What is the relationship between AI and data science?
$begingroup$
I think they share a lot (e.g. machine learning is a subset of both, right?), but maybe both have elements the other doesn't have?
Could you name some in that case? Or is one a subset of the other?
What is the relationship between AI and data science?
For example, when it comes to the relationship of AI and ML, I always say AI is a superset of ML. And the distinguishing set is search algorithms, which I would include in AI but not in ML. Would search algorithms be included in data science?
definitions ai
asked Feb 10 '18 at 22:47
Martin ThomaMartin Thoma
6,1801353127
$endgroup$
add a comment |
$begingroup$
I think they share a lot (e.g. machine learning is a subset of both, right?), but maybe both have elements the other doesn't have?
Could you name some in that case? Or is one a subset of the other?
What is the relationship between AI and data science?
For example, when it comes to the relationship of AI and ML, I always say AI is a superset of ML. And the distinguishing set is search algorithms, which I would include in AI but not in ML. Would search algorithms be included in data science?
definitions ai
asked Feb 10 '18 at 22:47
Martin ThomaMartin Thoma
6,1801353127
$endgroup$
$begingroup$
Actually my personal interpretation ìs that AI is a big field that ML is a branch of that. At least based on what I have learnt these years from professor Russel's book about definitions of AI.
$endgroup$
– Media
May 12 '18 at 9:24
add a comment |
$begingroup$
I think they share a lot (e.g. machine learning is a subset of both, right?), but maybe both have elements the other doesn't have?
Could you name some in that case? Or is one a subset of the other?
What is the relationship between AI and data science?
For example, when it comes to the relationship of AI and ML, I always say AI is a superset of ML. And the distinguishing set is search algorithms, which I would include in AI but not in ML. Would search algorithms be included in data science?
definitions ai
asked Feb 10 '18 at 22:47
Martin ThomaMartin Thoma
6,1801353127
$endgroup$
I think they share a lot (e.g. machine learning is a subset of both, right?), but maybe both have elements the other doesn't have?
Could you name some in that case? Or is one a subset of the other?
What is the relationship between AI and data science?
For example, when it comes to the relationship of AI and ML, I always say AI is a superset of ML. And the distinguishing set is search algorithms, which I would include in AI but not in ML. Would search algorithms be included in data science?
definitions ai
definitions ai
asked Feb 10 '18 at 22:47
Martin ThomaMartin Thoma
6,1801353127
asked Feb 10 '18 at 22:47
Martin ThomaMartin Thoma
6,1801353127
asked Feb 10 '18 at 22:47
Martin ThomaMartin Thoma
6,1801353127
asked Feb 10 '18 at 22:47
Martin ThomaMartin Thoma
6,1801353127
asked Feb 10 '18 at 22:47
Martin ThomaMartin Thoma
6,1801353127
6,1801353127
$begingroup$
Actually my personal interpretation ìs that AI is a big field that ML is a branch of that. At least based on what I have learnt these years from professor Russel's book about definitions of AI.
$endgroup$
– Media
May 12 '18 at 9:24
add a comment |
$begingroup$
Actually my personal interpretation ìs that AI is a big field that ML is a branch of that. At least based on what I have learnt these years from professor Russel's book about definitions of AI.
$endgroup$
– Media
May 12 '18 at 9:24
$begingroup$
Actually my personal interpretation ìs that AI is a big field that ML is a branch of that. At least based on what I have learnt these years from professor Russel's book about definitions of AI.
$endgroup$
– Media
May 12 '18 at 9:24
$begingroup$
Actually my personal interpretation ìs that AI is a big field that ML is a branch of that. At least based on what I have learnt these years from professor Russel's book about definitions of AI.
$endgroup$
– Media
May 12 '18 at 9:24
add a comment |
2 Answers
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$begingroup$
Though neither are well defined, as commonly used they are somewhat orthogonal concepts.
In my opinion, AI has a fairly narrow definition - it is about optimization through actions. AI is about decision making, either in deterministic or probabilistic environments. Typically, this is operationalized as action selection to maximize some reward function, or equivalently to minimize some loss function. Supervised or unsupervised learning (i.e. machine learning) about your environment can be helpful in using your experience to aid in selecting optimal actions.
As it's commonly used, data science has no rigorous definition - businesses use the term to refer to anything from creating charts Excel to deep reinforcement learning models that can win Go. From the point of view of a practitioner, these have absolutely nothing in common. From the point of view of a business owner, the common thread is extracting meaning, and therefore value, from raw data. A data scientist is a 'meaning extraction layer'. How this operation is performed, and the techniques used (again in my experience), make no difference to the employer of a data scientist. The job title may as well be 'data magician'. But the point is that data + data science = business value, whether that comes in the form of insights into customer trends, causal analysis of marketing campaigns, or an AI bot that is 'rewarded' when it recommends you a movie that you like. I suppose that means that AI is a subset of data science - but you could also say the same thing about clear communication, so it's a bit of a non-statement.
answered Feb 11 '18 at 3:17
tomtom
1,518311
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add a comment |
$begingroup$
Artificial Intelligence focuses on understanding core human abilities such as vision, speech, language, decision making, and other complex tasks, and designing machines and software to emulate these processes. Some AI roles are more research focused and concentrate on finding the right model to solve the task, while others are more focused on training, monitoring, and deploying AI systems in production.
What Data Scientists do in industry varies considerably. Data Scientists are often interfacing with internal (and sometime external) teams to help direct decisions which drive business. Data Scientists are also directly involved in building data products. The day-to-day for data scientists may involve cleaning and manipulating lots of data, scoping and testing out high ROI projects, building out customized algorithms, and communicating results to the team and company clients.
http://esds.co.in/artificial-intelligence
answered 7 mins ago
Naveen ParmarNaveen Parmar
1
New contributor
Naveen Parmar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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2 Answers
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2 Answers
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$begingroup$
Though neither are well defined, as commonly used they are somewhat orthogonal concepts.
In my opinion, AI has a fairly narrow definition - it is about optimization through actions. AI is about decision making, either in deterministic or probabilistic environments. Typically, this is operationalized as action selection to maximize some reward function, or equivalently to minimize some loss function. Supervised or unsupervised learning (i.e. machine learning) about your environment can be helpful in using your experience to aid in selecting optimal actions.
As it's commonly used, data science has no rigorous definition - businesses use the term to refer to anything from creating charts Excel to deep reinforcement learning models that can win Go. From the point of view of a practitioner, these have absolutely nothing in common. From the point of view of a business owner, the common thread is extracting meaning, and therefore value, from raw data. A data scientist is a 'meaning extraction layer'. How this operation is performed, and the techniques used (again in my experience), make no difference to the employer of a data scientist. The job title may as well be 'data magician'. But the point is that data + data science = business value, whether that comes in the form of insights into customer trends, causal analysis of marketing campaigns, or an AI bot that is 'rewarded' when it recommends you a movie that you like. I suppose that means that AI is a subset of data science - but you could also say the same thing about clear communication, so it's a bit of a non-statement.
answered Feb 11 '18 at 3:17
tomtom
1,518311
$endgroup$
add a comment |
$begingroup$
Though neither are well defined, as commonly used they are somewhat orthogonal concepts.
In my opinion, AI has a fairly narrow definition - it is about optimization through actions. AI is about decision making, either in deterministic or probabilistic environments. Typically, this is operationalized as action selection to maximize some reward function, or equivalently to minimize some loss function. Supervised or unsupervised learning (i.e. machine learning) about your environment can be helpful in using your experience to aid in selecting optimal actions.
As it's commonly used, data science has no rigorous definition - businesses use the term to refer to anything from creating charts Excel to deep reinforcement learning models that can win Go. From the point of view of a practitioner, these have absolutely nothing in common. From the point of view of a business owner, the common thread is extracting meaning, and therefore value, from raw data. A data scientist is a 'meaning extraction layer'. How this operation is performed, and the techniques used (again in my experience), make no difference to the employer of a data scientist. The job title may as well be 'data magician'. But the point is that data + data science = business value, whether that comes in the form of insights into customer trends, causal analysis of marketing campaigns, or an AI bot that is 'rewarded' when it recommends you a movie that you like. I suppose that means that AI is a subset of data science - but you could also say the same thing about clear communication, so it's a bit of a non-statement.
answered Feb 11 '18 at 3:17
tomtom
1,518311
$endgroup$
add a comment |
$begingroup$
Though neither are well defined, as commonly used they are somewhat orthogonal concepts.
In my opinion, AI has a fairly narrow definition - it is about optimization through actions. AI is about decision making, either in deterministic or probabilistic environments. Typically, this is operationalized as action selection to maximize some reward function, or equivalently to minimize some loss function. Supervised or unsupervised learning (i.e. machine learning) about your environment can be helpful in using your experience to aid in selecting optimal actions.
As it's commonly used, data science has no rigorous definition - businesses use the term to refer to anything from creating charts Excel to deep reinforcement learning models that can win Go. From the point of view of a practitioner, these have absolutely nothing in common. From the point of view of a business owner, the common thread is extracting meaning, and therefore value, from raw data. A data scientist is a 'meaning extraction layer'. How this operation is performed, and the techniques used (again in my experience), make no difference to the employer of a data scientist. The job title may as well be 'data magician'. But the point is that data + data science = business value, whether that comes in the form of insights into customer trends, causal analysis of marketing campaigns, or an AI bot that is 'rewarded' when it recommends you a movie that you like. I suppose that means that AI is a subset of data science - but you could also say the same thing about clear communication, so it's a bit of a non-statement.
answered Feb 11 '18 at 3:17
tomtom
1,518311
$endgroup$
Though neither are well defined, as commonly used they are somewhat orthogonal concepts.
In my opinion, AI has a fairly narrow definition - it is about optimization through actions. AI is about decision making, either in deterministic or probabilistic environments. Typically, this is operationalized as action selection to maximize some reward function, or equivalently to minimize some loss function. Supervised or unsupervised learning (i.e. machine learning) about your environment can be helpful in using your experience to aid in selecting optimal actions.
As it's commonly used, data science has no rigorous definition - businesses use the term to refer to anything from creating charts Excel to deep reinforcement learning models that can win Go. From the point of view of a practitioner, these have absolutely nothing in common. From the point of view of a business owner, the common thread is extracting meaning, and therefore value, from raw data. A data scientist is a 'meaning extraction layer'. How this operation is performed, and the techniques used (again in my experience), make no difference to the employer of a data scientist. The job title may as well be 'data magician'. But the point is that data + data science = business value, whether that comes in the form of insights into customer trends, causal analysis of marketing campaigns, or an AI bot that is 'rewarded' when it recommends you a movie that you like. I suppose that means that AI is a subset of data science - but you could also say the same thing about clear communication, so it's a bit of a non-statement.
answered Feb 11 '18 at 3:17
tomtom
1,518311
answered Feb 11 '18 at 3:17
tomtom
1,518311
answered Feb 11 '18 at 3:17
tomtom
1,518311
answered Feb 11 '18 at 3:17
tomtom
1,518311
1,518311
add a comment |
add a comment |
$begingroup$
Artificial Intelligence focuses on understanding core human abilities such as vision, speech, language, decision making, and other complex tasks, and designing machines and software to emulate these processes. Some AI roles are more research focused and concentrate on finding the right model to solve the task, while others are more focused on training, monitoring, and deploying AI systems in production.
What Data Scientists do in industry varies considerably. Data Scientists are often interfacing with internal (and sometime external) teams to help direct decisions which drive business. Data Scientists are also directly involved in building data products. The day-to-day for data scientists may involve cleaning and manipulating lots of data, scoping and testing out high ROI projects, building out customized algorithms, and communicating results to the team and company clients.
http://esds.co.in/artificial-intelligence
answered 7 mins ago
Naveen ParmarNaveen Parmar
1
New contributor
Naveen Parmar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
Artificial Intelligence focuses on understanding core human abilities such as vision, speech, language, decision making, and other complex tasks, and designing machines and software to emulate these processes. Some AI roles are more research focused and concentrate on finding the right model to solve the task, while others are more focused on training, monitoring, and deploying AI systems in production.
What Data Scientists do in industry varies considerably. Data Scientists are often interfacing with internal (and sometime external) teams to help direct decisions which drive business. Data Scientists are also directly involved in building data products. The day-to-day for data scientists may involve cleaning and manipulating lots of data, scoping and testing out high ROI projects, building out customized algorithms, and communicating results to the team and company clients.
http://esds.co.in/artificial-intelligence
answered 7 mins ago
Naveen ParmarNaveen Parmar
1
New contributor
Naveen Parmar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
Artificial Intelligence focuses on understanding core human abilities such as vision, speech, language, decision making, and other complex tasks, and designing machines and software to emulate these processes. Some AI roles are more research focused and concentrate on finding the right model to solve the task, while others are more focused on training, monitoring, and deploying AI systems in production.
What Data Scientists do in industry varies considerably. Data Scientists are often interfacing with internal (and sometime external) teams to help direct decisions which drive business. Data Scientists are also directly involved in building data products. The day-to-day for data scientists may involve cleaning and manipulating lots of data, scoping and testing out high ROI projects, building out customized algorithms, and communicating results to the team and company clients.
http://esds.co.in/artificial-intelligence
answered 7 mins ago
Naveen ParmarNaveen Parmar
1
New contributor
Naveen Parmar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
Artificial Intelligence focuses on understanding core human abilities such as vision, speech, language, decision making, and other complex tasks, and designing machines and software to emulate these processes. Some AI roles are more research focused and concentrate on finding the right model to solve the task, while others are more focused on training, monitoring, and deploying AI systems in production.
What Data Scientists do in industry varies considerably. Data Scientists are often interfacing with internal (and sometime external) teams to help direct decisions which drive business. Data Scientists are also directly involved in building data products. The day-to-day for data scientists may involve cleaning and manipulating lots of data, scoping and testing out high ROI projects, building out customized algorithms, and communicating results to the team and company clients.
http://esds.co.in/artificial-intelligence
answered 7 mins ago
Naveen ParmarNaveen Parmar
1
New contributor
Naveen Parmar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered 7 mins ago
Naveen ParmarNaveen Parmar
1
New contributor
Naveen Parmar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered 7 mins ago
Naveen ParmarNaveen Parmar
1
answered 7 mins ago
Naveen ParmarNaveen Parmar
1
1
New contributor
Naveen Parmar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Naveen Parmar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Naveen Parmar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
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$begingroup$
Actually my personal interpretation ìs that AI is a big field that ML is a branch of that. At least based on what I have learnt these years from professor Russel's book about definitions of AI.
$endgroup$
– Media
May 12 '18 at 9:24