Generative AI: Difference between revisions
From ACT Wiki
Jump to navigationJump to search
(Create page. Sources: Linked pages and The Treasurer - 2023 - Issue 3 - p10.) |
(Add link.) |
||
| (One intermediate revision by the same user not shown) | |||
| Line 3: | Line 3: | ||
(GenAI). | (GenAI). | ||
1. | |||
Artificial intelligence that can generate new text that is human-like, and in some cases may be difficult to distinguish from human-written text. | |||
2. | |||
More broadly, artificial intelligence that can generate new content including imagery, audio and synthetic data, as well as text. | |||
:<span style="color:#4B0082">'''''Improving financial forecasting with GenAI'''''</span> | |||
:"If I had to pick where GenAI would be most relevant, it would be the ability to accurately forecast financials. | |||
:The benefits of accurately being able to forecast would be tangible across both internal and external stakeholders. | |||
:This ranges across credit, liquidity and operational risk, all of which sit right within the remit of treasury functions. | |||
:Having the ability to generate accurate forecasts should reduce operational errors, improve cash management and facilitate access to greater sources of capital. | |||
:Better access to liquidity will then support areas that many businesses look to for their growth such as M&A." | |||
:''Robert Searle, chair of the ACT’s Future Leaders in Treasury Group - The Treasurer 2023 Issue 3 - p22.'' | |||
== See also == | == See also == | ||
* [[Artificial intelligence]] (AI) | * [[Artificial intelligence]] (AI) | ||
* [[Cash management]] | |||
* [[Chatbot]] | * [[Chatbot]] | ||
* [[ChatGPT]] | * [[ChatGPT]] | ||
* [[Credit risk]] | |||
* [[Generative pre-trained transformer]] | * [[Generative pre-trained transformer]] | ||
* [[Google Gemini]] | |||
* [[GPT-4]] | * [[GPT-4]] | ||
* [[Information technology]] | * [[Information technology]] | ||
* [[Large language model]] (LLM) | * [[Large language model]] (LLM) | ||
* [[Liquidity risk]] | |||
* [[M&A]] | |||
* [[Natural language]] | * [[Natural language]] | ||
* [[Natural language processing]] | * [[Natural language processing]] | ||
* [[Operational risk]] | |||
* [[Reinforcement Learning from Human Feedback]] (RLHF) | * [[Reinforcement Learning from Human Feedback]] (RLHF) | ||
* [[Robotics]] | * [[Robotics]] | ||
*[[Software]] | *[[Software]] | ||
*[[Stakeholder]] | |||
| Line 25: | Line 55: | ||
[[Category:The_business_context]] | [[Category:The_business_context]] | ||
[[Category:Treasury_operations_infrastructure]] | [[Category:Treasury_operations_infrastructure]] | ||
Latest revision as of 22:25, 11 May 2024
Information technology - software - natural language processing - artificial intelligence (AI).
(GenAI).
1.
Artificial intelligence that can generate new text that is human-like, and in some cases may be difficult to distinguish from human-written text.
2.
More broadly, artificial intelligence that can generate new content including imagery, audio and synthetic data, as well as text.
- Improving financial forecasting with GenAI
- "If I had to pick where GenAI would be most relevant, it would be the ability to accurately forecast financials.
- The benefits of accurately being able to forecast would be tangible across both internal and external stakeholders.
- This ranges across credit, liquidity and operational risk, all of which sit right within the remit of treasury functions.
- Having the ability to generate accurate forecasts should reduce operational errors, improve cash management and facilitate access to greater sources of capital.
- Better access to liquidity will then support areas that many businesses look to for their growth such as M&A."
- Robert Searle, chair of the ACT’s Future Leaders in Treasury Group - The Treasurer 2023 Issue 3 - p22.
See also
- Artificial intelligence (AI)
- Cash management
- Chatbot
- ChatGPT
- Credit risk
- Generative pre-trained transformer
- Google Gemini
- GPT-4
- Information technology
- Large language model (LLM)
- Liquidity risk
- M&A
- Natural language
- Natural language processing
- Operational risk
- Reinforcement Learning from Human Feedback (RLHF)
- Robotics
- Software
- Stakeholder
