Lmst

»#AI worse than humans at #summarising information, trial finds: A test of AI for Australia's corporate regulator found that the technology might actually make more work for people, not less.« https://www.crikey.com.au/2024/09/03/ai-worse-summarising-information-humans-government-trial/?eicker.news #tech #media

We just published a new 🎥 of #JCON EUROPE 2024!
Watch Miro Wengner talking about 'Boost Delivery Stream with #Code Discipline Engineering'

Gang Of Four has done an amazing job of #summarising and #identifying common #challenges that…

Watch it now: https://youtu.be/K8P1VpcczMQ

When ChatGPT summarises, it actually does nothing of the kind. – R&A IT Strategy & Architecture

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📌 Summary: LLM Chatbots, like ChatGPT, are not effective at generating reliable summaries of texts. Instead, they tend to simply shorten the text, often omitting important information or misrepresenting key points. This is due to a fundamental difference between the two processes: summarising requires a deep understanding of the text, while shortening does not. The use of LLM Chatbots in business and professional settings requires careful consideration, as they may not be able to provide the level of reliability and accuracy needed for critical tasks.

🎯 Key Points:
- LLM Chatbots tend to shortening rather than summarising texts.
- The process of summarising requires a deep understanding of the text, while shortening does not.
- LLM Chatbots are influenced by two key inputs: the parameters (based on training material) and the context (the prompts and answers up until the last generated or user-typed text).
- The parameters often dominate the summary, particularly for widespread topics, while the context dominates when it is relatively small and the subject is not well-represented by the parameters.

🔖 Keywords:
#LLMChatbots
#ChatGPT
#Summarising
#TextShortening
#Parameters
#Context
#TrainingMaterial
#GenerativeAI

#LLM #Summarising Abilities Comparison.

Tested 13 #AI #models available for #self-hosting on consumer hardware:
#llama3 vs #phi3 vs 3rd parties and the difference is huge.

The best in mid-weight is #llama3:8b-instruct-fp16.

See for details:
https://www.glukhov.org/post/2024/07/llm-summarising-comparison/

After reading and summarising J.R.R. Tolkien’s ‘Lord of the Rings’ for a Hollywood studio, American writer Helene Hanff billed them, hung out some laundry, and made dinner.

#tolkien #lordoftherings #lotr #reading #writing #reviewing #summarising #facts

#summarising

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