVeil. And Proton Mail’s full backup app has more flexibility. This one goes to Proton Mail.Recommended by Our EditorsWinner: Proton MailEmail Client IntegrationEven if you’ve grudgingly switched to a new email address, you can at least keep the email client that you’ve used for years, right? Well, not necessarily. To get your Proton Mail messages into Apple Mail, Outlook, or Thunderbird, you must install a separate “bridge” app and go through a configuration routine that can get complicated. It doesn’t work with the latest Outlook because it requires access to IMAP and SMTP. And you don’t get full access to encryption features in your old familiar email app.(Credit: PreVeil/PCMag)With PreVeil, integration can be as simple as installing a plug-in for Gmail or Outlook. The plug-in adds a few handy controls, like an encryption on/off switch for the messages you compose, and clearly separates encrypted messages from those you’ve sent without encryption.Winner: PreVeilTemporary Email AddressesI mentioned earlier that being forced to spin up a new email address can be a blessing in disguise, as doing so frees you from any spam and baggage associated with the old address. But if you use a temporary email address service, you can avoid accumulating those problems in the first place. Using such a service lets you communicate with online merchants and other possibly shady connections without ever revealing your actual email address. You see and respond to the messages in your normal inbox, but they see only an email alias. And if one of your connections sells you out to a spam cartel, you just delete the corresponding alias.Sounds convenient, right? The Proton team agrees. At the Unlimited subscription level, you get full access to SimpleLogin, a four-star temporary email service. Yes, that’s the most expensive level, but PreVeil doesn’t offer email aliases at any level. (Don’t feel too left out if you’re using PreVeil or haven’t opted for the expensive Proton Mail Unlimited. You can supplement your email encryption for free with email aliases from ManyMe or Bulc Club.)Winner: Proton MailAdvanced Security FeaturesAfter going to the trouble of switching to encrypted email, you’d feel pretty dumb if you lost your login and couldn’t get access to your important messages. Proton Mail encourages you to save a recovery key in the form of a lengthy code and a QR code, but that recovery key itself now becomes a weakness. Someone who acquires your code owns your account.PreVeil offers a similar recovery code system, but encourages you to use its Recovery Group system instead. This is a high-tech solution more commonly seen in Enterprise-level security. With PreVeil, your recovery key resides with multiple friends, and the recovery process requires participation by several of them. For example, you might enlist six friends to hold your secret and require any three of them to activate recovery.PreVeil’s wrapped keys encryption system is proprietary, but Proton Mail relies on the venerable and widely used PGP (Pretty Good Privacy) encryption system. Proton Mail users can set up encrypted communication with users of other encryption tools that rely on PGP, such as Private-Mail and StartMail. For those with the tech chops, using PGP opens up immense possibilities.(Credit: Proton/PCMag)Proton Mail also actively protects your privacy against tracking that relies on images. When your email client displays an image, it necessarily requests that image from a server. From that request, the sender can learn your IP address, among other things. Proton Mail wipes out web beacons, which are images that have no purpose beyond penetrating your privacy. And it acts as an intermediary for normal images, so the sender gets the IP address of a Proton Mail server, not your personal address.Both services have clever, high-tech features. And in both cases, most users won’t use or pay attention to these features. I call this a draw.Winner: TieFeatures Beyond Email EncryptionI’ve already mentioned that both services offer encrypted file storage and secure sharing. For PreVeil, that’s about it.Proton Mail, on the other hand, offers several other significant security features. These include the already-mentioned Proton Drive, Proton VPN, Proton Calendar, and the Proton Pass password manager.(Credit: Proton/PCMag)Like Proton Drive, Proton Calendar and Proton Pass are available to free users, but with limitations. Free users of Proton VPN can use it to protect one device at a time and can’t choose which country the VPN connects through. Paying for Proton Mail lifts some of these limitations. And if you choose Proton Unlimited, you get the maximum from all the Proton apps.Winner: Proton Mail

We’re happy to announce that we’ve launched a new technical e-book, Create modular game architecture in Unity with ScriptableObjects, which provides best practices from professional developers for deploying ScriptableObjects in production.Along with the e-book, you can download a demo project from GitHub inspired by classic ball and paddle arcade game mechanics. The demo shows how ScriptableObjects can help you create components that are testable and scalable, while also being designer-friendly. Although a game like this could be built with far fewer lines of code, this demo shows ScriptableObjects in action.This post explains the benefits of ScriptableObjects, but doesn’t cover the basics or general coding in Unity. If you’re new to programming in Unity, head over to Unity Learn, which offers helpful introductory tutorials. The first chapter in the e-book also offers a solid primer.Let’s look at six ways you can benefit from using ScriptableObjects in your projects. Want to know more? All of these examples are explored further in the e-book and demo project.Although many of the techniques shared here can also be achieved using C# classes, one of the main benefits of ScriptableObjects is the accessibility to artists and designers. They can use ScriptableObjects to configure and apply game logic in a project without having to edit the code.The Editor makes it convenient to view and edit ScriptableObjects, enabling designers to set up gameplay data without heavy support from the developer team. This also applies to game logic, such as applying behavior to an NPC by adding a ScriptableObject (explained in the patterns below).Storing data and logic on a single MonoBehaviour can result in time-consuming merge conflicts if two people change different parts of the same Prefab or scene. By breaking up shared data into smaller files and assets with ScriptableObjects, designers can build gameplay in parallel with developers, instead of having to wait for the latter to finish setting up the gameplay in code before testing it.Issues can arise when colleagues with different roles access the game code and assets at the same time. With ScriptableObjects, the programmer can control what part of the project is editable in the Editor. Additionally, using ScriptableObjects to organize your code leads naturally to a codebase that’s more modular and efficient to test.Christo Nobbs, a senior technical game designer who specializes in systems game design and Unity (C#), contributed to The Unity game designer playbook, and is the main author of a blog post series on designing game systems in Unity. His posts, “Systems that create ecosystems: Emergent game design” and “Unpredictably fun: The value of randomization in game design” provide interesting examples of how designers can use ScriptableObjects.Modularity is a general software principle which can be implemented in C# without using ScriptableObjects. But, as mentioned above, ScriptableObjects help promote clean coding practices by separating data from logic, which is a first step toward modular game code. This separation means it’s easier to make changes without causing unintended side effects, and improves testability.ScriptableObjects excel at storing static data, making them handy for configuring static gameplay values like items or NPC stats, character dialogue, and much more. Because ScriptableObjects are saved as an asset, they persist outside of game mode, making it possible to use them for loading in a static configuration that dynamically changes at runtime.While changes to ScriptableObject data do persist in the Editor, it’s important to note that they are not designed for saving game data. In that case, it’s better to use a serialization system, such as JSON, XML, or a binary solution if performance is critical.MonoBehaviours carry extra overhead since they require a GameObject – and by default a Transform – to act as a host. This means you need to create a lot of unused data before storing a single value. A ScriptableObject slims down this memory footprint and drops the GameObject and Transform. It also stores data at the project level, which is helpful if you need to access the same data from multiple scenes.It’s common to have many GameObjects which rely on duplicate data that does not need to change at runtime. Rather than having this duplicate local data on each GameObject, you can funnel it into a ScriptableObject. Each of the objects stores a reference to the shared data asset, rather than copying the data itself. This can provide significant performance improvements in projects with thousands of objects.In software design, this is an optimization known as the flyweight pattern. Restructuring your code in this way using ScriptableObjects avoids copying values and reduces your memory footprint. Check out our e-book, Level up your code with game programming patterns to learn more about using design patterns in Unity.A good example of how ScriptableObjects can simplify your code is to use them as enums for comparison operations. The ScriptableObject can represent a category or item type, such as a special damage effect – cold, heat, electrical, magic, etc.If your application requires an inventory system to equip gameplay items, ScriptableObjects can represent item types or weapon slots. The fields in the Inspector then function as a drag-and-drop interface for setting them up.Using ScriptableObjects as enums becomes more interesting when you want to extend them and add more data. Unlike normal enums, ScriptableObjects can have extra fields and methods. There’s no need to have a separate lookup table or correlate with a new array of data.While traditional enums have a fixed set of values, ScriptableObject enums can be created and modified at runtime, allowing you to add or remove values as needed.If you have a long list of enum values without explicit numbering, inserting or removing an enum can change their order. This reordering can introduce subtle bugs or unintended behavior. ScriptableObject-based enums don’t have these issues. You can delete or add to your project without having to change the code every time.Suppose you want to make an item equippable in an RPG. You could append an extra boolean field to the ScriptableObject to do that. Are certain characters not allowed to hold certain items? Are some items magical or do they have special abilities? ScriptableObject-based enums can do that.Because you can create methods on a ScriptableObject, they are as useful for containing logic or actions as they are for holding data. Moving logic from your MonoBehaviour into a ScriptableObject enables you to use the latter as a delegate object, making the behavior more modular.If you need to perform specific tasks, you can encapsulate their algorithms into their own objects. The original Gang of Four refers to this general design as the strategy pattern. The example below shows how to make the strategy pattern more useful by using an abstract class to implement EnemyAI. The result is several derived ScriptableObjects with different behavior, which then becomes a pluggable behavior since each asset is interchangeable. You just drag and drop the ScriptableObject of choice into the MonoBehaviour.For a detailed example showing how to use ScriptableObjects to drive behavior, watch the video series Pluggable AI with ScriptableObjects. These sessions demonstrate a finite state machine-based AI system that can be configured using ScriptableObjects for states, actions, and transitions between those states.A common challenge in larger projects is when multiple GameObjects need to share data or states by avoiding direct references between these objects. Managing these dependencies at scale can require significant effort and is often a source of bugs. Many developers use singletons – one global instance of a class that survives scene loading. However, singletons introduce global states and make unit testing difficult. If you’re working with a Prefab that references a singleton, you’ll end up importing all of its dependencies just to test an isolated function. This makes your code less modular and efficient to debug.One solution is to use ScriptableObject-based events to help your GameObjects communicate. In this case, you are using ScriptableObjects to implement a form of the observer design pattern, where a subject broadcasts a message to one or more loosely decoupled observers. Each observing object can react independently from the subject but is unaware of the other observers. The subject can also be referred to as the “publisher” or “broadcaster” and the observers as “subscribers” or “listeners.”You can implement the observer pattern with MonoBehaviours or C# objects. While this is already common practice in Unity development, a script-only approach means your designers will rely on the programming team for every event needed during gameplay.At first glance, it appears that you’ve added a layer of overhead to the observer pattern, but this structure offers some advantages. Since ScriptableObjects are assets, they are accessible to all objects in your hierarchy and don’t disappear on scene loading.Easy, persistent access to certain resources is why many developers use singletons. ScriptableObjects can often provide the same benefits without introducing as many unnecessary dependencies.In ScriptableObject-based events, any object can serve as publisher (which broadcasts the event), and any object can serve as a subscriber (which listens for the event). The ScriptableObject sits in the middle and helps relay the signal, acting like a centralized intermediary between the two.One way to think about this is as an “event channel.” Imagine the ScriptableObject as a radio tower that has any number of objects listening for its signals. An interested MonoBehaviour can subscribe to the event channel and respond when something happens.The demo shows how the observer pattern helps you set up game events for UI, sounds, and scoring.At runtime, you’ll often need to track a list of GameObjects or components in your scene. For example, a list of enemies is something you’d need to frequently access, but it’s also a dynamic list that changes as more enemies are spawned or defeated. The singleton offers easy global access, but it has several drawbacks. Instead of using a singleton, consider storing data on a ScriptableObject as a “Runtime Set.” The ScriptableObject instance appears at the project level, which means it can store data that’s available to any object from any scene, offering similar global access. Since the data is located on an asset, its public list of items is accessible at any time.In this use case, you get a specialized data container that maintains a public collection of elements but also provides basic methods to add to and remove from the collection. This can reduce the need for singletons and improve testability and modularity.Reading data directly from a ScriptableObject is also more optimal than searching the Scene Hierarchy with a find operation like Object.FindObjectOfType or GameObject.FindWithTag. Depending on your use case and the size of your hierarchy, these are relatively expensive methods that can be inefficient for per-frame updates.There are several ScriptableObjects frameworks which offer more use cases than these six scenarios. Some teams decide to use ScriptableObjects extensively, while others limit their use to loading in static data and separating logic from data. Ultimately, the needs of your project will determine how you use them.Create modular game architecture in Unity with ScriptableObjects is the third guide in our series for intermediate to advanced Unity programmers. Each guide, authored by experienced programmers, provides best practices for topics that are important to development teams.Create a C# style guide: Write cleaner code that scales assists you with developing a style guide to help unify your approach to creating a more cohesive codebase.Level up your code with game programming patternshighlights best practices for using the SOLID principles and common programming patterns to create scalable game code architecture in your Unity project.We created this series to provide actionable tips and inspiration to our experienced creators, but they aren’t rule books. There are many ways to structure your Unity project and what might seem like a natural fit for one application may not be for another. Evaluate the advantages and disadvantages of each recommendation, tip, and pattern with your colleagues before deploying it.Find more advanced guides and articles on the Unity best practices hub.

Hi, is there a way to get the typeid of an array of type T, if I have the typeid of T?Let me explain. enum TestEnum { TEST1, TEST2, TEST3 } class NewScript { TestEnum my_enum; array<TestEnum> my_array; } I'm using asITypeInfo::GetProperty to get the typeid of an enum inside a script. In my example this is:propName: “my_enum”propTypeId: 77 (0x0000004d)AndpropName: “my_array”propTypeId: 268435535 (0x1000004f)Now my question is, can I get the typeid of array<TestEnum> with only the typeid of TestEnum?

An illustration of what the Amniote (early reptile) would look like from 350 million years ago. CREDIT: Martin Ambrozik. Get the Popular Science daily newsletter💡 Breakthroughs, discoveries, and DIY tips sent every weekday. One of the most impactful stories in evolution is getting a rewrite, thanks to the exciting discovery of the earliest known set of reptile footprints. Craig A. Eury and John Eason, two amateur paleontologists exploring the fossil-rich Snowy Plains Formation in Australia, found a rock with an intriguing set of fossilized prints. They brought the intriguing specimen to professional paleontologists, who soon discovered that the roughly 356 million-year-old fossilized claw prints likely belong to an amniote–an early reptile relative.  Though small in stature, amniotes were a large evolutionary leap forward towards land-dwelling, four-limbed animals called tetrapods. The age of these prints suggest that amniotes evolved millions of years earlier than expected, according to a study published May 14 in the journal Nature.  “I’m stunned,” Per Ahlberg, a paleontologist at Uppsala University in Sweden who coordinated the study, said in a statement. “A single track-bearing slab, which one person can lift, calls into question everything we thought we knew about when modern tetrapods evolved.” When fish grew legs Tetrapods include all vertebrates with four limbs that primarily live on land, including everything from frogs to turtles to eagles, to tigers to humans. Their story began as fish left the water between 390 and 360 million years ago. Their descendants began to diversify into the ancestors of modern amphibians and amniotes–the group that includes birds, reptiles, and mammals. Originally, the timeline for how this massive diversification of life occurred was fairly clear-cut. The first tetrapods evolved roughly 390 million years ago during the Devonian period. Amniotoes and the earliest members of the modern groups of animals we see today followed fishapods during the Carboniferous period. Previously, the earliest amniote fossils dated back to  about 320 million years old to the late Carboniferous. Based on this new evidence, researchers concluded the start of the point on the evolutionary tree where the ancestors of amphibians and amniotes split actually happened in the earliest days of the Carboniferous or 356 million years ago.   Proof in the prints The newly discovered 356 million-year-old sandstone slab from this new study potentially changes this entire timeline by about 35 to 40 million years. The well-preserved footprints of long-toed feet with distinct claw impressions at the tips dot the stone and are the earliest known clawed footprints. Two sets of tracks were identified on the stone, seemingly from the same animal.  Footprints are important for paleontologists, as they can indicate the types of behaviors an extinct animal may have exhibited. The team compared the ancient tracks with a modern water monitor (Varanus salvator) lizard, since they have similarly shaped feet to what is seen on the footprints. They examined the spacing between the front and hind footprints against that living lizard’s feet. With these measurements, the team estimates that the ancient amniote may have been around 2.5 feet long, but that the exact proportions of the animal are still unknown. “Claws are present in all early amniotes, but almost never in other groups of tetrapods,” Ahlberg said. “The combination of the claw scratches and the shape of the feet suggests that the track maker was a primitive reptile.” If this new interpretation is correct, it pushes the origin of reptiles, and thus amniotes as a whole, back by roughly 40 million years to the earliest Carboniferous. A new set of fossil reptile footprints uncovered all the way across the globe in Poland are also detailed in the study and bolster the evidence. These European footprints are not as old as the ones from Australia, but are still older than previous specimens.  “The implications of this discovery for the early evolution of tetrapods are profound,” John Long, a study co-author and paleontologist at Flinders University in Australia, said. “All stem-tetrapod and stem-amniote lineages must have originated during the Devonian period – but tetrapod evolution proceeded much faster, and the Devonian tetrapod record is much less complete than we have believed.” A place on the evolutionary tree According to the team, this recalibration of the origin of reptiles has a ripple effect on the whole timeline of tetrapod evolution. Tetrapods must be older than even the earliest amniotes, since it has a deeper branching point on the evolutionary tree.  “It’s all about the relative length of different branches in the tree,” said Ahlberg. “In a family tree based on DNA data from living animals, branches will have different lengths reflecting the number of genetic changes along each branch segment. This does not depend on fossils, so it’s really helpful for studying phases of evolution with a poor fossil record.” The fossil trackways with the different tracks on it highlighted. CREDIT: Flinders University The team believes that amphibians and ammonites split apart further into the Devonian period and were likely a contemporary of the primitive, transitional “fishapod” called Tiktaalik. This evidence indicates that a diverse group of tetrapods existed when only transitional “fishapods” were believed to be dragging themselves around muddy shorelines and starting to explore the land.  If this new theory holds, it is likely that the evolution of tetrapods from aquatic creatures to those fully living on land may have occurred even faster than previously believed.   “The Australian footprint slab is about 50 cm [1.5 feet] across,” said Ahlberg, “and at present it represents the entire fossil record of tetrapods from the earliest Carboniferous of Gondwana – a gigantic supercontinent comprising Africa, South America, Antarctica, Australia and India. Who knows what else lived there?”   “The most interesting discoveries are yet to come and that there is still much to be found in the field,” added study co-author and paleontologist Grzegorz Niedźwiedzki. “These footprints from Australia are just one example of this.” 

Archaeopteryx lived about 150 million years ago during the Jurassic Period. Although the first Archaeopteryx fossil was discovered more than 160 years ago and the prehistoric bird has been well studied, an excellent specimen has yielded new information about the species, including why it could fly so well, according to a report in the journal Nature. Painstaking preparation made the “Chicago Archaeopteryx” (named because it resides in the city’s Field Museum) the best-preserved example of the species. That amount of care meant that CT scans and imaging via UV light have yielded the most vivid Archaeopteryx pictures yet. Scientists visualized its smallest bones as well as soft tissue, including some feathers.New Archaeopteryx Flight Details EmergeIllustration showing Archaeopteryx in life, including its tertial feathers that would have helped it fly. (Image Credit: Michael Rothman)Seeing Archaeopteryx in such detail revealed a long set of feathers called tertials on the its upper arm. Those feathers also place the species more accurately on the evolutionary tree among winged dinosaurs as well as a predecessor to contemporary birds, which also have tertials. “Archaeopteryx isn’t the first dinosaur to have feathers, or the first dinosaur to have ‘wings,’" Jingmai O’Connor a curator at the museum and an author of the paper, said in a press release. “But we think it’s the earliest known dinosaur that was able to use its feathers to fly.”Ancient FlightThe scientists now think they know why Archaeopteryx was such a good flier. Archaeopteryx’s upper arm bone is much longer than those of contemporary birds. That length creates a gap between the long primary feathers and others, as well as between the wings and the body. Air passing through that gap generates lift. Contemporary birds don’t need such long arms, because evolution solved their need to create lift another way: a set of tertial feathers between the bird’s body and the rest of its wing.“Our specimen is the first Archaeopteryx that was preserved and prepared in such a way that we can see its long tertial feathers,” O’Connor said in the release. “These feathers are missing in feathered dinosaurs that are closely related to birds but aren’t quite birds. Their wing feathers stop at the elbow. That tells us that these non-avian dinosaurs couldn’t fly, but Archaeopteryx could. This also adds to evidence that suggests dinosaurs evolved flight more than once — which I think is super exciting.”Other Bird Evolutionary FeaturesImaging also revealed some other key evolutionary features. For instance, seeing details of the tiny bones in the roof of its mouth are helping scientists understand how modern birds eventually developed the ability to move their beaks independent of the part of the skull that holds their brain.“That might not sound exciting, but to people who study bird evolution, it’s really important, because it’s been hypothesized that being able to evolve specialized skulls for different ecological niches might have helped birds evolve into more than 11,000 species today,” O’Connor said in the release.Also, because the scientists got a detailed look at some of the Archaeopteryx’s soft tissues they hypothesize that it may have spent a lot of time walking on the ground, and may even have climbed trees.The Chicago Archaeopteryx fossil went on display at the Field Museum in 2024. Its tiny hollow bones are embedded in a slab of limestone. At about the size of a pigeon, it is among the smallest known fossils of the species.Article SourcesOur writers at Discovermagazine.com use peer-reviewed studies and high-quality sources for our articles, and our editors review for scientific accuracy and editorial standards. Review the sources used below for this article:Before joining Discover Magazine, Paul Smaglik spent over 20 years as a science journalist, specializing in U.S. life science policy and global scientific career issues. He began his career in newspapers, but switched to scientific magazines. His work has appeared in publications including Science News, Science, Nature, and Scientific American.

Google DeepMind has once again used large language models to discover new solutions to long-standing problems in math and computer science. This time the firm has shown that its approach can not only tackle unsolved theoretical puzzles, but improve a range of important real-world processes as well. Google DeepMind's new tool, called AlphaEvolve, uses the Gemini 2.0 family of large language models (LLMs) to produce code for a wide range of different tasks. LLMs are known to be hit and miss at coding. The twist here is that AlphaEvolve scores each of Gemini’s suggestions, throwing out the bad and tweaking the good, in an iterative process, until it has produced the best algorithm it can. In many cases, the results are more efficient or more accurate than the best existing (human-written) solutions. “You can see it as a sort of super coding agent,” says Pushmeet Kohli, a vice president at Google DeepMind who leads its AI for Science teams. “It doesn’t just propose a piece of code or an edit, it actually produces a result that maybe nobody was aware of.” In particular, AlphaEvolve came up with a way to improve the software Google uses to allocate jobs to its many millions of servers around the world. Google DeepMind claims the company has been using this new software across all of its data centers for more than a year, freeing up 0.7% of Google's total computing resources. That might not sound like much, but at Google’s scale it’s huge. Jakob Moosbauer, a mathematician at the University of Warwick in the UK, is impressed. He says the way AlphaEvolve searches for algorithms that produce specific solutions—rather than searching for the solutions themselves—makes it especially powerful. “It makes the approach applicable to such a wide range of problems,” he says. “AI is becoming a tool that will be essential in mathematics and computer science.” AlphaEvolve continues a line of work that Google DeepMind has been pursuing for years. Its vision is that AI can help to advance human knowledge across math and science. In 2022, it developed AlphaTensor, a model that found a faster way to solve matrix multiplications—a fundamental problem in computer science—beating a record that had stood for more than 50 years. In 2023, it revealed AlphaDev, which discovered faster ways to perform a number of basic calculations performed by computers trillions of times a day. AlphaTensor and AlphaDev both turn math problems into a kind of game, then search for a winning series of moves. FunSearch, which arrived in late 2023, swapped out game-playing AI and replaced it with LLMs that can generate code. Because LLMs can carry out a range of tasks, FunSearch can take on a wider variety of problems than its predecessors, which were trained to play just one type of game. The tool was used to crack a famous unsolved problem in pure mathematics. AlphaEvolve is the next generation of FunSearch. Instead of coming up with short snippets of code to solve a specific problem, as FunSearch did, it can produce programs that are hundreds of lines long. This makes it applicable to a much wider variety of problems.     In theory, AlphaEvolve could be applied to any problem that can be described in code and that has solutions that can be evaluated by a computer. “Algorithms run the world around us, so the impact of that is huge,” says Matej Balog, a researcher at Google DeepMind who leads the algorithm discovery team. Survival of the fittest Here’s how it works: AlphaEvolve can be prompted like any LLM. Give it a description of the problem and any extra hints you want, such as previous solutions, and AlphaEvolve will get Gemini 2.0 Flash (the smallest, fastest version of Google DeepMind’s flagship LLM) to generate multiple blocks of code to solve the problem. It then takes these candidate solutions, runs them to see how accurate or efficient they are, and scores them according to a range of relevant metrics. Does this code produce the correct result? Does it run faster than previous solutions? And so on. AlphaEvolve then takes the best of the current batch of solutions and asks Gemini to improve them. Sometimes AlphaEvolve will throw a previous solution back into the mix to prevent Gemini from hitting a dead end. When it gets stuck, AlphaEvolve can also call on Gemini 2.0 Pro, the most powerful of Google DeepMind’s LLMs. The idea is to generate many solutions with the faster Flash but add solutions from the slower Pro when needed. These rounds of generation, scoring, and regeneration continue until Gemini fails to come up with anything better than what it already has. Number games The team tested AlphaEvolve on a range of different problems. For example, they looked at matrix multiplication again to see how a general-purpose tool like AlphaEvolve compared to the specialized AlphaTensor. Matrices are grids of numbers. Matrix multiplication is a basic computation that underpins many applications, from AI to computer graphics, yet nobody knows the fastest way to do it. “It’s kind of unbelievable that it’s still an open question,” says Balog. The team gave AlphaEvolve a description of the problem and an example of a standard algorithm for solving it. The tool not only produced new algorithms that could calculate 14 different sizes of matrix faster than any existing approach, it also improved on AlphaTensor’s record-beating result for multipying two four-by-four matrices. AlphaEvolve scored 16,000 candidates suggested by Gemini to find the winning solution, but that’s still more efficient than AlphaTensor, says Balog. AlphaTensor’s solution also only worked when a matrix was filled with 0s and 1s. AlphaEvolve solves the problem with other numbers too. “The result on matrix multiplication is very impressive,” says Moosbauer. “This new algorithm has the potential to speed up computations in practice.” Manuel Kauers, a mathematician at Johannes Kepler University in Linz, Austria, agrees: “The improvement for matrices is likely to have practical relevance.” By coincidence, Kauers and a colleague have just used a different computational technique to find some of the speedups AlphaEvolve came up with. The pair posted a paper online reporting their results last week. “It is great to see that we are moving forward with the understanding of matrix multiplication,” says Kauers. “Every technique that helps is a welcome contribution to this effort.” Real-world problems Matrix multiplication was just one breakthrough. In total, Google DeepMind tested AlphaEvolve on more than 50 different types of well-known math puzzles, including problems in Fourier analysis (the math behind data compression, essential to applications such as video streaming), the minimum overlap problem (an open problem in number theory proposed by mathematician Paul Erdős in 1955), and kissing numbers (a problem introduced by Isaac Newton that has applications in materials science, chemistry, and cryptography). AlphaEvolve matched the best existing solutions in 75% of cases and found better solutions in 20% of cases.   Google DeepMind then applied AlphaEvolve to a handful of real-world problems. As well as coming up with a more efficient algorithm for managing computational resources across data centers, the tool found a way to reduce the power consumption of Google’s specialized tensor processing unit chips. AlphaEvolve even found a way to speed up the training of Gemini itself, by producing a more efficient algorithm for managing a certain type of computation used in the training process. Google DeepMind plans to continue exploring potential applications of its tool. One limitation is that AlphaEvolve can’t be used for problems with solutions that need to be scored by a person, such as lab experiments that are subject to interpretation.    Moosbauer also points out that while AlphaEvolve may produce impressive new results across a wide range of problems, it gives little theoretical insight into how it arrived at those solutions. That’s a drawback when it comes to advancing human understanding.   Even so, tools like AlphaEvolve are set to change the way researchers work. “I don't think we are finished,” says Kohli. “There is much further that we can go in terms of how powerful this type of approach is.”

Piri piri or African bird’s eye chilli peppersSteidi/Alamy Accidentally made your food too spicy? One day, you might be able to reach for an “anti-spice” condiment to tame the heat of a dish, thanks to the discovery of chemicals found in chilli peppers that counteract their spicy sensation. A chilli’s heat comes from compounds called capsaicinoids, which bind to receptors on nerve fibres within your mouth, sending impulses to the brain that create a burning sensation similar to those caused by a fire’s heat or a sting. Advertisement Chilli aficionados compare the heat of different strains using the Scoville scale, which is based on the concentration of capsaicinoids, yet some varieties aren’t quite as hot as their Scoville rating suggests they should be. To investigate, Devin Peterson at the Ohio State University and his colleagues used an analytical method known as liquid chromatography-mass spectrometry to determine how much of two capsaicinoids – capsaicin and dihydrocapsaicin – were in powdered samples of 10 types of peppers, including chile de árbol, African bird’s eye and Scotch bonnet. Then they gave samples of tomato juice containing powder from the different chillis to a panel of tasters. Each contained the same amount of capsaicin and dihydrocapsaicin – which should have been enough to give all the samples a relatively mild kick of 800 Scoville units. But the tasters perceived the heat from the 10 peppers as different, so Peterson and his colleagues performed additional chemical analyses. This identified three compounds in the chilli powder – capsianoside I, roseoside and gingerglycolipid A – that were present in high quantities in the chillies that weren’t as intense as they should have been according to the Scoville scale. All three compounds are glucosides, molecules that contain the sugar glucose. The latest science news delivered to your inbox, every day. Sign up to newsletter A group of 37 tasters then tested two samples at once, one containing these suspected spice-killing compounds and one without, placed on either side of their tongue to stop an enflamed tongue affecting a second taste test. Their feedback revealed that the compounds decreased the chilli intensity by between 0.7 and 1.2 points on a 15-point scale, on average. “They are effectively anti-spice compounds,” says Peterson. He isn’t yet sure how they work, but says they could be altering receptors on nerve fibres in the mouth in a way that results in a reduction in their burning signals. Knowing about these anti-spice chemicals could allow growers to breed or genetically modify plants so they lack them to create valuable, even hotter chillis, or breed very mild fruit with higher amounts of anti-spice, says Peterson. Using the compounds could also enable the creation of a household ingredient to tone down excessive heat in dishes, he says, or they could work as relievers for severe pain by blocking pain signals. “Sometimes when I’ve ordered food with my kids and it’s too spicy, that’s a no-go,” says Peterson. “So, the idea of having some kind of a natural compound to dial it back may be appealing.” “The way the study was done using the half tongue was very clever,” says Barry Smith at the University of London’s School of Advanced Study, adding that it shows the Scoville scale isn’t a very precise instrument for describing how hot a chilli is. Smith also wonders if the perceived intensity of menthol or mint, which cause a cooling sensation in a similar way to how capsaicinoids cause a burning one, could also be muted by these kinds of compounds. Journal reference:Journal of Agricultural and Food Chemistry DOI: 10.1021/acs.jafc.5c01448 Topics:food and drink

The European Union Agency for Cybersecurity (Enisa) has debuted a European Union Vulnerability Database (EUVD) to provide “aggregated, reliable and actionable” information on newly disclosed cyber security vulnerabilities in IT products and services. The EUVD, which is mandated by the NIS2 Directive, is designed to gather publicly available information from sources such as EU member state national computer security incident response teams (CSIRTs), industry threat researchers, and other vulnerability databases, including Mitre’s CVE Program. Enisa said that to meet this goal, it has constructed its platform on a holistic approach as an interconnected database that it believes will allow for better analysis and help the community correlate vulnerabilities. It said this would ultimately make it a more trustworthy, transparent and broader information source. “The EU Vulnerability Database is a major step towards reinforcing Europe’s security and resilience,” said Henna Virkkunen, European Commission executive vice-president for tech sovereignty, security and democracy. “By bringing together vulnerability information relevant to the EU market, we are raising cyber security standards, enabling both private and public sector stakeholders to better protect our shared digital spaces with greater efficiency and autonomy.” Enisa executive director Juhan Lepassaar added: “Enisa achieves a milestone with the implementation of the vulnerability database requirement from the NIS2 Directive. The EU is now equipped with an essential tool designed to substantially improve the management of vulnerabilities and the risks associated with them. “The database ensures transparency to all users of the affected ICT products and services and will stand as an efficient source of information to find mitigation measures.” The launch of the EUVD comes mere weeks after the security community was rocked by the near-death experience of Mitre’s long-running CVE Program, a US government-backed and -funded resource that over the past two decades has become a fixture in the security world. Although Mitre’s funding was, in the end, restored at the last minute by the US authorities, the 24 hours of uncertainty prompted much soul-searching and many cyber professionals have begun to consider or discuss the idea of alternatives to a programme that is ultimately backed by a single government. Although EUVD is not designed to replace the US programme, Enisa said it had worked with Mitre on its development, and continues to work alongside the non-profit body to understand the impact of the funding crisis on the EUVD project. For now, data on common vulnerabilities and exposures (CVE), data provided by those disclosing vulnerabilities, and other sources such as the Cybersecurity and Infrastructure Security Agency’s (CISA’s) Known Exploited Vulnerabilities catalogue will be automatically transposed into EUVD with support from EU member state CSIRTs. For example, CVE-2025-32709, a privilege escalation vulnerability in Windows Ancillary Function Driver for WinSock – disclosed this week on Patch Tuesday – appears in the EUVD with the designation EUVD-2025-14439. Sylvain Cortes, strategy vice-president at Hackuity, said: “Enisa’s new EUVD is a good initiative when you consider the recent funding issues around Mitre’s CVE Program. “There’s also still some uncertainty around whether the Mitre database will continue to exist after the new contract expires in 10 months’ time, so having a European option in place means the industry can be less reliant on one vulnerability enrichment source. It’s an even greater alternative when you consider the fact that the NVD [the US National Vulnerability Database] has suffered backlogs in the past. “Ultimately, we need a source for all vulnerabilities that is reliable and open, and we hope that the new EUVD promises will provide this,” said Cortes. Crystal Morin, cyber security strategist at Sysdig, also welcomed the launch as part of the ongoing effort to strengthen global cyber security amid an uncertain future. She said she hoped the EUVD would complement the CVE Program. “Having both in play means more organisations handling CVE requests and, ultimately, faster public disclosure,” she said. “For security teams, the EUVD is simply another trusted source for vulnerability intelligence. As long as vulnerability submissions are streamlined – only submitted to one programme – we avoid duplication and confusion, and gain speed and resilience.” Read more about vulnerability disclosure practice The US National Institute of Standards and Technology is deferring future updates to thousands of cyber vulnerabilities discovered prior to 2018 amid surging volumes of new submissions. Many trends, notably a big shift to open source tools, are behind an expected boom in the number of disclosed vulnerabilities in 2025. New benchmarking data can help security practitioners identify gaps in healthcare vulnerability management and make the case for a proactive versus reactive approach to managing vulnerabilities.