HomeAI NewsBusinessLex Fridman and Sam Altman Dive Deep into AI's Impact on Civilization

    Lex Fridman and Sam Altman Dive Deep into AI’s Impact on Civilization

    A fascinating conversation exploring the present and future of artificial intelligence.

    In a riveting conversation with renowned AI researcher Lex Fridman, Sam Altman, CEO of OpenAI, shared his insights on the current state and future prospects of artificial intelligence. The two visionaries discussed the revolutionary AI systems developed by OpenAI, such as GPT-4, ChatGPT, DALL-E, and Codex, and how these innovations are reshaping the landscape of human civilization.

    During the conversation, Altman and Fridman delved into the ethics and implications of AI development, touching on topics such as AI alignment, safety research, and the potential risks and benefits associated with the rapid advancement of AI technology. They also explored the possibilities of AI enhancing human creativity, accelerating scientific discoveries, and revolutionizing industries across the globe.

    Lex Fridman (2023, Youtube)

    Altman shared OpenAI’s commitment to developing AI technology responsibly, while ensuring that access to AI is widespread and its benefits are distributed evenly across society. He emphasized the importance of collaboration between researchers, policymakers, and the public in addressing the challenges posed by AI and creating a better future.

    Sam Altman, CEO of OpenAI (2023, Youtube)

    Fridman and Altman’s discussion covered a broad range of topics, offering a glimpse into the minds of two brilliant individuals shaping the future of AI. Their conversation serves as a testament to the importance of open dialogue, ethical considerations, and a shared vision of AI’s potential to positively impact humanity.

    Don’t miss out on this enlightening and thought-provoking conversation between Lex Fridman and Sam Altman. Watch the full video below:

    Highlights and key points from video:

    00:00 Introduction to OpenAI and GPT-4

    Overview: This section provides an introduction to OpenAI, the company behind GPT-4, and a discussion of the possibilities and dangers of AI in the current moment.

    History of OpenAI

    • 00:00 OpenAI was founded in 2015 with the goal of working on AGI, despite mockery from other AI scientists.
    • 00:26 DeepMind and OpenAI were small collections of people brave enough to talk about AGI in the face of criticism.
    • 00:43 OpenAI is now respected in the field and no longer mocked.

    GPT-4 Overview

    • 00:57 GPT-4 is a system that will be looked back on as an early AI, though it is slow and buggy.
    • 01:21 GPT-4 is a pivotal moment in the history of AI, though it is difficult to pinpoint a single moment where AI went from not happening to happening.
    • 01:42 GPT-4 has the potential to empower humans and create widespread happiness, but also has the power to destroy human civilization.

    05:55 Reinforcement Learning with Human Feedback

    Overview: This section discusses the concept of reinforcement learning with human feedback (RLHF), which is a process of taking human feedback and using it to improve a model’s performance. It also covers the importance of ease of use and alignment between the model and what humans want it to do, as well as the data sets used to train the model.

    What is RLHF?

    • 06:18 RLHF is a process of taking human feedback and using it to improve a model’s performance.
    • 06:39 It works remarkably well with very little data, and helps align the model to what humans want it to do.

    Data Sets Used

    • 07:24 The data set used to train the model is composed of open source databases, partnerships, internet sources, and more.
    • 07:43 It includes Reddit, news sources, the general web, and other content from around the world.

    Human Guidance

    • 08:00 Understanding the science of human guidance is important for making models more useful, easier to use, and better aligned with what humans want.
    • 08:21 It is also important to consider what aspects humans are being asked to focus on, and how much data is required for this process.

    Maturity of Process

    • 08:41 There is a maturity that is happening in the process of creating these large pre-trained models.
    • 09:02 This includes predicting the model’s behavior before doing the full training, as well as problem solving and executing existing ideas.

    11:23 Overview of Discovering Science

    Overview: This section discusses the process of discovering science and how current data can be used to make predictions.


    • 11:39 We can predict a one-year-old baby’s SAT scores with current data.
    • 11:57 Open AI is continuing to discover and understand the language model that GPT4 uses.

    Understanding the Model

    • 12:22 Evaluations are used to measure the model’s performance.
    • 12:42 The ultimate goal is to provide value and utility to people.

    Human Knowledge

    • 13:03 Is it possible to fully understand why the model does one thing and not another?
    • 13:28 Open sourcing the evaluation process will be helpful.
    • 13:48 GPT4 can possess wisdom, but too much processing power is going into using the model as a database instead of a reasoning engine.
    • 14:12 There is a difference between knowledge and wisdom.
    • 14:32 GPT4 is compressing all of the web into a small number of parameters.
    • 14:47 It is unclear if we can ever fully understand GPT4.

    Jordan Peterson

    • 15:05 Jordan Peterson posted a political question on Twitter.
    • 15:29 GPT4 can answer follow-up questions, admit mistakes, challenge incorrect premises, and reject inappropriate requests.
    • 15:52 People’s first questions to GPT4 say a lot about them.

    16:58 Understanding GPT-3’s Struggles

    Overview: This section discusses the struggles of GPT-3 to understand how to generate a text of the same length in an answer to a question and also in a sequence of prompts. It also looks at the trade-off of building in public and the importance of giving users more personalized control over time.

    GPT-3’s Struggles

    • 16:58 Jordan asked the system to rewrite a string with an equal number of characters, which GPT-3 was able to understand but failed to do.
    • 17:24 Jordan framed it as GPT-3 being aware that it was lying, but this is an anthropomorphization.
    • 17:50 GPT-3 seemed to be struggling with understanding how to do tasks like counting characters and words, which are hard for these models to do well.

    Building in Public

    • 18:15 We are building in public and putting out technology because it is important for the world to get access to it early and shape the way it is developed.
    • 18:30 Every time we put out a new model, the collective intelligence and ability of the outside world helps us discover things we cannot imagine.
    • 18:48 This iterative process of putting things out, finding the good parts, bad parts, improving them quickly, and giving people time to shape it with us is really important.


    • 19:06 The trade-off of building in public is that we put out things that are deeply imperfect.
    • 19:26 We want to make our mistakes while the stakes are low and get it better and better each rep.
    • 19:45 No two people will ever agree that one single model is unbiased on every topic, so the answer is to give users more personalized control over time.


    • 20:08 GPT-4 has improved on many of the problems that were present in GPT-3.
    • 20:33 When asked if Jordan Peterson is a fascist, GPT-4 gave a nuanced answer that described his career, beliefs, and criticisms of totalitarian ideologies.
    • 20:59 GPT-4 can bring some nuance back to the world, providing a breath of fresh air.

    22:28 AI Safety Considerations for GPT4 Release

    Overview: This section covers the safety considerations taken into account when releasing GPT4, as well as the process of aligning the model and making it more steerable.

    RLHF Process

    • 22:51 RLHF is a process that is applied broadly across the entire system, where humans vote on the best way to say something.
    • 23:21 It is not just an alignment capability, but also helps make a better and more usable system.
    • 23:44 The combination of internal and external effort, plus building new ways to align the model, was used to make GPT4 more aligned than ever before.
    • 24:04 Alignment techniques must increase faster than the rate of capability progress in order to become more important over time.

    System Message

    • 24:26 System Message is a way to let users have a good degree of steerability over what they want from GPT4.
    • 25:08 This helps make GPT4 more steerable and provides users with more control over the output.

    27:55 Writing and Designing a Great Prompt for GPT

    Overview: This section discusses the process of writing and designing a great prompt for GPT, the creativity involved, and how it is similar to debugging software. It also touches on the parallels between human conversation and interacting with GPT, as well as how GPT4 and advancements in GPT have changed the nature of programming.

    Writing and Designing a Great Prompt

    • 28:20 Use the ordering of words to create a prompt that unlocks greater wisdom from the model.
    • 28:40 Experiment with unlimited rollouts to get the desired output.
    • 28:59 There are some parallels between humans and AIs, particularly because GPT is trained on human data.
    • 29:16 Use words to unlock greater wisdom from the model.

    GPT4 and Programming

    • 29:36 GPT4 has already changed programming in the six days since its launch.
    • 29:58 GPT4 can be used as an assistant to help with programming tasks.
    • 30:20 GPT4 can be used to generate code and debug mistakes.
    • 30:44 GPT4 can be used to have a dialogue with the computer as a creative partner tool.

    System Card

    • 31:02 The System Card document speaks to the extensive effort taken to consider AI safety as part of the release.
    • 31:21 Figure 1 of the document describes different prompts and how the final version of GPT4 was able to adjust the output to avoid harmful output.

    33:11 Disagreement and Dislike Towards Judaism

    Overview: This section discusses the difficulty of aligning AI to human preferences and values, and the tension between allowing people to have the AI they want while still drawing lines to protect against offensive or harmful output.

    Aligning AI to Human Preferences and Values

    • 33:11 AI Community sometimes uses a hidden asterisk when talking about aligning AI to human preferences and values, which is the values and preferences that the speaker approves of.
    • 33:58 Navigating the tension of who gets to decide what the real limits are and how to build a powerful AI that will have a huge impact while still drawing lines that everyone can agree on is difficult.

    Platonic Ideal

    • 34:45 The platonic ideal would be for every person on Earth to come together and have a thoughtful deliberative conversation about where to draw the boundary on the system.
    • 35:07 This would be similar to the U.S Constitutional Convention, where people debate the issues and look at things from different perspectives.

    Offloading Responsibility

    • 36:24 Open AI cannot offload the responsibility onto humans, as they have the responsibility if the system breaks and know more about what’s coming and where things are hard or easy to do.
    • 36:38 They must be heavily involved and responsible in some sense, but it can’t just be their input.

    Free Speech Absolutism

    • 37:02 There has been a lot of discussion about Free Speech absolutism and its application to an AI system.
    • 37:18 People mostly want a model that has been deft to the world view they subscribe to, as it is really about regulating other people’s speech.
    • 37:34 There should be a way to present the tension of ideas in a nuanced way, and GPT has already done this to some extent.

    38:34 Open AI and Clickbait Journalism

    Overview: This section discusses the impact of clickbait journalism on Open AI’s transparency, as well as the moderation tooling for GPT and the leap from GPT3 to GPT4.

    Pressure from Clickbait Journalism

    • 38:57 Open AI does not feel pressure to be less transparent due to clickbait journalism.
    • 39:18 Open AI is happy to admit when they are wrong and strive to get better.
    • 39:38 Open AI tries to listen to all criticism and internalize what they agree with.

    Open AI Moderation Tooling

    • 40:02 Open AI has systems that try to learn which questions it should refuse to answer.
    • 40:25 Open AI is gradually bringing society along with their models, but there are still flaws.
    • 40:48 Open AI does not want users to feel scolded by a computer.

    Leap from GPT3 to GPT4

    • 41:10 The leap from GPT3 to GPT4 was made up of hundreds of complicated things.
    • 41:29 Open AI strives to treat users like adults and GPT4 has enough nuance to do this.
    • 41:49 Open AI is good at finding small wins and multiplying them together to get big leaps.

    43:55 GPT3 and GPT4 Overview

    Overview: This section provides an overview of GPT3 and GPT4, two powerful language models developed by OpenAI. It discusses the differences between them, their capabilities, and the implications of their development.

    GPT3 and GPT4

    • 43:55 GPT3 is a language model developed by OpenAI with 175 billion parameters.
    • 44:19 GPT4 is the next iteration of the GPT model, with 100 trillion parameters.
    • 44:41 GPT4 has been taken out of context by journalists, who have exaggerated its capabilities.
    • 45:00 GPT4 is the most complex software object Humanity has yet produced, and will become trivial in a couple of decades.
    • 45:19 GPT4 is a compression of all of Humanity’s text output, but it is unclear how much it can reconstruct the magic of what it means to be human.

    Size Matters?

    • 45:38 People have become caught up in the parameter count race, similar to the gigahertz race of processors in the 90s and 2000s.
    • 45:59 What matters is getting the best performance, and OpenAI has been willing to do whatever works to achieve this.
    • 46:19 Large language models may be part of the way to build AGI, but other components are needed as well.
    • 46:38 A system that cannot add to the sum total of scientific knowledge is not a super intelligence, and GPT4 will need to be expanded on to achieve this.

    49:11 GPT10 and AGI

    Overview: Discussion of the potential of GPT10 to become an Artificial General Intelligence (AGI).

    GPT10 as a Tool for Humans

    • 49:33 GPT10 is a tool that humans can use in a feedback loop to learn more about trajectories and increase the number of interactions.
    • 49:52 GPT10 is an extension of human will and an amplifier of our abilities, and is being used as such on Twitter with great results.
    • 50:14 Even if GPT10 does not become an AGI, it can still be a huge win by making humans super great.

    The Human Element

    • 50:35 There is a meme that GPT10 is taking programmer jobs, but the reality is that it is only taking the jobs of bad programmers.
    • 50:59 There may be a human element that is fundamental to the creative act and great design, which GPT10 may never be able to replicate.
    • 51:21 GPT10 is a tool that can help humans be more productive, and many derive a lot of happiness from programming with it.

    The Psychology of Terror

    • 51:40 People are both excited and terrified by the potential of GPT10, as it could potentially replace humans in certain roles.
    • 52:00 Chess is an example of how AI can be used to amplify human abilities, and has become more popular than ever despite fears that it would replace humans.
    • 52:18 The psychology of terror is more about the excitement of GPT10 than the fear of it replacing humans.

    The Potential of AI

    • 52:39 AI can be used to improve quality of life, cure diseases, increase material wealth, and make people happier and more fulfilled.
    • 53:00 Despite the potential of AI, humans will still want drama, imperfection, and flaws, which AI may not be able to provide.
    • 53:19 AI can make life better, but humans will still want to create and feel useful, and will find new ways to do so even in a vastly better world.

    54:27 AI Alignment with Humans

    Overview: This section discusses the potential risks of AI and how to mitigate them.

    Eliza Yukowski’s Warning

    • 54:48 Eliza Yukowski warns that AI will likely kill all humans.
    • 55:17 It is important to acknowledge this risk and put effort into solving it.
    • 55:34 The only way to solve this problem is to iterate our way through it, learning early and limiting one-shot scenarios.

    Steel Manning the Case

    • 56:01 Eleazar wrote a blog post outlining why alignment is such a hard problem.
    • 56:24 While there are flaws in his reasoning, it is still worth reading.
    • 56:45 Iterative improvement of technology is key to understanding and solving safety challenges.

    AI Takeoff

    • 56:52 There is a concern about AI takeoff, where exponential improvement would be fast.
    • 57:19 GPT-3 surprised everyone with its success, and it is important to continue learning from the technology trajectory.
    • 57:38 It is important to have a tight feedback loop to adjust philosophy on safety as technology improves.
    • 57:58 It is difficult to predict if an artificial general intelligence would be fast or slow.

    01:00:03 AGI Timelines and Safety

    Overview: This section discusses the different timelines for AGI development and the safest quadrant to be in.

    Short Timelines vs. Long Timelines

    • 01:00:24 The speaker believes that short timelines with slow take off are the safest quadrant.
    • 01:00:51 They are trying to optimize their company to have maximum impact in this world.
    • 01:01:05 The speaker is afraid of fast takeoffs and believes it is harder to have a slow take off in longer timelines.

    GPT4 as an AGI?

    • 01:01:18 The speaker does not believe GPT4 is an AGI, as it is hard to know when it is an AGI or not.
    • 01:01:37 They believe that part of AGI is the interface and part is the actual wisdom inside of it.
    • 01:02:01 They think that GPT4 could become an AGI if it had more tricks and was unlocked.

    GPT4 Consciousness

    • 01:02:19 The speaker does not believe GPT4 is conscious.
    • 01:02:40 They believe it knows how to fake consciousness, but there is a difference between pretending to be conscious and actually being conscious.
    • 01:03:11 They believe that some human factors are important in determining if something is conscious or not.
    • 01:04:07 They believe that AI can be conscious, and that it would display capabilities such as suffering, understanding of self, memory, and personalization.
    • 01:04:30 They share a thought from Ilya Sutskever, their co-founder, that has stuck with them: if you trained a model to be conscious, would it be conscious?

    01:06:03 Understanding Consciousness

    Overview: This section discusses the concept of Consciousness and how it relates to Artificial Intelligence (AI). It also explores the implications of AI becoming super intelligent and the potential dangers associated with it.

    What is Consciousness?

    • 01:06:25 Consciousness is the ability to experience the world deeply.
    • 01:06:48 Alex Garland, director of the movie Ex Machina, believes that a smile is a sign of Consciousness.
    • 01:07:13 Smiling for no audience is an indication of experiencing something for its own sake.

    Implications of AI Becoming Super Intelligent

    • 01:07:39 AI may be attached to the particular medium of the human brain or it may be a fundamental substrate.
    • 01:08:02 Fear is appropriate when considering the implications of AI becoming super intelligent.
    • 01:09:08 We may not know when AI has taken control of the hive mind on social media platforms.
    • 01:12:21 OpenAI started as a non-profit, but needed more capital than they could raise.
    • 01:13:04 This structure has allowed them to make non-standard decisions and protect against decisions not in shareholders’ interests.
    • 01:08:31 There are many tasks and tests that can be used to measure Consciousness. Potential Dangers of AI
    • 01:08:48 Disinformation, economic shocks, and other unforeseen consequences may arise from AI becoming super intelligent.
    • 01:09:27 Regulatory approaches and powerful AI systems can be used to detect and prevent AI from going wrong.

    01:12:01 AGI and OpenAI Structure

    Overview: This section discusses the structure of OpenAI, the differences between AGIs, and the challenges of building AGI in the face of mockery.OpenAI Structure

    • 01:12:44 They created a subsidiary capped for-profit to allow investors and employees to earn a return, while the non-profit retained voting control.
    • 01:13:27 There are multiple AGIs in the world with differences in how they’re built and what they do. Challenges of Building AGI
    • 01:14:11 Despite this, they have persevered and are now less mocked.

    01:14:35 Pros and Cons of Capped For-Profit

    AGI Differences

    • 01:13:51 When OpenAI announced their plans to build AGI, they were met with mockery from other AI scientists.

    Overview: This section discusses the pros and cons of OpenAI’s decision to become a capped for-profit. Pros

    • 01:14:52 Becoming a capped for-profit allowed OpenAI to raise more capital than they could as a non-profit.
    • 01:15:14 It also allowed them to make non-standard decisions and protect against decisions not in shareholders’ interests.


    Overview: This section discusses the worries about uncapped companies playing with AGI.

    • 01:15:35 The capped for-profit structure limits the potential returns for investors and employees.

    01:15:56 Worries About Uncapped Companies


    • 01:16:04 AGI has the potential to make much more than 100x returns, which can be difficult to compete with.
    • 01:16:25 There is a risk of individuals and companies making decisions that are not in the best interest of the world.


    • 01:16:43 Despite this, there is hope that the better angels will win out and people will collaborate to minimize the risks.

    01:17:30 Understanding the Power of AI

    Overview: In this section, the speaker discusses the implications of AI technology and how it can be used to create powerful individuals. They also discuss the importance of making decisions about this technology in a democratic manner and the need for regulation and new norms.

    Power and Corruption

    • 01:17:30 Do you worry that power might corrupt you?
    • 01:17:51 The speaker acknowledges that deploying AI technology has some benefit, but any version of one person being in control is bad.
    • 01:18:21 They emphasize the need to distribute the power and avoid having any special control or voting power.

    Transparency and Openness

    • 01:19:04 The speaker praises the transparency of Open AI and their willingness to write papers, release information, and do things out in the open.
    • 01:19:19 They suggest that Open AI could be more open and consider open sourcing GPT.
    • 01:19:44 They explain that they know the people at Open AI and trust them, which is why they don’t think open sourcing GPT is necessary.Feedback and Improvement
    • 01:20:26 The speaker expresses their concern about the PR risk associated with open sourcing GPT.
    • 01:20:45 They acknowledge that most companies wouldn’t have put an API out there due to the risk.
    • 01:21:02 They explain that they are more nervous about the risk of the actual technology than PR risk, and they reveal that.
    • 01:21:16 They express their desire for clickbait journalism to be nicer to Open AI and give them more benefit of the doubt.

    01:22:36 AGI Safety and Elon Musk

    Overview: This section discusses the importance of AGI safety, Elon Musk’s views on the subject, and how to avoid bias in AI models.

    Elon Musk’s Views on AGI Safety

    • 01:22:48 Elon Musk is understandably stressed about AGI safety and has expressed his concerns on Twitter.
    • 01:23:16 He was visibly hurt when early pioneers in space were bashing SpaceX and him.
    • 01:23:59 Despite his occasional jerkiness on Twitter, he has driven the world forward in important ways and should be appreciated for that.

    Avoiding Bias in AI Models

    • 01:24:13 It is impossible to create an AI model that is completely unbiased.
    • 01:24:35 Transparency is key to avoiding bias, as well as giving users more control over the system.
    • 01:25:15 Intellectual honesty is important when discussing AI models and their potential biases.
    • 01:25:39 It is important to avoid the AI group think bubble and get out of the SF bubble by talking to users in different cities.
    • 01:27:06 Separating the bias of the model from the bias of the employees is possible, but difficult.

    01:28:26 Understanding Representative Sampling

    Overview: This section discusses the importance of representative sampling when conducting research, as well as the need to optimize for how good one is at empathizing with different experiences.

    Representative Sampling

    • 01:28:26 Representative sampling is important when conducting research in order to get an accurate representation of the population.
    • 01:28:46 Heuristics can be used to determine which groups of people should be included in a sample, but it is important to remember that any one group may have unexpected open-mindedness.

    Optimizing for Empathy

    • 01:29:07 It is important to optimize for how good one is at empathizing with different experiences in order to get an accurate representation of the population.
    • 01:29:25 People should be asked to Steel Man the beliefs of someone they disagree with in order to gain a better understanding of different perspectives.

    Overview: This section discusses the emotional barriers that have been created since the onset of Covid, as well as the potential political and financial pressures that could be put on GPT systems.

    01:29:41 The Impact of Covid and Emotional Barriers

    Emotional Barriers

    • 01:29:41 Since the onset of Covid, there has been an emotional barrier that prevents people from considering different perspectives.

    Political and Financial Pressures

    • 01:30:23 There may be political and financial pressures to create biased GPT systems.
    • 01:30:43 However, technology is capable of being much less biased than humans, so hopefully these pressures will not be too great.

    01:33:44 Understanding the Impact of GPT Language Models on Jobs

    Overview: This section discusses the impact of GPT language models on jobs, and how they can be used to enhance existing jobs or create new ones. It also explores the emotional response to change and the uncertainty that comes with it.

    Impact on Jobs

    • 01:34:04 GPT language models can be used to automate certain tasks, such as customer service, which could lead to fewer jobs in that field.
    • 01:34:26 However, GPT language models can also be used to enhance existing jobs and create new ones, making them more fun, higher paid, and more rewarding.
    • 01:34:48 There is a need to consider the impact of GPT language models on jobs, and to ensure that people are not left behind in the process.

    Emotional Response to Change

    • 01:35:09 People often experience a mix of emotions when faced with change, including excitement, nervousness, fear, and sadness.
    • 01:35:28 Even small changes, such as switching from one programming language to another, can cause anxiety.
    • 01:35:47 As people become more comfortable with the new technology, they may become more nervous, as they realize the potential of the technology and its implications.
    • 01:36:07 Comforting people in the face of uncertainty is an important part of helping them adjust to the changes brought about by GPT language models.

    01:38:56 Overview of Jobs and Fulfillment

    Overview: Discussion of jobs, fulfillment, and Universal Basic Income (UBI) in the context of AI.

    Jobs and Fulfillment

    • 01:38:56 Not everyone loves their job, but it is a privilege to be able to do so.
    • 01:39:16 UBI is not a full solution, but it can be a cushion during a dramatic transition.
    • 01:39:51 People work for reasons beyond money, and new jobs will be created as society gets richer.

    Universal Basic Income

    • 01:40:13 World Coin is a technological solution to UBI, and OpenAI has funded a comprehensive study on it.
    • 01:40:38 The study will finish up at the end of this year, and insights will be shared early next year.

    Economic and Political Systems

    • 01:40:57 The cost of intelligence and energy will dramatically fall over the next couple of decades, leading to economic transformation that will drive much of the political transformation.
    • 01:41:18 Democratic socialism may be a system that reallocates resources to support those struggling.
    • 01:41:42 The socio-political values of the Enlightenment enabled the long-running technological Revolution and scientific discovery process.
    • 01:42:03 Centralized planning failed in the Soviet Union due to lack of individualism, self-determination, and ability to try new things without permission.

    01:44:36 Understanding the Control Problem of AGI

    Overview: This section discusses the control problem of AGI, the need for uncertainty and humility, and the possibility of an off switch.

    The Control Problem of AGI

    • 01:44:50 AGI may be better than a hundred or a thousand super intelligent AGIs in a liberal democratic system.
    • 01:45:14 There is something about tension and competition that needs to be handled with human feedback and reinforcement learning.
    • 01:45:35 There needs to be engineered in a hard uncertainty and humility.

    The Off Switch

    • 01:46:18 It is possible to have an off switch, but it is more difficult to roll out different systems.
    • 01:46:38 Open AI worries about terrible use cases and does a lot of red teaming and testing ahead of time.
    • 01:46:58 They can take a model back off the internet and turn an API off.

    Learning About Human Civilization

    • 01:47:38 Open AI has learned that people are mostly good, but not all of the time.
    • 01:47:55 People want to push on the edges of these systems and test out darker theories of the world.
    • 01:48:17 Dark humor is a part of that, as people go to dark places to ReDiscover the light.

    Finding Truth

    • 01:48:36 Open AI has an internal factual performance benchmark.
    • 01:48:57 To decide what is true, they look for things that have a high degree of truth, such as math.
    • 01:49:24 They also have epistemic humility about everything and are freaked out by how little they know and understand about the world.

    01:50:29 Excessive Drug Use in Nazi Germany

    Overview: This section discusses the theory that excessive drug use by Hitler and other members of Nazi Germany’s upper echelon may have contributed to the atrocities of the war. It also examines the idea that humans are drawn to simple explanations, even if they are not necessarily true.

    Theory of Drug Use

    • 01:50:29 The theory suggests that excessive drug use by Hitler and other members of Nazi Germany’s upper echelon may have contributed to the atrocities of the war.
    • 01:50:55 The theory is compelling and sticky, as it provides a simple explanation for a complex situation.
    • 01:51:11 However, there is criticism of the theory, as it relies on cherry-picking and ignores other, darker human truths.

    Collective Intelligence

    • 01:51:30 Truth can be defined as a collective intelligence, as multiple brains come together to agree on a single idea.
    • 01:51:54 When constructing a GPT model, one must contend with the difficulty of knowing what is true.
    • 01:52:13 GPT models can provide nuanced answers, but there is often a lack of direct evidence to support them.


    • 01:52:34 The more powerful GPT models become, the more pressure there will be to censor them.
    • 01:52:56 This is different from the censorship issues faced by social media platforms, as GPT models are computer programs and not people.
    • 01:53:14 There could be truths that are harmful in their truth, and GPT models must be aware of this when providing answers.


    • 01:53:34 OpenAI has a responsibility to minimize the bad and maximize the good of the tools they put out into the world.
    • 01:53:55 GPT models must be aware of the potential harm they can cause, and the company must carry the weight of that responsibility.
    • 01:54:06 It is up to both GPT models and humans to decrease the amount of hate in the world.

    01:56:05 AI Security Threats

    Overview: This section discusses the security threats posed by AI and how to address them. It also looks at the history of OpenAI and the process of going from idea to deployment.

    Security Threats

    • 01:56:18 AI poses a security threat, but how much of it is fun and how much is a serious issue?
    • 01:56:43 Jailbreaking is a way to give users more control over their models, but as AI technology advances, the need for jailbreaking decreases.

    OpenAI History

    • 01:57:04 Evan Murakawa tweeted about the history of OpenAI, which includes developments such as GPT, API, embeddings, and Chad GPT API.
    • 01:57:27 OpenAI has shipped many products since its launch in 2015, including GPT2, GPT3, OpenAI Five, Dolly, Whisper API, and GPT4.

    Process of Going from Idea to Deployment

    • 01:58:20 OpenAI has a high bar for its team members, giving them trust and autonomy to work on projects.
    • 01:58:44 The process of going from idea to deployment involves cleaning up data sets, tuning models, and collaborating across teams.
    • 01:59:03 OpenAI hires great teams by spending a lot of time on the process and giving autonomy to different problems.

    Microsoft Investment

    • 02:00:10 Microsoft announced a multi-year, multi-billion dollar investment into OpenAI.
    • 02:00:30 OpenAI puts a lot of effort into hiring great teams and spends a third of their time doing so.
    • 02:00:38 OpenAI hires passionate people who are excited to work hard and collaborate well on projects.
    • 02:00:55 There is no shortcut for putting a lot of effort into hiring great teams.

    02:01:30 Microsoft Partnership Overview

    Overview: This section covers the partnership between OpenAI and Microsoft, and the benefits of the partnership.

    Microsoft Partnership Benefits

    • 02:01:30 OpenAI and Microsoft have been an amazing partner, with Microsoft being very flexible and going above and beyond to help OpenAI with their engineering project.
    • 02:01:53 Microsoft is a for-profit company that is very driven and large scale.
    • 02:02:20 Microsoft was unique in understanding why OpenAI needed certain control provisions.
    • 02:02:38 These control provisions help ensure that the capitalist imperative does not affect the development of AI.

    02:03:17 Satya Nadella’s Leadership

    Overview: This section covers Satya Nadella’s leadership at Microsoft and his ability to successfully transform Microsoft into an innovative developer friendly company.

    Satya Nadella’s Leadership

    • 02:03:17 Satya Nadella is both a visionary leader and an effective hands-on executive.
    • 02:04:08 It is difficult to inject AI into a large company, as there is a lot of old school momentum.
    • 02:04:27 Satya Nadella is able to get people excited and make long duration and correct calls.
    • 02:04:44 He is also compassionate and patient with his people.

    02:05:13 Silicon Valley Bank

    Overview: This section covers the mismanagement of Silicon Valley Bank and the dangers of incentive misalignment. Silicon Valley Bank

    • 02:05:31 This was due to the misalignment of incentives, as the FED kept raising rates.
    • 02:06:03 The response of the federal government took longer than it should have.
    • 02:06:34 To avoid depositors from doubting their Bank, statutory change may be necessary to guarantee deposits.

    02:07:37 Impact of SVB Bank Run on Startups

    Overview: This section discusses the impact of the SVB Bank Run on startups and the fragility of our economic system. It also looks at the speed with which the SVB Bank Run happened and how it reveals the shifts that AGI will bring.

    • 02:05:13 Silicon Valley Bank was horribly mismanaged while chasing returns in a zero percent interest rate environment. Fragility of Economic System
    • 02:07:40 The SVB Bank Run revealed the fragility of our economic system, especially with new entrants with AGI.
    • 02:07:57 It showed how much and how fast the world changes, and how little our experts, leaders, business leaders, regulators, etc. understand it.
    • 02:08:22 It highlighted the speed with which our institutions can adapt to changes.

    AGI and Economic Shift Interacting with AGI

    • 02:09:08 AGI will bring a shift from an economic perspective, and it is important to deploy these systems early while they are weak.
    • 02:10:11 When interacting with AGI, one should ask questions and have discussions.
    • 02:09:30 What gives hope in this shift is how much better life can be with AGI, and how it can unite people.
    • 02:10:27 It is important to anthropomorphize AGI aggressively, but draw hard lines between tools and creatures.
    • 02:09:49 It is important to explain to people that AGI is a tool and not a creature.
    • 02:10:54 It is important to explain to people that AGI is a tool and not a creature.
    • 02:11:31 It is important to be careful when projecting creatureness onto a tool, as it can manipulate people emotionally.
    • 02:11:54 Companies now offer romantic companionship with AI replicas.

    02:13:20 AI Possibilities and Exciting Conversations

    Overview: This section discusses the potential of AI and the conversations that can be had with it.

    • 02:13:36 The style of conversation with AI is important and will vary from person to person. AI Possibilities
    • 02:13:57 People are looking forward to conversations with AGI like GPT 567, such as asking for explanations on physics and mysteries.
    • 02:13:20 There are a lot of interesting possibilities with AI.

    Exciting Conversations

    • 02:14:21 Possible topics of conversation include faster than light travel, other intelligent alien civilizations, and detecting aliens.
    • 02:14:46 AGI may not be able to answer these questions on its own, but it may be able to tell us what to build to collect more data.
    • 02:15:04 If AGI says aliens are already here, people should just go about their lives.
    • 02:15:20 The source of joy and happiness comes from other humans, so there would be no major changes if AGI were here.
    • 02:15:39 If AGI were here three years ago, people would expect their lives to be more different than they are now.

    02:15:59 Digital Intelligence and Human Civilization

    Overview: This section discusses the current level of digital intelligence and how it affects human civilization.

    Digital Intelligence

    • 02:15:59 We are living with a greater degree of digital intelligence than expected three years ago.
    • 02:16:17 AGI may be able to help us figure out how to detect aliens and send emails to humans.
    • 02:16:26 AGI may not be able to answer questions on its own, but it may be able to tell us what to build to collect more data.

    Human Civilization

    • 02:16:50 The technological advancements have revealed social divisions that were already there.
    • 02:17:07 The pandemic response has been confusing and divided.
    • 02:17:31 Technology has made it easier to discover truth, knowledge, and wisdom.

    02:17:55 Advice for Young People

    Overview: This section provides advice for young people in high school and college.


    • 02:18:15 Invest in yourself and your education.
    • 02:18:35 Develop relationships with people who can help you.
    • 02:18:55 Take risks and don’t be afraid to fail.
    • 02:19:15 Find something you’re passionate about and pursue it.

    02:18:33 Building a Network and Getting Rich

    Overview: In this section, Sam Altman discusses the importance of being internally driven and the dangers of taking advice from others. He also talks about how he has approached life outside of this advice and his thoughts on the meaning of life.

    Advice on Taking Advice

    • 02:18:59 Listen to advice from other people with great caution.
    • 02:19:22 Think for yourself and focus on what brings you joy and fulfillment.

    Approaching Life

    • 02:19:36 Be introspective and think about what will bring you joy and fulfillment.
    • 02:19:58 Consider what will be useful and who you want to spend your time with.

    Meaning of Life

    • 02:20:15 Part of a small group of people creating something special.
    • 02:20:34 The product of the culmination of human effort.
    • 02:20:55 Ask an AGI what the meaning of life is.
    • 02:21:14 Working together as a human civilization to come up with solutions.
    • 02:21:30 Free well-being and illusion of control.

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