Sam Alman envisions a future where AI and OpenAI play a central role as the "core AI subscription" for users and developers. He sees OpenAI's models and infrastructure becoming the foundational layer, similar to an operating system, upon which other applications and services will be built.

Alman acknowledges that OpenAI has not yet fully figured out the API or SDK to enable this platform approach, but they are working towards it. He hopes this will enable "an unbelievable amount of wealth creation in the world" by allowing others to build on top of OpenAI's capabilities.

However, Alman's vision of OpenAI as the "core AI subscription" raises concerns about platform risk for entrepreneurs and developers. He recognizes the challenge of building on top of a platform that may also compete with its own offerings. Alman encourages others to build better "core AI subscription" services if they can, but admits that OpenAI's current lead and ability to adapt or copy successful models poses a significant challenge.

Alman also discusses the importance of voice as an interaction layer for AI, suggesting that OpenAI is working to crack the code on high-quality voice interfaces that could enable new classes of AI-powered devices. Additionally, he sees coding as a central capability for AI agents to "actuate the world" and interact with APIs on the user's behalf.

Overall, Alman paints a vision of OpenAI as the foundational platform for the future of AI, with the potential to become the dominant "core AI subscription" for both consumers and developers. However, this raises questions about the balance between platform control and enabling a thriving ecosystem of innovation.

OpenAI's ambition to become the "core AI subscription" and operating system-like platform for the future of computing presents both opportunities and challenges for entrepreneurs. While the company's advanced language models and APIs offer powerful capabilities, there is a risk of platform dependency and potential competition from the very platform they build on.

The key is to avoid becoming overly reliant on any single AI provider, including OpenAI. Entrepreneurs should explore ways to build flexible, modular systems that can integrate with multiple AI services and models. This may involve developing custom wrappers or abstraction layers to insulate their applications from the specifics of any particular platform.

Additionally, entrepreneurs should focus on building unique value-added services and applications that leverage AI capabilities in novel ways. Rather than simply replicating OpenAI's offerings, they should strive to create differentiated experiences that complement the platform's strengths.

Maintaining a diversified approach, investing in proprietary technology, and continuously exploring alternative AI providers can help mitigate the platform risk associated with building on OpenAI. Ultimately, the goal should be to create sustainable, resilient businesses that can adapt to the evolving AI landscape.

Sam Alman discusses the challenges large companies face in transforming their organizations to be more AI-native. He notes that smaller companies are often able to innovate and adopt new technologies faster than their larger counterparts.

The key issues he highlights are:

1. Organizational Inertia: Large companies get "incredibly stuck in their ways", with slow decision-making processes and outdated policies that prevent them from adapting quickly to technological changes.

2. Protecting Cash Cows: Successful companies often struggle to move away from their existing profitable business models, even as the market shifts around them - the classic "innovator's dilemma".

3. Automation vs. Transformation: Many companies focus on automating their existing processes rather than rethinking how AI can enable them to do things they couldn't do before. The real opportunity is in exploring new possibilities, not just optimizing the old.

4. Generational Divide: There is a stark difference in how younger and older employees approach and utilize AI tools like ChatGPT. Older workers tend to use them as Google replacements, while younger users integrate them more deeply into their workflows and decision-making processes.

In summary, Alman emphasizes that overcoming organizational inertia, embracing creative destruction, and adopting a forward-looking, transformative mindset are key for large enterprises to successfully leverage AI and keep pace with more agile competitors.

The generational divide in how people use AI tools like ChatGPT is quite striking. According to Sam Altman, younger users in their 20s tend to use these tools as an "operating system," integrating them deeply into their workflows and decision-making processes. They set up complex prompts and connections to leverage the AI's capabilities across various tasks.

In contrast, older users, such as those in their 30s, are more likely to use these AI assistants as a "Google replacement," turning to them for information and answers, but not necessarily integrating them as deeply into their lives.

Altman notes that the younger generation doesn't make major life decisions without first consulting the AI, using it as a kind of "life advisor" that provides insights and perspectives they may not have considered on their own. This level of reliance and integration is a stark contrast to the more limited use cases of older users.

Altman sees this generational divide as a natural progression, similar to how younger people were able to adapt to smartphones much more quickly than older generations. As AI tools become more sophisticated and ubiquitous, the way they are utilized will continue to evolve, with younger users leading the charge in pushing the boundaries of what's possible.

Sam Alman emphasizes the critical role of voice interaction in the future of AI devices. He acknowledges that OpenAI has not yet developed a satisfactory voice product, but believes they will eventually crack the code.

Alman sees voice interaction as enabling a new class of devices, where voice combined with graphical user interface (GUI) interaction can create a seamless and powerful user experience. He envisions voice as a primary input method, allowing users to interact with devices through natural language while still leveraging visual and touch-based interfaces.

Furthermore, Alman suggests that the ability to deliver human-level voice interaction will be a key differentiator, unlocking new possibilities for AI-powered devices. He believes voice will be central to how these models "actuate the world" and integrate with various APIs and services.

Overall, Alman's perspective highlights the importance of voice as a crucial input modality for the next generation of AI-driven devices and platforms. As OpenAI continues to develop its capabilities in this area, it could pave the way for more intuitive and versatile AI-powered experiences.

Coding is seen as a central and critical capability for the future of AI agents, according to Sam Altman. He believes that the ability to write code will be essential for AI models to "actuate the world" and interact with various APIs and systems.

Altman states that currently, when you ask ChatGPT for a response, you typically get text or an image back. However, he would like to see the ability to get a whole program or custom-rendered code as the output. This would allow the AI agents to take direct action and make things happen in the real world, rather than just providing information.

Coding is viewed as being more than just another vertical application of AI. It is seen as a core competency that will enable AI agents to truly integrate with and influence the world around them. Altman emphasizes that ChatGPT should be "excellent at writing code" in order to fulfill this vision.

The ability for AI agents to dynamically generate code on-demand is seen as a key differentiator and a central part of the future of AI-powered systems. This capability would allow agents to create interactive applications and automate tasks in ways that go beyond the traditional text-based responses.

According to Sam Altman, the value creation in the next 12 months will come from three key areas:

1. Building out more infrastructure: The foundational infrastructure for AI has been in development for years, making it difficult for new players to enter. However, the current focus is on building the necessary scaffolding to integrate AI into society.

2. Developing smarter models: While the initial wave of AI model development has already occurred, there is still room for improvement and innovation in this area.

3. Constructing the "scaffolding" to integrate AI: This includes aspects such as memory management, security, agent-based frameworks, and tool development that enable the effective utilization of AI models.

Altman believes that 2025 will be a year where agents, particularly in the domain of coding, will become a dominant category. In 2026, he expects AI to make significant scientific discoveries and assist humans in advancing knowledge. By 2027, he anticipates that AI-powered robots will transition from being a curiosity to becoming a serious economic driver of value.

The key takeaway is that the current focus is on building the necessary infrastructure, improving models, and creating the scaffolding to facilitate the widespread adoption and integration of AI into various aspects of society and the economy.

The future of computing and AI is rapidly evolving, with OpenAI playing a central role in shaping this landscape. Sam Altman's insights provide a glimpse into the ambitious goals and potential challenges faced by the company.

Key takeaways:

• OpenAI aspires to become the "core AI subscription" and operating system layer for the future of computing, integrating deeply with various platforms and devices.
• This vision presents both opportunities and risks for entrepreneurs and developers, who must navigate the potential platform dominance of OpenAI.
• The company is still working to define the optimal API and SDK to enable a thriving ecosystem, while also aiming to be the primary AI provider for consumers and businesses.
• Altman emphasizes the importance of voice interaction and agents that can dynamically generate code, hinting at the potential for new AI-powered devices and applications.
• The near-term focus is on building out the necessary infrastructure and scaffolding to integrate AI into society, with longer-term visions for AI-driven scientific discoveries and the rise of economically valuable robots.

Overall, Altman's perspective highlights the transformative potential of AI, as well as the complex balancing act that OpenAI must navigate to realize its ambitious vision while fostering a vibrant ecosystem of innovation.