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Nick Cort
Nick Cort

New Sky V 1.0

In this day and age, pretty much everyone who currently plays No Man's Sky and has done so since the beginning is prepared to forgive Hello Games for what originally released back in 2016. At the time, it had one of the most disastrous launches in video game history, but there's no denying that it has drastically changed. Along with a slew of updates and a dedicated fan base, for many, it's one of the most interesting sci-fi titles around, and some may have even forgotten what the game initially looked like.

New Sky v 1.0

Recently, YouTuber Cycu1 has shown exactly what No Man's Sky looked and played like six years ago when it first launched. The video shows them playing the game on PS5, but they've installed the game directly from the disc, Version 1.0, essentially turning it into the original incarnation of the game. Fans will no doubt see the differences between then and now, with the hour and a half footage possibly opening up old wounds from players who remember what the game used to be like. It really demonstrates how far things have come and the work that Hello Games has been putting into its galaxy exploration title.

Probably the most notable difference is with the space stations, which can be seen about an hour into the playthrough. While they are now bustling hubs full of side quests, NPCs, and traders, Cycu1's video shows just how empty and uninteresting these stations were in Version 1.0. No Man's Sky features 18 quintillion discoverable planets, but back then things seemed so empty, and seeing how little content each space station has in this footage is a sobering reminder of what used to be.

Things are much better these days, thankfully. The developer continues to offer free updates that simply pack the already enormous game with even more content. In fact, No Man's Sky is also getting a Nintendo Switch port later this year, showing that it's still making an impact on the industry. The game is easily one of the most famous redemption arcs in all of video game development, with the studio even winning a BAFTA back in April.

Hello Games has also said it's working on its next game, but the company's co-founder Sean Murray has insisted that the team has learned its lesson about overhyping projects. Little is known about what this next release will be. Whether it will have any ties with the No Man's Sky universe cannot be said, but whatever the studio is working on will have to go to great lengths to be as ambitious as its sci-fi IP.

Andrew is a freelance writer from the UK who's been contributing to Game Rant since 2021, but has also written for Rock Paper Shotgun and PCGamesN. Approaching 40 years old, he has practically grown up with the video game industry as we know it today, beginning his adventures with the likes of the NES and Game Boy before moving onto the Sega Genesis (or Mega Drive as it was known in the UK). Currently, Andrew is sticking with his Xbox One and laptop, though he's in the market for an Xbox Series X.Favorite games include: The Elder Scrolls series, classic FPS games like Doom, Quake, and Half-Life, Streets of Rage 2, the original Sonic installments (1-4). Actually, there are way too many games to reel off here. This list could go on forever.Oh, he does have a particular penchant for horror, especially the Amnesia series, Outlast, Silent Hill, Resident Evil, Alien Isolation, Phasmophobia. Basically, anything that has the potential to make him sweat.

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The Playstation 4 is the only system that received version 1.00 of No Man's Sky. Sony requires developers to submit a Golden Master version for them to verify prior to release, which is the version included on the disc.

On July 10 2016, Sean Murray tweeted that RC 1 of No Man's Sky had passed cert in reference to this tweet 3 days prior. This puts the build date of version 1.00 some time before then, depending on how long Sony's verification takes.

This version is accessible by playing the game from the Playstation 4 disc without updating from the internet. Since Update 1.03 was released on launch day, most people updated before playing and did not play 1.00.

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The first step is further divided into two stages: (1a) Using simple criteria for R (red), G (green), B (blue), and H (hue) values in the RGB and HLS colour codes, each pixel of a jpeg image is classified into several categories according to its colour as "visible diffuse", "green arc", "strong aurora" (which means saturated or mixed with N2 red line at 670 nm), "cloud", "artificial light", and "moon". (1b) The percentage of the occupying area (pixel coverage) for each category and the characteristic intensity of "strong aurora" are calculated.

The obtained ASC aurora index is posted in both a ascii format and plots on a real-time bases at When Level 6 is detected, automatic alert E-mail is sent out to the registered addresses immediately. The alert system started 5 November, 2021, and the results (both Level 6 detection and Level 4 detection) were compared to the manual (eye-)identification of the auroral activity during the rest of the auroral season of Kiruna ASC (i.e., total five months until April 2022). Unless the Moon or cloud blocks the brightened region, nearly one-to-one correspondence between Level 6 and Local-Arc-Breaking judged by original ASC images is achieved within ten minutes uncertainty.

The submitted Manuscript presents an approach for Aurora real-time detection based on hemispheric RGB camera images. In contrast to other approaches using deep learning, the introduced method uses spectra indices calculated from RGB image data.

The method is very complex and hard to understand due to missing figures that would definetely help to grasp the matter. Furthermore, it sounds like the approach is only applicable to one study area using one specific camera setup where the authors developed the method. It was not stated that the approch was tested / validated at some else location or using some other camera configuration. The evaluation is based on manual observations that AFAIK could be very subjective. Unfortunately it is not stated if the reference data is based on observations of several operateurs to have some quality control on the Groud Truth data.

To cover wider readers, we will add three (or more) figures in the revision: keogram, ASC image with different category and area marked, and image showing N2 red line) with more explanation in text. We actually have them nearly ready (used in oral presentations for non-auroral community) but not included here (this is our mistake). We also plan to add a table of example of actual classification (to be used in combination with the new figure).

In the planed revision, we will also explain the speciality of aurora where no classification method (including machine learning) can be applied to different cameras without changing parameters or more fundamental selection (for machine learning method, training set should be different between different cameras, and definition of such training set is as subjective as the colour definition in the present method).

I thank the authors for the interesting manuscript. The manuscripts details a simple method to classify images in an ASC aurora image collection according to the presented ASC index. The method is computationally lightweight, which is important for the goal of nowcasting local arc breaking of auroras in all-sky camera images. The single ASC index indicator makes the classification outcome easily interpretable by experts and novices in the field.

Thank you for your detailed comments and for reminding that potential readers are much wider than the auroral observation community (main target readers). To cover wider readers, we will add more explanations and figures/table (as written in the reply to reviewer 1), e.g., explaining the aurora image, aurora activity itself, and how to interpret the aurora.

Also, we will make it clearer that the presented two step method is the first trial of "translation" of how auroral scientists actually judge "onset" of auroral activity in the sky: first evaluate the colour information to judge if it is aurora or not (just using green colour cannot distinguish diffuse aurora or cloud because the morphology is similar to each other, and this is why we need three-four colours), and then evaluate the activity level from both intensity and area within the field-of-view.

The main user is auroral community scientists and operators (they asked us to describe our method that is already in successful operation) who are familiar with classifying the auroral activity level and ready to apply this method (after modification of the parameters). This is why the old version 0 is already applied in Finland (private communication, 2022).

In the revision, we would stress that there is no automated identification scheme of "onset" in both machine learning method and expert system method. What so far exist is just "one" category each picture of types of aurora, without telling the activity level, although the activity level is the most important parameter. Thus this is the first trial of such, and evaluation of the method much be done against eye identification method but not machine learning method. 041b061a72


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