My name is Esteban Maldonado and I’m a developer advocate for Unity. My job is to spread the word about Unity Gaming Services and create new educational material so developers can get started with the tools for their own multiplayer development journey.One of those solutions is Netcode for GameObjects (NGO), a first-party, mid-level networking library built for the Unity game engine. A netcode solution is essential in any multiplayer development project.One of the responsibilities of a developer advocate at Unity is to create sample games that showcase our tools, and an NGO sample was assigned to me – Galactic Kittens.However, although I’ve had my good share of professional gigs in the games industry, I personally have little experience making multiplayer games – so this was going to prove to be not just a learning opportunity for developers who use the sample, but also a learning experience for me making the game in the first place.Together with my team, we fleshed out the concept of Galactic Kittens – the difficulty level of the sample, the basic mechanics, the character abilities (which were later removed), and more.In order to tackle this sample game project, I joined forces with the talented team at Bromio in order to make this sample game come to life with polished art assets, music and SFX, and programming support. Our combined goal was to provide developers with a simple, beginner-friendly introduction to building a multiplayer game in Unity with Netcode for GameObjects.In this blog, I’ll cover the development journey for Galactic Kittens, from prototype to stable release, and how you can leverage this sample to start your own multiplayer project.Before I dive into its development, here’s a quick overview of our new sample game Galactic Kittens. This sample is a 2D co-op space adventure designed to help you learn some basics of multiplayer networking.The sample is meant to teach you necessary techniques to get started with multiplayer development, such as:Network session management, with automatic scene switchingBasic 2D movement synchronization, including changes in sprite sheetsSpawning game objects at runtime, on server sideTransferring ownership of the main players from the server to its clientVFX creation across all connected clientsHow to play sound effects and music to all clientsCommunicating player and game stats (health, enemies defeated, etc.) and displaying them on the game’s UIYou can learn more about Galactic Kittens on our website, or download the sample directly from GitHub to get started exploring the code.While I didn’t have too much experience making multiplayer games, Unity does have many public resources to help users get started with using NGO.With these resources, I started very simply by familiarizing myself with basic network concepts and terminology, using our Unity Multiplayer documentation. Next, I followed the Hello World project tutorials and studied available bitesize samples to start getting some results.After some trial and error, I was able to make a simple base prototype from scratch.At this point, there was no custom lobby, no real UI, no real connection management – you get the picture. The prototype was just two equal ships (with three Hit Points each) that moved around the screen and shot a cube bullet when you pressed the spacebar. It was just enough to show object spawning and movement synchronization across clients.It was a start, but I knew that Bromio would help us reach the finish line and turn this into a workable sample.After my initial progress, I started working with Bromio on fleshing out the prototype into something more production-ready. Like me, they did not have much experience making multiplayer games, but they took on the challenge and helped us reach our goal.In order to work more efficiently, we broke down the game into isolated components to start development in parallel – with artists working on assets and programmers working on the core logic of the game.Here’s a peak at the evolution of the art style in Galactic Kittens.Meanwhile, Bromio’s main developer and I were discovering fun and challenging aspects of making Galactic Kittens into a functioning game sample.One of the biggest challenges in development was connection management and character selection. We had to store the data of the characters in separate ScriptableObject files, which you will see when you download the project.These files contain the necessary information about each space explorer, including which sprites (player and ship) to show on the UI and the prefabs that should be spawned for each player once the gameplay scene starts.On the character selection screen, a big challenge was to make sure to acknowledge the event of a client disconnecting and to handle that event through the UI.We decided that users should not be able to pick the same character, in order to show how developers could actually do this in their own games. (It's actually easier to let players pick the same character since there’s no additional restriction.)The next challenge for connection management was the event of players disconnecting in the middle of a game session. This meant not only that the game had to adapt to players leaving, but also had to block other players from entering while a game is in session. We decided to make the connection manager only allow for new connections to come in while the host instance is on the character selection screen. This is not a one-size-fits-all solution – other games may allow for players to join late in an ongoing session, while other games may not – it’s up to developers to decide what’s best for their experience.We wanted to keep gameplay simple, with no complex AI or fancy behavior logic for the enemies or meteorites that players see. This way, we could provide a full game sample without taking away focus from showing users how to use the NGO library.As such, there are two main types of enemies and one meteorite obstacle: Space Shooter Space Ghost MeteoriteBoth enemies choose a random movement pattern, while the Space Shooter enemy is the only one that actually shoots back enemy lasers. Please refer to ourdeveloper guide for more information on how these enemies are built and how you can add your own logic.By the time we worked on the boss battle, all of the lessons learned from implementing the game’s lobby, player spaceship behavior, and simple enemies helped us to quickly build the final boss battle experience.One particular challenge was timing the warning alarm that you hear and see before the boss enters. In the end, we sent events with client and server RPCs in order to signal that the regular play experience was over and the final boss battle was about to begin.The behavior of the boss is structured as a finite state machine (FSM) that randomly selects which set of attacks to throw at the connected players. To do this, we used a C# class called BossController, which handles the transition from one boss state to another. Check the developer guide for information about the code behind this battle, and how you can add your own boss states.The #1 resource that helped us succeed in our mission to build this sample game was joining the Unity Multiplayer Networking Discord server and asking questions to the community. Here, we were able to actually speak with other developers who are making multiplayer games and also speak with Unity multiplayer service creators. The collective pool of knowledge was more than enough to help us reach the finish line.Working at Unity means I get to collaborate alongside networking savvy people who work hard to develop helpful resources and documentation that’s designed to assist everyone get started with multiplayer development. The Unity multiplayer documentation site came in handy many times – from familiarizing myself with basic networking terminology to dealing with latency to actually coding with NGO.We're definitely excited about Galactic Kittens. We’d like for you, and future NGO users, to use this sample as a step in the right direction toward your multiplayer learning journey. Please feel free to reach out in the Discord server or forums to ask questions or provide feedback and suggestions.One of the things I’m eager to learn is how to add object pooling to a multiplayer game sample. This is the technique that lets you pre-allocate the necessary memory for objects that get spawned repeatedly during a game session. In an earlier experiment, I tried this technique in an offline Unity project and it can definitely make an improvement to your game’s run-time efficiency. We’ve applied this technique to Boss Room and other UGS samples as well.If you’re starting out on your own multiplayer journey, then there are a lot of resources that my team at Unity provides to help make it easier for you.I would recommend starting at the Netcode for GameObjects page, where you can familiarize yourself with the package. Next, you can explore NGO through the Galactic Kittenssample or take small steps with bitesize samples.Once you’re on your journey, I recommend joining the Unity Multiplayer Networking Discord server and checking out the forums. And, if you feel like Galactic Kittens is too simple or not enough of a challenge, I would definitely encourage you to check out Boss Room, which is a complete 3D sample game that takes NGO development to a production-ready level.For taking your game online, Unity Gaming Services can help you even further – whether you’re looking to add the Lobby or Matchmaker services, voice and text chat with Vivox, or even hosting solutions like the P2P Relay service or Game Server Hosting. Happy creating!To find out more about recent trends and the future of multiplayer, read the 2022 Unity Multiplayer Report, which aggregates the results of over 1,500 survey responses across the US, UK, Japan, and Korea.

"Artificial intelligence, if we're being frank, is a con: a bill of goods you are being sold to line someone's pockets."That is the heart of the argument that linguist Emily Bender and sociologist Alex Hanna make in their new book The AI Con. It's a useful guide for anyone whose life has intersected with technologies sold as artificial intelligence and anyone who's questioned their real usefulness, which is most of us. Bender is a professor at the University of Washington who was named one of Time magazine's most influential people in artificial intelligence, and Hanna is the director of research at the nonprofit Distributed AI Research Institute and a former member of the ethical AI team at Google.The explosion of ChatGPT in late 2022 kicked off a new hype cycle in AI. Hype, as the authors define it, is the "aggrandizement" of technology that you are convinced you need to buy or invest in "lest you miss out on entertainment or pleasure, monetary reward, return on investment, or market share." But it's not the first time, nor likely the last, that scholars, government leaders and regular people have been intrigued and worried by the idea of machine learning and AI.Bender and Hanna trace the roots of machine learning back to the 1950s, to when mathematician John McCarthy coined the term artificial intelligence. It was in an era when the United States was looking to fund projects that would help the country gain any kind of edge on the Soviets militarily, ideologically and technologically. "It didn't spring whole cloth out of Zeus's head or anything. This has a longer history," Hanna said in an interview with CNET. "It's certainly not the first hype cycle with, quote, unquote, AI."Today's hype cycle is propelled by the billions of dollars of venture capital investment into startups like OpenAI and the tech giants like Meta, Google and Microsoft pouring billions of dollars into AI research and development. The result is clear, with all the newest phones, laptops and software updates drenched in AI-washing. And there are no signs that AI research and development will slow down, thanks in part to a growing motivation to beat China in AI development. Not the first hype cycle indeed.Of course, generative AI in 2025 is much more advanced than the Eliza psychotherapy chatbot that first enraptured scientists in the 1970s. Today's business leaders and workers are inundated with hype, with a heavy dose of FOMO and seemingly complex but often misused jargon. Listening to tech leaders and AI enthusiasts, it might seem like AI will take your job to save your company money. But the authors argue that neither is wholly likely, which is one reason why it's important to recognize and break through the hype.So how do we recognize AI hype? These are a few telltale signs, according to Bender and Hanna, that we share below. The authors outline more questions to ask and strategies for AI hype busting in their book, which is out now in the US.Watch out for language that humanizes AIAnthropomorphizing, or the process of giving an inanimate object human-like characteristics or qualities, is a big part of building AI hype. An example of this kind of language can be found when AI companies say their chatbots can now "see" and "think."These can be useful comparisons when trying to describe the ability of new object-identifying AI programs or deep-reasoning AI models, but they can also be misleading. AI chatbots aren't capable of seeing of thinking because they don't have brains. Even the idea of neural nets, Hanna noted in our interview and in the book, is based on human understanding of neurons from the 1950s, not actually how neurons work, but it can fool us into believing there's a brain behind the machine.That belief is something we're predisposed to because of how we as humans process language. We're conditioned to imagine that there is a mind behind the text we see, even when we know it's generated by AI, Bender said. "We interpret language by developing a model in our minds of who the speaker was," Bender added.In these models, we use our knowledge of the person speaking to create meaning, not just using the meaning of the words they say. "So when we encounter synthetic text extruded from something like ChatGPT, we're going to do the same thing," Bender said. "And it is very hard to remind ourselves that the mind isn't there. It's just a construct that we have produced."The authors argue that part of why AI companies try to convince us their products are human-like is that this sets the foreground for them to convince us that AI can replace humans, whether it's at work or as creators. It's compelling for us to believe that AI could be the silver bullet fix to complicated problems in critical industries like health care and government services.But more often than not, the authors argue, AI isn't bring used to fix anything. AI is sold with the goal of efficiency, but AI services end up replacing qualified workers with black box machines that need copious amounts of babysitting from underpaid contract or gig workers. As Hanna put it in our interview, "AI is not going to take your job, but it will make your job shittier."Be dubious of the phrase 'super intelligence'If a human can't do something, you should be wary of claims that an AI can do it. "Superhuman intelligence, or super intelligence, is a very dangerous turn of phrase, insofar as it thinks that some technology is going to make humans superfluous," Hanna said. In "certain domains, like pattern matching at scale, computers are quite good at that. But if there's an idea that there's going to be a superhuman poem, or a superhuman notion of research or doing science, that is clear hype." Bender added, "And we don't talk about airplanes as superhuman flyers or rulers as superhuman measurers, it seems to be only in this AI space that that comes up."The idea of AI "super intelligence" comes up often when people talk about artificial general intelligence. Many CEOs struggle to define what exactly AGI is, but it's essentially AI's most advanced form, potentially capable of making decisions and handling complex tasks. There's still no evidence we're anywhere near a future enabled by AGI, but it's a popular buzzword.Many of these future-looking statements from AI leaders borrow tropes from science fiction. Both boosters and doomers — how Bender and Hanna describe AI enthusiasts and those worried about the potential for harm — rely on sci-fi scenarios. The boosters imagine an AI-powered futuristic society. The doomers bemoan a future where AI robots take over the world and wipe out humanity.The connecting thread, according to the authors, is an unshakable belief that AI is smarter than humans and inevitable. "One of the things that we see a lot in the discourse is this idea that the future is fixed, and it's just a question of how fast we get there," Bender said. "And then there's this claim that this particular technology is a step on that path, and it's all marketing. It is helpful to be able to see behind it."Part of why AI is so popular is that an autonomous functional AI assistant would mean AI companies are fulfilling their promises of world-changing innovation to their investors. Planning for that future — whether it's a utopia or dystopia — keeps investors looking forward as the companies burn through billions of dollars and admit they'll miss their carbon emission goals. For better or worse, life is not science fiction. Whenever you see someone claiming their AI product is straight out of a movie, it's a good sign to approach with skepticism. Ask what goes in and how outputs are evaluatedOne of the easiest ways to see through AI marketing fluff is to look and see whether the company is disclosing how it operates. Many AI companies won't tell you what content is used to train their models. But they usually disclose what the company does with your data and sometimes brag about how their models stack up against competitors. That's where you should start looking, typically in their privacy policies.One of the top complaints and concerns from creators is how AI models are trained. There are many lawsuits over alleged copyright infringement, and there are a lot of concerns over bias in AI chatbots and their capacity for harm. "If you wanted to create a system that is designed to move things forward rather than reproduce the oppressions of the past, you would have to start by curating your data," Bender said. Instead, AI companies are grabbing "everything that wasn't nailed down on the internet," Hanna said.If you're hearing about an AI product for the first time, one thing in particular to look out for is any kind of statistic that highlights its effectiveness. Like many other researchers, Bender and Hanna have called out that a finding with no citation is a red flag. "Anytime someone is selling you something but not giving you access to how it was evaluated, you are on thin ice," Bender said.It can be frustrating and disappointing when AI companies don't disclose certain information about how their AI products work and how they were developed. But recognizing those holes in their sales pitch can help deflate hype, even though it would be better to have the information. For more, check out our full ChatGPT glossary and how to turn off Apple Intelligence.