105 karma · joined March 9, 2008
Interests: Startups, Running, Coding, Climbing, AgTech/FoodTech
When you publish to Facebook, WordPress etc you can't easily get your stuff out. You will have to process them even if they allow you to download your content as a zip folder. The images will be broken. Links between pages won't work etc.
I have tried to get them to publish markdown sites using GitHub pages, but the pain of having to git commit and do it via desktop was the blocker.
So I recently made them a mobile app called JekyllPress [0] with which they can publish their posts similar to WordPress mobile app. And now a bunch of them regularly publish on GitHub pages. I think with more tools to simplify the publishing process, more people will start using GitHub pages (my app still requires some painful onboarding like creating a repo, enabling GitHub pages and getting PAT, no oAuth as I don't have any server).
The best solution I like now is a knee stool. It fixes my posture without I having to try too hard.
[0] https://ciechanow.ski/ [1] https://ciechanow.ski/js/watch.js
For my farm and near by farms right inside the city, these quick commerce companies do milkruns and pick fresh produce twice/thrice everyday.
Traditional farming is not viable near the place of consumption. It needs a lot of land, and land parcels that size near a city is impossible to find. And even if you find, it would rather be used for more lucrative purposes such as commercial properties, than farming.
So to make farming viable near the place of consumption (there by reducing the distance produce has to travel, there by reducing cost of transportation and wastage during transportation, there by selecting seeds which are less hardy for transportation but more nutritious and tasty becomes a possibility), we need to improve the yield of the farm and the consistency and flexibility.
A. Yield of the farm depends on -> 1. space requirement between each plant (which depends on the ability for the plant to absorb nutrients and access to light), 2. amount of light (the bullets) and 3. the amount of carbon dioxide (targets). Photosynthesis is nothing but when the photons in the light break the carbon dioxide bonds and release the oxygen to the atmosphere and carbon combined with hydrogen from the water becomes hydrocarbons (the mass of the plant). 4. Quality (same size, no nutrient deficiency like tip burn or spotting) 5. No pest waste 6. cycles per year
In a hydroponics farm, since nutrients can be dissolved into the water uniformly the space requirement between plants is lower compared to traditional land based farming, the quality is uniform as the nutrients density in the water flowing is uniform, the light (including artificial lights can be increased), the carbon dioxide within the farm can be increased from 400 ppm to 1200 ppm (increasing the targets). More cycles in a year are possible, layers are possible.
With all the benefits, those farms near the city try to improve yield enough to make the 1-2 acre farm near the city viable (as thought it is a 20-30 acre farm 100s of km far away).
The savings is the transport cost, the wastage cost during the transport, the wastage during quality checking cost etc.
B. Consistency
Like mentioned about, good seed selection, uniform nutrient dosing and controlled environment so no pest attack means similar sized produce. This helps with inbounding for Retailers. They have to spend less time and money on quality checking or managing sell-able period.
C. Flexibility
In farming, big retailers have all the power. The contracts are one way forced. If they have a contract with you for 5 tonnes of cherry tomatoes and you aren't bale to deliver it on time, they will penalize you. But say you have 5 tonnes of spinach which you have harvested as per the contract, they can always ask you as a favor "Hey unfortunately our inventory is still not cleared, can you delay by 1 week". Now when you are running a farm at capacity, such delays are not easy to accommodate, because the next set of plants that need to be transplanted from the nursery are ready and you need these plants to be harvested out so they can be planted here. Harvesting and keeping it is also not an option due to low shelf life.
Here is where playing with light and carbon dioxide inside the CEA is super helpful. You can increase the CO2 and increase the light to speed up growth and you can decrease the CO2 and light to slow down the growth of the plants. And this flexibility means, you give more tolerance to the uncertainty in forecasting for the retailers. You take care of their headache. And this is valuable.
I run a pretty successful hydroponics farm in India and supply to online retailers and we are their preferred suppliers purely because we take care of their uncertainties. Ours is not super high tech. Labor is cheap in India. We have some essential tech, like the lights/CO2 etc. But that's about it. We didn't over-engineer.
Another thing you can do is go to the hackernews algolia and search of posts in your industry/domain. Find some of the smart answers with people who understand the domain deeply etc. Go to their profile see if they have some link to their twitter or something and connect with them. Again not super helpful if you are short on time. But leaving it here, for those who might like me want to find someone not in their network for some future collaboration.
I think most CS grad students can solve Advent of Code. Some people, probably don't finish it not because it is hard, but probably because they lose interest.
And basically when you next write queries, it just auto completes for you. This would improve the productivity of the analysts a lot. With the flexibility of them being able to tweak the query. Here if something is not right, the analyst updates. The Copilot AI keeps learning and giving weights to recent queries more than older queries.
Unlike the previous solution where if something breaks, you can do nothing till you clean up the ETL and redeploy it.
So yes, I can understand if there is incentive for the startups to invest in Data Engineers to make well maintained data models.
But I do think, the most important value here is not the chatgpt interface, it is getting DEs to maintain the data model in a company where product/biz is moving fast and breaking things. If that is done, then existing tools (Power BI for instance has "ask in natural language" feature) will be able to get the job done.
The google moment, the other person talks about in another comment, is where google or 1998 didn't require a webpage owner to do anything. They didn't need him/her to make something in a different format. Use specific tags. Use some tags around key words etc. It was just "you do what you do, and magically we will crawl and make sense of it".
Here unfortunately that is not the case. Say in a ecom business which always delivers in 2 days for free, a new product is launched (same day delivery for $5 dollars), the sales table is going to get two extra columns "is_same_day_delivery_flag" and "same_day_delivery_fee". The revenue definition will change to include this shipping charges. A new filter will be there, if someone wants to see the opt in rate for how many are going for same day delivery or how fast it is growing. Current table probably has revenue. But now revenue = revenue + same_day_delivery_fee and someone needs to make the BO connection to this. And after launch, you notice you don't have enough capacity to do same day shipping, so sometimes you just have to return the fee and send it as normal delivery. Here the is_same_day_delivery_flag is true, but the same_day_delivery_fee is 0. And so on and on...
Getting DE to keep everything up to date in a wiki is tough, let alone a BO type solution. But I do hope getdot.ai etc. someone incentivizes them to change this way of doing things.
I am going to not heed the author's suggestion of setting up the problem correctly and use intuition:
For the week problem it was 14+13 = (7 * 4 -1) in the bottom and 13 (7*2-1) on the top.
So for a normal year (365 days), it would be (365*2 - 1)/(365*4 - 1). Close to 1/2.
I think a big reason for this significant drop between last quarter of 2022 and first quarter of 2023 is AGI. All the money in the VC world is now flowing towards AI and all other industries are going to take a hit similar to AgTech
When the ai is wrong, I just move on.
I fear some small portion of people who want to prompt engineer and prove the AI is dumb or wrong or evil will end up winning and make all these companies scale down to avoid the backlash and in the end people like me will have to live without the good things.
Somehow the first split is 1000, then on every order of 100 gets a name. It sure is confusing, but there must be some reason to this.
But all the languages under Indo-Iranian(https://lingweb.eva.mpg.de/channumerals/Indoeuro.htm) for instance Hindi (https://lingweb.eva.mpg.de/channumerals/Hindi.htm) have 1-100 as different numbers and then follow the base principle.
20 in Hindi is 'bis'. 2 is 'do'. But 22 is 'bais'. Know 30 and knowing 7 in Hindi or any of those Indo-Iranian language will not help you tell 37.
But knowing 100 and 37 will be enough to say 137 in those languages. 100 in hindi is ek sau. And 37 is 'senthis'. So you will be able to say 'ek sau senthis'.
It is fascinating that those languages chose to not follow base till 100 and then followed the base while naming their numbers.
Right now the politics is shit. And hence we aren't able to relate to this. And it would be insane for us to write a letter to loved ones with political statements. But at that time, when it was a national movement, maybe it wasn't that odd.
For instance I can publish an article on the economics of ecommerce. And someone consuming my article might want to check the unit economics and might want to just divide the numbers by the total units sold. Instead of having to do that on a calculator, he can just do it on the spreadsheet.