[ENG] 팔란티어 AIP와 chatGPT 그리고 테슬라

빅데이터닥터

15 Apr 202307:35

Summary

TLDRThe transcript discusses the evolving role of language in AI, highlighting the distinction between knowledge and language. It uses examples to illustrate how language, being imperfect and subjective, contrasts with mathematical precision. The speaker then explores the implications of AI's ability to interact with external programs, suggesting a future where AI like GPT could revolutionize how we communicate with technology. The narrative also touches on the potential for AI to transform enterprise operations, drawing parallels between integrated OS in cars and the need for a unified mathematical language in businesses to maximize AI's capabilities.

Takeaways

😎 The CTO of Palantir left a profound tweet suggesting that companies will be divided into those that understand the concept 'language is not knowledge' and those that do not.
🌐 Language is imperfect and subjective, as illustrated by the example of asking for the distance between Seoul and Busan, which can vary depending on the starting and ending points.
🤖 AI like GPT uses statistical probabilities to generate language, which can lead to nonsensical answers when faced with mathematical or precise questions.
🚀 Recent upgrades to AI have allowed it to interface with external programs to provide more accurate responses to mathematical and technical queries.
🔌 The introduction of GPT plugins signifies a shift where AI can interact with and utilize various software programs, potentially automating tasks that were previously done by humans.
🏢 The script suggests that while AI might replace human roles in certain tasks, the complexity and nuances of human language within collectives make it difficult for AI to fully integrate into all aspects of a company.
🤝 The success of AI integration in a company depends on the company's ability to unify its operations and data into a 'mathematical language' that AI can interact with effectively.
🚗 The example of Tesla versus legacy car manufacturers highlights the difference between individual components operating in their own 'languages' versus a unified OS that allows for integrated decision-making.
🧠 Palantir's approach, termed 'Ontology,' involves restructuring a company's data into a unified language that can be effectively utilized by AI, much like a company-wide OS.
💡 The script implies that the future of AI and company operations may lie in the seamless integration of AI with companies that have already transitioned to a 'mathematical language' structure.

Q & A

What did the CTO of Palantir tweet on April 1st?
-The CTO of Palantir tweeted that language is not knowledge and predicted that companies in the future would be divided into those that understand this and those that do not.
Why does the script argue that language is not mathematically perfect?
-The script argues that language is not mathematically perfect because it lacks precise definitions and can be subjective, as illustrated by the example of the distance from Seoul to Busan, which can vary depending on the starting and ending points and the mode of travel.
What is the significance of the statement 'Language is not knowledge' in the context of the script?
-The statement 'Language is not knowledge' signifies that language is an imperfect tool for conveying information, as it is often subjective and lacks the precision of mathematical language, which is crucial for accurate communication and understanding in the context of AI and data analysis.
How does the script use the example of the distance between Seoul and Busan to illustrate the imperfections of language?
-The script uses the example to show that without a clear definition of the starting and ending points, and the mode of travel, the information provided by language can be misleading and imprecise, thus not mathematically perfect.
What is the role of GPT in the context of language generation as described in the script?
-GPT is described as an AI that generates language through a statistical probability approach, selecting the most commonly used expressions based on statistical data rather than mathematical understanding.
Why might GPT provide incorrect answers to mathematical questions according to the script?
-GPT might provide incorrect answers to mathematical questions because it relies on statistical probability and language patterns rather than mathematical understanding, leading to incorrect or fabricated responses when faced with uncommon mathematical expressions.
How has GPT been upgraded to handle mathematical questions more accurately?
-GPT has been upgraded to handle mathematical questions by using external programs to read and provide results, rather than relying solely on its internal language generation capabilities.
What is the significance of GPT plugins in the context of the script?
-GPT plugins are significant because they allow GPT to interact with and utilize external programs, enabling it to perform tasks such as making recommendations and placing orders on shopping apps, thus bridging the gap between human language and computer functionality.
How does the script suggest that the use of GPT could change the way companies operate?
-The script suggests that the use of GPT could lead to companies prioritizing AI over human intelligence for productivity, potentially leading to a situation where AI, rather than humans, becomes the primary workforce in various enterprises.
What is the concept of 'Ontology' as mentioned in the script in relation to Palantir?
-In the script, 'Ontology' refers to the process of reconfiguring all the data of a company into a single, integrated language or system, similar to an operating system, which allows for a more unified and efficient operation of the company.
How does the script compare Tesla and legacy car manufacturers in terms of integration and AI potential?
-The script compares Tesla and legacy car manufacturers by highlighting that Tesla, with its integrated OS, can make unified decisions and integrate AI to perform tasks like self-driving, while legacy car manufacturers, lacking such integration, cannot achieve the same level of coordinated functionality.

Outlines

00:00

🤖 The Imperfection of Language and AI's Role

The paragraph discusses the limitations of language as a form of knowledge and how it contrasts with mathematical precision. It uses examples such as the distance between Seoul and Busan to illustrate how language can be imprecise without context. The speaker then compares this to AI's language generation capabilities, particularly GPT, which uses statistical probabilities to form sentences. The paragraph highlights that while AI can generate natural-sounding language, it lacks mathematical understanding, often leading to nonsensical answers to mathematical questions. However, recent advancements have allowed AI like GPT to interface with external programs to provide accurate responses to mathematical queries, signifying a breakthrough in human-computer communication where AI can now understand and respond in human language while also interfacing with computer programs in mathematical language.

05:02

🚀 The Integration of AI with Corporate Operations

This paragraph explores the potential of AI to revolutionize corporate operations by acting as an integrated operating system within a company. It suggests that while individual AI plugins can perform optimally within their domains, integrating them into a cohesive corporate strategy is challenging due to the inherent imperfections in human language and the diversity of 'languages' used across different departments within a company. The speaker then poses a hypothetical scenario where an AI like GPT interacts with a company that operates on a unified, mathematical language, leading to synergistic effects. The example of Tesla and its integrated OS is used to contrast with traditional car manufacturers, highlighting the benefits of a unified system where AI can interact with all components of a system, leading to autonomous decision-making. The paragraph concludes with a vision of companies like Palantir that are working towards creating a unified mathematical language for all corporate data, which could potentially maximize the synergies between AI and corporate operations.

Mindmap

Keywords

💡Language

Language in the video is discussed as a tool for communication that is inherently imperfect and subjective. It is contrasted with mathematical language, which is precise. The video uses examples like the distance between Seoul and Busan to illustrate how language can be ambiguous without specific context. The concept is central to the video's theme of how language interfaces with artificial intelligence and the potential for AI to misunderstand or provide incorrect information due to the subjective nature of language.

💡Knowledge

Knowledge, as mentioned in the video, is distinguished from language. It implies a deeper understanding that goes beyond the surface level of communication. The video suggests that while language can convey information, it may not always equate to knowledge, especially in the context of AI where the understanding of language is based on statistical probabilities rather than true comprehension.

💡Artificial Intelligence (AI)

AI is a central theme in the video, particularly focusing on language-generating AI like GPT. The video discusses how AI interprets and generates language based on statistical probabilities and how it has evolved to interact with external programs for more accurate responses. AI's role in the future of enterprise and its potential to revolutionize how businesses operate is a key point of discussion.

💡Mathematical Language

Mathematical language is presented as the opposite of natural language, being precise and unambiguous. The video uses it in contrast to natural language to highlight the challenges AI faces in understanding and generating human language. It also suggests that for AI to reach its full potential, it needs to operate within a framework that uses mathematical language, which is more aligned with its capabilities.

💡GPT (Generative Pre-trained Transformer)

GPT is a specific type of AI mentioned in the video that generates human-like text. The video discusses how GPT has been upgraded to utilize external programs for more accurate responses to mathematical questions, indicating a significant advancement in AI's ability to interact with and understand complex information.

💡Plugins

Plugins in the context of the video refer to the ability of AI like GPT to interact with external programs to enhance its functionality. The video suggests that with plugins, AI can perform tasks that would typically require human intelligence, such as making purchases or recommendations, blurring the line between AI and human roles in business.

💡Enterprise

Enterprise is discussed in the video in terms of how businesses will adapt to using AI. It suggests a future where enterprises might prioritize AI over human intelligence for certain tasks, leading to a potential shift in the workforce dynamics and the way businesses operate.

💡Incomplete Information

The concept of incomplete information is used in the video to describe the limitations of language and the challenges it presents for AI. Examples such as the distance between cities or locations are used to show how language can lack the specificity needed for precise AI understanding and action.

💡Subjective Expression

Subjective expression is highlighted as a characteristic of human language that makes it challenging for AI to interpret accurately. The video gives the example of 'nearby' to illustrate how such expressions are relative and can lead to misunderstandings when AI attempts to process them.

💡Ontology

Ontology, as used in the video, refers to a systematic representation of knowledge as a set of concepts within a domain. It is mentioned in the context of how Palantir, a company, restructures data into a unified language that can be understood and utilized by AI, suggesting a move towards a more integrated and efficient use of AI in enterprise.

💡Legacy Systems

Legacy systems are contrasted with integrated operating systems in the video, using the example of traditional cars versus Tesla. Legacy systems are depicted as separate, non-communicating components, whereas integrated systems, like Tesla's, allow for a holistic approach that can be enhanced by AI, leading to more innovative and efficient outcomes.

Highlights

The CTO of Palantir suggests a future where companies are divided into those that understand and those that do not understand the concept that 'language is not knowledge'.

Language is imperfect and cannot be considered as knowledge, as it lacks the precision of mathematical language.

An example is given comparing the imprecise nature of saying 'Seoul to Busan is 400km' without specifying the exact points or the type of distance (straight line, highway, etc.).

The conversational example of 'I'm near Gangnam Station Exit 4' is highlighted as being insufficient for precise location without mathematical coordinates.

Language's imprecision is contrasted with the visual information we use to complement incomplete linguistic data.

The creation of language by AI like GPT is based on statistical probability rather than mathematical understanding.

GPT might give nonsensical answers to mathematical questions due to the lack of linguistic expressions for rare mathematical concepts in its training data.

A recent upgrade allows GPT to use external programs to answer mathematical questions, showing an evolution where human language interfaces with computer language.

The introduction of GPT plugins suggests a future where AI can interact with various programs, potentially automating tasks that currently require human intelligence.

The concept of productivity in modern society is linked to the use of computer programs, which GPT can now potentially enhance through its plugins.

The concern is raised that if all companies adopt AI like GPT, it could lead to a scenario where Microsoft's AI dominates the world.

The argument is made that human collectives form unique languages within groups, which AI might not fully understand or integrate.

The challenge for AI in enterprises is that companies are made up of diverse groups with their own languages, making integration difficult.

The potential of a language AI like GPT is discussed in the context of it meeting a mathematically structured plugin or enterprise, hinting at significant synergistic effects.

Tesla and Palantir are given as examples of companies that have been integrating all their data into a single mathematical language, or 'Ontology', to function as a unified OS.

The idea that Tesla and Palantir have been preparing for over a decade to integrate AI with their unified OS is explored.

The narrative ends with a speculative question about what would happen if a language AI like GPT were to interact with a fully integrated, mathematically structured enterprise.