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🧠 New ability coming soon: Concentration This skill lets the pilot resist high G-forces for a longer time. While active, the jet can hold maximum overload without blackout — but the pilot’s vision becomes narrower and less clear. #Multiplayer #JetFighters #OnlineGaming #unity3d #madewithunity #gamedev #indiegames #indiegamehour #IndieGameDev #screenshotsaturday #gamedevelopment #gamedesign

15,282 görüntüleme • 8 ay önce •via X (Twitter)

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MIT’s latest research just just gave Robots a great new skill to grip delicate yet heavy objects without breaking them. The big problem is robots often cannot pick up heavy but fragile things because gripping hard enough usually means crushing or slipping. A single gripper shape has to do 2 conflicting jobs, it must move freely to form a wrap, then resist big forces while staying gentle. Open-ended grippers can snake into place, but they usually need stiffness to hold, and stiffness puts load into a few high-pressure contact points. Very soft grippers spread pressure well, but they can buckle or slide when the object is heavy, so they fail at the holding stage. This new idea from MIT, called loop closure grasping, completely avoids that tradeoff. Loop closure grasping starts as an open loop, meaning the robot has a free tip that can snake around clutter and find a good wrap. Once the wrap is right, the tip locks back onto the base, turning the shape into a closed loop that surrounds the object. Now the load is carried mainly by tension, like a sling, so the loop can stay very floppy in bending and still hold strongly without pointy pressure. The prototype uses inflatable “vine” beams that grow from the tip, then a clamp and winch to fasten, tighten, and finally deflate for soft holding. That combo lets it do awkward grasps, like lifting a 6.8kg kettlebell from a cluttered bin or pulling an object from 3m away. --- Paper - science. org/doi/10.1126/sciadv.ady9581

Rohan Paul

1,632,855 görüntüleme • 8 ay önce

We're only year 3 of a decade (if not multi-decades) long transformation of work. 3 years ago we bet on building an horizontal platform for work with agents, a chance to invent a new operating system for companies, from scratch, with AI as a fundamental premise. Many people considered us crazy for going after that, praising verticalized AI products as the winning strategy. But here's the thing: the time horizon of tasks successfully handled by agents has been predictively increasing form minutes to hours and will in all likelihood reach the equivalent of days and weeks of human work equivalent in the coming quarters. This is were verticalized and/or single-player AI falls short. Single-player tools, one person, one agent, confined to your machine is the wrong architecture for what's coming. We're shifting from using AI to produce things, to managing fleets of agents that do the producing. 3 years ago I wrote[1]: "ChatGPT is the Pong of LLMs. [...] Imagine, one day we'll get the DOOM, Civ, Red Alert, and Counter Strike of LLMs. Let alone multiplayer modes." Weeks long tasks in companies are inherently collaborative and mechanically spanning multiple teams. The new bottleneck in harnessing agents within organizations is coordination: multiple humans and multiple agents need to work together, with shared context, shared tools, shared goals. Agents that can hand work off to other agents or surface decisions to the right person at the right time. Humans who can review, steer, and step in without losing the thread. Teams that can run parallel workstreams and actually stay aligned. This is Multiplayer AI, and that's what we've been building at Dust. Across Datadog, Clay, Persona, 1Password, Doctolib and 3,000+ organizations globally, we've watched teams figure out what this looks like in practice. 300,000+ agents deployed. 70% weekly active. 240%+ NRR. Today we're announcing a $40M Series B with Abstract, Sequoia, Snowflake, and Datadog to accelerate our vision. Designing the right interfaces for multiplayer AI is the next frontier. Join us to redefine work by defining multiplayer AI.

Stanislas Polu

1,327,399 görüntüleme • 3 ay önce

We’re living through a strange inversion: the habits most people can adopt are losing status, while the traits few people can change are becoming the new currency of success. Traits that are widely attainable and reliably linked to success seem to be losing cultural status, while traits that are far less within individual control are becoming more prized. By “attainable,” I mean the traditional, middle-class virtues: showing up on time, keeping your word, working hard, exercising discipline, treating others with respect, staying within the law. These are not evenly distributed, but they are broadly accessible. Almost anyone, regardless of background, can improve at them on the margin. You can be a little more punctual. A little more prepared. A little more conscientious. And those marginal improvements compound. By contrast, many of the traits that now seem to carry greater weight are far less malleable. Physical attractiveness has some room for improvement, but there are clear limits. The same is true of cognitive ability. People can develop skills and knowledge, but underlying aptitude is much harder to move. The ceiling is tighter, and the returns to effort are less predictable. What’s striking is not just this shift, but the accompanying change in how we talk about it. The older virtues are increasingly treated with suspicion or even contempt. Suggest that someone might benefit from working harder or being more disciplined, and the response is often defensive or hostile. The implication is that such advice is naive at best, or unfair at worst—that outcomes are driven primarily by forces outside individual control. Some of that critique is valid. Circumstances matter. But if we lose sight of the habits that remain within reach for most people, we risk devaluing the very behaviors that, historically, have offered the most reliable path to upward mobility.

Rob Henderson

38,477 görüntüleme • 4 ay önce

This is big. NVIDIA and Apple just unlocked the next level for Vision Pro with CloudXR. Here’s what you need to know: It streams from a PC or the cloud directly to your Vision Pro. No cables. Up to 4K at 120fps. The technology is called dynamic foveated streaming. Your eyes only see in full resolution at the center of your gaze. CloudXR tracks exactly where you’re looking and delivers maximum resolution there. Everything in your periphery gets optimized. The stream stays efficient without you ever noticing a difference. Why does this matter? Vision Pro is already the most advanced spatial computer ever made. But standalone processing has a ceiling. There are workflows that need more compute than any headset can carry. CloudXR removes that ceiling by connecting Vision Pro to the full power of NVIDIA RTX in real time. This is not a workaround. It is a native visionOS integration. Also worth knowing. Gaze data never leaves your device. Not to the app. Not to the server. Developers get the full performance benefit of foveation without ever touching your raw eye tracking data. Privacy built into the architecture. Three industries are already on this: Kia, Rivian, and Volvo are running 1:1 scale design reviews with photorealistic accuracy. Full size vehicle models evaluated in spatial computing before a physical prototype exists. That is a fundamental shift in how design works. Foxconn is walking factory floors digitally, optimizing facilities before construction begins. Switch is managing data center infrastructure through a full digital twin. Companies using this approach are reporting up to 30% improvement in development processes. And sim enthusiasts finally get to cut the cord. iRacing and X-Plane 12 are the first titles. Full GeForce RTX power, streamed wirelessly to Vision Pro, inside your physical space. For developers: one Xcode template, one codebase, deployed across Vision Pro, iPhone, and iPad. And multiple headsets can share the same streamed environment at once. Some fully immersed, others on a tablet. That collaborative layer is what enterprise has been asking for. Coming this spring with visionOS 26.4. It’s wild to think about what this unlocks. The future of spatial computing is incredibly bright. Live from GTC. More coming soon.

Justin Ryan

43,685 görüntüleme • 5 ay önce

$APP's pivot to e-commerce is a very intriguing strategy. The market perceives the entry of non-gaming advertisers as a potential friction point that could crowd out core gaming clients or inflate pricing, but this ignores the massive asymmetry between AppLovin’s reach of over one billion daily active users and its historically thin roster of active advertisers. This imbalance has meant that the vast amount of inventory were previously under-monetized, as the algorithm could only serve gaming ads to users who had no intent to install new games. By layering in e-commerce demand, the platform effectively monetizes this wasted inventory, driving up overall yield and floor prices without cannibalizing the high-intent impressions reserved for gaming clients. This creates a margin-accretive dynamic where the same unit of supply generates significantly higher revenue per user solely through better demand matching. This efficiency gain feeds directly into a data-driven moat that becomes increasingly difficult for competitors to replicate. The flywheel is the introduction of transactional e-commerce data that radically improves the Axon AI model's predictive capabilities for all participants. Unlike app install data, which is binary and relatively sparse, e-commerce purchase data provides immediate high-fidelity signals about user intent and purchasing power. As the model ingests this new layer of behavioral data, its ability to predict conversion improves universally, meaning that gaming advertisers actually benefit from the presence of e-commerce bids through sharper targeting and higher return on ad spend. The rapid 50% week over week growth in the self-service pilot is a great preliminary validation that this automated demand engine is functional. This signals that AppLovin can scale this new vertical with software operating leverage. The requirement for high-production video ads has left out the long tail of millions of small business advertisers who dominate platforms like $META. The launch of generative AI creative tools targets this specific bottleneck, commoditizing the production of high-performing video assets and allowing AppLovin to unlock global SMB demand instantly. If successful, this creates a self-reinforcing liquidity cycle where increased advertiser density leads to better data, which drives superior model performance, which in turn attracts more diverse advertisers. This helps decouple the company's growth trajectory from the cyclicality of the mobile gaming market. Really interesting biz and great CEO.

CapexAndChill

29,897 görüntüleme • 6 ay önce