Lifelong Learning - Revision history

BPeat at 00:58, 29 April 2024

2024-04-29T00:58:04Z

BPeat at 00:57, 29 April 2024

2024-04-29T00:57:46Z

BPeat: Text replacement - "* Conversational AI ... ChatGPT | OpenAI ... Bing | Microsoft ... Bard | Google ... Claude | Anthropic ... Perplexity ... You ... Ernie | Baidu" to "* Conversational AI ... [[C...

2024-03-16T15:46:10Z

BPeat at 03:11, 2 March 2024

2024-03-02T03:11:53Z

BPeat at 00:06, 9 September 2023

2023-09-09T00:06:47Z

BPeat at 20:11, 2 September 2023

2023-09-02T20:11:22Z

BPeat: /* Forgetting */

2023-08-13T01:29:28Z

‎Forgetting

BPeat: /* Forgetting */

2023-08-13T01:27:07Z

‎Forgetting

BPeat at 01:05, 13 July 2023

2023-07-13T01:05:13Z

BPeat at 06:06, 7 May 2023

2023-05-07T06:06:57Z

← Older revision		Revision as of 00:58, 29 April 2024
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	In recent years, researchers have developed deep neural networks that can perform a variety of tasks, including visual recognition and natural language processing (NLP) tasks. Although many of these models achieved remarkable results, they typically only perform well on one particular task due to what is referred to as "catastrophic forgetting." Essentially, catastrophic forgetting means that when a model that was initially trained on task A is later trained on task B, its performance on task A will significantly decline. [https://techxplore.com/news/2019-03-approach-multi-model-deep-neural-networks.html A new approach to overcome multi-model forgetting in deep neural networks] and [https://techxplore.com/news/2019-03-memory-approach-enable-lifelong.html A generative memory approach to enable lifelong reinforcement learning] \| Ingrid Fadelli		In recent years, researchers have developed deep neural networks that can perform a variety of tasks, including visual recognition and natural language processing (NLP) tasks. Although many of these models achieved remarkable results, they typically only perform well on one particular task due to what is referred to as "catastrophic forgetting." Essentially, catastrophic forgetting means that when a model that was initially trained on task A is later trained on task B, its performance on task A will significantly decline. [https://techxplore.com/news/2019-03-approach-multi-model-deep-neural-networks.html A new approach to overcome multi-model forgetting in deep neural networks] and [https://techxplore.com/news/2019-03-memory-approach-enable-lifelong.html A generative memory approach to enable lifelong reinforcement learning] \| Ingrid Fadelli

−	~~https://3c1703fe8d.site.internapcdn.net/newman/csz/news/800/2019/11-anewapproach.jpg~~

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 [https://www.google.com/search?q=lifelong+learning+neural+network+Multi+model ...Google search]
 * [[Learning Techniques]]
 ** [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]]
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 * [https://www.darpa.mil/news-events/2018-05-03 Researchers Selected to Develop Novel Approaches to Lifelong Machine Learning | DARPA]
 * [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Ernie]] | [[Baidu]]

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 * [https://www.darpa.mil/news-events/2019-03-12 Progress on Lifelong Learning Machines Shows Potential for Bio-Inspired Algorithms | USC & DARPA]
 * [https://www.darpa.mil/news-events/2018-05-03 Researchers Selected to Develop Novel Approaches to Lifelong Machine Learning | DARPA]
-* [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing]] | [[Microsoft]] ... [[Bard]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[Ernie]] | [[Baidu]]
+* [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Ernie]] | [[Baidu]]
 * [[Memory]]

← Older revision		Revision as of 03:11, 2 March 2024
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	* [https://www.darpa.mil/news-events/2018-05-03 Researchers Selected to Develop Novel Approaches to Lifelong Machine Learning \| DARPA]		* [https://www.darpa.mil/news-events/2018-05-03 Researchers Selected to Develop Novel Approaches to Lifelong Machine Learning \| DARPA]
	* [[Conversational AI]] ... [[ChatGPT]] \| [[OpenAI]] ... [[Bing]] \| [[Microsoft]] ... [[Bard]] \| [[Google]] ... [[Claude]] \| [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[Ernie]] \| [[Baidu]]		* [[Conversational AI]] ... [[ChatGPT]] \| [[OpenAI]] ... [[Bing]] \| [[Microsoft]] ... [[Bard]] \| [[Google]] ... [[Claude]] \| [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[Ernie]] \| [[Baidu]]
		+	* [[Memory]]

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 ** [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]]
 ** [[Transfer Learning]]
-* [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
+* [[Artificial General Intelligence (AGI) to Singularity]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
 * [https://www.darpa.mil/program/lifelong-learning-machines Lifelong Learning Machines (L2M) | DARPA]
 * [https://www.darpa.mil/news-events/2019-03-12 Progress on Lifelong Learning Machines Shows Potential for Bio-Inspired Algorithms | USC & DARPA]

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← Older revision		Revision as of 01:27, 13 August 2023
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	* [https://venturebeat.com/2020/02/25/openais-jeff-clune-on-deep-learnings-achilles-heel-and-a-faster-path-to-agi/ OpenAI’s Jeff Clune on deep learning’s Achilles’ heel and a faster path to artificial general intelligence (AGI) - Khari Johnson - VentureBeat]		* [https://venturebeat.com/2020/02/25/openais-jeff-clune-on-deep-learnings-achilles-heel-and-a-faster-path-to-agi/ OpenAI’s Jeff Clune on deep learning’s Achilles’ heel and a faster path to artificial general intelligence (AGI) - Khari Johnson - VentureBeat]
	* [https://en.wikipedia.org/wiki/Catastrophic_interference Catastrophic Interference]		* [https://en.wikipedia.org/wiki/Catastrophic_interference Catastrophic Interference]
		+	* [https://venturebeat.com/ai/machine-unlearning-the-critical-art-of-teaching-ai-to-forget/ Machine unlearning: The critical art of teaching AI to forget \| Matthew Duffin - VentureBeat] ... outlines several different methods for machine unlearning, including sharding and slicing, incremental training, and data deletion. Sharding and slicing divides the data into smaller subsets, which can then be unlearned independently. Incremental training trains the model on a new dataset while keeping the old data in place, gradually removing the old data as it becomes outdated. Data deletion removes specific data points from the model, either manually or automatically. The article concludes by discussing the challenges and opportunities of machine unlearning. One challenge is that it can be computationally expensive to unlearn large models. Another challenge is that it can be difficult to ensure that the unlearning process does not damage the model's accuracy.

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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
 }}
 [https://www.youtube.com/results?search_query=lifelong+learning+neural+network+Multi+model YouTube search...]
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 * [https://www.darpa.mil/news-events/2019-03-12 Progress on Lifelong Learning Machines Shows Potential for Bio-Inspired Algorithms | USC & DARPA]
 * [https://www.darpa.mil/news-events/2018-05-03 Researchers Selected to Develop Novel Approaches to Lifelong Machine Learning | DARPA]
-* [[Generative AI]]  ... [[Conversational AI]] ... [[OpenAI]]'s [[ChatGPT]] ... [[Perplexity]]  ... [[Microsoft]]'s [[Bing]] ... [[You]] ...[[Google]]'s [[Bard]] ... [[Baidu]]'s [[Ernie]]
+* [[Generative AI]] ... [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing]] | [[Microsoft]] ... [[Bard]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[Ernie]] | [[Baidu]]