ActuGaming.net Chris Avellone (Star Wars Jedi, Fallout New Vegas) rejoint Republic Games, studio fondé par un ancien de Quantic Dream La dernière fois que l’on avait quitté Chris Avellone, qui a été l’un des piliers […] L'article C

Xbox, Microsoft, gaming devices, Windows, next-gen gaming, multiplatform strategy, gaming hardware, Xbox Series X, video games, Microsoft gaming vision --- In a world where dreams are as fragile as glass, Microsoft has once again stirred the hearts of gamers, igniting a flicker of hope amid the shadows of uncertainty. The recent teaser for the next-gen Xbox and a lineup of new gaming devices...

In early-stage start-ups, the pitch deck is often the first thing investors see. Sometimes, it’s the only thing. And yet, it rarely gets the same attention as the website or the socials. Most decks are pulled together last minute, with slides that feel rushed, messy, or just off. That’s where designers can really make a difference. The deck might seem like just another task, but it’s a chance to work on something strategic early on and help shape how the company is understood. It offers a rare opportunity to collaborate closely with copywriters, strategists and the founders to turn their vision into a clear and convincing story. Founders bring the vision, but more and more, design and brand teams are being asked to shape how that vision is told, and sold. So here are five handy things we’ve learned at SIDE ST for the next time you’re asked to design a deck. Think in context Designers stepping into pitch work should begin by understanding the full picture – who the deck is for, what outcomes it’s meant to drive and how it fits into the broader brand and business context. Their role isn’t just to make things look good, but to prioritise clarity over surface-level aesthetics. It’s about getting into the founders’ mindset, shaping visuals and copy around the message, and connecting with the intended audience. Every decision, from slide hierarchy to image selection, should reinforce the business goals behind the deck. Support the narrative Visuals are more subjective than words, and that’s exactly what gives them power. The right image can suggest an idea, reinforce a value, or subtly shift perception without a single word. Whether it’s hinting at accessibility, signalling innovation, or grounding the product in context, design plays a strategic role in how a company is understood. It gives designers the opportunity to take centre stage in the storytelling, shaping how the company is understood through visual choices. But that influence works both ways. Used thoughtlessly, visuals can distort the story, suggesting the wrong market, implying a different stage of maturity, or confusing people about the product itself. When used with care, they become a powerful design tool to sharpen the narrative and spark interest from the very first slide. Keep it real Stock photos can be tempting. They’re high-quality and easy to drop in, especially when the real images a start-up has can be grainy, unfinished, or simply not there yet. But in early-stage pitch decks, they often work against your client. Instead of supporting the story, they flatten it, and rarely reflect the actual team, product, or context. This is your chance as a designer to lean into what’s real, even if it’s a bit rough. Designers can elevate even scrappy assets with thoughtful framing and treatment, turning rough imagery into a strength. In early-stage storytelling, “real” often resonates more than “perfect.” Pay attention to the format Even if you’re brought in just to design the deck, don’t treat it as a standalone piece. It’s often the first brand touchpoint investors will see—but it won’t be the last. They’ll go on to check the website, scroll through social posts, and form an impression based on how it all fits together. Early-stage startups might not have full brand guidelines in place yet, but that doesn’t mean there’s no need for consistency. In fact, it gives designers a unique opportunity to lay the foundation. A strong, thoughtful deck can help shape the early visual language and give the team something to build on as the brand grows. Before you hit export For designers, the deck isn’t just another deliverable. It’s an early tool that shapes and impacts investor perception, internal alignment and founder confidence. It’s a strategic design moment to influence the trajectory of a company before it’s fully formed. Designers who understand the pressure, pace and uncertainty founders face at this stage are better equipped to deliver work that resonates. This is about more than simply polishing slides, it’s about helping early-stage teams tell a sharper, more human story when it matters most. Maor Ofek is founder of SIDE ST, a brand consultancy that works mainly with start-ups. 

The government has axed a scheme for upgrading energy efficiency in public sector buildings. The Public Sector Decarbonisation Scheme (PSDS) delivered more than £2.5bn in its first three phases for measures such as heat pumps, solar panels, insulation and double glazing, with further funding of nearly £1bn recently announced. But the Department for Energy Security and Net Zero (DESNZ) has told Building Design that the scheme has been dropped after the spending review, leaving uncertainty about how upgrades will be funded when the current phase expires in 2028. Source: UK Government/FlickrEd Miliband’s Department for Energy Security and Net Zero is responsible for the scheme The department said it would set out plans for the period after 2028 in due course. In a post on LinkedIn, Dave Welkin, director of sustainability at Gleeds, said he had waited for the release of the spending review with a “sense of trepidation” and was unable to find mention of public sector decarbonisation when Treasury documents were released. “I hoped because it was already committed in the Budget that its omission wasn’t ominous,” he wrote. Yesterday, he was told by Salix Finance, the non-departmental public body that delivers funding for the scheme, that it was no longer being funded. It comes after the withdrawal of funding for the Low Carbon Skills Fund (LCSF) in May. According to the government’s website, PSDS and LCSF were intended to support the reduction of emissions from public sector buildings by 75% by 2037, compared to a 2017 baseline. “Neither LCSF or PSDS were perfect by any means, but they did provide a vital source of funding for local authorities, hospitals, schools and many other public sector organisations to save energy, carbon and money,” Welkin said. “PSDS has helped replace failed heating systems in schools, keeping students warm. It’s replaced roofs on hospitals, helping patients recover from illness. It’s replaced windows in our prisons, improving security and stopping drugs getting behind bars.” However, responding to Welkin’s post, Steve Connolly, chief executive at Arriba Technologies, a low carbon heating and cooling firm, said that the scheme was being “mismanaged” with a small number of professional services firms “scooping up disproportionately large grants for their clients”. The fourth phase of the scheme was confirmed last September, with allocations confirmed only last month. This latest phase, which covers the financial years between 2025/26 and 2027/28, saw the distribution of £940m across the country. A DESNZ spokesperson said: “Our settlement is about investing in Britain’s renewal to create energy security, sprint to clean power by 2030, encourage investment, create jobs and bring down bills for good. “We will deliver £1bn in current allocations of the Public Sector Decarbonisation Scheme until 2028 and, through Great British Energy, have invested in new rooftop solar power and renewable schemes to lower energy bills for schools and hospitals across the UK. “We want to build on this progress by incentivising the public sector to decarbonise, so they can reap the benefits in lower bills and emissions, sharing best practice across government and exploring the use of repayable finance, where appropriate.” A government assessment of phase 3a and 3b projects identified a number of issues with the scheme, including delays and cost inflation, with more than a tenth being abandoned subsequent to grants being offered. Stakeholders interviewed for the report also identified “difficulties in obtaining skilled contractors and equipment”, especially air source heat pumps. The first come first served approach to awarding funding was also said to be “encouraging applicants to opt for more straightforward projects” and “potentially undermining the achievement of PSDS objective by restricting the opportunity for larger [and] more complex measures which may have delivered greater carbon reduction benefits”. But the consensus among stakeholders and industry representatives interviewed for the report was that the scheme was “currently key to sustaining the existing UK heat pump market” and that it was “seen as vital in enabling many public sector organisations to invest in heat decarbonisation”.

You’ve drawn fifty versions of the same screen — and you still hate every one of them. Begrudgingly, you pick three, show them to your product manager, and hear: “Looks cool, but the idea doesn’t work.” Sound familiar? In this article, I’ll unpack why designers fall into detail work at the wrong moment, examining both process pitfalls and the underlying psychological reasons, as understanding these traps is the first step to overcoming them. I’ll also share tactics I use to climb out of that trap. Reason #1 You’re Afraid To Show Rough Work We designers worship detail. We’re taught that true craft equals razor‑sharp typography, perfect grids, and pixel precision. So the minute a task arrives, we pop open Figma and start polishing long before polish is needed. I’ve skipped the sketch phase more times than I care to admit. I told myself it would be faster, yet I always ended up spending hours producing a tidy mock‑up when a scribbled thumbnail would have sparked a five‑minute chat with my product manager. Rough sketches felt “unprofessional,” so I hid them. The cost? Lost time, wasted energy — and, by the third redo, teammates were quietly wondering if I even understood the brief. The real problem here is the habit: we open Figma and start perfecting the UI before we’ve even solved the problem. So why do we hide these rough sketches? It’s not just a bad habit or plain silly. There are solid psychological reasons behind it. We often just call it perfectionism, but it’s deeper than wanting things neat. Digging into the psychology (like the research by Hewitt and Flett) shows there are a couple of flavors driving this: Socially prescribed perfectionismIt’s that nagging feeling that everyone else expects perfect work from you, which makes showing anything rough feel like walking into the lion’s den. Self-oriented perfectionismWhere you’re the one setting impossibly high standards for yourself, leading to brutal self-criticism if anything looks slightly off. Either way, the result’s the same: showing unfinished work feels wrong, and you miss out on that vital early feedback. Back to the design side, remember that clients rarely see architects’ first pencil sketches, but these sketches still exist; they guide structural choices before the 3D render. Treat your thumbnails the same way — artifacts meant to collapse uncertainty, not portfolio pieces. Once stakeholders see the upside, roughness becomes a badge of speed, not sloppiness. So, the key is to consciously make that shift: Treat early sketches as disposable tools for thinking and actively share them to get feedback faster. Reason #2: You Fix The Symptom, Not The Cause Before tackling any task, we need to understand what business outcome we’re aiming for. Product managers might come to us asking to enlarge the payment button in the shopping cart because users aren’t noticing it. The suggested solution itself isn’t necessarily bad, but before redesigning the button, we should ask, “What data suggests they aren’t noticing it?” Don’t get me wrong, I’m not saying you shouldn’t trust your product manager. On the contrary, these questions help ensure you’re on the same page and working with the same data. From my experience, here are several reasons why users might not be clicking that coveted button: Users don’t understand that this step is for payment. They understand it’s about payment but expect order confirmation first. Due to incorrect translation, users don’t understand what the button means. Lack of trust signals (no security icons, unclear seller information). Unexpected additional costs (hidden fees, shipping) that appear at this stage. Technical issues (inactive button, page freezing). Now, imagine you simply did what the manager suggested. Would you have solved the problem? Hardly. Moreover, the responsibility for the unresolved issue would fall on you, as the interface solution lies within the design domain. The product manager actually did their job correctly by identifying a problem: suspiciously, few users are clicking the button. Psychologically, taking on this bigger role isn’t easy. It means overcoming the fear of making mistakes and the discomfort of exploring unclear problems rather than just doing tasks. This shift means seeing ourselves as partners who create value — even if it means fighting a hesitation to question product managers (which might come from a fear of speaking up or a desire to avoid challenging authority) — and understanding that using our product logic expertise proactively is crucial for modern designers. There’s another critical reason why we, designers, need to be a bit like product managers: the rise of AI. I deliberately used a simple example about enlarging a button, but I’m confident that in the near future, AI will easily handle routine design tasks. This worries me, but at the same time, I’m already gladly stepping into the product manager’s territory: understanding product and business metrics, formulating hypotheses, conducting research, and so on. It might sound like I’m taking work away from PMs, but believe me, they undoubtedly have enough on their plates and are usually more than happy to delegate some responsibilities to designers. Reason #3: You’re Solving The Wrong Problem Before solving anything, ask whether the problem even deserves your attention. During a major home‑screen redesign, our goal was to drive more users into paid services. The initial hypothesis — making service buttons bigger and brighter might help returning users — seemed reasonable enough to test. However, even when A/B tests (a method of comparing two versions of a design to determine which performs better) showed minimal impact, we continued to tweak those buttons. Only later did it click: the home screen isn’t the place to sell; visitors open the app to start, not to buy. We removed that promo block, and nothing broke. Contextual entry points deeper into the journey performed brilliantly. Lesson learned: Without the right context, any visual tweak is lipstick on a pig. Why did we get stuck polishing buttons instead of stopping sooner? It’s easy to get tunnel vision. Psychologically, it’s likely the good old sunk cost fallacy kicking in: we’d already invested time in the buttons, so stopping felt like wasting that effort, even though the data wasn’t promising. It’s just easier to keep fiddling with something familiar than to admit we need a new plan. Perhaps the simple question I should have asked myself when results stalled was: “Are we optimizing the right thing or just polishing something that fundamentally doesn’t fit the user’s primary goal here?” That alone might have saved hours. Reason #4: You’re Drowning In Unactionable Feedback We all discuss our work with colleagues. But here’s a crucial point: what kind of question do you pose to kick off that discussion? If your go-to is “What do you think?” well, that question might lead you down a rabbit hole of personal opinions rather than actionable insights. While experienced colleagues will cut through the noise, others, unsure what to evaluate, might comment on anything and everything — fonts, button colors, even when you desperately need to discuss a user flow. What matters here are two things: The question you ask, The context you give. That means clearly stating the problem, what you’ve learned, and how your idea aims to fix it. For instance: “The problem is our payment conversion rate has dropped by X%. I’ve interviewed users and found they abandon payment because they don’t understand how the total amount is calculated. My solution is to show a detailed cost breakdown. Do you think this actually solves the problem for them?” Here, you’ve stated the problem (conversion drop), shared your insight (user confusion), explained your solution (cost breakdown), and asked a direct question. It’s even better if you prepare a list of specific sub-questions. For instance: “Are all items in the cost breakdown clear?” or “Does the placement of this breakdown feel intuitive within the payment flow?” Another good habit is to keep your rough sketches and previous iterations handy. Some of your colleagues’ suggestions might be things you’ve already tried. It’s great if you can discuss them immediately to either revisit those ideas or definitively set them aside. I’m not a psychologist, but experience tells me that, psychologically, the reluctance to be this specific often stems from a fear of our solution being rejected. We tend to internalize feedback: a seemingly innocent comment like, “Have you considered other ways to organize this section?” or “Perhaps explore a different structure for this part?” can instantly morph in our minds into “You completely messed up the structure. You’re a bad designer.” Imposter syndrome, in all its glory. So, to wrap up this point, here are two recommendations: Prepare for every design discussion.A couple of focused questions will yield far more valuable input than a vague “So, what do you think?”. Actively work on separating feedback on your design from your self-worth.If a mistake is pointed out, acknowledge it, learn from it, and you’ll be less likely to repeat it. This is often easier said than done. For me, it took years of working with a psychotherapist. If you struggle with this, I sincerely wish you strength in overcoming it. Reason #5 You’re Just Tired Sometimes, the issue isn’t strategic at all — it’s fatigue. Fussing over icon corners can feel like a cozy bunker when your brain is fried. There’s a name for this: decision fatigue. Basically, your brain’s battery for hard thinking is low, so it hides out in the easy, comfy zone of pixel-pushing. A striking example comes from a New York Times article titled “Do You Suffer From Decision Fatigue?.” It described how judges deciding on release requests were far more likely to grant release early in the day (about 70% of cases) compared to late in the day (less than 10%) simply because their decision-making energy was depleted. Luckily, designers rarely hold someone’s freedom in their hands, but the example dramatically shows how fatigue can impact our judgment and productivity. What helps here: Swap tasks.Trade tickets with another designer; novelty resets your focus. Talk to another designer.If NDA permits, ask peers outside the team for a sanity check. Step away.Even a ten‑minute walk can do more than a double‑shot espresso. By the way, I came up with these ideas while walking around my office. I was lucky to work near a river, and those short walks quickly turned into a helpful habit. And one more trick that helps me snap out of detail mode early: if I catch myself making around 20 little tweaks — changing font weight, color, border radius — I just stop. Over time, it turned into a habit. I have a similar one with Instagram: by the third reel, my brain quietly asks, “Wait, weren’t we working?” Funny how that kind of nudge saves a ton of time. Four Steps I Use to Avoid Drowning In Detail Knowing these potential traps, here’s the practical process I use to stay on track: 1. Define the Core Problem & Business Goal Before anything, dig deep: what’s the actual problem we’re solving, not just the requested task or a surface-level symptom? Ask ‘why’ repeatedly. What user pain or business need are we addressing? Then, state the clear business goal: “What metric am I moving, and do we have data to prove this is the right lever?” If retention is the goal, decide whether push reminders, gamification, or personalised content is the best route. The wrong lever, or tackling a symptom instead of the cause, dooms everything downstream. 2. Choose the Mechanic (Solution Principle) Once the core problem and goal are clear, lock the solution principle or ‘mechanic’ first. Going with a game layer? Decide if it’s leaderboards, streaks, or badges. Write it down. Then move on. No UI yet. This keeps the focus high-level before diving into pixels. 3. Wireframe the Flow & Get Focused Feedback Now open Figma. Map screens, layout, and transitions. Boxes and arrows are enough. Keep the fidelity low so the discussion stays on the flow, not colour. Crucially, when you share these early wires, ask specific questions and provide clear context (as discussed in ‘Reason #4’) to get actionable feedback, not just vague opinions. 4. Polish the Visuals (Mindfully) I only let myself tweak grids, type scales, and shadows after the flow is validated. If progress stalls, or before a major polish effort, I surface the work in a design critique — again using targeted questions and clear context — instead of hiding in version 47. This ensures detailing serves the now-validated solution. Even for something as small as a single button, running these four checkpoints takes about ten minutes and saves hours of decorative dithering. Wrapping Up Next time you feel the pull to vanish into mock‑ups before the problem is nailed down, pause and ask what you might be avoiding. Yes, that can expose an uncomfortable truth. But pausing to ask what you might be avoiding — maybe the fuzzy core problem, or just asking for tough feedback — gives you the power to face the real issue head-on. It keeps the project focused on solving the right problem, not just perfecting a flawed solution. Attention to detail is a superpower when used at the right moment. Obsessing over pixels too soon, though, is a bad habit and a warning light telling us the process needs a rethink.

The Inefficiency of Static Chain-of-Thought Reasoning in LRMs Recent LRMs achieve top performance by using detailed CoT reasoning to solve complex tasks. However, many simple tasks they handle could be solved by smaller models with fewer tokens, making such elaborate reasoning unnecessary. This echoes human thinking, where we use fast, intuitive responses for easy problems and slower, analytical thinking for complex ones. While LRMs mimic slow, logical reasoning, they generate significantly longer outputs, thereby increasing computational cost. Current methods for reducing reasoning steps lack flexibility, limiting models to a single fixed reasoning style. There is a growing need for adaptive reasoning that adjusts effort according to task difficulty.  Limitations of Existing Training-Based and Training-Free Approaches Recent research on improving reasoning efficiency in LRMs can be categorized into two main areas: training-based and training-free methods. Training strategies often use reinforcement learning or fine-tuning to limit token usage or adjust reasoning depth, but they tend to follow fixed patterns without flexibility. Training-free approaches utilize prompt engineering or pattern detection to shorten outputs during inference; however, they also lack adaptability. More recent work focuses on variable-length reasoning, where models adjust reasoning depth based on task complexity. Others study “overthinking,” where models over-reason unnecessarily. However, few methods enable dynamic switching between quick and thorough reasoning—something this paper addresses directly.  Introducing OThink-R1: Dynamic Fast/Slow Reasoning Framework Researchers from Zhejiang University and OPPO have developed OThink-R1, a new approach that enables LRMs to switch between fast and slow thinking smartly, much like humans do. By analyzing reasoning patterns, they identified which steps are essential and which are redundant. With help from another model acting as a judge, they trained LRMs to adapt their reasoning style based on task complexity. Their method reduces unnecessary reasoning by over 23% without losing accuracy. Using a loss function and fine-tuned datasets, OThink-R1 outperforms previous models in both efficiency and performance on various math and question-answering tasks.  System Architecture: Reasoning Pruning and Dual-Reference Optimization The OThink-R1 framework helps LRMs dynamically switch between fast and slow thinking. First, it identifies when LRMs include unnecessary reasoning, like overexplaining or double-checking, versus when detailed steps are truly essential. Using this, it builds a curated training dataset by pruning redundant reasoning and retaining valuable logic. Then, during fine-tuning, a special loss function balances both reasoning styles. This dual-reference loss compares the model’s outputs with both fast and slow thinking variants, encouraging flexibility. As a result, OThink-R1 can adaptively choose the most efficient reasoning path for each problem while preserving accuracy and logical depth.  Empirical Evaluation and Comparative Performance The OThink-R1 model was tested on simpler QA and math tasks to evaluate its ability to switch between fast and slow reasoning. Using datasets like OpenBookQA, CommonsenseQA, ASDIV, and GSM8K, the model demonstrated strong performance, generating fewer tokens while maintaining or improving accuracy. Compared to baselines such as NoThinking and DualFormer, OThink-R1 demonstrated a better balance between efficiency and effectiveness. Ablation studies confirmed the importance of pruning, KL constraints, and LLM-Judge in achieving optimal results. A case study illustrated that unnecessary reasoning can lead to overthinking and reduced accuracy, highlighting OThink-R1’s strength in adaptive reasoning.  Conclusion: Towards Scalable and Efficient Hybrid Reasoning Systems In conclusion, OThink-R1 is a large reasoning model that adaptively switches between fast and slow thinking modes to improve both efficiency and performance. It addresses the issue of unnecessarily complex reasoning in large models by analyzing and classifying reasoning steps as either essential or redundant. By pruning the redundant ones while maintaining logical accuracy, OThink-R1 reduces unnecessary computation. It also introduces a dual-reference KL-divergence loss to strengthen hybrid reasoning. Tested on math and QA tasks, it cuts down reasoning redundancy by 23% without sacrificing accuracy, showing promise for building more adaptive, scalable, and efficient AI reasoning systems in the future.  Check out the Paper and GitHub Page. All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 100k+ ML SubReddit and Subscribe to our Newsletter. Sana HassanSana Hassan, a consulting intern at Marktechpost and dual-degree student at IIT Madras, is passionate about applying technology and AI to address real-world challenges. 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