Home / Recipes / Neural Networks ๐ป How to Make Neural Networks in Infinite CraftNeural Networks is a long haul. Even on the shortest known route it takes 71 combinations to get there, and the final one is Deep Learning plus Telegrams. Expect to build several intermediate elements you will never use again.
The final combination
๐ง ๐ป Deep Learning+ ๐จ Telegrams= ๐ป Neural Networks
Marathon 71 steps from the base elements ยท crafting depth 102
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What is worth knowing At 71 steps it is longer than 100% of solved elements, which puts it in our marathon band. Its crafting depth of 102 is unusually deep. Depth counts the longest chain needed to reach it, and most elements people search for sit well below this. Full crafting path from the base elements Start with Water, Fire, Wind and Earth, then follow these 71 combinations in order.
1 ๐ฅ Fire+ ๐ง Water= ๐จ Steam2 ๐จ Steam+ ๐จ Wind= โ๏ธ Cloud3 ๐ Earth+ ๐จ Wind= ๐ซ๏ธ Dust4 ๐ซ๏ธ Dust+ ๐ Earth= ๐ช Planet5 ๐ฅ Fire+ ๐ช Planet= โ๏ธ Sun6 ๐ฅ Fire+ โ๏ธ Sun= โ๏ธ Solar7 ๐ช Planet+ โ๏ธ Solar= ๐ป System8 ๐ฅ Fire+ ๐ป System= ๐ป Computer9 โ๏ธ Cloud+ ๐ป Computer= โ๏ธ Cloud Computing10 ๐ง Water+ ๐ง Water= ๐ Lake11 โ๏ธ Cloud Computing+ ๐ Lake= ๐๐๏ธ Data Lake12 ๐ Earth+ ๐ง Water= ๐ฑ Plant13 ๐ฅ Fire+ ๐จ Wind= ๐จ Smoke14 ๐ฑ Plant+ ๐จ Smoke= ๐ฏ๏ธ Incense15 ๐ง Water+ ๐จ Wind= ๐ Wave16 ๐ Earth+ ๐ Wave= ๐๏ธ Sand17 ๐ฅ Fire+ ๐๏ธ Sand= ๐ฅ Glass18 ๐ฅ Fire+ ๐ฅ Glass= ๐ Lens19 ๐ Lens+ ๐ง Water= ๐ฌ Microscope20 ๐ฏ๏ธ Incense+ ๐ฌ Microscope= ๐ฌ Science21 ๐๐๏ธ Data Lake+ ๐ฌ Science= ๐ Data Science22 ๐ฑ Plant+ ๐จ Wind= ๐ผ Dandelion23 ๐ผ Dandelion+ ๐ง Water= ๐ท Wine24 ๐ง Water+ ๐ท Wine= ๐ฆ Holy Water25 ๐ฅ Fire+ ๐ฆ Holy Water= ๐ง Vampire26 ๐ผ Dandelion+ ๐ฑ Plant= ๐ฟ Weed27 ๐ง Vampire+ ๐ฟ Weed= ๐งฎ Count28 ๐งฎ Count+ ๐ Wave= ๐ข Counting29 ๐ข Counting+ ๐ฟ Weed= ๐ Math30 ๐ Data Science+ ๐ Math= ๐ค Machine Learning31 ๐ฑ Plant+ ๐ง Water= ๐ Swamp32 ๐ฅ Fire+ ๐ Swamp= ๐ Dragon33 ๐ Dragon+ ๐ซ๏ธ Dust= ๐ Dragonfly34 ๐ Dragonfly+ ๐ Earth= ๐ Ant35 ๐ฅ Fire+ ๐จ Steam= ๐ Engine36 ๐ผ Dandelion+ ๐ Engine= ๐ Helicopter37 ๐ Earth+ ๐ Earth= ๐๏ธ Mountain38 ๐ Helicopter+ ๐๏ธ Mountain= ๐ Rescue39 ๐ Ant+ ๐ Rescue= ๐ Aid40 ๐ซ๏ธ Dust+ ๐จ Wind= ๐ช๏ธ Sandstorm41 ๐ช๏ธ Sandstorm+ ๐ง Water= ๐๏ธ Oasis42 ๐๏ธ Oasis+ ๐ฑ Plant= ๐ Date43 ๐ Date+ ๐ง Water= ๐ Dating44 ๐ Earth+ ๐จ Steam= ๐ฉ Mud45 ๐ฅ Fire+ ๐ฉ Mud= ๐งฑ Brick46 ๐งฑ Brick+ ๐งฑ Brick= ๐งฑ Wall47 ๐ Dating+ ๐งฑ Wall= ๐ฌ Facebook48 ๐ฌ Facebook+ ๐ฅ Fire= ๐ Like49 ๐ Aid+ ๐ Like= ๐ Similar50 ๐ค Machine Learning+ ๐ Similar= ๐ง ๐ป Deep Learning51 ๐จ Wind+ ๐จ Wind= ๐ช๏ธ Tornado52 ๐ช๏ธ Tornado+ ๐ง Water= ๐ Tsunami53 ๐ Earth+ ๐ Tsunami= ๐๏ธ Island54 ๐ Earth+ ๐๏ธ Island= ๐ Continent55 ๐จ Steam+ ๐ Wave= ๐ Surf56 ๐ Continent+ ๐ Surf= ๐ฆ Australia57 ๐๏ธ Mountain+ ๐จ Wind= ๐จ๏ธ Avalanche58 ๐จ๏ธ Avalanche+ ๐จ Wind= โ๏ธ Snow59 ๐ฆ Australia+ โ๏ธ Snow= ๐
No60 ๐ Lake+ ๐ง Water= ๐ Ocean61 ๐
No+ ๐ Ocean= ๐ซ Not62 ๐ซ๏ธ Dust+ ๐ Engine= ๐งน Vacuum63 ๐ฅ Fire+ ๐งน Vacuum= ๐ณ๏ธ Black Hole64 ๐ณ๏ธ Black Hole+ ๐ช๏ธ Tornado= ๐ Singularity65 ๐ซ Not+ ๐ Singularity= ๐ค Plural66 ๐๏ธ Sand+ ๐ง Water= ๐๏ธ Beach67 ๐ Earth+ ๐ฅ Glass= ๐พ Bottle68 ๐๏ธ Beach+ ๐พ Bottle= ๐ฌ Message69 ๐ฌ Message+ ๐จ Steam= ๐ฒ Telegram70 ๐ค Plural+ ๐ฒ Telegram= ๐จ Telegrams71 ๐ง ๐ป Deep Learning+ ๐จ Telegrams= ๐ป Neural NetworksCrafting tree 1 Fire + Water โ Steam 2 Steam + Wind โ Cloud 3 Earth + Wind โ Dust 4 Dust + Earth โ Planet 5 Fire + Planet โ Sun 6 Fire + Sun โ Solar 7 Planet + Solar โ System 8 Fire + System โ Computer 9 Cloud + Computer โ Cloud Computing 10 Water + Water โ Lake 11 Cloud Computing + Lake โ Data Lake 12 Earth + Water โ Plant 13 Fire + Wind โ Smoke 14 Plant + Smoke โ Incense 15 Water + Wind โ Wave 16 Earth + Wave โ Sand 17 Fire + Sand โ Glass 18 Fire + Glass โ Lens 19 Lens + Water โ Microscope 20 Incense + Microscope โ Science 21 Data Lake + Science โ Data Science 22 Plant + Wind โ Dandelion 23 Dandelion + Water โ Wine 24 Water + Wine โ Holy Water 25 Fire + Holy Water โ Vampire 26 Dandelion + Plant โ Weed 27 Vampire + Weed โ Count 28 Count + Wave โ Counting 29 Counting + Weed โ Math 30 Data Science + Math โ Machine Learning 31 Plant + Water โ Swamp 32 Fire + Swamp โ Dragon 33 Dragon + Dust โ Dragonfly 34 Dragonfly + Earth โ Ant 35 Fire + Steam โ Engine 36 Dandelion + Engine โ Helicopter 37 Earth + Earth โ Mountain 38 Helicopter + Mountain โ Rescue 39 Ant + Rescue โ Aid 40 Dust + Wind โ Sandstorm 41 Sandstorm + Water โ Oasis 42 Oasis + Plant โ Date 43 Date + Water โ Dating 44 Earth + Steam โ Mud 45 Fire + Mud โ Brick 46 Brick + Brick โ Wall 47 Dating + Wall โ Facebook 48 Facebook + Fire โ Like 49 Aid + Like โ Similar 50 Machine Learning + Similar โ Deep Learning 51 Wind + Wind โ Tornado 52 Tornado + Water โ Tsunami 53 Earth + Tsunami โ Island 54 Earth + Island โ Continent 55 Steam + Wave โ Surf 56 Continent + Surf โ Australia 57 Mountain + Wind โ Avalanche 58 Avalanche + Wind โ Snow 59 Australia + Snow โ No 60 Lake + Water โ Ocean 61 No + Ocean โ Not 62 Dust + Engine โ Vacuum 63 Fire + Vacuum โ Black Hole 64 Black Hole + Tornado โ Singularity 65 Not + Singularity โ Plural 66 Sand + Water โ Beach 67 Earth + Glass โ Bottle 68 Beach + Bottle โ Message 69 Message + Steam โ Telegram 70 Plural + Telegram โ Telegrams 71 Deep Learning + Telegrams โ Neural Networks
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Neural Networks at a glance
Steps to craft 71 Marathon
Crafting depth 102 longer than 100% of solved elements
Known recipes 1 only one way
Used in 0 other combinations Other elements that take 71 steps Similar effort to Neural Networks, if you want something else to chase.
Frequently asked questions How do you make Neural Networks in Infinite Craft? Combine Deep Learning with Telegrams. The full path from the base elements takes 71 steps.
How many steps does it take to make Neural Networks? 71 steps on the shortest known path from Water, Fire, Wind and Earth.
Is Neural Networks hard to make in Infinite Craft? It rates as marathon. At 71 steps it is longer than 100% of solved elements.
Is there more than one way to make Neural Networks? Only one known combination produces Neural Networks.
Path verified against the open recipe graph on 2026-10-23 . Method described in our methodology , data credited on data sources .