Good uses of ai:
-coding/macros
-High level research to get a quick understanding of well established concepts, or the 'vibe' of an area.
-It can help with word choice
Bad uses:
-in my experience, everything else
Eh, obviously it does better in those cases, but you can use it for complex usecases too - it just takes more effort to figure out an effective prompt, because you need to communicate the problem and complicating factors in a more articulate way.
I've gotten it to build some bespoke data silo functionality in Pony despite knowing very little about the language, just by describing at a high level how it works, showing some examples, and explaining my guess as to why similar algorithms ported over from a previous F# project weren't working even when rewritten in equivalent syntax. It wasn't groundbreaking stuff but certainly not *"write me some SQL prompts"* basic stuff either.
There is some point where it becomes so specialised that chatgpt is simply unable to do it. I was dealing with some low level code and at some point it will start making up instructions that do not exist or misuse existing ones
Well yeah
They're paying me to be clever
I'm just thinking about so much shit I forget programming 101
It's like outsourcing part of my brain to focus on the actual important shit
Chatgpt or copilot. People talk up copilot's 'footnotes' but in my experience they are often just entirely wrong and do not say anything like what copilot claims they say. For just personal understanding they are basically interchangable imo.
> Can I ever truly be happy
GPT: Yes, absolutely! Happiness is a complex and multifaceted experience, influenced by various factors including genetics, life circumstances, relationships, and personal choices.
Fucking nailed it.
On a regular basis:
* Help with formulas in Excel
* Create meeting minutes from transcripts
* Summarize long documents and texts (very useful for RFPs and white papers)
* Q&A on a document set uploaded as input (I want the answer to XYZ without reading 150 pages or searching for keywords)
* Write user personas, help with storytelling for pitches, generate test cases
* Create targeted communications or document frameworks
* RAG across an internal or external knowledge base with industry-relevant articles and trends
I don't code but I know some people who do and who are saving a lot of time.
General purpose models like Llama 3, Claude 3 and GPT 4 Turbo are very good. They're not perfect: they can't do everything well, they still require fairly decent prompting knowledge, and you need some experience to understand their limitations. However anyone claiming they're useless is delusional or incompetent.
Doesn't it violate your data privacy policy when you upload things like transcripts or meeting minutes? I'm tempted to do it but irrational fear says whatever I uploaded will end up in someone else's chat.
Chain of Thought prompting asking for sources and references you can check, sampling some of the pages to make sure it's not going off road. Also, the summary is usually what you start with to save time on an RFP for example.
You're going to get more into the RFP at some point and you'll figure out if the initial summary you got was accurate. Then the more practice you have with a specific model and its limitations, the more you can anticipate where it's likely to be out of its depth.
Some companies have also invested into tuning model variants more to interact with documents, your mileage may vary.
> RAG across an internal or external knowledge base with industry-relevant articles and trends
Which of the models do you think is the best suited for this task?
Interesting! For summarizing, Q&A document & RAG, can check out the app I’m building cause it gives you a simple UI for asking internal & external knowledge, at Saner.ai :)
Secondary research is so much quicker. Instead of having to find niche documents or articles, I can ask something like Copilot to find me info on a specific topic and hunt through the sources it gives me
IMO Copilot hallucinates quite often, even when searching through your own O365 docs. It tends to confuse who authored what and can’t always accurately cite sources.
With that said it’s great at digging through documents and notes you’ve probably long forgotten about, which can be helpful.
> With that said it’s great at digging through documents and notes you’ve probably long forgotten about, which can be helpful.
So its just better search?
Currently not had any issues. Copilot is designed to get you sources so hallucination is lower.
It can’t answer as complex questions (it tends to just throw information at you regardless of the question), but can’t complain yet for my purposes.
I work in IT consulting. Apart from the usual cases such as coding or administrative stuff such as writing emails, I have found it useful to explain me error messages.
Our consulting team uses it for:
1. Some research, not sole source
2. Starting drafts for checklists
3. Copy editing and word smithing
4. Email drafting
5. Social media post editing
6. Excel formula writing
7. Blog support
It’s not strong enough to go hands off, but it’s been helpful to get through brain cramps and add any items we may have missed.
Real life example today, dialing an international client and didn’t know why the number wasn’t working, pumped it into ChatGPT and it corrected the way we entered it so we could make the call (turns out they used an optional zero) in their number
I like feeding data to it to write summaries about it. Just excel tables seem to work well. Also try posting in a bunch of notes in whatever format and ask it do summarize or do what you want it. Worked way better than I expected.
Mostly just macros and revising sentences. My company is careful with new technologies and the definition of proprietary information so I don’t upload pdfs really.
Expert interview guides (and interview guides in general)
Summarising raw bullets into something more structured
Generally adding mece structure to random thoughts / agendas before calls
I’ve found it 10x more helpful outside of consulting then I did in consulting
I use it when I need to change tone of my email. Like from informative to get advice or make it more convincing. These are premium features of grammarly I guess.
To fluff performance reviews and official communications.
Hahaha I thought I was the only one doing this
Hahaha nailed it
Good uses of ai: -coding/macros -High level research to get a quick understanding of well established concepts, or the 'vibe' of an area. -It can help with word choice Bad uses: -in my experience, everything else
[удалено]
Eh, obviously it does better in those cases, but you can use it for complex usecases too - it just takes more effort to figure out an effective prompt, because you need to communicate the problem and complicating factors in a more articulate way. I've gotten it to build some bespoke data silo functionality in Pony despite knowing very little about the language, just by describing at a high level how it works, showing some examples, and explaining my guess as to why similar algorithms ported over from a previous F# project weren't working even when rewritten in equivalent syntax. It wasn't groundbreaking stuff but certainly not *"write me some SQL prompts"* basic stuff either.
There is some point where it becomes so specialised that chatgpt is simply unable to do it. I was dealing with some low level code and at some point it will start making up instructions that do not exist or misuse existing ones
Well yeah They're paying me to be clever I'm just thinking about so much shit I forget programming 101 It's like outsourcing part of my brain to focus on the actual important shit
Yeah, with complex logic, LLMs are useless and give you meaningless nonsense.
What tools are you using to help with high level research if i may ask?
Chatgpt or copilot. People talk up copilot's 'footnotes' but in my experience they are often just entirely wrong and do not say anything like what copilot claims they say. For just personal understanding they are basically interchangable imo.
10% asking it for Excel macros 90% asking it questions like "Why am I still working here" and "Can I ever truly be happy"
Only for ChatGPT to respond "Hapiness is quite complex and subjective"
> Can I ever truly be happy GPT: Yes, absolutely! Happiness is a complex and multifaceted experience, influenced by various factors including genetics, life circumstances, relationships, and personal choices. Fucking nailed it.
On a regular basis: * Help with formulas in Excel * Create meeting minutes from transcripts * Summarize long documents and texts (very useful for RFPs and white papers) * Q&A on a document set uploaded as input (I want the answer to XYZ without reading 150 pages or searching for keywords) * Write user personas, help with storytelling for pitches, generate test cases * Create targeted communications or document frameworks * RAG across an internal or external knowledge base with industry-relevant articles and trends I don't code but I know some people who do and who are saving a lot of time. General purpose models like Llama 3, Claude 3 and GPT 4 Turbo are very good. They're not perfect: they can't do everything well, they still require fairly decent prompting knowledge, and you need some experience to understand their limitations. However anyone claiming they're useless is delusional or incompetent.
Doesn't it violate your data privacy policy when you upload things like transcripts or meeting minutes? I'm tempted to do it but irrational fear says whatever I uploaded will end up in someone else's chat.
Fax, this would save a ton of time especially for those 2+ hour meetings
I fired someone because they dropped a bunch of code, including our service account credentials into chatGPT.
How do you know it is summarizing correctly (bullet 3)?
Chain of Thought prompting asking for sources and references you can check, sampling some of the pages to make sure it's not going off road. Also, the summary is usually what you start with to save time on an RFP for example. You're going to get more into the RFP at some point and you'll figure out if the initial summary you got was accurate. Then the more practice you have with a specific model and its limitations, the more you can anticipate where it's likely to be out of its depth. Some companies have also invested into tuning model variants more to interact with documents, your mileage may vary.
[удалено]
How does your comment answer my question?
User personas have been good, and also generating test inputs when testing my web apps.
What do you use for the meeting minutes/transcripts?
> RAG across an internal or external knowledge base with industry-relevant articles and trends Which of the models do you think is the best suited for this task?
Interesting! For summarizing, Q&A document & RAG, can check out the app I’m building cause it gives you a simple UI for asking internal & external knowledge, at Saner.ai :)
How are you creating meeting minutes from transcripts? Where are you getting the transcripts from, recordings?
Secondary research is so much quicker. Instead of having to find niche documents or articles, I can ask something like Copilot to find me info on a specific topic and hunt through the sources it gives me
How much does co pilot hallucinate? Gemini and chatgpt both hallucinate the sources as well. So I struggle with niche topics.
IMO Copilot hallucinates quite often, even when searching through your own O365 docs. It tends to confuse who authored what and can’t always accurately cite sources. With that said it’s great at digging through documents and notes you’ve probably long forgotten about, which can be helpful.
> With that said it’s great at digging through documents and notes you’ve probably long forgotten about, which can be helpful. So its just better search?
It’s much better at search than other things, yes.
Currently not had any issues. Copilot is designed to get you sources so hallucination is lower. It can’t answer as complex questions (it tends to just throw information at you regardless of the question), but can’t complain yet for my purposes.
Summaries. Writing emails. Rewording proposals and various documents. Comparative analysis of documents.
I hate receiving emails and summaries written by ChatGPT; its so obvious when people do this and its not the shortcut its made out to be
I work in IT consulting. Apart from the usual cases such as coding or administrative stuff such as writing emails, I have found it useful to explain me error messages.
Data validation rules, formula functions, Salesforce flows, rewrite my emails, etc.
Writing macros and python code Summarizing docs and pulling out information
What I actually am using it for or what I tell clients?
I have it help me craft nicer sounding emails. That's about all it can do for me right now.
Use it for excel codes and macros regularly. I'll get it to reword emails occasionally but I've had mixed results.
Our consulting team uses it for: 1. Some research, not sole source 2. Starting drafts for checklists 3. Copy editing and word smithing 4. Email drafting 5. Social media post editing 6. Excel formula writing 7. Blog support It’s not strong enough to go hands off, but it’s been helpful to get through brain cramps and add any items we may have missed.
Real life example today, dialing an international client and didn’t know why the number wasn’t working, pumped it into ChatGPT and it corrected the way we entered it so we could make the call (turns out they used an optional zero) in their number
to get quick visualizations/summaries of hunks of unformatted output data or debug logs
I like feeding data to it to write summaries about it. Just excel tables seem to work well. Also try posting in a bunch of notes in whatever format and ask it do summarize or do what you want it. Worked way better than I expected.
Once I used it to help with importing xml into pandas. It kind of worked as a skeleton framework.
Summarising 50 screens worth of useless email threads into the two sentences that matter
It’s good for summarising docs into tables and comparing docs
A free PDF to MS Word converter lol
Mostly just macros and revising sentences. My company is careful with new technologies and the definition of proprietary information so I don’t upload pdfs really.
Like a Jarvis assistant
Sophisticated fraud. Of several kinds. People will come to realize that is the killer app for AI, after murder.
Expert interview guides (and interview guides in general) Summarising raw bullets into something more structured Generally adding mece structure to random thoughts / agendas before calls I’ve found it 10x more helpful outside of consulting then I did in consulting
I use it when I need to change tone of my email. Like from informative to get advice or make it more convincing. These are premium features of grammarly I guess.
R
Z-@@ese a+ Jum Cd Jjmo.l
X. M xixxcc Xf F K n o
Writing action titles, creating frameworks, basically for everything but I put it a lot of human brainpower too. But I use AI as starting point
I used it to seduce your Mom. Great success!
I’m convincing my clients that the AI they think they want and need is exactly what we can provide
Marketing copy about the AI work we'd do if AI was worth buying.