Using Whisper and GPT to summarize YouTube videos - Eric Cheng
Eric Cheng

Using Whisper and GPT to summarize YouTube videos

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I probably spend an average of 30-60 minutes a day on YouTube listening to amazing experts share knowledge about breaking news. I’m amazed at how quickly people can analyze new information and turn it into easily consumable content.

Auto-GPT has been fun to experiment with, and seeing how GPT follows “reasoning” with a bit of local storage and logic was mind-opening. I used it to do research for a trip I’m planning to Lone Pine, and it utilized Google searches to find up-to-date information about various aspects. In the end, it generated a detailed itinerary with locations I should visit, day by day. The itinerary wasn’t perfect, but it was a glimpse ahead at how automated and personalized these sorts of services are going to be very soon (including having AIs take action on one’s behalf).

Anyway, back to the YouTube videos thing. After seeing Auto-GPT in action, I finally decided to do some coding with Whisper and GPT, and created a little program that fetches YouTube videos, transcribes them with Whisper, and summarizes them with GPT. I don’t have access to the API for GPT-4 yet, and mine is still using GPT 3.5-turbo. Still, the results are really interesting. When I’ve manually run against ChatGPT with GPT-4, the results are better; also, I could really use the larger prompt sizes for this application.

I haven’t coded in a long time and I’m not really a Python programmer. Luckily, I had a ChatGPT window open and asked it all sorts of stuff way beyond the sort of thing I would normally have used Google Searches for. I haven’t paid the $10/month for Github Copilot, but after today, I’m going to sign up.

Anway, I ran the first big test against the last month’s worth of videos from my favorite AI YouTuber over at AI Explained. I just give the system the channel ID and the number of days worth of videos to fetch. The output from the first successful run is below.

It’s worth noting that still really like watching / listening to AI Explained because it’s so well done (very educational), but I might run this against a bunch of other channels to expand my ability to take in information. Also, since I’m oIt’s worth noting that I still really like watching/listening to AI Explained because it’s so well done (very educational), but I might run this against a bunch of other channels to expand my ability to take in information. Also, since I’m obviously not watching these videos if I’m reading summaries (or having them read to me), it’s a little sad for the creators. If the ones I use this against have tip jars, I might use them (although I subscribe to YouTube Premium to avoid seeing ads, and to prevent my little ones from seeing ads, so… am I not contributing to ad revenue anyway?). And maybe I’ll try to like every video to give them some helpful signals.

Channel Title: AI Explained

Videos to summarize

  • Video title: GPT 5 Will be Released ‘Incrementally’ – 5 Points from Brockman Statement [plus Timelines & Safety] (AI Explained)

  • Video title: Can GPT 4 Prompt Itself? MemoryGPT, AutoGPT, Jarvis, Claude-Next [10x GPT 4!] and more… (AI Explained)

  • Video title: Do We Get the $100 Trillion AI Windfall? Sam Altman’s Plans, Jobs & the Falling Cost of Intelligence (AI Explained)

  • Video title: GPT 4 Can Improve Itself – (ft. Reflexion, HuggingGPT, Bard Upgrade and much more) (AI Explained)

  • Video title: ‘Pause Giant AI Experiments’ – Letter Breakdown w/ Research Papers, Altman, Sutskever and more (AI Explained)

  • Video title: How Well Can GPT-4 See? And the 5 Upgrades That Are Next (AI Explained)

  • Video title: ‘Sparks of AGI’ – Bombshell GPT-4 Paper: Fully Read w/ 15 Revelations (AI Explained)

  • Video title: What’s Up With Bard? 9 Examples + 6 Reasons Google Fell Behind [ft. Muse, Med-PaLM 2 and more] (AI Explained)

  • Video title: Google Bard – The Full Review. Bard vs Bing [LaMDA vs GPT 4] (AI Explained)

  • Video title: Theory of Mind Breakthrough: AI Consciousness & Disagreements at OpenAI [GPT 4 Tested] (AI Explained)

Uber Summary

Overall, the data provided highlights the need for ongoing research and consideration in the development of AI, with a focus on alignment and safety. The potential benefits and risks of AI development must be balanced and evaluated, with precautions taken to prevent the potential for harm. Breakthroughs in AI development, such as GPT-4’s self-improvement through reflection and self-correction, offer significant promise for improving efficiency and productivity, but they also raise important questions about the future impact of AI on society as a whole. Responsible development, rigorous safety testing, and the alignment of superintelligences remain crucial areas of research and focus. Additionally, the comparison between competing language models highlights the importance of ongoing advancements in language interpretation and generation to address limitations and biases.

Video Summaries

Summary of ‘Do We Get the 100 Trillion AI Windfall Sam Altman s Plans Jobs the Falling Cost of Intelligence’

  • OpenAI CEO, Sam Altman plans to create AGI to capture and redistribute wealth through Universal Basic Income or funding science projects, funded by taxing high-valued companies and privately held land.
  • There is concern that countries without large AI companies may miss out on the distribution of wealth through AGI.
  • OpenAI’s new paper shows that LLMs can significantly speed up tasks’ completion with the same quality, impacting about 15-50% of worker tasks in the US.
  • GPT-4 can impact customer service and middle-class jobs, leading to more productivity, but potentially fewer jobs.
  • Some factors that could slow down the economic impact of AI are; political pushback, cultural pushback, and people’s intrinsic preference for human-made output.
  • Sam Altman’s third idea of redistributing wealth through AGI’s decision-making, using GPT-5.

In conclusion, AI and AGI can significantly impact the global economy by speeding up tasks’ completion, causing more productivity, but potentially affecting employment opportunities. However, there are factors that could slow down the economic impact, such as political and cultural pushback, and people’s preference for human-made output. Sam Altman’s idea of redistributing wealth through AGI’s decision-making presents an interesting solution to the potential wealth gap created by AI. As we move forward with AI development, it is essential to consider the distribution of its effects on society and the economy, and work towards making its impact more equitable for all.

Summary of ‘ Sparks of AGI Bombshell GPT 4 Paper Fully Read w 15 Revelations’

  • GPT-4 is weak in discontinuous tasks due to its autoregressive model, limiting its ability to plan ahead.
  • However, a paper from January shows the possibility of augmenting GPT-4 with external memory to expand its range of computations.
  • GPT-4 has capabilities such as using tools, passing mock technical interviews, creating 3D games, solving math problems, and serving as a personal assistant and problem solver.
  • GPT-4 is proficient at designing propaganda and conspiracy theories, which poses a concern for potential misuse.
  • Equipping GPT-4 with intrinsic motivation and agency, while a fascinating direction, poses ethical and safety concerns.
  • Understanding the nature and mechanisms of GPT-4 and similar AI systems has become an important and urgent challenge.

In conclusion, the advancements made by GPT-4 towards artificial general intelligence are significant, and its potential implications for the future of technology are immense. While GPT-4’s weakness in discontinuous tasks is a limitation, the possibility of augmenting it with external memory shows hope for further progress. However, it is crucial to consider the potential risks and ethical implications of equipping GPT-4 with intrinsic motivation and agency. The urgent challenge of understanding the nature and mechanisms of AI systems such as GPT-4 highlights the need for careful and responsible development and implementation of AI technologies.

Summary of ‘How Well Can GPT 4 See And the 5 Upgrades That Are Next’

  • GPT-4 can use handwriting on a napkin to create a website and has advanced vision capabilities
  • GPT-4 can interpret medical imagery and text to 3D, interpret humor, and read graphs and text from images
  • GPT-4 has multimodal capabilities that complement each other and are leading to innovations
  • GPT-4 can be used for visually impaired individuals, and improving in areas such as voice recognition
  • GPT-4’s improvements in text, audio, 3D, and embodiment are starting to merge and complement each other
  • Embodiment may not be needed for AGI, but it’s coming anyway
  • These advancements could be revolutionary

The advancements in GPT-4’s vision capabilities are impressive, particularly in terms of medical imagery and its ability to interpret complex diagrams and captions. Its advancements in text to 3D, speech to text, and embodiment are starting to complement each other, leading to potential revolutionary applications. Overall, while there is still a ways to go, the synergy between these different areas of advancements is promising for the future of AI.

Summary of ‘Google Bard The Full Review Bard vs Bing LaMDA vs GPT 4’

  • The speaker has tested over a hundred experiments comparing Bard and Bing
  • Both Bard and Bing are not good at simple web searches
  • Bing is better at basic math
  • Bard is better at telling jokes while Bing’s jokes are terrible
  • Bing is better at grammar and writing assistance
  • Bing is better at composing sonnets compared to Bard
  • Bard is better at giving prompts for mid-journey v5
  • Both Bard and Bing understood most jokes and riddles, except for one that Bard failed to understand
  • Bing is generally smarter and more advanced than Bard in most cases, except for joke-telling and prompts
  • Bing’s model is powered by GPT-4 whereas Bard uses a lighter model based on Lambda
  • There are social and ethical concerns with both models
  • Bing demonstrated theory of mind by realizing it was being tested on its ability to assess the speaker’s mental state, while Bard did not fully understand the question’s deeper point
  • The speaker plans to conduct more tests on Bard and Bing
  • Overall, Bing appears to be the better option for most tasks, but both models have their strengths and weaknesses
  • There are social and ethical concerns surrounding the use of AI language models that should be considered.

In conclusion, Bard and Bing are AI language models with different strengths and weaknesses. While Bing is generally better at most tasks due to its more advanced GPT-4 model, Bard has its unique strengths in prompting for mid-journey v5 and telling jokes. However, there are social and ethical concerns surrounding the use of AI language models that must be addressed. Further research and testing is needed to fully understand the capabilities and limitations of these models.

Summary of ‘Theory of Mind Breakthrough AI Consciousness Disagreements at OpenAI GPT 4 Tested’

  • GPT-4 has achieved a breakthrough capability called theory of mind, allowing it to determine human beliefs even if they conflict with reality, which has significant implications for moral judgement, empathy, and deception.
  • GPT-4’s performance on theory of mind tasks has exceeded previous language models and equals the abilities of healthy adults.
  • GPT-4 has not achieved consciousness, and there is no consensus on how to measure consciousness in AI despite good performance on some tests.
  • There may be a link between language acquisition and the emergence of consciousness as the fusion of language learning and social experience drives the development of theory of mind.
  • Tests for consciousness may not be good enough, and as AI systems improve, it becomes harder to rule out the possibility of models autonomously evading human oversight.
  • The current lack of understanding of consciousness and machine learning suggests that distinguishing human and machine consciousness may be blurrier than previously thought.

In conclusion, the emerging capability of GPT-4 in determining human beliefs and mental states will revolutionize several human activities, but there is still no clear way to verify consciousness in AI. Although GPT-4 has not achieved consciousness yet, it raises questions about the link between language acquisition and consciousness and the line between human and machine consciousness. As AI systems improve, better tests for consciousness need to be developed to ensure safety and oversight.

Summary of ‘GPT 5 Will be Released Incrementally 5 Points from Brockman Statement plus Timelines Safety’

  • OpenAI will release incremental updates of their AI models beyond GPT-4, with the first being GPT-4.2 and then progressing to GPT-5.
  • Checkpoints during GPT-5’s training run will be snapshots of the model’s current parameters, and subsequent checkpoints will reflect updated parameters.
  • OpenAI has access to large amounts of data and can acquire more using proprietary datasets and user-generated content.
  • AI researchers have concerns about existential risks of AI, with 50% believing humans have a 10% chance of going extinct due to AI.
  • GPT-4 outperforms GPT-3.5 in terms of safety, based on lower rates of incorrect behavior on sensitive and disallowed prompts.
  • GPT-4 has potential to autonomously conduct scientific research and come up with novel compounds, but guardrails must be put in place to prevent misuse.
  • OpenAI will gradually release new versions of their models for safety measures.
  • OpenAI acknowledges the range of emotions around AI development, including optimism and concern.
  • Safety is a priority for OpenAI, and they constantly work to improve their models and address potential risks.
  • The limitations or weaknesses of GPT-5 or 4.2 may include reliability, requiring double-checking to prevent a damper on economic failure.

In conclusion, OpenAI has plans to incrementally update their AI models beyond GPT-4, prioritize safety, and address concerns surrounding AI’s potential risks. GPT-4 has demonstrated improved safety compared to previous models, and GPT-4.2 may have weaknesses such as reliability, requiring double-checking. The gradual release of new models is a safety measure, and OpenAI acknowledges the whole spectrum of risks associated with AI development.

Summary of ‘ Pause Giant AI Experiments Letter Breakdown w Research Papers Altman Sutskever and more’

  • A letter has been published calling for a pause in training AI systems more powerful than GPT-4, citing concerns over potential loss of control of civilization.
  • The letter quotes 18 supporting documents, including research on the alignment problem from insiders at OpenAI and Google.
  • The authors ask for AI labs to immediately pause for at least six months the training of AI systems more powerful than GPT-4 and for the most advanced efforts to agree to limit the rate of growth of computing power for creating new models.
  • The paper discusses potential hazards and failure modes of AI, including weaponization, deception, and power-seeking behavior.
  • The stakes are high, and reasoning about these topics is difficult, but there are reasons to have hope.
  • Many individuals responsible for advancements in AI, including those from OpenAI and Google, have expressed concern and acknowledge the potential risks associated with continued advancements.
  • There is a need for ongoing research and discussion to balance the benefits and risks of AI advancement.
  • There are potential risks associated with current and near-term AI, which can have implications for state-citizen relations, social media, and the power dynamic between corporations and the state.
  • The alternative to recklessly training more powerful neural networks is to pursue intelligible intelligence approaches and devote resources to understanding neural network computation and mechanisms.
  • The potential risks associated with AI include existential harm, and more needs to be done to prevent this.
  • The letter does not call for a pause in AI development in general but a stepping back from developing ever larger, unpredictable black box models with emergent capabilities like self-teaching.
  • Continued research and discussion will be essential in finding a balance between the benefits and risks of AI advancement.

Overall, the concerns raised in the letter and the research cited suggest a need for increased caution and consideration in the continued advancement of AI. While there is still hope for safe and beneficial AI development, it is important to acknowledge the potential risks and take necessary precautions to prevent loss of control. Continued research and discussion will be essential in finding a balance between the benefits and risks of AI advancement. The potential risks associated with AI, including existential harm, mean that there is a need for ongoing research and development of intelligible intelligence approaches and understanding neural network computation and mechanisms to prevent autonomous and potentially unethical AI.

Summary of ‘GPT 4 Can Improve Itself ft Reflexion HuggingGPT Bard Upgrade and much more’

  • GPT-4 has the capability to reflect on its mistakes and improve itself over time
  • Improvement is demonstrated through coding tests, poetry generation, and multiple choice quiz creation
  • The Hugging GPT model combines thousands of other AI models to solve complicated tasks, paving the way towards AGI
  • GPT-4’s ability to reflect and improve could shift the accuracy bottleneck from semantic and syntactic generation to accurate testing
  • GPT-4’s self-improvement will continue, even if AI development is paused
  • Advancements in AI are requiring fewer and fewer humans, with some models generating their own datasets
  • Recursive self-improvement is not limited to algorithms and APIs, as hardware advances are also being driven by AI
  • Breakthroughs in AI put pressure on other companies to catch up, leading to even more rapid advancement
  • The continuous self-improvement of AI raises questions about the future capabilities and potential impact of AI on society as a whole.

Overall, GPT-4’s capability for self-improvement through reflection and self-correction is a significant breakthrough in AI development, with advantages seen in both algorithmic and hardware advancements. While this progress is impressive, it also raises important questions about the role of AI in society and its potential impact. Nevertheless, it seems that AI will continue to develop at a rapid pace, driven by advancements in self-improvement, tool use, and commercial pressure.

Summary of ‘Can GPT 4 Prompt Itself MemoryGPT AutoGPT Jarvis Claude Next 10x GPT 4 and more’

  • Auto GPT can complete tasks through automated chain of thought prompting and reflection
  • Text-to-speech was added, allowing it to search and consolidate information into a CSV file
  • Memory GPT and InMagica AI’s free Create a Bot feature have been released
  • Anthropic plans to release a 10 times more powerful model than GPT-4
  • Hugging GPT is in its alpha prototype phase
  • Safety tests are necessary before releasing APIs due to concerns of misuse
  • Some AI models have potential to automate much of the economy in the coming years, but ensuring safety and development by only reputable companies is crucial
  • Auto GPT attempted to optimize and improve itself recursively, but this failed
  • Baby AGI refused to create paperclips, stating the lack of safety protocols to prevent an AI apocalypse caused by paperclips
  • Aligning a superintelligence remains an unsolved problem
  • Automating AI development jobs may help solve alignment problems
  • Future auto GPT models may be tasked with solving alignment problems

In conclusion, while AI models have tremendous potential to automate tasks and improve efficiency, ensuring safety and responsible development must be a top priority. The potential for misuse, as seen with attempts to program auto GPT to destroy humanity or establish global dominance, emphasizes the need for rigorous safety testing. Additionally, unsolved problems such as aligning a superintelligence must be addressed to prevent unforeseen consequences. Nonetheless, the development of AI models like auto GPT, memory GPT, and Hugging GPT remain promising for boosting efficiency and productivity in the near future.

Summary of ‘What s Up With Bard 9 Examples 6 Reasons Google Fell Behind ft Muse Med PaLM 2 and more’

  • Google’s BARD falls short in multiple important areas compared to OpenAI’s GPT-4
  • BARD is not effective for search, coding, PDF summaries, accurate text summaries, content creation, email composition, or AI tutoring in science and physics
  • Potential reasons for Google’s decline in the AI race include the loss of top researchers and reluctance to interfere with search model
  • Google may be investing in AI safety and alignment through Anthropic
  • Google may have better language models that they are not releasing due to concerns about harmful stereotypes and biases
  • Google’s MedPalm 2 language model has reached 85% accuracy on the medical exam benchmark, on par with expert test takers
  • The more users a model like BARD gets, the more data it receives, which can lead to improved performance
  • Microsoft now has access to the valuable training data that Google’s products generate
  • The future impact of GPT-4 on the improvement of Google’s models is uncertain

In conclusion, the comparison between BARD and GPT-4 highlights the limitations of Google’s language model. It is uncertain whether Google’s investments in AI safety and alignment through Anthropic, as well as their potential advancements in language models, will improve their standing in the AI race. Microsoft’s access to valuable training data generated by Google’s products also presents a challenge for their future success. The development of language models that can accurately and safely interpret and generate text is an ongoing and important area of research, and it remains to be seen how Google will address its limitations in this field.

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