Kingsley,
Your reply shows how and why many applications of LLMs can be valuable.
KI: [They] can be more concise, aligned with the objectives of the message. In my experience, NotebookLM encourages a more disciplined approach to communication. It also highlights an often-overlooked aspect of LLMs—they’re just tools. Operator skills still significantly impact the output, meaning one size still doesn’t fit all in our diverse world :)
I agree that they can gather valuable information and produce useful results, but the human user has to evaluate the results. In your example, 6 out of 8 steps depend on some human to accept, reject, or guide what the LLM-based technology is doing.
Our Permion.ai company uses LLMs for what they do best, The symbolic methods of our VivoMind company (prior to 2010) were very advanced for that time. The new Permion.ai technology combines the best features of the symbolic methods with the LLM methods. It builds on the good stuff, rejects the bad stuff, and gets advice from the users about the doubtful stuff.
John
From: "Kingsley Idehen' via ontolog-forum" <ontolog-forum@googlegroups.com>
Hi Dan,
On 10/11/24 8:18 AM, 'Dan Brickley' via ontolog-forum wrote:
Something like
- What are you trying to do? Articulate your objectives using absolutely no jargon.
- How is it done today, and what are the limits of current practice?
- What is new in your approach and why do you think it will be successful?
- Who cares? If you are successful, what difference will it make?
- What are the risks?
- How much will it cost?
- How long will it take?
- What are the mid-term and final “exams” to check for success?
Yes, but it can be more concise, aligned with the objectives of the message. In my experience, NotebookLM encourages a more disciplined approach to communication. It also highlights an often-overlooked aspect of LLMs—they’re just tools. Operator skills still significantly impact the output, meaning one size still doesn’t fit all in our diverse world :)
Kingsley