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Last week, Google released Project Genie, a powerful new AI-powered platform for videogame design. Project Genie, which is currently only available for Googles AI Ultra subscribers, uses AI to build virtual worlds. That sounds interesting, if not necessarily revolutionary. Videogame developers already model and build virtual worlds all the time. Project Genies simple concept, though, belies the techs potential impact. The new system, and the Genie 3 model behind it, have the potential to forever change how videogames are built and played. Model the World Most videogames today rely on a handful of game engines to render their virtual worlds so they look realistic for players. Engines like Unreal and Unity have long dominated the space. To build a game within them, developers first create virtual spaces, populating them with 3D digital models of objects, characters, buildings and the like. They then release players into their worlds. As a player explores, the game engine renders the currently-visible portions of the virtual world in near real-time, creating the seamless experience of wandering through a realistic environment. Game engines revolutionized game design because they allowed developers to hand off messy and complex things like physics and lighting to the engine. Instead of worrying about modeling how fur moves in a breeze or how fast bullets travel, they could focus on creative jobs like building delightfully scary monsters or realistic weaponry. Game engines come with their own set of limitations, though. Although players are free to explore a world as they please, developers still generally need to create every element of that world themselves. Todays virtual worlds are massive. Players could reportedly spend as many as 130 real-world hours exploring the worlds inside games like No Mans Sky without seeing the same part twice. But even so, everything in that virtual world had to be put there on purpose. The worlds feel huge, but nothing in them is truly new. Worlds on the fly Googles new Project Genie is different. Rather than creating a world piece by piece, the new tool allows developers to upload concept art or even a simple text prompt. Google Genie 3 model, which underlies the system, then transforms those inputs into a seamless, virtual space that players can move within. Crucially, though, Project Genies worlds arent bounded, like the worlds of traditional game engines. Genie 3 imagines its worlds on the fly, literally creating them fresh as a player explores. That means Genies worlds are effectively infinite. As a player reaches the bounds of the world, the Genie 3 model simply expands them, imagining new parts that have never existed before. In an example video, Google shows a developer asking the system for an undersea world. Project Genie spins up a virtual coral reef environment, with the player controlling a realistic-looking fish. As the fish swims around the reef, Project Genie adds new parts seamlessly. As the player-controlled fish swims upwards, the system even creates realistically-shimmery water above the virtual reef. The user could presumably have their fish leap from the ocean into the air, and Project Genie would go right on imagining new parts of the worldperhaps an ocean landscape complete with (hopefully friendly) seagulls, buoys and boats. Truly open worlds Currently, Project Genie has some serious limitations. It can only perform its magic for about 60 seconds at a time, before its imagined worlds go off the rails. Its also limited to 24 frames per secondimpossibly slow for a modern game, where FPS can easily hit 120 on a powerful computer. Practically, this means Project Genies worlds have movement thats too choppy for real world use. Project Genies demo games also lack actual gameplay elements, like rules and goals. You can only swim around as a fish for so long before getting boredeven if the virtual reef around you is being automatically generated by an insanely powerful AI. The bones are there, though. And the implications for the future of gaming are massive. As the Genie 3 model improves, game designers could use it to create worlds that players could explore forever. Each time players loaded a game, theyd be experiencing something completely newand theyd never run out of territory in which to play. Genie 3 could potentially also create bespoke models of a world, tailored to individual players. Imagine playing a game like Grand Theft Auto, but with the action taking place in your hometownwhether you live in Los Angeles or Lincoln, Nebraska. And Genie could create entirely new kinds of gamesones where the player actively participates in building the world. Because Genie can accept prompts and imagery, players could provide input on the places theyd like to explore. Genie could then build them a custom world based on their ideas. Traditional game designers are clearly taking note. The stocks of gaming companies like Nintendo and Roblox promptly dropped when Project Genie was announced. So-called open world gameswhere players explore an environment for hours on end, sometimes without specific goalsare already massively popular. Making those worlds truly open and unbounded using Genie would almost certainly make the games more compellingand better selling. For now, Project Genie is a cool demo. Soon, though, its AI magic could spell disruption for an entire industry.
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E-Commerce
The 2026 Winter Olympic Games kick off in Italy on Friday, with top athletes from across the world competing for not just any prize, but for the most expensive medals in Olympics history. The Milano Cortina-based games come as the value of precious metals have skyrocketed, most notably gold and silver. Gold was worth about $2,500 per ounce when the Paris Summer Olympics took place in 2024. Now, less than two years later, gold sits at just over $4,800 per ounceand even thats a significant drop from its recent record-high of about $5,600 per ounce just last week. Silver averaged around $28 per ounce during the last Olympic games, but is now valued at about $77 per ounce. Again, this is a downturn from a high of over $121 per ounce at the end of January. [Photo: Fondazione Milano Cortina 2026] How much are Olympic medals worth during the 2026 winter games? At time of writing, a rough calculation shows that each gold medal is worth about $2,176up from about $900 in Paris. Meanwhile, a silver medal is valued at about $1,245, based on the metals current worth. Notably, the Olympic gold medals havent been pure gold in over 100 years, as CNN previously reported. Instead, they are now made up of 500 grams of silver and just six grams of gold. The silver medal is solely made of 500 grams of, well, silver. There will be 735 Olympic medals and 411 Paralympic medals awarded during the two events. Each medal is a thickness of just 10 millimeters with an 80 millimeter diameter. Of course, the cost of each medal is more significant for the manufacturer than the recipient (you can learn more about how the Olympic medals are made here). Olympic medals are not commonly sold and, when they are, typically go for a lot more than face value. In January, swimmer Ryan Lochte sold three gold medals for about $385,000, Swimming World reports. Previously, he sold six Olympic medals for $166,000.
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E-Commerce
Large-language models (LLMs) have taken the world by storm, but theyre only one type of underlying AI model. An under-the-radar company, Fundamental, is set to bring a new type of enterprise AI model to the masses: large tabular models, or LTMswhich could have an even bigger impact for businesses. What are LTMs? A major difference between LLMs and LTMs is the type of data theyre able to synthesize and use. LLMs use unstructured datathink text, social media posts, emails, etc. LTMs, on the other hand, can extract information or insights from structured data, which could be contained in tables, for instance. Since many enterprises rely on structured data, often contained in spreadsheets, to run their operations, LTMs could have an immediate use case for many organizations. What does Fundamental do? San Francisco-based Fundamental, founded roughly 18 months ago by CEO Jeremy Fraenkel, has made a public LTM model, NEXUS, which will allow organizations to tap into that data to make predictions and forecasts. The data types in the mix could include customer behavior, information from various sensors, or myriad other thingsbut again, its all locked up in rows and columns. If you look at what LLMs have done with unstructured data, its been amazing. But it only covers 20% of [overall] data, Fraenkel says. Thats the opportunity were going after. Its potentially a big deal, because Fraenkel says that roughly 80% of enterprise data used by companies to make predictions and decisions is structuredmeaning that its on private servers in columns and rows, not really usable by LLMs. You can try things with LLMs, but theyre not really adapted to do it, Fraenkel says. They dont work well with the structured data. They can work with, say, 100,000 rows. But a bank might have tens of billions of rows of data, which can overwhelm the model. Fundamental’s aim is the ability to make better predictions using that structured data. Fundamental is also announcing that its closed a $225 million Series A funding round. The round was led by Oak HC/FT, and included participation from Battery Ventures, Valor Equity Partners, and Salesforce. And it’s already worked out some big partnerships, too. That includes one with Amazon Web Services, meaning AWS customers can buy and deploy NEXUS directly through AWS dashboard, and even make payments using Amazon credit, and its available today. Well be fully integrated with AWS, Fraenkel says. AWS customers will have access to Fundamentals model through their existing contracts, and any company can use it out of the box. Annie Lamont, the founder and managing partner at VC firm Oak HC/FT, which led Fundamentals Series A round, says that at first, she was a little skeptical, but that was soon replaced by excitement as to what the company could be capable of. Werent these LLM companies, with endless capital, going to do this? Theyre not. Theyre different, she says. We knew that LLMs are great with unstructured data, but theres a hole when it comes to structured datawe hadnt heard of anybody solving the problem. Nobody has commercialized [this type of AI model] for enterprise, so they have a good head start, she adds. As for whats ahead? Deployment, adoption, and proliferation, Fundamental hopes. And if LTMs take off as LLMs did, theres a very high ceiling: A few years from now, every Fortune 50 will need to rely on these models to make better business decisions, Fraenkel predicts.
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E-Commerce
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