This is such a weird thing to read. You try to project your ideas on the kids, thinking that is the best thing to do. Let them be.
I learned Linux when I was like 13 or 14 and not because my father told me. He didn't know much about computers in early 2000/late 90ties.
The curiosity, the desire to learn, the need to set up my own isp, the need to start to make money, the curiosity of how html, php and other stuff worked let me to Linux.
Teach them how to be curious and feed that curiosity, the rest will happen.
And if they choose Mac over Linux, just get of their way, otherwise they will rebel.
Rolling your own generally has mainly downsides in the context they are in.
1. This is clearly a small team with very little spend
2. Tomorrow someone leaves and next engineer will have to manage all of this.
3. I don't think they realize that they actually increased cost of this service not decreased it. Now they need to manage their own Kafka monthly. Engineering time is expensive.
I do. I use assistants as containers for different conversations for my GTM work:
An assistant for marketing and copywriting
An assistant for customer support
An assistant sales conversations.
These agents aren't super smart: just few PDFs for context plus a few sentences system prompts.
I do get what I want in 80% of use cases (not measured, just a feeling).
This is a weird demand to have in my opinion. You have plenty of applications on your computer and they only do what they were designed for. You can't ask a note taking app (even if it's open soured) to do video editing, unless you modify the code.
Thanks for sharing ChatbotUI. While I'm not an author, I use it extensively and contribute to it. Thanks to the permissive license, I could offer ChatbotUI as a hosted solution with our API keys. https://labs.writingmate.ai.
This is very well written and entertaining post. I enjoyed reading it.
Selfishly, would you mind sharing literature or blog posts that led you to this level of understanding of LLMs? I'm trying hard to understand the inner workings via experiments but definitely far behind your expertise.
I'm surprised that only 3 people reported the error.
While problem is not trivial, my initial reaction was "it can't be 3, it's too obvious". And it seems that a lot of people in the comments here do get to the right answer on their own.
I'm grateful to have parents who in their age, have energy, health and financial freedom to join us for celebrations from overseas. I'm grateful for my parents to be friends to me and all my friends.
As someone said here, I'm extremely grateful for free quality higher education I have received in my home country. And I'm saddened that many are in student debts for decades.
I'm grateful to be in the best health I've been in last 10 years.
I'm grateful to myself for quitting alcohol more than a year ago and sticking with it.
I'm grateful, for the first time, to feel financially stable for many years to come.
I'm grateful to United States of America for being our home and safe harbor for the past 10 years, especially last 3, given the global instability.
Hey folks, I'm a free customer here and a big-big fan of their project. I've been using narrative.bi for my project and sharing the results on Twitter [1] lately.
How I'm using narrative.bi:
- A high-level report of WoW, and MoM changes on our website traffic that land in my email.
- Alternative to GA4 UI, which drives me nuts.
What I don't get yet and I want to see implemented (I'll definitely pay for this):
- Dimensional analysis: Which dimensions contribute to the topline change the most. I.e. Say unique users increased by 30% WoW, what top 5 dimensions have contributed to this change? Country? Device? Etc
- Global event correlation: are there any global events that influence the metrics change? Maybe a holiday in the Country?
You can downvote me here for a promo, but by using gpt3 directly you can bypass all the restrictions. Thats one of the reasons we built writingmate.ai (often outages of GPT3 being the second reason)
Can't reply I'm the original thread (why?) So I'll post it here. Somebody mentioned that large language models is potentially a great solution to bridge the gap of data literacy. I love this idea.