Key Loading Systems And Methods: Fill & Download for Free

When the Europeans first arrived the Māori were essentially a feudal society stuck with stone age technology. Their methods could be sophisticated but the weaponry was fairly primitive. That changed extremely quickly during the 19th century as new weapons became available and the political landscape of the country was turned upside down by the ever-increasing numbers of European settlers.Pre-European tribal warfare included a lot of raiding, where it escalated to more serious warfare a typical set-piece battle might occur when one side invaded the other tribe’s land and constructed a Pā, which was a fortified position. These were temporary earth and log forts; well thought out and very dangerous to assault. Combat was fought hand-to-hand and was somewhat ritualised. Your enemy constructing a pā on your land was intolerable and to maintain your honour you would be obliged to attack it and drive the invaders away.Permanent villages were also fortified, often sited on hills and surrounded with a pallisade. They were used to secure food storage and assert dominance over an area. Māori society was agrarian and control of arable land was key.There were small groups of Europeans in early days, but by the mid-19th century numbers were rapidly increasing and many traders arrived who were happy to sell firearms to iwi. Some bought large numbers and this radically changed tactics and methods.A Māori “tupara” or double-barrelled shotgun. A favoured weapon of this period of warfare. Māori also used muskets, but the short range firepower of shotguns were considered ideal for combat in dense bush or a pā. Tupara could also be loaded with musket balls if more range was required.Very quickly they developed the “gunfighter pā” which they used so effectively against the British when fighting broke out in the land wars.This was a completely different style of pā, essentially it was similar to a WW1 trench system with a pallisade instead of barbed wire. There were deep shelters able to withstand artillery bombardment, and dug in fighting positions. There were interlocking fields of fire, and even if the enemy gained entry there was defence in depth, with concealed tunnels and firing positions to ambush the attackers. At Gate Pā the British storming party were actually allowed to gain entrance to the pa before being ambushed on all sides simultaneously and annihilated.It is said that if the British army had learned their lessons better from the fighting in NZ about the ability of good earthworks to resist artillery bombardment and assault then WW1 might not have been quite such a bloodbath. Māori shelter dugouts neutralised British artillery just as effectively as German ones on the Western Front, but by then the British army had forgotten the lessons it paid for in blood fifty years earlier.Despite all their sophistication offensive pā were considered expendable. The objective was to strike a powerful blow against the enemy and once that was done, or if the tactical situation turned unfavourable they were often quickly abandoned.

The fact that the price is flatlining now for a couple months means we are forming a bottom and agreeing on the new price of Bitcoin after many more people came to know about it.Before the run Bitcoin was around $1K, the value being now a household name is $6K. In my opinion the future value of being a household name is much more valuable than this 6x.[Update] Obviously this was written before the November 2018 crash. However my general point still stands. The price is now $3600.Some countries have weak financial control systems (read, almost all, as the easiest way to get out of tough situations is just to print money and who wants to be that unpopular politician saying no and losing valuable voters) but some are weaker than others. Before Bitcoin became more well known, people from failing countries with huge rates of inflation, had nowhere to go. They were at mercy of their financial and political system that ruined their life and their life savings.Fast forward to a situation where the people from a failing country know about Bitcoin. What they will do is start buying and using Bitcoin and leave their country’s currency for what it is. They don’t trust their government and their financial system and decisions. This creates country-level demand for Bitcoin and drives prices up. Better yet, people in these countries will start using Bitcoin for transactions. Venezuela, Turkey, and Iran are countries with strong demand for Bitcoin because of huge inflation.The failing of financial systems will continue. If you think this can not happen to the rich western countries, well remember the 2008 banking crisis? The banks didn’t change. They rely on being bailed out because that’s actually quite profitable. Bankers load their pockets, fail, get bailed out by tax money.Now that the general public know about Bitcoin and adoption and real world use cases are slowly entering our lives, I don’t feel people will accept another banking crisis again. We became stronger and have more influence as individuals because of Bitcoin. Because Bitcoin created an alternative as a store of value and method of payment. I can use gold as a store of value but I can’t buy a coffee with a nugget of gold. But you might possibly be able to buy it with Bitcoin nowadays.So what I said before about that I think the value of being a household recognized name is more than 6x, is because the next time a country fails, the next banking crisis, people know about Bitcoin and will have an option to flee towards it. As a political statement and to secure their money. Of course this will drive prices up significantly.This can’t happen if people don’t know about Bitcoin. You can’t buy or flee to something you don’t know. That’s the reason why December 2017 was so important for us. Not the price action, but the overall recognition and knowledge of what blockchain and Bitcoin is and does under the general public. We need to challenge our financial systems.What are the chances of this happening?Banks didn’t really change. There are 195 countries in the world. Every one is printing money to solve their national problems. One by one will they fail and each will accelerate this process. I don’t know if Bitcoin will replace traditional financial systems but it will play a role in a new system.A lot of blockchain solutions are young and immature. There is no widespread adoption and there are technical hurdles to overcome. But we take babysteps and every day you will see more and more businesses starting to accept Bitcoin/use blockchain services. Institutional money can’t participate yet, but many organizations are working on this. Everything is pointing in the right direction.Price is not only decided by demand, how about supply?There will be 21M Bitcoins max by 2140. We have mined 80%, so most of the Bitcoins have been mined already. Rumours say around 4M have been lost. People will lose their private keys, people will die and take their Bitcoins with them, people will send it to the wrong address, and people will just forget about it. So the supply side is limited and going down long-term. We’ll also have to find a solution for this in the future but for now, supply is working favourably towards a higher price.That’s a perfect scenario for high prices, high demand, low supply. Therefore price predictions like $100K, $1M are not even that crazy. With that said, the chances of never seeing a price increase is highly unlikely. We just need a couple more financial systems to fail ;)Please leave an upvote if this answer helpful or informative. Thanks!I develop and maintain automated trading strategies using a risk managed first approach aiming to grow your portfolio over time and keep its value during bear markets.Want know my thoughts and Quora answer on Do you think Bitcoin will rise or fall in 2019?[Update] Shout out to User-13355761504526607114 for fixing my bad grammar. Thanks so much!

I'll try to keep the answer as simple as possible. After reading this answer if you correctly comprehend what I'm saying here, you'll at least be in a position to throw the big data jargons around!Distributed computing is a paradigm (a method/approach) of solving a problem. You break a huge problem down into pieces then you give it to each individual node to complete a small chunk of the work and finally you collate your partial results into a complete result.Say you have 10 linux boxes.. you could manually divide your input into 10 parts.. give your reduced problem to these 10 nodes and finally collate your answers together and produce your final output. But what if you had 10,000 linux boxes with you? and a problem with input of a few petabyte in size? Would you want to be doing it manually? Atleast I wouldn't.. this is where Apache Hadoop comes into picture. There's a master node which automatically divides your problem (called mapping) finds free nodes (individual slave linux nodes) and then gives them work when free. This guy manages who's free.. who's not.. how much work can a slave take on etc. Finally after your subproblems have beens solved, you start collating and postprocessing your results (called reducing).Here's a pictorial toy example which explains MapReduce:Source: RamHadoop. Zoom into the picture for a detailed viewHere you'll have to note that for every new input you give you'll have to load the input from the disk into your RAM, do the processing and put your output back into the disk.In the above example.. you would notice that the input is divided into three parts (mapped into three) and reduced later on. What if two of those inputs never change! Wouldn't you save time if you could keep the two which don't change in the RAM? This would give you a drastic speedup when compared to reading the disk every time you want to load the input from the disk.If you see the latency numbers for disk seek vs. RAM access.. you realize that you can process data up to a 100,000 times faster! No kidding go see the chart and comparisons for yourself.This is exactly what Apache Spark does. This is especially useful if you're running machine learning algorithms in a distributed environment. Usually your machine learning algorithms are optimizations where you have your input data and you keep playing around with it until you're satisfied that this input data can correctly predict the output on this training set.PS: For simplicity I have completely omitted the concept of the underlying distributed file systems like HDFS etc. Once you read up the basics here: HDFS Architecture Guide, you'll realize that the key intuition in distributed systems is the concept of bringing compute to data rather than taking data to the compute which happens in a traditional DBMS system. And it happens that moving compute to data is far more cheaper than moving data to compute when the size of the data exceeds a certain size. This is exactly why the buzzword BIG data was coined.