It's much easier to ask ChatGPT "what can I cook using only these <insert-here> ingredients within 30 minutes using only a wok?" than Googling it. Once I have names of dishes that fit my criteria, I can find highly rated recipes on Google.
This is a very interesting use case of LLM and something I'm looking into these days. Would appreciate if you could share more details on the challenges you ran into in using DSL's with LLM's and how you solved them?
This is a fascinating topic and something I'm looking into these days, specifically removing need for Data Scientists to write Spark code. Would be great if you can share more details around the DSL. The DSL also sounds interesting in it's own right!
I have a relevant anecdote to share. My father [0] bought a pair for African grey parrots [1] last year. Both were around 6 months old at that time. They do require attention and looking after them has certainly brought happiness to him.
[0] Runs a business which loses $200-$300 per month and works only 2-3 hours a day. So sort of retired.
[1] I'm not encouraging keeping animals, endangered or not, as pets or in cages.
One idea would be to start by looking at technological trends in your country. If they persist, what problems would lend themselves to easier solutions? Examples:
1. Smartphone penetration is increasing. This can help with improving access to education when there's a dearth of content in your local language on YouTube, Coursera, edX etc. You can build a platform for teachers to easily create videos / content in your local language and upload them on YouTube.
2. Mobile adoption is on the rise. This can help with infrastructure planning by collaborating with telecom providers and analyzing anonymized data. You can create a tool for planners / ministries to visualize and analyze these datasets.
3. A significant proportion of people use feature phones. You can create a news delivery service or something similar to bring to them what's easily available on the web and would be useful.