HiLearn has multi-functional teams (3-5 years of experience working together) located in Yerevan, Armenia (team members include gradates from MIT, with work experience in Silicon Valley and London) are actively looking for new projects in
1. Computation / R&D projects (i.e. ML, AI, Computational Finance), past projects include
- Recommendation system for MoneyLion Inc.’s mobile application’s Today Feed (both Research, Development, and Production Deployment)
- Investment Portfolio Risk Assessment using Monte Carlo future simulations (WealthTech Inc.)
- Algorithmic Personalized Financial Planning Tool
- Quantitative trading algorithms for automated cryptocurrency trading
2. Front-end heavy projects (e.g. building consumer products) [Preferred tech stack: React JS (frontend) + nodejs, python, or Java (backend)]
- Personal Loan Marketplace developed for MoneyLion Inc. https://www.moneylion.com/market-place/personal-loans/ (use VPN if outside US)
- Financial Widgets/Calculators developed for MoneyLion Inc. https://www.moneylion.com/learn/financial-calculators/ (use VPN if outside US)
- Personalized Financial Planning App (aqqru.com, shut down)
that's how our ETH processing works at the moment, we derive different BIP44 addresses and the customers pay to them. But that approach is possible only because the transactions fees are paid in ethereum as well; you cannot pay the tx fees in ERC20. With smart contracts someone else can pay the fees, which makes it ideal for our use case.
There are two places where gas is paid:
1) when the customer pays to these intermediate addresses
2) when the funds are moved from the intermediate to the final address
1) is always paid by the customer that initiates the payment.
2) can be paid by anyone, as these contracts are permissionless and anyone can interact with them. At the moment Coinbase picks up the tab for doing this, but we will likely not be doing this in the long-term
> The impact of plastic bottles is probably lower than for alternatives like glass. Glass is heavier and causes more CO2 emissions because of the increased energy use for transporting them.
I'm curious about this, any chance you have references?
60% is pretty low for PET, Glass isn't recycled perfectly either, but is generally better than PET.
In Switzerland 82% of PET is recycled. (Note that this number is the percentage that is really reused. Not the percentage that is collected.) The same number for glass is 96%. That means only 44% of glass gets recycled 20 times.
However, this is for reuse, not recycling. Not many glass bottles get reused, most get recycled. Recycling glass is less energy efficient than reusing.
> According to this paper, glass bottles need to be recycled 20 times in order to reach the same CO2 footprint as a PET bottle
This does not support the OP's case that "Glass is heavier and causes more CO2 emissions because of the increased energy use for transporting them."
There is going to be plenty of transport taking place during those 20 cycles of use and recycle. If the main energy cost of glass is in transport, as he asserted, that's only going to make it less competitive vs. plastic as the number of cycles increases.
The quote is inaccurate. The paper talks about glass bottle _reuse_.
As long as transport + washing cost of glass bottles are less than production + transport cost of plastic bottles there will be some number of reuses that make glass the winner.
60% recycling rate for PET bottles sounds very low compared to the 90% in Finland [1]. The deposit we have on plastic bottles ranges from 0.10€ to 0.40€ depending on the bottle size (the most common 0.5 ltr bottle has a deposit of 0.20€). Cans are recycled at an even higher rate of 95%.
In the UK we used to have electric milk floats with milkmen that would deliver milk in glass bottles. The dairy would be local. The cows would be local. Big cities had trains to get the milk in. Or the milk would travel in tankers.
The bottling plant would be for local distribution. The empties would be carried back on the milk float.
Moving on we now have dairies many, many miles away. They are not a common sight. The milk goes into single use plastic bottles and gets sent to supermarket depots. It then travels by road vast distances to supermarkets and convenience stores. People then drive to the supermarket and buy the milk.
I personally preferred the way milk was delivered. I liked the community value of having a milkman. I liked washing the bottles and putting them out for collection. The milk wasn't homogenised then, it had not the same shelf life.
I don't believe that having four pints (2 litres) of milk driven over two hundred miles of roads is that efficient. Particularly when I can see cows out the window. Then, since it is the EU, milk can be driven from Germany. Or in yogurt form over the Alps in a 1000 mile journey.
So at one level the CO2 emissions of glass are higher but driving milk hundreds of miles is where the CO2 problem really is.
From a capitalist perspective everything is now really efficient and the market is working. But when milk was government and cared for that way, there was a lot more employment going on. We could have kept it all local with solar and other renewables powering the milk floats instead of coal. But when those former dairies have been shuttered and sold for housing developments there is no goin back. We are stuck with mega dairies.
Water is even worse. There are lorries driving from the Alps with bottled water. This is plain absurd. There was a time when tap water was as good as it could get.
Beer is different, as are spirits and wines. Beer should be brewed locally and served in glasses that get washed in a public house. But widgets in cans and other tricks have made canned beer fine, what most people drink.
Anyway, saying that plastic is less CO2 than glass is just not fair to all the issues of globalised food.
We are a 2 year old startup focused on applying ML algorithms to finance, i.e. we do ML, algorithmic trading, etc. We have also done some freelancing work related to long term financial market predictions for retirement planning.
Currently we are trying to pivot, and looking for related projects in algorithmic trading, or ML applications to time series.
We mostly work with python (django for our website, and visualizations), we have also done minor work with c family languages.
I was always surprised how little people care in Armenia about the old airport. Imagine you land in an airport that is nothing like all the other "conventional" airports with high ceilings and huge open areas. Wouldn't you want to just fly to Armenia if your experience starts in a museum like airport? Probably Armenians would not care too much to frequent in the old terminal, but it could be a nice turist attraction, no?
The people would agree with you, local business owners would agree with you, but the leaders are basically organized crime types, corruption is rampant, most money dedicated to this project would be stolen and end up in London and Toronto real estate. They also suffer from the influence of Russia, i.e. destabilize as many former soviet countries as possible in order to benefit from the chaos. That part of the world is in for a lot of trouble over the next 50 years.
The old Terminal is really small, but the new terminal is not that much bigger. Having flowed out of both I don't think the size is the problem. The problem is lack of desire to invest (probably justifird financially) in presercing the building.
Through Orchestra, the human-assisted AI work platform we open sourced (http://orchestra.b12.io/), our customers benefit from a high-touch experience - equivalent to what you would expect with an agency custom website build - and a self-optimizing, intelligent website at a fraction of the cost/time.
Meanwhile, our automation-augmented experts are free to focus on what they do best: creative and analytical work. Orchestra and our algorithmic design tooling allow the machines to automate away the nagging repetition of mundane tasks, like staffing, process check-ins, and quality assurance.
I'm happy to expand on this answer, and you can find a bunch of papers that this is all based on at the Orchestra website.
HiLearn has multi-functional teams (3-5 years of experience working together) located in Yerevan, Armenia (team members include gradates from MIT, with work experience in Silicon Valley and London) are actively looking for new projects in
1. Computation / R&D projects (i.e. ML, AI, Computational Finance), past projects include
2. Front-end heavy projects (e.g. building consumer products) [Preferred tech stack: React JS (frontend) + nodejs, python, or Java (backend)] Website: https://www.hilearn.io/Email: partners@hilearn.io