Generative Deep Learning, 2nd Edition [David Foster]
https://www.oreilly.com/librar....y/view/generative-de

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TOC:
Introducing Generative Deep Learning [00:00:00]
Model Families in Generative Modeling [00:02:25]
Auto Regressive Models and Recurrence [00:06:26]
Language and True Intelligence [00:15:07]
Language, Reality, and World Models [00:19:10]
AI, Human Experience, and Understanding [00:23:09]
GPTs Limitations and World Modeling [00:27:52]
Task-Independent Modeling and Cybernetic Loop [00:33:55]
Collective Intelligence and Emergence [00:36:01]
Active Inference vs. Reinforcement Learning [00:38:02]
Combining Active Inference with Transformers [00:41:55]
Decentralized AI and Collective Intelligence [00:47:46]
Regulation and Ethics in AI Development [00:53:59]
AI-Generated Content and Copyright Laws [00:57:06]
Effort, Skill, and AI Models in Copyright [00:57:59]
AI Alignment and Scale of AI Models [00:59:51]
Democratization of AI: GPT-3 and GPT-4 [01:03:20]
Context Window Size and Vector Databases [01:10:31]
Attention Mechanisms and Hierarchies [01:15:04]
Benefits and Limitations of Language Models [01:16:04]
AI in Education: Risks and Benefits [01:19:41]
AI Tools and Critical Thinking in the Classroom [01:29:26]
Impact of Language Models on Assessment and Creativity [01:35:09]
Generative AI in Music and Creative Arts [01:47:55]
Challenges and Opportunities in Generative Music [01:52:11]
AI-Generated Music and Human Emotions [01:54:31]
Language Modeling vs. Music Modeling [02:01:58]
Democratization of AI and Industry Impact [02:07:38]
Recursive Self-Improving Superintelligence [02:12:48]
AI Technologies: Positive and Negative Impacts [02:14:44]
Runaway AGI and Control Over AI [02:20:35]
AI Dangers, Cybercrime, and Ethics [02:23:42]

In this conversation, Tim Scarfe and David Foster, the author of 'Generative Deep Learning,' dive deep into the world of generative AI, discussing topics ranging from model families and auto regressive models to the democratization of AI technology and its potential impact on various industries. They explore the connection between language and true intelligence, as well as the limitations of GPT and other large language models. The discussion also covers the importance of task-independent world models, the concept of active inference, and the potential of combining these ideas with transformer and GPT-style models.

Ethics and regulation in AI development are also discussed, including the need for transparency in data used to train AI models and the responsibility of developers to ensure their creations are not destructive. The conversation touches on the challenges posed by AI-generated content on copyright laws and the diminishing role of effort and skill in copyright due to generative models.

The impact of AI on education and creativity is another key area of discussion, with Tim and David exploring the potential benefits and drawbacks of using AI in the classroom, the need for a balance between traditional learning methods and AI-assisted learning, and the importance of teaching students to use AI tools critically and responsibly.

Generative AI in music is also explored, with David and Tim discussing the potential for AI-generated music to change the way we create and consume art, as well as the challenges in training AI models to generate music that captures human emotions and experiences.

Throughout the conversation, Tim and David touch on the potential risks and consequences of AI becoming too powerful, the importance of maintaining control over the technology, and the possibility of government intervention and regulation. The discussion concludes with a thought experiment about AI predicting human actions and creating transient capabilities that could lead to doom.

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Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world.

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How Powerful Will AI Be In 2030?
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Welcome to our channel! In this exciting video, we delve into the fascinating realm of artificial intelligence (AI) and explore the question that has intrigued tech enthusiasts and experts alike: "How powerful will AI be in 2030?" Join us as we embark on a captivating journey into the future of AI, examining the possibilities, advancements, and potential impact that await us.

In the next decade, AI is poised to revolutionize numerous industries and transform the way we live and work. As we peer into the crystal ball of technological progress, we aim to shed light on the potential power and capabilities that AI could possess by 2030. Brace yourself for mind-blowing insights and expert analysis that will leave you in awe.

We begin by exploring the current state of AI and its rapid advancements. From machine learning algorithms to neural networks and deep learning models, AI has already demonstrated exceptional prowess in various fields, including healthcare, finance, transportation, and more. By building upon these achievements, AI is set to evolve exponentially, opening doors to a future where intelligent machines collaborate seamlessly with humans.

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Welcome to AI Uncovered, your ultimate destination for exploring the fascinating world of artificial intelligence! Our channel delves deep into the latest AI trends and technology, providing insights into cutting-edge AI tools, AI news, and breakthroughs in artificial general intelligence (AGI). We simplify complex concepts, making AI explained in a way that is accessible to everyone.

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It seems that not a day goes by without there being some news about generative AI that ranges from inspiring, to weird, to just plain terrifying. Unsurprisingly, the sheer volume of information has aspiring creators asking, "What's my place in an AI future?” This talk seeks to find a clear path through the noise. It presents an overview of what AI actually is in today's world, what it might look like in five years and how we can use it to make ourselves indispensable to future employers.

Speaker:
Shaun McCabe

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Don't click this: https://tinyurl.com/bde5k7d5

💚 Link to Code: https://www.patreon.com/greencode

How I Learned This: https://nnfs.io/ (by the awesome @sentdex )

I'm not an AI expert by any means, I probably have made some mistakes. So I apologise in advance :)

Also, I only used PyTorch to test the forward pass. Apart from that, everything else is written in pure Python (+ use of Numpy).


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🔊 Music I Used in this Video: https://share.epidemicsound.com/7i1d0b



Current Subs: 14,219

1 The First Time Ever I Saw Your Face - Roberta Flack
2 Alone Again (Naturally) - Gilbert O'Sullivan
3 American Pie - Don McLean
4 Without You - Harry Nilsson
5 The Candy Man - Sammy Davis, Jr.
6 I Gotcha - Joe Tex
7 Lean on Me - Bill Withers
8 Baby, Don't Get Hooked on Me - Mac Davis
9 Brand New Key - Melanie
10 Daddy Don't You Walk So Fast - Wayne Newton
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12 Brandy (You're a Fine Girl) - Looking Glass
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14 Nice to Be with You - Gallery
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16 (If Loving You Is Wrong) I Don't Want to Be Right - Luther Ingram
17 Heart of Gold - Neil Young
18 Betcha by Golly, Wow - The Stylistics
19 I'll Take You There - The Staple Singers
20 Ben - Michael Jackson
21 The Lion Sleeps Tonight - Robert John
22 Outa-Space - Billy Preston
23 Slippin' Into Darkness - War
24 Long Cool Woman in a Black Dress - The Hollies
25 How Do You Do - Mouth & MacNeal
26 Song Sung Blue - Neil Diamond
27 A Horse with No Name - America
28 Popcorn - Hot Butter
29 Everybody Plays the Fool - The Main Ingredient
30 Precious and Few - Climax

MIT 15.773 Hands-On Deep Learning Spring 2024
Instructor: Rama Ramakrishnan
View the complete course: https://ocw.mit.edu/courses/15....-773-hands-on-deep-l
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Introduction to natural language processing, including vectorization, the bag-of-words model, and includes demonstration in CoLab.

License: Creative Commons BY-NC-SAMore information at https://ocw.mit.edu/termsMore courses at https://ocw.mit.eduSupport OCW at http://ow.ly/a1If50zVRlQ

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✅ 2. https://youtu.be/DfFoMhfYNLI?si=gxT5Dy5rUZ7OXh1l
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