Dr. Mike Pound, an expert in AI and computer vision, shares his insights on the future of artificial intelligence. He discusses the need for a multidisciplinary approach to AI, especially in fields like cybersecurity. Exploration of AI's limitations highlights the importance of hands-on experience and a critical assessment of new technologies. Mike also addresses privacy concerns and the societal divide created by AI advancements. Finally, he tackles fears about job security, emphasizing that human insight remains indispensable despite automation.
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insights INSIGHT
AI Development Shift
The focus in AI has shifted from simply making language models bigger to integrating them into tools.
This allows for smarter systems and improved performance by incorporating actual data.
insights INSIGHT
AGI Hype
Sam Altman's prediction of AGI's arrival might be influenced by OpenAI's stock price.
Many researchers believe that LLMs are tools within larger systems, not standalone solutions.
insights INSIGHT
AI Growth Trend
Despite initial hype, AI's growth has followed a logarithmic trend, not an exponential one.
Recent papers demonstrate LLMs' limitations in reasoning and handling superfluous information.
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// Mike SOCIAL //
X: / _mikepound
Website: https://www.nottingham.ac.uk/research...
// YouTube video reference //
Teach your AI with Dr Mike Pound (Computerphile): • Train your AI with Dr Mike Pound (Com...
Has Generative AI Already Peaked? - Computerphile: • Has Generative AI Already Peaked? - C...
// Courses Reference //
Deep Learning: https://www.coursera.org/specializati...
AI For Everyone by Andrew Ng: https://www.coursera.org/learn/ai-for...
Pytorch Tutorials: https://pytorch.org/tutorials/
Pytorch Github: https://github.com/pytorch/pytorch
Pytorch Tensors: https://pytorch.org/tutorials/beginne...
https://pytorch.org/tutorials/beginne...
https://pytorch.org/tutorials/beginne...
Python for Everyone: https://www.py4e.com/
// BOOK //
Deep learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville: https://amzn.to/3vmu4LP
// PyTorch //
Github: https://github.com/pytorch
Website: https://pytorch.org/
Documentation: / pytorch
// David's SOCIAL //
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// MY STUFF //
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// MENU //
0:00 - Coming Up
0:43 - Introduction
01:04 - State of AI in 2025
02:10 - AGI Hype: Realistic Expectations
03:15 - Sponsored Section
04:30 - Is AI Plateauing or Advancing?
06:26 - Overhype in AI Features Across Industries
08:01 - Is It Too Late to Start in AI?
09:16 - Where to Start in 2025
10:20 - Recommended Courses and Progression Paths
13:26 - Should I Go to School for AI?
14:18 - Learning AI Independently with Resources Online
17:24 - Machine Learning Progression
19:09 - What is a Notebook?
20:10 - Is AI the Top Skill to Learn in 2025?
23:49 - Other Niches and Fields
25:05 - Cyber Using AI
26:31 - AI on Different Platforms
27:13 - AI isn’t Needed Everywhere
29:57 - Leveraging AI
30:35 - AI as a Productivity Tool
31:55 - Retrieval Augmented Generation
33:28 - Concerns About Privacy with AI
36:01 - The Difference Between GPU’s, CPU’s, NPU’s etc.
37:30 - The Release of Sora38:56 - Will AI Take Our Job?
41:00 - Nvidia Says We Don’t Need Developers
43:47 - Devin Announcement
44:59 - Conclusion
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Disclaimer: This video is for educational purposes only.