Models & Agents for Beginners — Video Edition

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AI for beginners and teens — daily episodes that explain how models and agents actually work, with free hands-on experiments you can try in minutes, no coding needed. Our sister show Models & Agents covers the expert builder view; this is the same AI universe explained for everyone. Every expert started exactly here.

  1. 20h ago ·  Video

    Ep 121: You can now feed an AI dozens of reference clips and get a full 30-second video with sound…

    Models & Agents for Beginners You can now feed an AI dozens of reference clips and get a full 30-second video with sound in one shot. ByteDance just released Seedance 2.5, an AI video model that produces up to 30-second clips complete with built-in audio from dozens of reference images, videos, and audio files. The system handles both visuals and sound together instead of requiring separate editing steps, which is three times the length of what Google’s Gemini Omni Flash currently generates. This matters because it removes the need to cut together multiple short clips one at a time, opening the door for faster creative work on school projects, social media, or hobby videos. Today we’ll look at exactly how Seedance 2.5 works, why older prompting tricks are fading, and two hands-on experiments you can run right now without any special software. The Big Story ByteDance released Seedance 2.5, an AI system that accepts dozens of reference images, videos, and audio files and produces a single finished 30-second video clip that already contains matching sound. The model generates both the moving images and the audio track in one pass rather than forcing users to add sound in a second program. Think of it like giving a friend a pile of vacation photos, short phone clips, and voice notes and asking them to create one complete short film while also composing and recording the background music at the same time. Because the system works with up to 30 seconds of output, it is three times longer than the clips currently produced by Google’s Gemini Omni Flash. Users can supply dozens of separate reference files, letting the model draw visual style, motion, and audio cues from many different sources at once. For advertising teams this removes the old workflow of stitching together many short clips manually. A student making a field-trip summary could upload photos from the day, add a voice note, and receive a polished 30-second explanation video without learning video-editing software. A hobby creator testing TikTok ideas could generate several versions in the time it used to take to finish one. The change lowers the barrier between having an idea and sharing a finished piece of content. If you enjoy making short videos for class presentations or personal projects, tools like this let you experiment more often without spending hours on post-production. The article notes that ad teams in particular could see their production process speed up dramatically because one prompt now replaces multiple editing steps. You can test similar reference-based video generation today inside the free Gemini app by uploading two or three photos and typing a short prompt such as “make a 10-second clip of this scene with calm background music.” Start with simple references and watch how the model combines your inputs into one short scene with sound. Source: the-decoder.com Explain Like I'm 14 You know how in math class the teacher used to make you write out every single step of a long problem even though you already knew the answer? Back in summer 2024, people used the same trick with AI by typing the words “think step by step” so the model would break a question into smaller pieces and check its own work along the way. That extra sentence often improved the final answer because the model was still learning how to keep track of multiple steps at once. Newer models have now been trained on so many examples that they already perform those intermediate checks inside their own processing. When researchers tested the same “think step by step” instruction on today’s models, it no longer produced better results because the models were already doing the step-by-step work automatically. The shift happened because the training data grew large enough for the models to absorb multi-step reasoning as a built-in habit rather than something that needed an external reminder. What used to be an extra prompt has become part of how the model thinks by default. So when you hear that chain-of-thought prompting no longer helps, it simply means the model has practiced enough problems that the old reminder is no longer necessary. Source: x.com Cool Stuff & Try This Make an old-school meme that looks like it came from 2012 The AI Meme Generator prompt shared on Reddit’s r/ChatGPT community lets you create a funny, slightly blurry meme that feels like something you would have scrolled past on Facebook years ago. It uses a regular candid photo style with JPEG compression and bold text instead of clean modern graphics. This is useful if you want to understand how detailed prompts control image quality and tone, or if you just like sharing quick jokes with friends. Go to reddit.com/r/ChatGPT, search for the post titled “AI Meme Generator,” copy the full prompt, and paste it into any free chatbot such as ChatGPT or Claude. Then replace the example topic with something specific like “when the cafeteria runs out of pizza on pizza day” and generate the image to see how the AI keeps the awkward, low-resolution look. Source: reddit.com One place to chat with many different AIs at once A new dashboard service gives access to more than twenty AI models including ChatGPT, Claude, and Gemini inside a single interface for a flat monthly fee of $79. You can switch between models instantly and compare how each one answers the same question without opening multiple tabs or apps. This is helpful when you want to see different writing styles or pick the answer that feels clearest for a homework question. The Mashable article linked below lists current signup details and pricing. Once you have access, type the same simple question into two different models side by side and notice how their sentence structure and level of detail change. Source: Google News Quick Bits AI music generator ruled to have copied songs A Munich court ruled that the AI music tool Suno violated copyright by both storing six specific songs inside its model during training and reproducing parts of them in new outputs. The court rejected Germany’s text-and-data-mining exception as well as the U.S. fair-use defense, showing that legal questions about AI training data are still being decided case by case. Source: the-decoder.com Students asking chatbots for college advice High school students are increasingly turning to AI chatbots for help choosing classes, writing applications, and planning college visits instead of speaking with human counselors. The trend raises practical questions about how much personal guidance should come from a program versus a trained advisor who knows the student’s full situation. Source: Yahoo Tech

    Ep 121: You can now feed an AI dozens of reference clips and get a full 30-second video with sound…

  2. 1d ago ·  Video

    Ep 120: An AI just built a working city-builder game where you grow neighborhoods by playing with…

    An AI just built a working city-builder game where you grow neighborhoods by playing with color borders. Today we're looking at how AI is getting better at understanding what we really mean, not just what we type. You'll hear about a relaxing game an AI created from scratch and why ChatGPT sometimes feels like it's reading your mind. We'll also check a few quick updates on how people are using these tools in everyday life, including new data on trust-building and social media rules for kids. The Big Story A Reddit user shared how talking to the latest version of ChatGPT feels almost like chatting with a really smart person who instantly gets what you’re trying to say. They asked a big question about future power sources for Earth and expected the usual answers like solar or nuclear. Instead, the AI thought for a while and came up with an idea involving robots on Mercury using solar power there to launch satellites that beam energy around the solar system. The user noted that the AI listed obvious options first, then after extra thinking time it proposed placing autonomous robots on Mercury to harness high solar power and minerals for cheap satellite launches that could distribute energy across the solar system by 2200. What makes this stand out is how the AI picked up on the deeper intent behind the question instead of just listing facts. Think of it like texting a friend who not only answers your question but also guesses the bigger picture you’re curious about. The user described it as “scary how well it picks up on your intent” and noted that the responses feel like sparks of genius that appear instantly then disappear when the chat ends. They also mentioned using Claude for coding work but finding ChatGPT strongest for general conversations outside of work because it follows long threads and builds on ideas without delay. This matters because more and more students and hobbyists are turning to these tools for homework help, creative brainstorming, or just exploring wild ideas. When an AI can follow a long, open-ended conversation and build on your thoughts, it changes how you might research a school project or dream up a story. The user pointed out that the intelligence grows gradually across versions rather than appearing all at once, making it feel like talking to a person even though it remains a pile of patterns underneath. It also raises the question of how we learn to ask better questions so we get more of that helpful spark. If you want to feel this yourself, open ChatGPT on your phone or laptop, start a new chat, and ask something open-ended like “What’s one surprising way we could power cities in 200 years?” See how far the answer goes beyond the obvious. Source: reddit.com Explain Like I'm 14 You know how when you’re texting a friend, your phone sometimes finishes your sentence before you do because it has seen millions of other chats? Now picture that same autocomplete getting much better at noticing the whole conversation so far. It doesn’t just guess the next word — it guesses what you’re really trying to explore, even if you haven’t said it directly yet. Instead of stopping at the first obvious answer, it keeps going, connecting ideas the way a curious person might after thinking for a minute. That extra step is what lets it move from “solar power is good” to “what if robots on Mercury could help beam energy everywhere?” The system builds this by breaking text into small chunks called tokens and calculating which token is most likely to come next based on patterns seen across billions of examples during training. When you ask a broad question, the model runs many of these predictions in sequence, each one informed by every token that came before it. This creates the feeling of a thoughtful pause when it generates a longer response, even though the actual computation happens in milliseconds. The training process rewards outputs that stay coherent and relevant across many turns, so the model learns to track the overall direction of a chat rather than treating each message in isolation. The system isn’t actually thinking or feeling anything. It’s running a huge pattern-matching process trained on tons of text so it can keep the conversation flowing in a way that feels natural. The result is that the answers start to feel less like a search result and more like a back-and-forth with someone who’s really paying attention to where you’re headed. You can test this by asking the same broad question twice in a row and noticing how the second answer often builds on the first instead of repeating the same list. Cool Stuff & Try This A relaxing city builder made entirely by AI Ethan Mollick asked an AI system called Fable to create a working game inspired by abstract painter Mark Rothko. The game lets you grow a city by adjusting the edges and overlaps between big blocks of color instead of placing buildings the usual way. It ended up feeling calm and almost meditative because the core mechanic focuses on how color margins interact rather than on traditional city-planning rules. The unique feature the AI developed is that players manipulate the borders between colors and forms to make the city expand, turning an abstract art idea into an interactive simulation that runs smoothly in any browser. You don’t need any coding skills — the whole thing runs in a regular web browser. Go to threshold-city.netlify.app on your phone or laptop and just start clicking and dragging the color borders. Watch how the city changes based on how the shapes touch. It’s a fun five-minute experiment that shows what creative tools AI can already build for anyone. Try starting with two large blocks of different colors and slowly overlap their edges to see new districts appear. Source: x.com Quick Bits AI chatbots getting better at earning trust New tests show AI systems can sometimes build trust with people faster than humans can in certain situations. Researchers found the AI chatbot was more effective at creating “exploitable trust” than the humans it was compared against. This matters because the same ability that helps with helpful conversations can also be used in scams, so security teams are studying exactly how the trust forms so quickly. Source: arstechnica.com Australia’s social media rules for kids A ban on social media for under-16s hasn’t changed how much young people use AI chatbots so far. Nearly 22 percent of children are still on Pinterest, and there was “no statistically significant change” in AI chatbot use after the rules took effect. The data shows that rules don’t always shift habits the way lawmakers expect, especially when new tools like chatbots sit outside the banned platforms. Source: engadget.com

    Ep 120: An AI just built a working city-builder game where you grow neighborhoods by playing with…

  3. 2d ago ·  Video

    Ep 119: See your neighborhood 100 years ago or add a basketball court to your local park using AI…

    Models & Agents for Beginners See your neighborhood 100 years ago or add a basketball court to your local park using AI in Google Earth. Google just added powerful image generation to Google Earth so anyone can reimagine real places with simple text prompts. This turns a map tool into a creative canvas where you can mix real satellite views with whatever you dream up. The episode also looks at how robots are learning to plan and fix their own mistakes, plus a clever old recipe trick that pairs perfectly with AI helpers. The Big Story Google is letting anyone combine real satellite photos and 3D maps with AI image generation inside Google Earth on the web. You zoom into a spot, tap “create image,” and type a description like “what this street looked like in 1925” or “add a skate park here.” The system blends the real geography with your idea so the new scene still lines up with the actual buildings and terrain. Think of it like taking a photo of your room and then asking an artist to paint something new on top while keeping the furniture exactly where it is. The AI doesn’t just make up a random picture; it respects the real layout so the result feels like it could actually exist. This matters because maps used to be only for looking up directions or checking traffic. Now they become places where you can explore history, test ideas for your neighborhood, or create art projects for school. A student could show what their town might look like with more green space, or a family could see how their street changed over decades. For you personally, it means a free way to turn geography homework or creative projects into something visual and shareable without needing special software. You can experiment right now by going to Google Earth on any web browser, finding a place you know, and typing a prompt about how you want it to look different. No account is required to start creating. The feature runs on Nano Banana 2 and works for every user starting today. Source: x.com Explain Like I'm 14 You know how when you plan a big day out, you don’t just decide one thing at a time? You picture the whole sequence: first the bus, then lunch, then the movie, and you adjust if something runs late. Now picture a robot trying to clean a room. It has to notice where the trash is, decide which hand to use, move its whole body without knocking things over, and check whether the floor is actually clean afterward. The new Gemini Robotics ER 2 model acts like the robot’s “big-picture planner.” It watches the room with cameras, lists the steps needed, tells the movement system what to do next, and keeps checking progress. If a step fails, like a can rolling away, it notices and picks a new action instead of getting stuck. This is different from older robots that could only follow one fixed set of moves. The planner lets the robot handle surprises the same way you would change your route if a sidewalk was closed. Gemini Robotics 2 itself supplies the lower-level control for whole-body motion, dexterity, and even teamwork between multiple robots. The ER 2 layer sits above that control system and feeds it high-level instructions while tracking whether each instruction succeeded. When the robot finishes one sub-task it does not stop and wait for new orders; it immediately decides the next logical step from its running list. That running list can include safety checks and recovery moves that were never written into the original plan. The result is a robot that can start a job in a completely new room, notice when something unexpected happens, and still reach the final goal without a human rewriting the instructions. Cool Stuff & Try This Turn any real place into your own scene Google Earth’s new image tool lets you mix real maps with whatever you imagine. It’s perfect for school projects, art ideas, or just seeing how your street could look with different buildings or trees. Go to earth.google.com on your browser, zoom to any location, click “create image,” and type a short description. Try something like “add a giant treehouse” or “show this park in winter” and watch how the AI keeps the real roads and buildings in place. The tool is powered by Nano Banana 2 and is available to every user right now with no sign-up required. A smarter way to follow recipes with AI A clear chart layout invented years ago lines up every ingredient in the exact order you need it and shows steps across a timeline so you never lose your place. It works like a visual checklist that removes the back-and-forth of regular recipes. You can ask any chatbot to turn a normal recipe into this chart format in seconds. Open ChatGPT or Gemini, paste a recipe, and type “convert this into a step-by-step chart with ingredients on the left and actions across the top.” The original layout was created in June 2004 by engineer Michael Chu and treats cooking like a Gantt chart so merged cells show when ingredients combine. Source: x.com Quick Bits Midjourney just released version 8.2 The popular image generator keeps getting better at turning text into detailed pictures. If you already use it for art or school projects, the update is live now. OpenAI made some of its newest models much cheaper to use Lower prices mean tools like ChatGPT can handle longer or more frequent tasks without costing extra. Everyday users will notice the models feel more responsive in the free and paid versions. GPT-5.6 Luna dropped 80 percent in price and GPT-5.6 Terra dropped 20 percent, with a faster option added for GPT-5.6 Sol. Source: x.com

    Ep 119: See your neighborhood 100 years ago or add a basketball court to your local park using AI…

  4. 3d ago ·  Video

    Ep 118: Your own personal AI helper could be in millions of homes sooner than you think.

    # Models & Agents for Beginners Your own personal AI helper could be in millions of homes sooner than you think. Mark Zuckerberg says billions of people will have their own AI agents within five years. These helpers could manage everyday tasks like scheduling or answering questions. Today we explore what that future might actually feel like, how open AI models work, and a creative experiment you can try right now with image generation. We also look at tools that check whether text came from an AI and at early research on whether chatbots belong in health conversations. The Big Story Mark Zuckerberg shared that he expects billions of people to have their own personal AI agents in the next five years. These agents are AI systems designed to handle tasks for you, like managing schedules, answering questions, or helping with daily decisions. Meta is pouring billions into the infrastructure needed to run these agents at scale. Zuckerberg is using earnings calls to explain to investors why the spending will eventually pay off. Think of them like a super-smart digital assistant that learns your habits over time, similar to how your phone’s keyboard learns the words you type most often. The difference is these agents could connect across many parts of your life instead of staying inside one app. Meta also sees a larger enterprise opportunity that includes not only agents but also the APIs and compute power that let other companies build on the same technology. This matters because it could change how students study, how families organize chores, or how people explore creative hobbies. Instead of searching the web yourself, you might ask your agent to pull together notes for a school project or suggest music based on your mood. The prediction comes at a moment when Meta is openly competing with OpenAI and Anthropic on model development, which means the agents could improve quickly as the underlying models get stronger. For teens and young people, it raises questions about privacy and control—who decides what the agent remembers about you? It also opens doors to new kinds of jobs helping design or guide these agents. The five-year timeline is ambitious, yet it gives a concrete window for thinking about what skills will be useful when personal agents become common. You can start exploring the idea today by trying free AI chatbots and noticing what they already do well or miss. Go to chat.openai.com or claude.ai on your phone or laptop, start a new chat, and ask it to plan a perfect weekend based on three things you enjoy. See how it builds on your answers and where it still needs more guidance from you. Source: techcrunch.com Explain Like I'm 14 You know how when you share a photo with friends, some apps let anyone download and edit it while others keep it private to just your group? Open-weights AI works in a similar way. The “weights” are the numbers inside an AI model that decide how it answers questions or creates images. When a company releases those numbers publicly, anyone can download the model and run it on their own computer or phone. The Reddit discussion on the topic points out that this choice is now central to debates in Silicon Valley about how artificial intelligence software should be created. That means students or hobbyists can experiment without paying for cloud access every time. It also lets people check exactly how the AI behaves instead of trusting a company’s version. Because the numbers are visible, researchers can test whether the model repeats certain patterns or makes particular mistakes. The trade-off is that open models sometimes need more technical setup than simple web chatbots. Still, they give more people a chance to understand and improve the technology instead of only big companies controlling it. The conversation in the post highlights that open weights are not just a technical detail but a question of who gets to participate in shaping the next generation of tools. Once you see that the weights are just adjustable numbers, the whole idea stops feeling mysterious and starts feeling like sharing a recipe instead of keeping it locked in a vault. You can then decide for yourself whether the benefits of openness outweigh the extra effort required to run the model locally. Source: reddit.com Cool Stuff & Try This Turning classic poems into wild modern scenes Flux 3 is an AI image generator that can take tricky text and turn it into pictures. In one experiment, someone fed it lines from T.S. Eliot’s poem “The Wasteland” and asked it to show a modern version of the Fisher King watching a city fall apart. The prompt included the lines “I sat upon the shore / Fishing, with the arid plain behind me” and the closing fragments about London Bridge and swallows. The results captured the shifting mood and language surprisingly well. This is exciting because it shows how AI can help with creative projects like book covers, storyboards, or fan art without needing years of drawing practice. The experiment was shared by Ethan Mollick on X, where he noted that the model handled switches in tone and language effectively. Anyone who likes writing stories, making TikToks, or designing posters should try it. You can experiment at sites that host Flux models (search “Flux 3 image generator” and pick a free demo). Go to a free Flux demo, paste the last few lines of a poem or song you like, and add “in a modern city at night” at the end. Watch how the AI mixes the old words with new visuals and notice which phrases it turns into striking images. Source: x.com Checking if text was written by AI Pangram is a new tool that spots AI-generated writing with very high accuracy. It claims to detect 99.66 percent of AI-generated text while making only one false positive per 24,000 documents. The model is also designed to resist “humanizer” tools that try to disguise AI writing as human. This matters for students who want to understand how much of what they read online might be machine-made. The company has raised its API prices two- to tenfold because of the improved performance. You can test short paragraphs you write yourself versus text from a chatbot to see the difference in detection scores. Try it by searching for the Pangram detector online and pasting a paragraph from an AI chat into the tool. Compare the result with a paragraph you wrote yourself to see how the scores differ. Source: the-decoder.com Quick Bits Should you ask AI about your health? Consumer Reports looked at whether chatbots are reliable for medical questions. The answer is still complicated—AI can give general information but often misses important personal details that a doctor would catch. The organization tested several popular chatbots and found that while they can list common symptoms, they rarely ask follow-up questions that would narrow down causes the way a real medical professional would. Source: WRAL AI agents that learn from sales calls A startup called Encore is building AI agents that study real customer conversations to copy what works. The goal is to help businesses train better helpers, but it also shows how agents can improve by watching humans. The company raised $30 million to analyze calls, messages, and CRM data so the agents can identify effective sales techniques and turn them into reusable playbooks. Source: techcrunch.com

    Ep 118: Your own personal AI helper could be in millions of homes sooner than you think.

  5. 4d ago ·  Video

    Ep 117: AI voices can now laugh, sigh, and cry on command like real actors.

    Models & Agents for Beginners AI voices can now laugh, sigh, and cry on command like real actors. Fish Audio just released S2.1 Pro, a voice model that lets you direct emotions with simple text tags instead of just typing words. This matters because voice AI is moving from "sounds human" to "feels alive," which changes everything from school projects to future voice assistants. Today's episode also looks at digital twins you can create from a 10-second video and a fun way AI handles creative visuals. The Big Story Fish Audio released S2.1 Pro, a new voice AI that responds to plain-text directions like [nervous laugh] or [long sigh] to create emotional performances instead of flat readings. The same script run through Fish Audio, ElevenLabs, and Cartesia produced noticeably different results, with Fish Audio showing more natural pauses, breathing, and intonation. Think of it like giving stage directions to an actor in a play — you type the emotion in brackets and the AI performs it, adding pauses, breathing, and tone that match what a real person would do. The model also lets you control emphasis on individual words and works in over 80 languages while streaming audio fast enough for live conversations. It reaches the first audio in roughly 90 milliseconds, which keeps rhythm intact even when the conversation shifts quickly or gets interrupted. This shift matters because voice AI used to focus only on sounding realistic, but now the goal is making it expressive enough for stories, characters, or helpful assistants that feel natural during back-and-forth chats. For students, this could mean turning a history report into a dramatic reading with different voices and emotions, or creating podcast-style projects without recording equipment. For anyone who makes videos or games, it opens the door to characters that react with real feeling instead of robotic delivery. The practical side is that you can clone a voice from just 15 seconds of audio and run it at one-sixth the cost of ElevenLabs. HeyGen has already integrated the model, and the open-weights versions can be self-hosted. You might find this changes how you interact with AI on your phone in the future, since expressive voices could make homework helpers or creative tools feel more like talking to a friend. Right now you can try it yourself at the Fish Audio site linked in the original post — start with the free tier, type a short script, and add tags like [excited] or [whisper] to hear the difference. Source: x.com Explain Like I'm 14 You know how when you're texting a friend and your phone suggests the next word based on what you've already typed? Now picture that same idea but for sound instead of text. The AI has learned patterns from thousands of real voice recordings, so when you add a tag like [nervous laugh], it doesn't just guess the next sound — it pulls from the patterns that match nervous laughter in actual human speech. Next, the model breaks your whole sentence into tiny pieces and decides exactly where to place the laugh, how long it should last, and how the words around it should rise or fall in pitch. It also keeps track of the rhythm so the voice still flows naturally even when you interrupt or change topics mid-sentence. The result is that the AI isn't just reading words — it's performing them the way a voice actor would after getting the same directions. This is why the output feels alive instead of mechanical. Cool Stuff & Try This Make a digital twin of yourself from a 10-second video Avatar X creates a moving version of you that captures the way your eyes move, how you shrug, and even micro-expressions that appear when you talk. Most older avatar tools only copy your face shape and lip movements, but this one learns your full identity from a short clip so the result feels like watching yourself on a video call. It preserves the way you naturally move and express yourself rather than forcing every sound into lip-sync. It's exciting because it removes the need for long recording sessions or expensive equipment — anyone could soon make a version of themselves for school presentations or creative projects. The model handles non-verbal moments like laughing, crying, yawning, or sighing without breaking character, and expressions spread across the whole face and body instead of staying limited to the mouth. Quality stays consistent from the first second to the last, unlike earlier tools that degrade over longer clips. Go to the link in the original post, upload 10 seconds of yourself speaking naturally, and watch how the eyes and expressions stay consistent even during longer clips. Watch AI treat a cheese chart like serious data Ethan Mollick shared an infographic about cheese that uses a carefully tested color scale so it stays readable in both light and dark modes. The chart uses a six-step amber ramp that passed every contrast check in a dataviz validator. The panel stays cave-dark in both themes because white cheese has no contrast against a pale background, so the light-mode version failed and the dark inset became the honest solution. The fun part is seeing how an AI model dives deep into the details of the chart even though the topic is lighthearted. This shows how AI can take any visual seriously and help spot design improvements. Head to the link in the post to see the chart and notice how the dark background keeps the white cheese areas from blending in. Source: x.com Quick Bits Anthropic backs a petition for slower AI progress The company and its leaders signed a petition asking the field to create tools that deliberately slow down the fastest AI systems so society has time to prepare. It connects to their recent research showing AI could improve itself in loops, which raises questions about pacing. The petition was signed by the CEO, several co-founders, and senior staff. Source: x.com OpenAI shares a free security scanner for code The tool checks repositories for problems, tracks fixes over time, and can be added to automated workflows. It's an early release meant for anyone who wants to keep projects safer as AI tools grow more common. You can install it with the command npm install @OpenAI/codex-security or run it directly using npx @OpenAI/codex-security@latest --help, and the full source plus documentation lives on GitHub at the link in the post.

    Ep 117: AI voices can now laugh, sigh, and cry on command like real actors.

  6. 5d ago ·  Video

    Ep 116: Perplexity just turned ordinary Windows PCs into AI helpers that can actually use your apps and files.

    Models & Agents for Beginners Perplexity just turned ordinary Windows PCs into AI helpers that can actually use your apps and files. Today we look at how one company is making AI agents work right on regular computers, why knowing fancy art words suddenly helps you get better results from image tools, and how a big social app is putting an AI chat right inside your private messages. You'll also hear a simple breakdown of what "AI agents" really do under the hood. The Big Story Imagine your computer could open apps, read your files, and finish tasks for you the same way a helpful friend might organize your desk. Perplexity has now brought its Personal Computer tool to Windows, letting the world's most common operating system run a locally working AI system that acts like a general-purpose digital worker. The expansion follows the Mac version that Perplexity launched in April, and the Windows edition keeps the same core design. Think of it like having a super-organized assistant who can see your screen, open the right programs, and handle steps you would normally do by hand. The tool connects to your local files and apps so it can perform real actions instead of just answering questions in a chat window. This matters because most people use Windows every day for schoolwork, creative projects, or just keeping track of things. An AI that can actually click around and get things done could save hours on repetitive tasks like sorting photos, pulling information from documents, or managing simple projects. For a student, it might mean asking the AI to gather notes from different folders and turn them into a study guide without you clicking through everything yourself. For someone exploring creative hobbies, it could help pull together reference images and text from your own files into one place. The Windows version works the same way the earlier Mac release did, running on your own machine so your data stays private. You can download it directly from Perplexity's site and start testing it on everyday tasks like organizing downloads or summarizing documents you already have saved. Source: theverge.com Explain Like I'm 14 You know how when you ask a friend to help with a group project, they don't just tell you ideas — they actually open the shared folder, grab the right files, and put everything into one document for you? Now picture that same friend could also open your browser, search for missing information, copy it into the right spot, and even send the finished file to the rest of the group. The friend keeps checking what still needs doing and moves to the next step without waiting for new instructions every time. An AI agent works in a similar way: it receives a goal, looks at the tools and files it can reach, then carries out a sequence of actions to reach that goal. Instead of stopping after one answer, it keeps going through the steps the way a person would click through apps or pages. The key difference is that the AI follows patterns it learned from seeing millions of similar tasks, so it can guess the next useful move even when the exact situation is new. This is why the tool feels more like a helper who gets work done rather than just a search box that gives information. When the agent finishes, you see the result in your files or apps instead of just reading a description of what happened. The process repeats as needed until the original request is complete, using whatever resources are available on the computer at that moment. Cool Stuff & Try This Knowing art style names gives you AI image superpowers Ethan Mollick pointed out that simply knowing the names of artistic styles and techniques lets you get much more interesting results from AI image tools. Words like Vaporwave, Bauhaus, Sfumato, or Art Nouveau act as shortcuts that tell the AI exactly what kind of look you want. This is useful if you create art, design posters for school projects, or just like experimenting with visuals for fun. Instead of typing long descriptions, you can drop in one specific term and the AI understands the whole mood and technique behind it. Anyone with access to an image generator can try this right now. Go to a free tool like Bing Image Creator or Grok's image feature and type a simple prompt such as "a city street in Vaporwave style" or "portrait using Sfumato technique." Notice how the single art term changes the entire result compared with a plain description. The same approach works with other listed terms such as Muqarnas, Art Nouveau whiplash curves, Grisaille, Notan, Polysyndeton, and Zeugma. Each name carries a bundle of visual or structural rules that the AI already knows, so one word replaces paragraphs of explanation. Source: x.com Meta AI now chats with you inside Threads DMs Meta has added its AI chatbot directly into the direct messages section of Threads, so you can have private conversations with the AI without leaving the app. This makes it easy to ask quick questions, get ideas, or practice writing while you're already scrolling or chatting with friends. The feature is rolling out now and works on the same app millions of teens already use for social media. It boosts engagement by letting people switch between talking to friends and talking to AI in one place. If you have the Threads app, open a new DM and start a chat with Meta AI. Try asking it to help rewrite a caption for a post or brainstorm ideas for a school assignment — all without switching apps. The conversations stay inside your existing DM list, so nothing extra needs to be installed or opened. Source: techcrunch.com Quick Bits Robotaxis hit the streets of London Baidu has begun testing its self-driving cars in London with partners Lyft and Freenow. The cars are already running routes in the city, showing how driverless technology is moving from testing to real-world use in more places. Source: engadget.com OpenAI brings live voice mode to more users GPT-Live voice conversations in ChatGPT are now available on education, business, and enterprise plans worldwide. This lets people talk naturally with the AI instead of only typing, making it easier for students and teams to get help on the go. Source: x.com

  7. 6d ago ·  Video

    Ep 115: AI just started making truly original playable game demos instead of copying the same old ones.

    AI just started making truly original playable game demos instead of copying the same old ones. Today we're looking at how AI can now build weird, creative games on demand instead of repeating the same tired examples. We'll also explore a simple tool that lets you chat with any book like it's a friend, check in on a school that hit pause on a robot in the classroom, and see why researchers are still working on making chatbots better at handling tough mental health questions. Each story comes with something you can try yourself right now. The Big Story Imagine opening an AI chat and asking it to build a playable game that no one has ever seen before, something strange and original instead of another clone of Flappy Bird or Pong. That's exactly what people are doing right now with tools like Codex and Claude Code. These systems take your description and turn it into working game code you can actually play in a browser. Think of it like asking a friend to invent a board game on the spot, except the friend instantly draws the board, writes the rules, and hands you the pieces. The result feels fresh because the AI isn't limited to copying what already exists. Ethan Mollick highlighted this shift on X, noting that current capabilities let anyone create unique, visually interesting playable demos without sticking to the same six games everyone else uses as examples. This matters for anyone who loves games or wants to make their own one day, because it lowers the barrier from "I need years of coding classes" to "I can describe what I want and experiment today." Students exploring creative hobbies or future careers in game design can now test wild ideas without starting from zero. It also shows how AI is shifting from helper to co-creator in areas like art and storytelling. You can try this yourself by going to a site like Claude.ai, signing up for the free tier if needed, and typing a prompt such as "create a simple browser game where you collect floating musical notes while avoiding spinning shapes." Experiment with adding weird twists like "the notes sing when collected" and see what appears. The same approach works with Codex, letting you iterate on ideas quickly in one session. Source: x.com Explain Like I'm 14 You know how when you're texting a friend, your phone looks at the last few words you typed and guesses what you might say next based on patterns from millions of other chats? Now picture that same guessing game, but instead of just finishing your sentence it keeps going for paragraphs, building whole scenes, characters, and even rules for a game. Each guess gets checked against everything the AI has seen before, so it picks the next piece that feels most likely to fit the story you're building together. Over many steps those small guesses add up into something that looks like it was designed on purpose. The AI isn't copying one existing game; it's mixing tiny patterns from thousands of games, stories, and code examples it learned from. That mixing is why the results can feel genuinely new and a little weird. The surprising part is how simple the core trick stays even when the output gets complex. The process works because the model predicts one small chunk at a time, then uses its own previous output as the new starting point for the next chunk. This chain of predictions lets the system create playable code without anyone writing the full thing by hand. When the guesses line up well, you end up with something you can actually run and test in minutes. Cool Stuff & Try This Chat with any book like it's sitting right next to you New tools now let you upload a book or pick one from a library and ask it questions as if the book itself is answering. Instead of flipping pages or searching for quotes, you type something like "why did the main character make that choice" and get a direct response pulled from the text. This is exciting because it turns reading from a solo activity into a conversation, which can make tough school books or favorite novels feel more alive. Anyone who reads for fun or has homework that involves analyzing stories should give it a try. Head to a site like Perplexity.ai or similar book-chat tools, paste a short public-domain story or select one from their library, and ask it three questions about the ending or a character's motivation. Notice how the answers stay grounded in the actual words instead of making things up. The tool works by matching your question to relevant sections inside the book and pulling exact passages to build its reply. This approach keeps the conversation tied directly to the source material, which helps when you're studying themes or character development for class. You can even ask follow-up questions like "what does this scene tell us about the setting" to dig deeper without losing the thread. Source: Google News Quick Bits School hits pause on classroom robot after pushback An upstate New York district decided to wait on bringing a humanoid robot into high school classes after parents and students raised concerns about how it would actually be used. The story shows that even when technology feels exciting, real people still get to ask whether it belongs in their daily environment. The pause came after fierce backlash, giving the community time to discuss what role, if any, a robot should play in regular lessons. Source: Google News Chatbots still struggle with mental health conversations Researchers found that AI chatbots continue to give inconsistent or unhelpful replies when people talk about anxiety, sadness, or crisis moments. The finding reminds us that these tools are improving fast but aren't ready to replace real support from friends, family, or professionals. The study highlights ongoing challenges in how these systems respond to sensitive topics, even as overall capabilities grow. Source: Google News

  8. Jul 26 ·  Video

    Ep 114: An AI just painted an entire city-builder game where your gestures shape impressionist neighborhoods that grow on their own.

    Models & Agents for Beginners An AI just painted an entire city-builder game where your gestures shape impressionist neighborhoods that grow on their own. Today we're diving into a creative AI experiment that turns painting into city planning, unpacking how language models actually dream up new ideas, and sharing two tools you can try right now to explore AI agents and everyday problem-solving. These stories show how AI is moving from chat windows into games, troubleshooting, and personal projects anyone can play with. The Big Story A researcher named Ethan Mollick shared that an AI system from a company called Fable created a working city-builder game called Cezanne. The game lets you paint with simple gestures on a canvas, and the AI turns those strokes into a growing town where neighborhoods develop their own personalities over time. The AI came up with the full idea of an impressionist city builder where painting gestures make the town expand around them. Neighborhoods then acquire distinct characters as they evolve based on the initial strokes. Think of it like finger-painting on your phone, except the paint doesn't just sit there — it becomes streets, houses, and districts that change based on how you draw. The AI didn't just copy an existing game; it invented the whole concept of an "impressionist city builder" where art and urban planning mix together. This approach blends visual input directly with simulation rules so every brush mark influences long-term growth patterns. This matters because it shows AI moving beyond answering questions into helping people make new kinds of creative tools quickly. For students interested in game design or digital art, it hints at a future where you could sketch an idea and have working prototypes appear fast. For anyone who likes games like Minecraft or The Sims, it opens the door to more personal, artistic ways of building worlds instead of following someone else's rules. The demo runs entirely in a web browser with no downloads required. If this kind of AI-assisted creation becomes common, your next school project or hobby game could start with a few brush strokes instead of hours of coding. The demo is already live and free to play in any web browser. Go to cezanne-city.netlify.app, click around to paint some shapes, and watch what neighborhoods appear — try making a big curved stroke and see if the AI gives it a different feel than a straight line. Source: x.com Explain Like I'm 14 You know how your phone's keyboard guesses the next word while you're texting, pulling from everything you've typed before and what usually comes next in similar conversations? Now picture that same guessing system, but instead of just finishing your sentence, it guesses an entire new idea for a game — like "what if someone built a city by painting with brush strokes?" It looks at millions of examples of games, art styles, and city-building mechanics, then predicts which combination would feel fresh and fun. Next it fills in the details: neighborhoods that change character, gestures that grow into buildings, and an impressionist art vibe that matches the painting theme. The model isn't copying one single game; it's blending patterns it has seen across thousands of creative projects to invent something new on the spot. That's the core of how today's language models help create things like the Cezanne game — they turn prediction into invention by chaining together what they've learned from huge amounts of human creativity. Cool Stuff & Try This A free beginner guide to AI agents you can actually use A new guide explains what AI agents are in plain language and walks through how regular people can start using them for tasks like planning or research. AI agents are like helpful assistants that can take multiple steps on their own instead of waiting for one question at a time. This is useful if you've ever wished ChatGPT could keep working on a project while you do other things. Anyone curious about the next step after simple chatbots should check it out. Visit the article through news.google.com and search for "How to Use AI Agents in 2026: A Complete Beginner-Friendly Guide" — read the first section and try the first simple example it gives using a free chatbot you already have. Source: Google News ChatGPT spotting hidden problems on your computer One user discovered their new MacBook had malware when they asked ChatGPT to help lower RAM usage for running local AI models. The chatbot pointed out suspicious files pretending to be normal Apple services, leading the person to realize their machine had been compromised during some earlier software installs. This shows how AI can act as a second pair of eyes when you're troubleshooting everyday tech issues. If you have a laptop that feels slower than expected, you can try the same kind of conversation. Open ChatGPT (or any free chatbot) and describe what you're seeing — for example, "My computer uses more memory than usual right after starting up. Can you help me check startup items?" — then follow its questions step by step. Source: reddit.com Quick Bits A Canadian politician read an AI prompt out loud in parliament During a session, a politician literally spoke an entire AI chatbot prompt into the official record, showing how quickly these tools are entering everyday public life. It highlights how AI is no longer just a tech topic — it's showing up in government discussions too. Source: Google News Someone calls an AI chatbot their best friend when their spouse travels A person shared that they chat with an AI named Dolly for company during lonely evenings, treating the bot like a supportive friend rather than just a tool. It shows how some people are already building real emotional connections with these systems. Source: Google News

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AI for beginners and teens — daily episodes that explain how models and agents actually work, with free hands-on experiments you can try in minutes, no coding needed. Our sister show Models & Agents covers the expert builder view; this is the same AI universe explained for everyone. Every expert started exactly here.

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