AI For Real

Category: AI Tools

  • Google launches AI platform that lets users create video games without coding

    Google launches AI platform that lets users create video games without coding

    Google has launched an experimental platform that allows people to create and play their own video games using artificial intelligence, potentially opening game development to people without coding or technical experience.

    Playground, unveiled on Wednesday, lets users describe a game idea through text prompts and then build it directly in a web browser. Users can start with a blank canvas, modify suggested concepts or use guided prompts to develop their ideas.

    The platform allows creators to change elements including characters, game rules, physics and environments simply by telling the AI what they want to alter. Google said creators remain in control of the creative direction, from the initial concept through to the finished game.

    The games can then be played privately, shared with friends through a link or published to Playground’s community gallery, where other users can discover and play them.

    Google said Playground also supports multiplayer games in selected genres and includes leaderboards, allowing players to compete and follow creators. Games published to the gallery will undergo safety screening based on Google’s community guidelines, with users also able to report content.

    The browser-based platform is designed to work across devices, allowing users to play games on smartphones and laptops rather than requiring specialised software or hardware.

    Google is also planning a more advanced route for creators through Unity Spark, an integration that will bring professional-level game mechanics, high-fidelity 3D capabilities and the Unity runtime to Playground.

    Unity Spark is currently being tested, with a closed beta planned, potentially allowing games that begin as simple AI-generated experiments to evolve into more sophisticated experiences.

    Google described Playground as an early experiment aimed at making game creation more accessible and encouraging everyday creativity.

    The platform launched on Wednesday for users aged 18 and over in the US, with access to game creation being rolled out in tiers based on Google One membership.

  • Here’s a lowdown on “Muse” by Meta

    Here’s a lowdown on “Muse” by Meta

    For those within our community who have still not got this piece of news….

    “Muse” is Meta’s new personal artificial intelligence (AI) agent, designed to do more than simply answer questions. Instead of acting like a chatbot that waits for instructions, Muse is intended to take on tasks, make plans and carry out actions on a user’s behalf.

    Meta introduced Muse in September 2026 as part of its push towards what it calls “personal superintelligence”.

    The simplest way to understand Muse is to think of it as a digital assistant that can actually get things done.

    You could ask it to organise a trip, manage a project, send an email, research a subject or help with a purchase.

    Muse can use a web browser, interact with connected services and continue working on longer tasks after you have closed the app. It can then return to you when it needs approval or when something important changes.

    This makes Muse different from conventional AI chatbots. With a chatbot, you might ask for a holiday itinerary and then have to book the flights and hotels yourself. With an AI agent such as Muse, the goal is for the system to handle much more of that process itself, subject to the permissions you give it.

    Muse can also remember information that matters to you. For example, Meta says it could turn a recipe you saved on Instagram into a shopping list, remember dietary requirements and use that information when helping organise a dinner.

    A few days ago, Meta launched “Muse Charm”.

    This is a small, keychain-sized physical device designed to give people instant access to their personal Muse AI agent without having to unlock a phone or open an app.

    Zuckerberg described it as a way to talk to Muse and show it what is happening around you.

    The device has a small display showing Muse’s animated avatar, known internally as Jolly, and a fingerprint sensor that lets users start talking to Muse. Meta says it plans to ship the device in December, although it has not announced a price.

    Here is how Meta has demonstrated it working:

    1. You tap the fingerprint sensor.
      The sensor is built into the corner of the device. Tapping it lets you start talking to Muse without unlocking your phone or opening an app. Zuckerberg demonstrated exactly this at Meta Connect.
    2. You speak naturally to Muse.
      Charm contains Meta’s real-time voice and avatar technology, so the interaction is intended to feel like having a conversation rather than typing questions into a chatbot. The small screen displays a visual representation of your Muse while you talk.
    3. Muse does the actual AI work.
      This is the key distinction. Charm isn’t primarily there to provide computing power. It gives you a quick physical interface for reaching Muse, while Muse can perform tasks using Meta’s connected services. Meta describes Muse as an agent that can continue working on tasks in the background.
    4. Charm can give Muse visual information.
      Zuckerberg said it would be a fast way to “show it what’s going on around you”. That means, for example, you could point the device towards something and ask Muse about it, rather than having to describe what you are seeing. Meta has not yet published all the technical details of how the camera and cloud processing will work.
    5. It can work away from Wi-Fi.
      Reports from the Connect announcement say the device includes cellular connectivity, allowing it to access Muse while you’re out and about.

    So why not just use your phone?

    That’s actually the interesting part.

    With a phone, the sequence is take out phone → unlock it → find the app → start talking.

    With Charm, Meta is trying to reduce that to tap → talk.

    Zuckerberg explicitly described it as the fastest way to reach Muse for people who aren’t wearing Meta’s AI glasses.

    What about privacy?

    Meta says privacy and security are central to how Muse works.

    It runs inside a dedicated virtual computer, with controls designed to prevent it from taking sensitive actions without permission. Users decide which services Muse can access and what it is allowed to do.

    Meta is also bringing Muse to its AI glasses, allowing users to interact with their personal agent hands-free and eventually ask it to act on what they are looking at.

    Image credit: Meta

  • Google’s CC AI assistant: what it does and how it could help families manage daily life

    Google’s CC AI assistant: what it does and how it could help families manage daily life

    In late 2025, Google introduced on an experimental basis an AI productivity agent Google CC or simply CC to help you stay organized in your daily tasks.

    Today, Google Labs has announced it was expanding its experimental CC AI assistant from a personal productivity tool into a shared household service, allowing families to coordinate calendars, tasks, emails and everyday chores.

    But again, as we have seen with AI, the move does raise new questions about how much personal information each family member must share before the system can operate effectively.

    CC is currently an early experiment for people aged 18 and over in the US with personal Google accounts.

    The new version turns CC into a shared household assistant that can work with up to six people through its own Google account.

    What can CC do?

    • CC can create a shared “Your Day Ahead” briefing, bringing together appointments, tasks and other information so family members can see what needs attention.
    • It can automatically identify important dates and to-dos from information shared with it and add relevant events to a family Calendar or Task list.
    • It can help with practical jobs such as filling in permission slips and activity registration forms, preparing school shopping lists and creating weekly meal plans.
    • CC can also use Google tools including Gmail, Chat, Docs and Calendar, while Google says it can check information such as driving times when completing household tasks.
    • The agent develops a shared memory, allowing it to remember household information while distinguishing it from details that belong to individual members.

    How does it work for families?

    • CC has its own verified Google account, giving it a separate identity and permissions framework rather than simply operating through one family member’s account.
    • Every member decides what information they want to share with CC, and Google says those choices can be changed at any time.
    • Members can automatically share emails from selected senders, such as a child’s school, or send individual emails, messages, images, files, Drive folders or Calendar information to CC.
    • CC can take actions such as completing forms, but Google says it does so with the user’s permission.

    The privacy questions

    • The important question is how comfortable each family member is with giving an AI access to personal emails, calendars, files and household information, particularly when information about one person may affect everyone else.
    • Google says CC will only see what each member chooses to share, will respond only to group members and will not act or share information outside the group without permission.
    • But families may still want to ask exactly what happens to shared information, how long CC retains it, who can see its shared memory and what happens when a member leaves the group.
    • Those details matter because CC is moving beyond answering questions and into organising information and taking actions on behalf of a household.

    What do you have to say about CC? Do comment.

    Image credit: Google Labs

  • Mistral and Mozilla develop AI assistant designed to protect user privacy

    Mistral and Mozilla develop AI assistant designed to protect user privacy

    Mistral and Mozilla are joining forces to develop an artificial intelligence (AI) assistant for Firefox that aims to give users the benefits of AI without requiring them to hand over their personal information.

    The companies said their partnership is designed around privacy, with Mistral committing to a model in which users’ conversations with the assistant are not retained or used to build profiles about them.

    Why this?

    The technology will power Mozilla’s experimental Smart Window, an AI feature designed to help people search the web, understand information and work with content across multiple browser tabs.

    Unlike many online AI services, the smart assistant intends to keep users’ interactions private, reducing the amount of personal data that needs to leave the browser or be stored by the companies providing the service.

    For users, this means they could ask an AI assistant to summarise information, answer questions or help navigate the web without necessarily creating a lasting record of those interactions.

    The partnership reflects a broader concern about the amount of personal information that AI services can collect as they become more deeply integrated into everyday online activities.

    As some of you may know, Mozilla, the organisation behind Firefox, has long positioned privacy and user control as important principles, while French AI company Mistral has developed models that it says can be deployed with greater control over data.

    The companies said the partnership will combine Mozilla’s experience in building privacy-focused products with Mistral’s AI technology to explore a different approach to AI-powered browsing.

    Smart Window is being introduced experimentally, allowing Mozilla and Mistral to test how people use an AI assistant while addressing concerns about privacy and control.

    The initiative therefore goes beyond adding another chatbot to a web browser, as the companies are testing whether AI can become part of everyday browsing while keeping users’ personal data under tighter control.

    Image credit: Mistral/Mozilla

  • The Rising Popularity Of AI Detection Tool “Pangram”

    The Rising Popularity Of AI Detection Tool “Pangram”

    Artificial intelligence (AI) has made it remarkably easy to create essays, articles, social-media posts, reviews and even books within seconds. But this convenience has created a new problem: How do we know whether something was actually written by a person? This is the question behind the growing popularity of “Pangram”, an AI-content detection tool.

  • Wispr Flow: The AI Tool That Lets You Write by Speaking

    Wispr Flow: The AI Tool That Lets You Write by Speaking

    There’s a new voice-to-text tool that’s in the market that everyone’s talking about. Well, almost everyone.

    “Wispr Flow” is an AI-powered voice-to-text tool that turns spoken thoughts into clean, structured writing across your apps. Unlike basic dictation, it uses AI to clean up speech, remove filler words, add formatting and adapt to your vocabulary.

    🚀 What Wispr Flow Does

    • Voice-to-text everywhere: Works across apps including Gmail, Slack, Notion, Google Docs, code editors and AI tools such as ChatGPT.
    • Smart cleanup: Removes filler words, false starts and repetitions while adding punctuation and formatting.
    • Fast dictation: Wispr Flow says users can dictate at up to 220 words per minute, potentially making voice input several times faster than conventional typing.
    • Personal vocabulary: Learns and remembers words, names and terminology that are specific to you.
    • Snippets & shortcuts: Create reusable text shortcuts for things such as emails, links, bios and frequently used phrases.
    • Multilingual: Supports 100+ languages, although performance can vary between languages.
    • Cross-platform: Available on Mac, Windows, iPhone and Android.

    🛠 How to Use Wispr Flow

    1. Download Flow and set it up on your device.
    2. Open any supported app and place your cursor where you want the text.
    3. Speak naturally. Flow converts your speech into polished, formatted text rather than simply reproducing every word.
    4. Personalize it with your vocabulary, snippets and preferences.
    5. Upgrade to Pro if you need unlimited dictation and additional features.

    ⚡ Why It’s Different

    • Beyond basic transcription: Flow doesn’t simply convert speech to text; it interprets spoken language and cleans it up as it goes.
    • Formatting on the fly: It can turn spoken instructions into paragraphs, lists and structured messages.
    • Personalized writing: It adapts to words and terminology you commonly use.
    • Works across platforms: Your voice-based workflow can follow you across desktop and mobile devices.

    ⚠️ Cons & Limitations

    • Free-tier limits: The basic plan has a weekly word limit, while Pro offers unlimited dictation.
    • Audio quality matters: Wispr recommends avoiding Bluetooth earbuds such as AirPods because audio compression can affect recognition.
    • Some setup helps: Adding personal vocabulary and snippets can improve the experience for specialized workflows.
    • Not a replacement for editing: AI-generated dictation can still require manual refinement, particularly for complex or highly precise writing.

    Bottom line: Wispr Flow turns voice into more than transcription. Its real appeal is the ability to speak naturally and get writing-ready text back, making it particularly interesting for professionals, creators, developers and anyone who finds typing slower than thinking.

    Image credit: WisprFlow

    (Disclaimer: Community members/readers must do their own due diligence before buying this app. This is just an explainer post published from publicly available material.)

  • Duh. Someone’s Already Made A Claude Watermark Remover

    Duh. Someone’s Already Made A Claude Watermark Remover

    A new online tool, “Claude Watermark Remover”, has emerged just days after Anthropic introduced an invisible watermarking system for newer Claude models, highlighting a rapidly developing contest between AI transparency measures and tools designed to circumvent them.

    The website, claudewatermarkremover.app, allows users to paste Claude-generated text and receive a re-written version designed to break the statistical signature embedded in the original output.

    According to the site, the process uses a non-Claude model to substantially alter wording and sentence structure while attempting to preserve the original meaning. The service is advertised as free and requires no registration.

  • Cisco’s New Antares AI Models Could Make Software Security Faster And Cheaper

    Cisco’s New Antares AI Models Could Make Software Security Faster And Cheaper

    Finding a security vulnerability in a large codebase is a bit like searching for a leaking pipe inside a skyscraper. You know water is escaping somewhere, but figuring out which floor, which room, and which pipe is the real challenge.

    Cisco believes it has found a better way.

    The company has introduced Antares, a family of security small language models (SLMs) designed specifically for vulnerability localization. Instead of writing code or generating patches, these open-weight models focus on one important job. They help developers identify where a known security flaw is likely hiding inside a software repository.

    That distinction matters.

    (BTW: An open weight model is an AI model whose trained parameters (weights) are publicly available, allowing organizations to run, inspect, and often fine tune it on their own infrastructure without having to build the model from scratch.)

    Many organizations today rely on large general purpose AI models for coding assistance. While they are powerful, they can also be expensive to run and often require sending sensitive source code to cloud services.

    Antares takes a different approach. It is a smaller, specialized model that can run locally, keeping proprietary code inside an organization’s own environment while significantly reducing compute costs.

    Think of it this way. If a Swiss Army knife can do twenty different jobs reasonably well, Cisco’s Antares model is a precision screwdriver built for one task. It may not do everything, but it performs its intended job with remarkable efficiency.

    The Implications

    For businesses, this could mean faster security reviews, lower AI infrastructure costs, and fewer delays when responding to newly disclosed vulnerabilities. Security teams no longer have to sift through thousands of files manually before deciding where to focus their attention. The AI helps narrow the search, allowing human experts to spend their time verifying and fixing issues instead of hunting for them.

    Developers also benefit. Because the models are open weight, organizations can inspect, fine tune, and integrate them into their own development pipelines. That flexibility makes them attractive for enterprises that want greater control over their AI tools instead of relying entirely on closed commercial services.

    The two models—Antares-350M and Antares-1B—as open-weight models now available to the broader community on Hugging Face.

    Cisco’s announcement reflects a broader trend in enterprise AI. Bigger is not always better. Sometimes the smartest solution is a smaller model that excels at one critical task. In cybersecurity, where speed, privacy, and cost all matter, that focused approach may prove more valuable than another all purpose AI assistant.

  • Make Your Own AI with Pi (Raspberry)

    Make Your Own AI with Pi (Raspberry)

    Who says you need a supercomputer to build artificial intelligence (AI)? Today, something as powerful as AI can run on something as small as a Raspberry Pi!

    This tiny, affordable computer is opening the doors to a world of smart technology, allowing students, makers, and tech enthusiasts to create everything from face-recognition systems and voice assistants to robots and smart home gadgets.

    With “AI Projects with Raspberry Pi”, learning AI is no longer limited to experts. It’s now fun, hands-on, and within reach of anyone with curiosity and a Raspberry Pi.

    The new guide is packed with hands-on projects that enable students, hobbyists, educators, and makers to explore the rapidly growing world of artificial intelligence using Raspberry Pi hardware.

    The publication introduces readers to essential AI concepts such as computer vision, machine learning, and natural language processing through practical, project-based learning. Instead of focusing only on theory, it encourages users to build real-world applications, including smart cameras, voice-controlled assistants, environmental monitoring systems, and intelligent automation projects. Many of these applications run directly on Raspberry Pi devices, showcasing the power of edge AI, where data is processed locally for faster performance, enhanced privacy, and reduced reliance on cloud services.

    What’s Raspberry Pi?

    Raspberry Pi is a series of compact, affordable single-board computers developed to make computing, programming, and digital innovation accessible to everyone.

    Since its launch in 2012, Raspberry Pi has become a global favourite among students, educators, hobbyists, and professionals for learning coding, building electronics projects, and developing applications in robotics, IoT, AI, and automation. Despite its small size, a Raspberry Pi delivers impressive computing power and supports a wide range of programming languages, operating systems, and hardware accessories. With a strong emphasis on hands-on learning and innovation, Raspberry Pi has empowered millions of people worldwide to turn creative ideas into real-world technology solutions.

    Beyond teaching technical skills, “AI Projects with Raspberry Pi” inspires creativity and innovation. It highlights how affordable computing can be transformed into intelligent systems capable of solving real-world problems across education, robotics, smart homes, and environmental monitoring. By combining powerful AI tools with easy-to-use hardware, Raspberry Pi continues to empower the next generation of innovators.

    Image credit: Raspberry Pi

  • Samsung’s New AI SSD Won’t Fix the Memory Crisis. But It’s A Sign Of Where Relief Will Come From

    Samsung’s New AI SSD Won’t Fix the Memory Crisis. But It’s A Sign Of Where Relief Will Come From

    Samsung just began mass production of an enterprise SSD purpose-built for artificial intelligence (AI) and high-performance computing (HPC) servers.

    Read against the backdrop of 2026’s brutal memory shortage, it’s tempting to ask: does this bring costs down? The honest answer is not directly, not soon. But it does hint at how relief eventually arrives.

    (An SSD (Solid State Drive) is a data storage device that uses flash memory chips to store data, instead of spinning magnetic disks like older hard drives (HDDs).

    No moving parts — data is stored electronically on NAND flash chips, so there’s nothing physically spinning or moving to read/write data.)

    What Samsung Actually Shipped

    The PM1763 is built on 9th-generation V-NAND and a new 4nm controller, available in 4TB, 8TB, and 16TB capacities.

    The flagship 16TB drive hits sequential read/write speeds of 28,400/21,900 MB/s, over double its predecessor, the PM1753. And it’s fast enough to move a 40GB language model in about 1.4 seconds.

    Where consumption of electricity is concerned, the new SSD’s power efficiency improves by more than 1.8x, and it’s designed for liquid-cooled, direct-to-chip server racks, with post-quantum cryptography baked in for security-conscious deployments.

    In short: it’s a performance and efficiency play, not a supply play. It doesn’t add wafer capacity or NAND bits to a starved market.

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    Why That Distinction Matters Right Now

    2026 has been defined by what analysts are calling a “structural” — not cyclical — memory shortage.

    Manufacturers have been reallocating fab capacity away from conventional NAND and DRAM toward high-margin, AI-driven products like HBM and high-capacity enterprise SSDs, since a single AI server rack can demand over 1,000TB of NAND.

    It is this reallocation, not a lack of manufacturing, that is driving contract prices up. TrendForce and IDC both expect meaningful new fab capacity — the kind that would actually ease scarcity — no earlier than late 2026, with real relief likely 2027-2028.

    Where A Chip Like This Actually Helps

    Doing more with less is the real short-term win here, not making more chips.

    If the PM1763 lets a data center handle the same amount of AI work using fewer drives, thanks to better speed and nearly double the power efficiency, that means buying fewer SSDs for the same job, and spending less on power and cooling per server rack.

    For a data center operator, that can offset, not reverse, rising per-unit NAND prices. It’s a way of doing more with the same starved allocation of chips, rather than a way of making more chips available.

    There’s also a signaling effect. Samsung, SK Hynix, and Micron are all funneling R&D toward exactly this segment — high-capacity, high-margin enterprise storage — because that’s where hyperscaler demand and pricing power both sit.

    Bottom line for the community

    Don’t expect AI infrastructure costs to fall because of this launch. Expect them to keep climbing through 2026, with a slower rate of increase for operators using the newest, most efficient hardware. Expect real price relief only once new fab capacity actually comes online, not before.

    Image credit: Samsung