What's the Difference Between Cognitive Computing and AI?

Database Trends and Applications
6 Jan 202003:33

TLDRThe transcript discusses the evolution of AI and cognitive computing, highlighting the distinction between fully autonomous AI systems and those that depend on human input. It emphasizes the market's confusion regarding these terms and the lack of clear guidelines, which led to the formation of the cognitive computing consortium. The script also points out the need for cross-departmental communication within organizations to effectively utilize cognitive applications and make informed decisions.

Takeaways

  • 📈 IBM began using the term AI around 2016, and by 2017, AI became a widely discussed topic.
  • 🤔 The distinction between cognitive computing and AI is based on the machine's ability to emulate human thought processes, behaviors, and interactions.
  • 🚀 Fully autonomous systems that can perform tasks without human input are considered AI.
  • 🤖 Most current AI systems are not fully autonomous, meaning they still require human interaction or oversight.
  • 🧠 Under the AI umbrella, the machine is seen as an author of its own actions, independent of human brain involvement.
  • 🔄 In contrast, cognitive computing involves machines that are dependent on human input, acting more as information tools or assistants.
  • 🌐 There is a general market confusion regarding the definitions and distinctions between cognitive computing and AI.
  • 📊 The lack of trusted resources and clear guidelines contributes to the confusion in the AI field.
  • 👥 Cross-silo communication within organizations is needed to fully leverage cognitive applications and make informed decisions.
  • 💡 The Cognitive Computing Consortium was founded to address the shortage of skillsets and to promote better understanding of these technologies.

Q & A

  • When did IBM start using the term AI?

    -IBM started using the term AI around 2016.

  • What is the main differentiation between AI and cognitive computing as proposed by the consortium?

    -The main differentiation is the extent to which the machine can emulate human thought processes, behaviors, and interactions. Fully autonomous systems that can perform the work of the human brain without any human intervention are considered AI, while cognitive computing involves machines that are dependent on human input and act more as information tools or assistants.

  • What does 'fully autonomous system' mean in the context of AI?

    -A fully autonomous system refers to an AI that can independently perform tasks traditionally requiring human brains, essentially authoring its own actions without the need for human input or control.

  • Why is there confusion around the vision of AI in the market?

    -The confusion arises from multiple vendor interpretations, a lack of trusted resources, credible guidelines, and information in short supply.

  • What led to the formation of the cognitive computing consortium?

    -The formation of the cognitive computing consortium was driven by the need for a clear understanding and guidelines around cognitive technologies, as well as the shortage of skillsets to deal with these technologies.

  • What is the significance of cross-silo networks within organizations regarding cognitive applications?

    -Cross-silo networks are crucial for different departments within organizations to communicate and collaborate effectively about cognitive applications, enabling them to generate decisions similar to those made by a human committee from those groups.

  • How does the term 'gray matter' relate to the human dependency in cognitive computing?

    -The term 'gray matter' is used metaphorically to describe the human intellect that sets up and influences the machine in cognitive computing. The machine's behavior is dependent on the human input, making it more of an assistant or tool rather than an independent actor.

  • What is the current era in AI and cognitive computing according to the transcript?

    -The current era is referred to as the 'early chaotic era' due to the confusion and lack of clear understanding around AI and cognitive technologies.

  • What are some challenges faced by organizations in adopting cognitive applications?

    -Challenges include a shortage of skillsets to deal with the technologies, missing cross-silo networks within the organization, and the need for better communication and collaboration between different departments.

  • What is the role of human interaction in cognitive computing?

    -In cognitive computing, human interaction is essential as the machine relies on human input and acts as an information tool or assistant, facilitating business processes or human intentions.

  • How does the transcript suggest improving the understanding and application of cognitive technologies?

    -The transcript suggests that improving understanding requires clear differentiation between AI and cognitive computing, fostering cross-silo networks, and providing credible guidelines and information.

Outlines

00:00

🤖 The Evolution and Terminology of AI and Cognitive Computing

This paragraph discusses the transition in terminology from cognitive computing to artificial intelligence (AI) and the distinction between the two. It explains that cognitive computing refers to systems that emulate human thought processes, behaviors, and interactions. The speaker proposes that only fully autonomous systems should be classified as AI, where the machine acts as an author of its actions, replacing human brainwork. In contrast, cognitive computing is described as machine behavior that is dependent on human input, with the machine serving as an information tool or assistant rather than an independent actor.

Mindmap

Keywords

💡AI

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. In the context of the video, AI is a term that has become widely used and is often confused with cognitive computing. The speaker discusses the differentiation between AI and cognitive computing, emphasizing that AI should be reserved for fully autonomous systems that can perform tasks independently without human intervention.

💡Cognitive Computing

Cognitive computing is a type of artificial intelligence that aims to simulate the human thought process by self-learning and interpretation of external data to make decisions. Unlike AI, cognitive computing doesn't necessarily imply full autonomy. In the video, the speaker proposes that cognitive computing involves machines emulating human thought processes and behaviors, and it may act more as an assistant or a tool rather than an independent decision-maker.

💡Autonomous Systems

Autonomous systems are those that can operate independently, without human input or control. They are capable of performing tasks traditionally requiring human intelligence, such as making decisions and solving problems. In the video, the speaker argues that fully autonomous systems should be considered AI, as they replicate the work of the human brain without the need for human intervention.

💡Human Thought Processes

Human thought processes refer to the complex cognitive functions that humans use to understand, interpret, and respond to the world around them. In the context of the video, the speaker suggests that cognitive computing and AI aim to emulate these processes, with AI systems striving to replicate the full spectrum of human cognitive abilities, including learning, reasoning, and problem-solving.

💡Behaviors and Interactions

Behaviors and interactions refer to the ways in which a system or entity acts and communicates with its environment or other entities. In the video, the distinction is made between AI systems that operate autonomously and those that are part of cognitive computing, where the machine's behavior is dependent on human input and interaction.

💡Early Chaotic Era

The term 'early chaotic era' in the context of the video refers to the current state of the AI and cognitive computing industry, characterized by confusion and a lack of clear, trusted resources or guidelines. This period is marked by multiple interpretations from vendors and a general uncertainty about the definitions and capabilities of AI and cognitive computing technologies.

💡Cognitive Computing Consortium

The Cognitive Computing Consortium is an organization founded to address the confusion and lack of resources in the AI and cognitive computing field. Its purpose is to provide a platform for sharing knowledge, establishing guidelines, and fostering collaboration among professionals in the industry.

💡Cross-Silo Networks

Cross-silo networks refer to the connections and communication between different departments or groups within an organization that traditionally operate independently, known as 'silos.' In the context of the video, the speaker emphasizes the importance of these networks for the effective implementation and decision-making involving cognitive computing applications.

💡Skillsets

Skillsets refer to the specific abilities, knowledge, and expertise required to perform certain tasks or roles effectively. In the video, the speaker points out that there is a shortage of skillsets needed to deal with AI and cognitive computing technologies, indicating a gap in the workforce's ability to understand and utilize these advanced systems.

💡Trusted Resources

Trusted resources are reliable and authoritative sources of information that can be used to guide decisions and actions. In the context of the video, the speaker discusses the lack of trusted resources in the AI and cognitive computing field, which contributes to the confusion and the 'early chaotic era' that the industry is currently experiencing.

💡Gray Matter

Gray matter is a term used in the video to metaphorically refer to the human brain and its cognitive functions. It is used to illustrate the dependency of machine behavior on human input and decision-making in cognitive computing, as opposed to the autonomy of AI systems.

Highlights

IBM started using the term AI by 2016, indicating a shift in the industry's language.

The term AI became widely used in 2017, leading to a broader discussion on the subject.

The distinction between cognitive computing and AI is based on the machine's ability to emulate human thought processes and behaviors.

Fully autonomous systems should be considered under the AI umbrella, as they replicate human brain functions without human intervention.

Most systems labeled as AI today are not fully autonomous, raising questions about the appropriate use of the term.

In the cognitive computing realm, machines are seen as tools or agents that depend on human input and are part of business processes.

The gray area between cognitive computing and AI is where the machine's behavior is influenced by human interaction.

There is a current confusion in the market regarding the vision and definition of AI and cognitive computing.

The lack of trusted resources and credible guidelines contributes to the confusion around AI and cognitive technologies.

The cognitive computing consortium was founded to address the shortage of skillsets and the need for cross-silo communication within organizations.

Cognitive applications require collaboration between different groups within an organization for effective decision-making.

The analogy of a human committee is used to describe the ideal decision-making process involving cognitive technologies.

The transcript discusses the early chaotic era in AI and cognitive computing due to multiple vendor interpretations and a lack of clear standards.

The importance of cross-silo networks within organizations for the effective use of cognitive applications is emphasized.

The transcript suggests that the machine's role in cognitive computing is more of an assistant rather than an independent actor.

The transcript highlights the need for a clear understanding and differentiation between AI and cognitive computing to avoid confusion.

The term 'cognitive' is used throughout the transcript to refer to applications that mimic human thought processes.

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