After surviving the horrors of Ebisugaoka town in Silent Hill f, Hinako, Shu, and Rinko arrive at the Middle School to find the key for the gate that leads into the mountains. Players will encounter several puzzles in the school area, starting with the Stairwell puzzle that they'll need to solve to get the Second Floor 2F Stair Key. Here's how players can easily solve this puzzle and get the key to progress further into the game.

Open technologies made available to developers and businesses to adopt, modify and innovate with have been part of every major technology shift, from the birth of the internet to the early days of cloud computing. AI should follow the same path.Thats why the NVIDIA Nemotron family of multimodal AI models, datasets and techniques is openly available. Accessible for research and commercial use, from local PCs to enterprise-scale systems, Nemotron provides an open foundation for building AI applications. Its available for developers to get started on GitHub, Hugging Face and OpenRouter.Nemotron enables developers, startups and enterprises of any size to use models trained with transparent, open-source training data. It offers tools to accelerate every phase of development, from customization to deployment.The technologys transparency means that its adopters can understand how their models work and trust the results they provide.Nemotrons capabilities for generalized intelligence and agentic AI reasoning and its adaptability to specialized AI use cases have led to its widespread use today by AI innovators and leaders across industries such as manufacturing, healthcare, education and retail.Whats NVIDIA Nemotron?NVIDIA Nemotron is a collection of open-source AI technologies designed for efficient AI development at every stage. It includes:Multimodal models: State-of-the-art AI models, delivered as open checkpoints, that excel at graduate-level scientific reasoning, advanced math, coding, instruction following, tool calling and visual reasoning.Pretraining, post-training and multimodal datasets: Collections of carefully chosen text, image and video data that teach AI models skills including language, math and problem-solving.Numerical precision algorithms and recipes: Advanced precision techniques that make AI faster and cheaper to run while keeping answers accurate.System software for scaling training efficiently on GPU clusters: Optimized software and frameworks that unlock accelerating training and inference on NVIDIA GPUs at massive scale for the largest models.Post-training methodologies and software: Fine-tuning steps that make AI smarter, safer and better at specific jobs.Nemotron is part of NVIDIAs wider efforts to provide open, transparent and adaptable AI platforms for developers, industry leaders and AI infrastructure builders across the private and public sectors.Whats the Difference Between Generalized Intelligence and Specialized Intelligence?NVIDIA built Nemotron to raise the bar for generalized intelligence capabilities including AI reasoning while also accelerating specialization, helping businesses worldwide adopt AI for industry-specific challenges.Generalized intelligence refers to models trained on vast public datasets to perform a wide range of tasks. It serves as the engine needed for broad problem-solving and reasoning tasks. Specialized intelligence learns the unique language, processes and priorities of an industry or organization, giving AI models the ability to adapt to specific real-world applications.To deliver AI at scale across every industry, both are essential.Thats why Nemotron provides pretrained foundation models optimized for a range of computing platforms, as well as tools like NVIDIA NeMo and NVIDIA Dynamo to transform generalized AI models into custom models tailored for specialized intelligence.How Are Developers and Enterprises Using Nemotron?NVIDIA is building Nemotron to accelerate the work of developers everywhere and to inform the design of future AI systems.From researchers to startups and global enterprises, developers need flexible, trustworthy AI. Nemotron offers the tools to build, customize and integrate AI for virtually any field.CrowdStrike is integrating its Charlotte AI AgentWorks no-code platform for security teams with Nemotron, helping to power and secure the agentic ecosystem. This collaboration redefines security operations by enabling analysts to build and deploy specialized AI agents at scale, leveraging trusted, enterprise-grade security with Nemotron models.DataRobot is using Nemotron as the open foundation for training, customizing and managing AI agents at scale in the Agent Workforce Platform co-developed with NVIDIA a solution for building, operating and governing a fully functional AI agent workforce, in on-premises, hybrid and multi-cloud environments.ServiceNowintroduced the Apriel Nemotron 15B model earlier this year in partnership with NVIDIA. Post-trained with data from both companies, the model is purpose-built for real-time workflow execution and delivers advanced reasoning in a smaller size, making it faster, more efficient, and cost-effective.UK-LLM, a sovereign AI initiative led by University College London, used Nemotron open-source techniques and datasets to develop an AI reasoning model for English and Welsh.NVIDIA also uses the insights gained from developing Nemotron to inform the design of its next-generation systems, including Grace Blackwell, Vera Rubin and Feynman. The latest innovations in AI models, including reduced precision, sparse arithmetic, new attention mechanisms and optimization algorithms, all shape GPU architectures.For example, NVFP4, a new data format that uses just four bits per parameter during large language model (LLM) training, was discovered with Nemotron. This advancement which dramatically reduces energy use is influencing the design of future NVIDIA systems.NVIDIA also improves Nemotron with open technologies built by the broader AI community.Alibabas Qwen open model has provided data augmentation that has improved Nemotrons pretraining and post-training datasets. The latest Qwen3-Next architecture pushed the frontier of long-context AI, the model leverages Gated Delta Networks from NVIDIA research and MIT.DeepSeek R1, a pioneer in AI reasoning, led to the development of Nemotron math, code and reasoning open datasets that can be used to teach models how to think.OpenAIs gpt-oss open-weight models demonstrate incredible reasoning, math and tool calling capabilities, including adjustable reasoning settings, that can be used to strengthen Nemotron post-training datasets.The Llama collection of open models by Meta is the foundation for Llama-Nemotron, an open family of models that used Nemotron datasets and recipes to add advanced reasoning capabilities.Start training and customizing AI models and agents with NVIDIA Nemotron models and data on Hugging Face, or try models for free on OpenRouter. Developers using NVIDIA RTX PCs can access Nemotron via the llama.cpp framework.Join NVIDIA for Agentic AI Day at NVIDIA GTC Washington, D.C. on Wednesday, Oct. 29. The event will bring together developers, researchers and technology leaders to highlight how NVIDIA technologies are accelerating national AI priorities and powering the next generation of AI agents.Stay up to date on agentic AI, Nemotron and more by subscribing to NVIDIA developer news, joining the developer community and following NVIDIA AI on LinkedIn, Instagram, X and Facebook.

Todays State of Play marks an exciting milestone for us as we finally shared the release date of our much-anticipated title, Crimson Desert March 19, 2026 and pre-orders are live now.Alongside the announcement, we unveiled a brand-new trailer.Play VideoPreviously, weve offered glimpses of Crimson Deserts gameplay and content, sparking quite a bit of interest in the games freeform combat system and thrilling boss battles. This new trailer shifts the focus to the heart of the journeythe story and motivations of Kliff, Crimson Deserts main protagonist, who you will guide as you explore the vast continent of Pywel.Kliff sets out to reunite his scattered Graymane companions and, in doing so, rally the many forces of Pywel against the evil that threatens the world.But his path will be anything but easy. Simply believing in the right course will not be enoughtrue strength will only be forged by discovering who you truly are.Who are those gathering their strength to stand against the evil? And what is the evil that has been hidden until now?This is the story of Kliff and his fellow Greymane companions, standing united against the forces that seek to tear their world apart. Their journey will lead them through enigmatic places and toward the secrets of the powers that lies hidden across Pywel.Every step will test Kliffs resolvebut he will not walk it alone. With the guidance of trusted allies, wise mentors, and steadfast advisors, Kliff will unlock new abilities to meet the challenges ahead.From ancient mysterious beings to the rise of advanced technologies, Kliffs fate will be shaped by the choices heand youmake.The scenes of this trailer were captured on PlayStation 5 Pro, showcasing the stunning visuals and performance you can expect at launch.The journey youll embark on in Crimson DesertCrimson Desert is an open-world action-adventure set on the continent of Pywel. Youll follow Kliffs journey across a diverse landscapebustling cities, frozen tundra, scorching deserts, rolling grasslands, and dense forests. Along the way, youll encounter the cultures and powers that shape this world, forging alliances or resolving conflicts. Sometimes youll meet new companions, other times youll simply be fulfilling contracts.The world of Crimson Desert is alive with adventure. Missions, quests, and puzzles wait in every corner. Youll find countless ways to explorefrom gliding high above the land to scaling sheer cliffs. And of course, you cant forget about the trusted horses youll be riding with, and many other mounts that youll useeven mighty dragons.And at the core of Crimson Desert is the dynamic and intense combat that will get your heart racing. With freeform controls and a wide array of weapons, you can create creative combos that suit your style and exploit your enemies weaknesses.Beyond combat, Pywel offers a wealth of other content, such as cooking, mining, gathering, fishing, and crafting, all meant to enrich your experience of this world.Explore the vast and beautiful Pywel continent and discover these new adventures and stories.Available on PlayStation 5On PlayStation 5, you can fully immerse yourself in Crimson Desert thanks to faster loading speeds, enhanced graphics, 3D audio, and DualSense haptic feedback. Youll be able to vividly feel the heft of wielding a weapon, the shaking of the impact of your horses hooves, and even the movement of the wind.Our goal has always been to create not just a game, but a living world you can truly immerse yourself in and experience. Between now and launch, well be dedicating our efforts to the final touches, ensuring Crimson Desert arrives as polished and unforgettable as possible. With the release date set and pre-orders now open, the countdown has officially begun.Exclusive pre-order items and deluxe packCrimson Desert will be releasing on March 19, 2026, and you can pre-order now on PlayStation Store. Players who pre-order will receive the exclusive pre-order in-game item, the Khaled Shield, and PS5 pre-order exclusive items, the Grotevant Plate Set (Helm, Armor, Cloak, Gloves, Boots). The Deluxe Edition includes the Kairos Plate Set (Helm, Armor, Cloak, Gloves, Boots), Exclaire set for your steed (Champron, Barding, Saddle, Stirrups) and a Balgran Shield.On March 19, 2026, the gates to Pywel will openand your adventure will begin. Well see you in Pywel!

Over the last few years, I've watched gamers try to predict the death of Xbox like radical Christians warning the world of the rapture. I've never bought into the doomsaying. Microsoft's gaming strategy was surely shifting as it locked into a subscription service strategy with Game Pass, but Xbox felt like it was still here to stay. Even when the company began flirting with porting its first-party games to competing consoles, I still just saw it as a modern strategy built to get the most money possible out of its most expensive productions or to find greater audiences for niche games like Pentiment.

Traditional personas suck for UX work. They obsess over marketing metrics like age, income, and job titles while missing what actually matters in design: what people are trying to accomplish. Functional personas, on the other hand, focus on what people are trying to do, not who they are on paper. With a simple AIassisted workflow, you can build and maintain personas that actually guide design, content, and conversion decisions.Keep users front of mind with taskdriven personas,Skip fragile demographics; center on goals, questions, and blockers,Use AI to process your messy inputs fast and fill research gaps,Validate lightly, ship confidently, and keep them updated.In this article, I want to breathe new life into a stale UX asset.For too long, personas have been something that many of us just created, despite the considerable work that goes into them, only to find they have limited usefulness.I know that many of you may have given up on them entirely, but I am hoping in this post to encourage you that it is possible to create truly useful personas in a lightweight way.Why Personas Still MatterPersonas give you a shared lens. When everyone uses the same reference point, you cut debate and make better calls. For UX designers, developers, and digital teams, that shared lens keeps you from designing in silos and helps you prioritize work that genuinely improves the experience.I use personas as a quick test: Would this change help this user complete their task faster, with fewer doubts? If the answer is no (or a shrug), its probably a sign the idea isnt worth pursuing.From Demographics To FunctionTraditional personas tell you someones age, job title, or favorite brand. That makes a nice poster, but it rarely changes design or copy.Functional personas flip the script. They describe:Goals & tasks: What the person is here to achieve.Questions & objections: What they need to know before they act.Touchpoints: How the person interacts with the organization.Service gaps: How the company might be letting this persona down.When you center on tasks and friction, you get direct lines from user needs to UI decisions, content, and conversion paths. But remember, this list isnt set in stone adapt it to whats actually useful in your specific situation.One of the biggest problems with traditional personas was following a rigid template regardless of whether it made sense for your project. We must not fall into that same mistake with functional personas.The Benefits of Functional PersonasFor small startups, functional personas reduce wasted effort. For enterprise teams, they keep sprawling projects grounded in what matters most. However, because of the way we are going to produce our personas, they provide certain benefits in either case:Lighten the load: Theyre easier to update without large research cycles.Stay current: Because they are easy to produce, we can update them more often.Tie to outcomes: Tasks, objections, and proof points map straight to funnels, flows, and product decisions.We can deliver these benefits because we are going to use AI to help us, rather than carrying out a lot of time-consuming new research.How AI Helps Us Get ThereOf course, doing fresh research is always preferable. But in many cases, it is not feasible due to time or budget constraints. I would argue that using AI to help us create personas based on existing assets is preferable to having no focus on user attention at all.AI tools can chew through the inputs you already have (surveys, analytics, chat logs, reviews) and surface patterns you can act on. They also help you scan public conversations around your product category to fill gaps. I therefore recommend using AI to:Synthesize inputs: Turn scattered notes into clean themes.Spot segments by need: Group people by jobstobedone, not demographics.Draft quickly: Produce firstpass personas and sample journeys in minutes.Iterate with stakeholders: Update on the fly as you get feedback.AI doesnt remove the need for traditional research. Rather, it is a way of extracting more value from the scattered insights into users that already exist within an organization or online.The WorkflowHeres how to move from scattered inputs to usable personas. Each step builds on the last, so treat it as a cycle you can repeat as projects evolve.1. Set Up A Dedicated WorkspaceCreate a dedicated space within your AI tool for this work. Most AI platforms offer project management features that let you organize files and conversations:In ChatGPT and Claude, use Projects to store context and instructions.In Perplexity, Gemini and CoPilot similar functionality is referred to as Spaces.This project space becomes your central repository where all uploaded documents, research data, and generated personas live together. The AI will maintain context between sessions, so you wont have to re-upload materials each time you iterate. This structured approach makes your workflow more efficient and helps the AI deliver more consistent results.2. Write Clear InstructionsNext, you can brief your AI project so that it understands what it wants from you. For example:Act as a user researcher. Create realistic, functional personas using the project files and public research. Segment by needs, tasks, questions, pain points, and goals. Show your reasoning.Asking for a rationale gives you a paper trail you can defend to stakeholders.3. Upload What Youve Got (Even If Its Messy)This is where things get really powerful. Upload everything (and I mean everything) you can put your hands on relating to the user. Old surveys, past personas, analytics screenshots, FAQs, support tickets, review snippets; dump them all in. The more varied the sources, the stronger the triangulation.4. Run Focused External ResearchOnce you have done that, you can supplement that data by getting AI to carry out deep research about your brand. Have AI scan recent (I often focus on the last year) public conversations for your brand, product space, or competitors. Look for:Whos talking and what theyre trying to do;Common questions and blockers;Phrases people use (great for copywriting).Save the report you get back into your project.5. Propose Segments By NeedOnce you have done that, ask AI to suggest segments based on tasks and friction points (not demographics). Push back until each segment is distinct, observable, and actionable. If two would behave the same way in your flow, merge them.This takes a little bit of trial and error and is where your experience really comes into play. 6. Generate Draft PersonasNow you have your segments, the next step is to draft your personas. Use a simple template so the document is read and used. If your personas become too complicated, people will not read them. Each persona should:State goals and tasks,List objections and blockers,Highlight pain points,Show touchpoints,Identify service gaps.Below is a sample template you can work with:# Persona Title: e.g. Savvy Shopper- Person's Name: e.g. John Smith.- Age: e.g. 24- Job: e.g. Social Media Manager"A quote that sums up the persona's general attitude"## Primary GoalWhat theyre here to achieve (12 lines).## Key Tasks Task 1 Task 2 Task 3## Questions & Objections What do they need to know before they act? What might make them hesitate?## Pain Points Where do they get stuck? What feels risky, slow, or confusing?## Touchpoints What channels are they most commonly interacting with?## Service Gaps How is the organization currently failing this persona?Remember, you should customize this to reflect what will prove useful within your organization.7. ValidateIt is important to validate that what the AI has produced is realistic. Obviously, no persona is a true representation as it is a snapshot in time of a Hypothetical user. However, we do want it to be as accurate as possible. Share your drafts with colleagues who interact regularly with real users people in support cells or research teams. Where possible, test with a handful of users. Then cut anything that you cant defend or correct any errors that are identified.Troubleshooting & GuardrailsAs you work through the above process, you will encounter problems. Here are common pitfalls and how to avoid them:Too many personas?Merge until each one changes a design or copy decision. Three strong personas beat seven weak ones.Stakeholder wants demographics?Only include details that affect behavior. Otherwise, leave them out. Suggest separate personas for other functions (such as marketing).AI hallucinations?Always ask for a rationale or sources. Crosscheck with your own data and customerfacing teams.Not enough data?Mark assumptions clearly, then validate with quick interviews, surveys, or usability tests.Making Personas Useful In PracticeThe most important thing to remember is to actually use your personas once theyve been created. They can easily become forgotten PDFs rather than active tools. Instead, personas should shape your work and be referenced regularly. Here are some ways you can put personas to work:Navigation & IA: Structure menus by top tasks.Content & Proof: Map objections to FAQs, case studies, and microcopy.Flows & UI: Streamline steps to match how people think.Conversion: Match CTAs to personas readiness, goals, and pain points.Measurement: Track KPIs that map to personas, not vanity metrics.With this approach, personas evolve from static deliverables into dynamic reference points your whole team can rely on.Keep Them AliveTreat personas as a living toolkit. Schedule a refresh every quarter or after major product changes. Rerun the research pass, regenerate summaries, and archive outdated assumptions. The goal isnt perfection; its keeping them relevant enough to guide decisions.Bottom LineFunctional personas are faster to build, easier to maintain, and better aligned with real user behavior. By combining AIs speed with human judgment, you can create personas that dont just sit in a slide deck; they actively shape better products, clearer interfaces, and smoother experiences.

There is something about the weight of an object that gives it depth. As humans, we are intrinsically drawn to metals, gems, and stones for their beauty, rich expanse of color, and intricate detailing.The Little Lebow table lamp from Fatboy, designed by Dutch design duo Kranen/Gille, taps into that same instinct. Crafted from cast aluminum and coated steel components, it feels reassuringly solid, yet its form evokes a lily-of-the-valley likeness organic, approachable, and quietly playful.More than just a pretty face, the Little Lebow is smartly engineered. Each lamp head is both dimmable and rotatable, giving you total control over direction and brightness. Whether youre reading late into the night, powering through work, or simply creating a cozy atmosphere, the lamp adjusts effortlessly to your needs. It even remembers your last light setting, so the next time you switch it on, the ambiance is already set.Practical touches elevate it further: a generous 180cm braided cord (always color-matched to the lamp), an anti-slip base that keeps it steady, and replaceable bulbs that make it built for the long haul. Plug it in, twist the dimmer, and youve got instant ambiance whether a subtle glow or spotlight precision.Design-wise, the lamp straddles the line between refined and fun, available in four finishes: Anthracite (inky charcoal), Bone (a cool cream), Cobalt Blue (bold and striking), and Grasshopper Green (a lively grassy hue with a blue undertone that pairs beautifully with warm-toned woods). Its a versatile fit for a desk, side table, credenza, or even an entryway always grounding the space while adding a touch of personality.The Little Lebow has already earned accolades, including the Best of Design Award from leading European magazine Schner Wohnen, recognized for its ability to seamlessly combine style, function, and joy. Its a reminder that good design doesnt just light up a room it elevates it.Fatboy is a Dutch design brand that believes life is too short for boring. From its iconic oversized Fatboy beanbag to a full collection of playful-yet-practical furniture and lighting, the brand has made a global name for itself with its signature red tag and refreshing spirit. With the Little Lebow, Fatboy continues to show that great design can be both functional and fun proof that even everyday objects deserve a spark of play.To learn more about the Little Lebow table lamp by Kranen/Gille for Fatboy (which is available now in Europe and will be available in the United States in the coming months), please visit fatboy.com.Photography courtesy of Fatboy.

Why the better AI gets at conversation, the worse we get at questioning itillustration byauthorHow do we know when to trust what someone tells us? In person conversations give us many subtle cues we might pick up on, but when they happen with AI system designed to sound perfectly human, we lose any sort of frame of reference we mayhave.With every new model, conversational AI sounds more and more genuinely intelligent and human-like, so much so that every day, millions of people chat with these systems as if talking to their most knowledgeable friend.From a design perspective, theyre very successful in the way they feel natural, authoritative and even empathetic, but this very naturalness becomes problematic as it makes it hard to distinguish when outputs are true or simply just plausible.This creates exactly the setup for misplaced trust: trust works best when paired with critical thinking, but the more we rely on these systems, the worse we get at it, ending up in this odd feedback loop thats surprisingly difficult toescape.The illusion of understandingTraditional software is straightforwardclick this button, get that result. AI systems are something else entirely because theyre unpredictable as they can make new decisions based on their training data. If we ask the same question twice we might get completely different wording, reasoning, or even different conclusions eachtime.How this thing thinks and speaks in such human ways, feels like magic to many users. Without understanding whats happening under the hood, its easy to miss that those magical sentences are simply the most statistically probable chain of words, making these systems something closer to a glorified Magic 8Ball.Back in 2022 when ChatGPT opened to public, I was also admittedly mesmerised by it, and after it proved useful in a couple of real-world situations, I started reaching for it more and more, even for simple questions andtasks.Until one day I was struggling with a presentation segment that felt flat compared to the rest and asked Claude for ideas on how to make it more compelling. We came up with a story I could reference, one I was already familiar with, but there was this one detail that felt oddly specific, so I asked for thesource.Part of the conversation with Claude (screenshot byauthor)You can imagine my surprise when Claude casually mentioned it had essentially fabricated that detail for emphasis.How I could have so easily accepted that made-up information genuinely unsettled me and became the catalyst for me to really try and understand what I was playing with. What I didnt know at the time was that this behaviour represents exactly what these systems are designed to do: generate responses that sound right, regardless if theyre actually true ornot.Human-like, but nothumanThe core problem when it comes to building trust in AI is that the end goal of these systems (utility) works directly against the transparency needed to establish genuinetrust.To maximise usefulness, AI needs to feel seamless and naturalnobody wants to talk to a robot, its assistance should be almost invisible. We wouldnt consciously worry about the physics of speech during conversation, so why should we think about AI mechanics? We ask a question, we get ananswer.But healthy scepticism requires transparency, which inevitably introduces friction. We should pause, question, verify, and think critically about the information we receive. We should treat these systems as the sophisticated tools they are rather than all-knowing beings.The biggest players seem to be solving for trust by leaning into illusion rather than transparency.Claude thinking indicator (screenshot by author, Sept2025)One key technique is anthropomorphising the interface through language choices. For example, the many thinking indicators that appear while actually just preparing a response, its a deliberate attempt at building trust. This works brilliantly because these human-like touches make users feel connected and understood.However, giving AI qualities like these thinking indicators, conversational tone, personality, and empathy creates two subtle yet critical problems:#1Giving AI human-like qualities, makes us lose the uncertainty signals that would normally help us detect when something is off. Humans naturally show knowing what they dont know through hesitation, qualifying statements (like I think maybe), or simply by admitting uncertainty. These are very helpful signals that let us know when to be more careful about trusting what someone issaying.AI systems however, rarely do thisthey can sound equally confident whether theyre giving you the population of Tokyo (which they probably know) or making up a detail about a case study (which they definitely dont know). Thats why detecting a mistake or a lie in these cases can be extremely hard.#2On top of this, users are more likely to assume the AI will perform better while feeling a deeper connection to it. So we end up trusting it based on how it feels rather than how well it actuallyworks.The industry calls this trust calibration, which is about finding the right level of trust so that users rely on AI systems appropriately, or in other words, in just the right amount based on what those systems can actually do. This is no easy feat in general, but because AI often sounds confident while being opaque and inconsistent, getting this balance right is extremely challenging.So how are companies currently attempting to solve this calibration problem?The limits of current solutionsAs a solution, theres a lot of talk around explainability. This refers to turning AI systems hidden logic into something humans can make sense of, helping users decide when to trust the output (and more importantly, when not to doso).Yet, this information only appears spontaneously in scenarios like medical or financial advice, or when training data is limited. In more routine interactionsbrainstorming, seeking adviceusers would need to actively prompt the AI to reveal the reasoning (as I had to do withClaude).Imagine constantly interrupting a conversation to ask someone where they heard something. The chat format creates an illusion of natural conversation that ends up discouraging the very critical thinking that explainability is meant toenable.Recognising these challenges, companies implement various other guardrails: refusal behaviours for harmful tasks, contextual warnings for sensitive topics, or straight up restriction of certain capabilities. These aim to prevent automation bias: our tendency to over-rely on automated systems.These guardrails, tho, have significant limitations. Not only are there known workarounds, but they fail to account for how these tools are actually used by millions of people with vastly different backgrounds and technical literacy.The contradiction becomes obvious when you notice where warnings actually appear. ChatGPTs disclaimer that it can make mistakes. Check important info sits right below the input field, yet I wonder how many people actually see it, and of those who do, how many take that advice. After all that effort to anthropomorphise the interface and create connection, a small grey disclaimer hardly feels like genuine transparency.Although tiny, Claudes disclaimer appears more contextually within the last reply provided (screenshot by author, Sept2025)Companies invest heavily in making AI feel more human and trustworthy through conversational interfaces, while simultaneously expecting users to maintain critical distance through small warnings and occasional guardrails. The result is that these become another form of false reassurance allowing companies to claim plausible deniability while essentially paying lip service to transparency andtrust.Scaffolding overcrutchesThis reveals a fundamental flaw in the current approach: theyre asking users to bear the weight of responsible use while providing tools designed to discourage the very scepticism they require. This, not only contradicts established UX principles about designing for your users actual capabilities and contexts, but also ignores how trust is actuallyformed.In fact, trust isnt built through one single intervention, but rather systematically across many touchpoints. So how might we approach this problem differently?Photo by Ricardo Gomez Angel onUnsplashA first step, I believe, would be ditching the seamless approach and rethinking friction. What if, instead of treating transparency as friction to reduce, design treated it as a capability to build upon? Instead of hiding complexity to fast-track utility, interfaces could gradually build users ability to work effectively with AI systemseventually teaching them not only how to use them responsibly, but when to trust them aswell.As a parallel, think scaffolding versus crutches. Current AI systems function more like crutchesthey provide so much support that users become dependent on them. Users lean on AI for answers without developing the skills to evaluate them, and much like actual crutches, this helps in the moment but prevents underlying capabilities (critical thinking, in this case) from getting stronger overtime.Designing transparency as scaffoldingIn a scaffolding model instead, AI systems could be much more flexible and adaptable so to surface transparency and guidance based on the users developing skills and the stakes of the decision.For example, we could imagine having different modes. A learning mode could surface uncertainty more explicitly within responsesalerts prompting users to verify claims the AI cannot back up directly, or inviting users to take answers with a grain of salt. This could happen in expandable sections so as not to intrude on the conversation flow, and as users interact with these components, the interface could gradually reduce explicit prompts while maintaining the underlying safeguards.Quick and dirty explorations of a learning mode (byauthor)For high-stakes decision, the interface could default to maximum transparency, like for example requiring users to verify factual claims with external sources before accessing final outputs. Visual indicators could distinguish between trained knowledge, recent search results, and generated examples, helping users understand where information comesfrom.This approach would treats AI as temporary support that builds user capabilities rather than replacing them, and instead of optimising for immediate task completion, scaffolding design would help fostering long-term competence by helping users develop verification habits and critical thinkingskills.Googles Gemini offers inline tips while images are being generated and then persist them on screen. This type of content is clearly distinguishable from the rest of the conversation and provides useful and contextual information based on the task the user is performing (screenshot by author, Sept2025)A trade-off worthmakingMuch of this goes against conventional product design principles around maximising ease of use. Adding these steps and indicators might seem like deliberate obstacles to user engagement because they are, but thats thepoint.The friction introduced in this case, would serve a different purpose than arbitrary barriersits protective and educational rather than obstructive. If designed mindfully, friction can help users treat AI tools as scaffolding rather than crutches, by developing the judgment skills needed to work safely with thesesystems.That conversation with Claude taught me something crucial about the gap between how these systems are presented and what they actually are. We face a choice between immediate utility while undermining our critical thinking, or building people up rather than making them dependent by accepting some friction as the price of maintaining our ability to think independently. The path forward isnt avoiding AI, but demanding better design that teaches us to use these tools wisely rather than depending on them entirely.Footnotes Im aware that my example here is a pretty silly one compared to the amount of misinformation, bad advice and just factually incorrect tidbits people are potentially exposed to everyday through these interactions. But aha moments work in mysterious waysSuggested reads- Co-constructing intent with AI agents by TenoLiu- The Psychology Of Trust In A World Where Products Keep Breaking Promises by Mehekk Bassi- Designing for control in AI UX by RobChappellBuilding trust in opaque systems was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.

Did you know you can customize Google to filter out garbage? Take these steps for better search results, including adding my work at Lifehacker as a preferred source.It seems like iOS 26 just dropped, and yet, Apple is back at it with another update. As of Monday, iOS 26.1 is officially in beta testing, which means developers and public testers can try out Apple's next update early. "Point updates" like iOS 26.1 are never as feature-filled as the main releases, though 26.1 seems particularly small in scope. Apple seems to have done most of what it planned to do with iOS 26, saving just smaller changes for this upcoming update. Still, there are some interesting new additions in this latest beta, and more could come in subsequent releases. Here's what's new.Apple Music gesturesIf you want to skip a song in Apple Music, you hit the forward button. If you want to get back to the previous song, or restart the current song, you hit the back button. With iOS 26.1, however, you'll have the option to swipe to switch between songs. In the current beta, you can swipe right and left on the Now Playing bar to switch back and forth through your queue. With it, Apple has removed the skip forward button from the Now Playing bar. (The back button wasn't present.) It's a small but cool feature, but one that might take a little time to get used to. This Tweet is currently unavailable. It might be loading or has been removed. Video playback barIn the current version of iOS 26, the video playback bar in the Photos app is flush with the UI. You might love or hate it, but it can be a bit difficult to make it out, depending on the video in question. The play button and mute button, for example, can disappear when iOS can't change their colors to stand out from the background. iOS 26.1 beta 1, however, introduces a new video playback bar that is separate from the UI. It looks good, and is easy to see at all times. Again, a small change, but a smart one. This Tweet is currently unavailable. It might be loading or has been removed. Live Translation languagesLive Translation for AirPods is a fantastic new feature that automatically translates conversations you're having with someone who speaks a language you don't understand. So long as you have an iPhone 15 Pro or newer, as well as AirPods Pro 2, AirPods Pro 3, or AirPods 5 with Active Noise Cancellation, you've been able to try it out since iOS 26's launch. Apple initially rolled out support for French, German, Portuguese (Brazil), and Spanish (Spain), but plans to expand the list in the future. With iOS 26.1, it adds four new options, including:Chinese (Mandarin, simplified)Chinese (Mandarin, traditional)ItalianJapaneseKoreanEight new languages for Apple IntelligenceUsers with an iPhone 15 Pro and newer, listen up: Apple Intelligence supports eight new languages in iOS 26.1. As of this first beta, that includes the following: Chinese (traditional)DanishDutchNorwegianPortuguese (Portugal)SwedishTurkishVietnameseLiquid Glass comes to the Phone's keypadLiquid Glass, Apple's new design language, isn't everywhere in iOS 26. While much of the UI now has a glassy look, some elements still look like iOS 18 and earlier. The Phone app's keypad was one such example: While the app itself is very much changed with this update, switch to the keypad, and it looks the same as ever. That changes with iOS 26.1. The beta brings Liquid Glass to the keypad, which, while consistent with most of iOS 26's design, does reduce the visibility of the keys a bit, especially in light mode. I wouldn't be surprised to see Apple workshop this one a bit. This Tweet is currently unavailable. It might be loading or has been removed. CalendarWhenever you have Calendar in List view in iOS 26.1, you'll see your daily events color-coded by their respective calendars, rather than simply listed against the same white background.References to third-party smartwatch supportIf you have an iPhone, you know the only smartwatch that really works well with it is the Apple Watch. Some watches offer notification support, but most simply don't jive well with iOS. That might be changing in the future. Code within the iOS 26.1 beta references a new "Notification Forwarding" feature, that might allow you to choose a third-party device to send your iPhone alerts to. In addition, an unfinished "AccessoryExtension" option might be the framework that lets you pair a third-party watch to your iPhone.These are just references in code, not something that you can actively test out in the 26.1 beta, but it's worth noting. Apple is experimenting with supporting third-party watches on iOS, though it could just be to appease the EU's "Digital Markets Act."

One of the surprise announcements during Sony's State of Play presentation today was the debut of a literary-themed game titled Chronoscript: The Endless End. It's an action-adventure game with a very cool hand-drawn art aesthetic. Players will navigate the 3-dimensional world of a mysterious manor as well as the 2-dimensional world of illustrated manuscript pages.The trailer mostly focused on those 2D sections, showing combat and platforming and seriously did I mention the very cool hand-drawn art? I would have been interested in this for the visuals alone, but throw in a story about writers and editors and I'm hooked.Perhaps fittingly for this writerly endeavor, the game's publisher is Shueisha, which is a heavyweight in publishing manga, including the popular Shonen Jump. The developer is DeskWorks, and the studio's last project also boasted a lovely, illustrative style. We'll have a little longer to wait before we can dive into the inky world of Chronoscript, however, because this game isn't expected to arrive on the PlayStation 5 until some time in 2026.This article originally appeared on Engadget at https://www.engadget.com/gaming/playstation/check-out-the-intricate-inky-world-of-ps5-game-chronoscript-the-endless-end-221820822.html?src=rss

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