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Xbox Game Pass has added another title with the arrival of Lightyear Frontier in early access mode, today, 19 March.
The indie game combines a farming sim with mech elements as players roam to discover the landscape on a solo run, or together with up to three additional users.
To get started on the game developed by Frame Break, players are urged to choose a flat area in The Meadows to set up camp. This allows space for building, farming and proximity to water for efficient resource management.
This step will be required once you have located and repaired the damaged Mech you fell from the sky in.
One of several tasks to be completed in the gameplay is to restore Pine Heights, a multi-step process, including using the map to locate the area, collecting tools with your Mech, and utilizing specific tools.
Jump inside and wander around the map until you have collected all the tools it tells you to. You can spot them on the terrain because they will be issuing colored smoke from the wreckage.
How does Microsoft’s Xbox Game Pass work?
Xbox Game Pass gives gamers a diverse game library accessible across Xbox consoles, PCs, and compatible devices.
Subscribers enjoy a constantly refreshed selection of AAA and indie titles, making it a versatile gaming solution. This subscription model has revolutionized the gaming industry, offering a cost-effective and flexible way for players to access a wide range of gaming experiences without needing to buy individual titles.
It’s not without drawbacks, however. The rotating library, which sees games removed or added sporadically, is not for everyone, and this lack of ownership may be a concern for those who prefer to have a permanent collection.
Other games coming to Xbox Game Pass in March 2024
Final Fantasy 14 Online – Starter Edition (Xbox Game Pass Perk (21 March)
The Last Case of Benedict Fox: Definitive Edition (26 March)
Diablo 4 (28 March)
Open Roads (28 March)
Image credit: Lightyear Frontier/X
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It seems as though complaints about wooden acting and poor NPC dialogue will become a thing of the past as gaming development continues to use more and more generative AI in its processes. We aren’t there yet, but by the end of the year, we will probably have our first game with NPC characters generating their own realistic dialogue depending on what you ask them.
For gaming realism, this could be a game changer, and while it is unclear where it may actually lead us, Unity and generative AI company Convai are keen to give us a sneak peek into the future with the release of Project Neural Nexus – a demo “game” which will feature smart NPCs and Unity’s MUSE behavior tool.
“Step into the world of Neo City, a cyberpunk theme city where danger lurks at every corner. You wake up at a hotel and are being chased by the police and killer robots. Your objective is to make out of the hotel filled with assassins – alive. But you are not alone. You have help from your AI companion, who can equip you with weapons, teach you how to shoot, guide you at every step and is helping you get out of the hotel. Your decisions change the storyline but be careful, one wrong step and it’s game over. The game is powered by Convai’s smart NPCs where you can have open-ended conversations, make decisions, perform actions, interact with various environmental objects, and are guided by an AI companion. Welcome to Neo City. Your survival story begins now.”

That’s how Convai is positioning PNN and is more of a tech demonstration of where gaming could be headed and headed quickly. The problem will be if an NPC can talk to you about anything, and you can ask it anything, how do you keep the story on track? The idea of an NPC answering questions more realistically is appealing. What we see in demonstrations like this is the “game” being played the way the developers intend. The general public will not necessarily play as nicely.
When you watch the video there is no doubt it is exciting and impressive in equal amounts. Text to Speech might not still be quite there yet when it comes to vocal emotion and some of the dialogue sounds a little stilted but the potential is there for all to see. Especially as we move along towards a world that has GPT5 in it.
You can sign up for early access now and it should be released later in the year. Interesting times ahead
The post A cyberpunk game with AI actors that make up their own dialogue? Count us in appeared first on ReadWrite.

It could soon be possible to speak without vocal cords, as engineers are focusing on a square-inch device that can help people regain their voice.
This could be extremely beneficial for people with pathological vocal cord conditions or those who are recovering from laryngeal cancer surgery as this tiny new patch is being developed by engineers at the University of California.
In a journal published in Nature Communications last week (Mar. 12), the researchers outlined their invention and the results of testing the device on eight adults.
They describe the wearable tool as being a “self-powered sensing-actuation system” based on soft magnetoelasticity to enable assisted speaking. It works by patients articulating sentences through muscle movements that are usually used in regular speech or lip-synching.
The sensing component of the device then recognizes the movements without the vibration of vocal folds. Electrical signals are then fed to a pre-trained machine-learning model that converts throat movement into voice signals.
Other solutions for helping people without vocal cords to speak are available but these largely include handheld electro-larynx devices or tracheoesophageal-puncture procedures. Both of these options could be considered to be inconvenient and uncomfortable.
How does it work?
The system was attached to the throat of the participants and data on laryngeal muscle movement was collected, with a machine-learning algorithm used to correlate the resulting signals to specific words.
The research team had the patients pronounce five sentences – both out loud and voicelessly – including ‘I don’t trust you’ and ‘I love you.’ Each person had to repeat the five sentences 100 times for data collection purposes.
The overall prediction accuracy of the model was 94.68%, working well across the different people involved.
Going forward, the research team plans to expand the vocabulary of the device through machine learning and test their findings in people with speech disorders. 
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