ALFRED - Revision history

BPeat at 13:00, 16 June 2024

2024-06-16T13:00:03Z

BPeat at 19:12, 7 July 2023

2023-07-07T19:12:21Z

BPeat at 19:11, 7 July 2023

2023-07-07T19:11:10Z

BPeat at 14:20, 20 May 2023

2023-05-20T14:20:07Z

BPeat at 14:14, 20 May 2023

2023-05-20T14:14:30Z

BPeat at 14:07, 20 May 2023

2023-05-20T14:07:22Z

BPeat at 13:57, 20 May 2023

2023-05-20T13:57:06Z

BPeat at 13:43, 20 May 2023

2023-05-20T13:43:09Z

BPeat at 13:42, 20 May 2023

2023-05-20T13:42:24Z

BPeat: Created page with "{{#seo: |title=PRIMO.ai |titlemode=append |keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, M..."

2023-05-20T13:40:41Z

Created page with "{{#seo: |title=PRIMO.ai |titlemode=append |keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, M..."

New page

{{#seo:
|title=PRIMO.ai
|titlemode=append
|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
}}

[https://www.youtube.com/results?search_query=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives Youtube]
[https://www.quora.com/search?q=ai%20ALFRED%20Action%20Learning%20From%20Realistic%20Environments%20Directives ... Quora]
[https://www.google.com/search?q=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives ...Google search]
[https://news.google.com/search?q=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives ...Google News]
[https://www.bing.com/news/search?q=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives&qft=interval%3d%228%22 ...Bing News]

<b>ALFRED; Action Learning From Realistic Environments and Directives</b> is a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. It includes long, compositional tasks with non-reversible state changes to shrink the gap between research benchmarks and real-world applications

<youtube>-YmHT2fSQDo</youtube>
<youtube>1XoRLNmXffo</youtube>

@@ Line 22: / Line 22: @@
 * [[Embodied AI]]
 * [[AlfWorld]]
-* [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[3D Simulation Environments]] ... [[Simulated Environment Learning]] ... [[Point Cloud]]
+* [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[Point Cloud]]
 <b>ALFRED; Action Learning From Realistic Environments and Directives</b> is a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. It includes long, compositional tasks with non-reversible state changes to shrink the gap between research benchmarks and real-world applications. a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. It includes long, compositional tasks with non-reversible state changes to shrink the gap between research benchmarks and real-world applications. ALFRED consists of expert demonstrations in interactive visual environments for 25k natural language directives. These directives contain both high-level goals like “Rinse off a mug and place it in the coffee maker” and low-level language instructions like "Walk to the coffee maker on the right."

@@ Line 22: / Line 22: @@
 * [[Embodied AI]]
 * [[AlfWorld]]
-* [[Robotics]]
+* [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[3D Simulation Environments]] ... [[Simulated Environment Learning]] ... [[Point Cloud]]
 <b>ALFRED; Action Learning From Realistic Environments and Directives</b> is a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. It includes long, compositional tasks with non-reversible state changes to shrink the gap between research benchmarks and real-world applications. a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. It includes long, compositional tasks with non-reversible state changes to shrink the gap between research benchmarks and real-world applications. ALFRED consists of expert demonstrations in interactive visual environments for 25k natural language directives. These directives contain both high-level goals like “Rinse off a mug and place it in the coffee maker” and low-level language instructions like "Walk to the coffee maker on the right."

@@ Line 15: / Line 15: @@
 * [[Embodied AI]]
 * [[AlfWorld]]
 <b>ALFRED; Action Learning From Realistic Environments and Directives</b> is a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. It includes long, compositional tasks with non-reversible state changes to shrink the gap between research benchmarks and real-world applications. a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. It includes long, compositional tasks with non-reversible state changes to shrink the gap between research benchmarks and real-world applications. ALFRED consists of expert demonstrations in interactive visual environments for 25k natural language directives. These directives contain both high-level goals like “Rinse off a mug and place it in the coffee maker” and low-level language instructions like "Walk to the coffee maker on the right."

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 [https://www.bing.com/news/search?q=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives&qft=interval%3d%228%22 ...Bing News]
 * [[Embodied AI]]
 * [[AlfWorld]]

← Older revision		Revision as of 13:57, 20 May 2023
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	[https://www.bing.com/news/search?q=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives&qft=interval%3d%228%22 ...Bing News]		[https://www.bing.com/news/search?q=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives&qft=interval%3d%228%22 ...Bing News]

		+	* [[Embodied AI]]
	* [[AlfWorld]]		* [[AlfWorld]]

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 |title=PRIMO.ai
 |titlemode=append
-|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
+|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
-|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
+<!-- Google tag (gtag.js) -->
 }}
 [https://www.youtube.com/results?search_query=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives Youtube]
 [https://www.quora.com/search?q=ai%20ALFRED%20Action%20Learning%20From%20Realistic%20Environments%20Directives ... Quora]

← Older revision		Revision as of 13:43, 20 May 2023
Line 12:		Line 12:
	[https://www.bing.com/news/search?q=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives&qft=interval%3d%228%22 ...Bing News]		[https://www.bing.com/news/search?q=ai+ALFRED+Action+Learning+From+Realistic+Environments+Directives&qft=interval%3d%228%22 ...Bing News]

−	* [[ALFRED]]
	* [[AlfWorld]]		* [[AlfWorld]]