sagaro

The main difference is the data structure and the intent of the export. Facebook's tool is built for data compliance and local offline viewing, not web portability. If you open that Facebook zip file, the HTML version is just a massive dump of proprietary markup. To actually migrate those posts to a new blog, you'd have to write a custom scraper just to extract your own text from their messy div tags. If you use their JSON export, you still have to write a custom script to parse their specific schema and remap all the hardcoded local image paths so they work on a live server. With a Github Pages repo, your content is already sitting there as raw, standardized Markdown. You can just take that folder of .md files, drop it into Hugo, 11ty, or any other static site generator, and it just works. No scraping or data-wrangling required.

But it is portable. It is essentially markdown files. You can download your repo, compile the Jekyll to static pages and publish them anywhere.

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 agree with the point that big companies have persuaded people that only they can offer ease of publishing content. most of my friends publish on Facebook, X, Instagram 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).

[0] https://www.gapp.in/projects/jekyllpress/

I have tried standing desks, but not for burning calories like the article suggests. It was more for fixing my posture. But standing and working made my lean and support myself with my hands.

The best solution I like now is a knee stool. It fixes my posture without I having to try too hard.

This is pretty well made. The progression is good and there are no distractions. And best part it doesn't force you to create an account.

The issue is there is no incentive for the person leaving to make these handover docs and videos. They will just say the bare minimum and complete the task.

One of the best torchbearers for Vanilla Web is Bartosz Ciechanowski[0]. The best part the code is super readable [1].

[0] https://ciechanow.ski/ [1] https://ciechanow.ski/js/watch.js

In excalidraw I just have to click share session and anyone with that url can see my whiteboard and interact with it. I get tldraw has much more features etc. but how exactly is it making sharing whiteboard so easier compared to excalidraw?

Correct. Which is why hydroponically grown produced focuses on low shelf life items like salad greens. And in countries like India where quick commerce is taking off (Zepto, Blinkit, BB Now etc.) it is helpful for the companies to source fresh produce locally many times a week as their dark stores are tiny and they can't have huge inventory.

For my farm and near by farms right inside the city, these quick commerce companies do milkruns and pick fresh produce twice/thrice everyday.

CEA (Controlled Environment Agriculture) is not bad. When over-engineered and quickly expanded without working on unit economics it might be a bad idea.

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.

I wish there was a video of this in that article. The reading was very descriptive, but would have loved to see the video of the octopus playing with the bottle.

Might not really help if you are short on time and need someone quick. When I started my first startup (working on POC before even registering the startup), I was hanging on ultra niche internet pockets. Forums/reddit/niche twitter and having conversations there about where the industry was heading, what was happening, trends etc. And that is where I found my cofounder. We did some private dms, got on a call and then decided we wanted to build this thing. Started the company, scaled it, ran it for 4+ years, got acquired and exited.

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 play short time controls like blitz in lichess. But for rapid I prefer chess.com as lichess has too much cheating. I find lichess UI/UX better and faster than Chess.com.

Unlike Project Euler etc. where one really needs to be good at algorithms/math etc to make the most efficient code, else it will just run for days to brute force, most of advent of code can be solved with terrible algo as the input data is very small.

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.

I think getting clean tables/ETLs is a big blocker for move fast and break things. I would be more interested in actually github copilot style sql IDE (like datagrip etc.), which has access to all the queries written by all the people within a company. Which runs on a local server or something for security reasons and to get the nod from the IT/Sec department.

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.

There used to be a company/product called Business Objects aka BO (SAP bought them), which had folks meticulously map every relationship. When done correctly, it was pretty good. You could just drag drop and get answers immediately.

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.

All these products that pitch about using AI to find insights from your data always end up looking pretty in demos and fall short in reality. This is not because the product is bad, but because there is enormous amount of nuance in DB/Tables that becomes difficult to manage. Most startups evolve too quickly and product teams generally tries to deliver by hacking some existing feature. Columns are added, some columns get new meaning, some feature is identified by looking at a combination of 2 columns etc. All this needs to be documented properly and fed to the AI and there is no incentive for anyone to do it. If the AI gives the right answer, everyone is like wow AI is so good, we don't need the BAs. If the AI gives terrible answers they are like "this is useless". No one goes "wow, the data engineering team did a great job keeping the AI relevant".

There are two ways to do a delivery on demand (like quick commerce or food delivery): 1. Take responsibility for the delivery. Here is a customer orders and a Restaurant accepts and prepares the food, you take the responsibility to find a rider and get it delivered. If there are no riders, it is not simple to cancel the order, as the restaurant has prepared the food. In this case, you have to take the hit on the delivery fee (surge price it) and pay out of your pocket. 2. Don't take responsibility of the delivery. Here when a customer orders and there is no delivery guy, the restaurant takes the customers money as they have prepared the food. The customer is pissed and the app will slowly die.

Netflix has a problem of multiple people sharing same account. So the number could be that of 2-3 people's watching time clubbed as one.

This is so true in this world of A/B testing everything. When A/B tests are poorly designed and results are interpreted for a short time frame, in my experience it always leads to poor decisions which impact long term.

I tell you I have two children, and (at least) one of them is a boy born on April 1. What probability should you assign to the event that I have two boys? If you think that is going to be too cumbersome, simply tell me whether the probability is close to 1/2 or to 1/3, or to some other simple fraction, and provide an estimate as to how close.

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.

Funding has all but dried up. The industry raised a record $895 million in last year’s first quarter. So far in the current quarter, the figure is about $10 million, according to data provider AgFunder.

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

Like I said, I use it for coding. I don't possess any magical intuition. When it is wrong the program doesn't work and so I know it is wrong. If it gets an algorithm worng and the output is not what I expect, i don't go about trying to school it and make it blunder more and take screenshots to show off how it is dumb and I schooled it.

I have used chatgpt, sage, bing exclusively for gettibg code snippets and ideas on how to solve something complicated. They have significantly improved my productivity and enabled me to make many small tools to help me and my friends.

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.

This is very true. Amazon wouldn't enter South Korea because there is this company called Coupang, which does everything that Amazon does (eCommerce, video streaming, food delivery etc )

That is an interesting way of looking at it. Kind of makes sense considering unlike western units, 100k in Hindi is "ek lakh". And in India, the numbers are expressed as xx,xx,xx,xxx. So 100 is sau (hundred), 1,000 is hazar (thousand) 1,00,000 is lakh (hundred thousand) 1,00,00,000 is crore (10 million)

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.

Ah yes. "Not". Thanks for pointing out.

It is interesting how many languages originating in different parts of the world all somehow figured to have a base and name the numbers by base. For instance if you know 1 to 9. And then you know 10, 20, 30, 40... 90. And then 100, 200, 300... you will be able to say the numbers 57 (fifty, seven) or 69 (sixty nine) or 237 (two hundred, thirty, seven).

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.

I am not sure about the 1950s in Russia. But to add some color to this patriotism, I have heard many stories from my grandfather in India who had fought for freedom against the British, where it was quite common for people to put country first, strongly identify themselves with the freedom movement and write letters to loved ones about missions/movements they are going to take part in where they might not return and how they hoped their sacrifice would lead to a better and free India.

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.

There are some use cases where it doesn't need to be bidirectional and yet provide users with the ability to run some formulas or sanity checks etc.

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.