Different Blank Forms In Land Bank: Fill & Download for Free

Well I have lived for the past 6–1/2 years in the Sonoran Desert, both in the mountains of the Sierra Madres and on the beautiful Sea of Cortes (Gulf of California, as it is locally known). There seems to be more than 300 days of sunshine, almost 340–350, so much so that you almost take that sunshine for granted. There are amazing starry skies and a vastness to the land that is a lot like being on the open ocean. In this regard, there are even Sky Islands, as they are known near the Border.The beautiful seaside town of San Carlos is where I call home 6–8 months of the year, usually October-May and then it gets too hot for me…but it is a dry heat :)Much of that time is spent exploring the coastal areas and the mountains and the canyons. My hotel is in a town called Banamichi and it lies in the heart of “La Ruta Rio Sonora” a historic route from Cananea to Ures that is comprised of a dozen pueblos founded in the early 1600’s, each like jewels on a priceless long forgotten necklace. This area is much like a time capsule and has not been modernized, not much, but it is coming. When I bought “La Posada del Rio Sonora” the town had no gas station, no OXXO and no bank. Luckily there is still no bank, but we have an ATM.Right now, in mid-June, I am in Hawaii, on one of America’s number one beaches and living in a big estate (as a house setter) in Lanikai on O’ahu.Even with the incredible views and wonderful breezes, and much lower temps, I must say I miss my desert life. I miss the wide open spaces, the roads you can drive on for hours without seeing another vehicle. I miss the open fields and trails with zero tourists. Of course it is cleaner here, probably a bit safer too. But golly it seems like everyone is here or is coming to visit, and the prices reflect that too.Most years we take 3–4 months off to travel around and see the United States and Mexico, sometimes Central America. But this year is my first time living on an island, unless I count Key West. That was different because I lived on my boat and could leave anytime I wanted, so it was not as confining.But here on this lava rock, this gorgeous, humid, tropical jungle rock, I do feel somewhat constrained. Even the sky is not as big. Maybe there are too many homes and their lights diminish that Milky Way I am used to seeing back home every night.Most of all, I miss my dogs and my people. Zeus and Kit are being cared for by some cruisers that needed a Summer off the boat. My girls at the hotel are taking care of business during the slow season, monsoon season. Speaking of monsoon season in the mountains of the Sonoran Desert, there is nothing like it. It is Magical. There is no way to describe it with my simple vocabulary and writing skill, but I should try.It starts with a hot scorcher of a day, probably in the triple digits in F and mid 40’s in C. The kind of day that makes you really appreciate air-conditioning and siestas. Then the evening rolls around and a sweet breeze picks up. There is a charge in the air, the kind that makes the hair on your arm stand up and then you hear it, a slow, low grumbling miles away. You get up on the upper terrace or even on the roof, and you catch your first glimpse of it. It is pouring some five miles away and you know not everyone is going to get this lifeblood, the rain, the sweetwater poured down on them, only the lucky ones. So you do a little rain dance, just because your ancestors did and just because it might bring it in your direction, and just because it is fun. Then it turns, almost like it heard you call or saw you dance and it heads your way. You get the feeling that you have just called a T-Rex because you can feel its ferocious power and in seconds that seem like hours it is upon you and the rain is so strong and so thick that you feel like you could drown.After getting soaked as thoroughly as if you had jumped in a lake with all your clothes on, you make your way down the ladder from the roof and go inside to get dry and naked. You feel a sense of accomplishment because you know this rain means lfe, life to the farmers, life to the ranchers, life to the animals and the plants. Practically overnight you are shown an even greater miracle when the desert metamorphosizes from a dry brown almost blank canvas into a tropical over-filled color palette seemingly overnight. You can hardly believe it is even the same place.Thanks for reading and I hope you get to experience and enjoy the Great Desert.

First…Stop it.Artificial intelligence is not "intelligence". And it's not "artificial consciousness".Everyone is afraid that AI will suddenly wake up, get upset, and take over the world.Or that AI will wake up and take all of our jobs. This will happen. But without the "wake up" part.Below I describe what real AI is.If we want to understand the “existential threat” we first need to know what AI is.Then, if you are at a cocktail party and someone says, "but what if robots are intelligent?" you can argue with facts, mixed with a little bit of alcohol.---------A) STATISTICSStatistics is at the heart of most AI programs.Just like statistics is at the heart of a lot of human decision making.For instance, if you see clouds in the sky, your brain thinks: "Hmmm, the last 100 times I saw clouds this dark, it usually meant it was about to rain".When you think like that, you are using statistics to make the decision: "I should _probably_ go inside now."I'll give an AI example: Siri or Alexa. How does Alexa understand the words you just said?In 1989 I was visiting Carnegie Mellon to decide if I would go to graduate school there.One of the graduate students, Kai-Fu-Lee (now one of the most famous investors in the world and I would check out his excellent recent TED talk on AI) showed me what he was working on:It was speech recognition for the 60 or so commands that might happen on a Navy battleship (ten guesses as to who was funding his project).When you say the word "Fire!" a sound wave is created. When you say the word "hello" a sound wave that looks different is created.If 100 people say "Fire" and 100 people say "hello", all of those sounds waves are stored in a database.Now, if a brand new person says "Hello" the computer program needs to determine if that person said "Hello" or "fire".There might be 10 different attributes of every sound wave. It breaks the new person's sound wave into those 10 attributes.Then it compares that "vector" of 10 attributes with all of the vectors in its database for "Hello" and "Fire!"It uses a statistical technique called "Hidden Markov Analysis" to determine if the sound wave is more like the "hello"s in the database or more like the "Fire!" in the database.Then it says to itself, "This guy said "Hello". "It then has a line of code that says, "If someone says "Hello" Then say "Hello" back".Additionally, it adds your "Hello" to its database.Your "Hello" might be slightly different than the other 100 "Hello"s so it just learned a new way to say "Hello". That gives it greater ability in the future to recognize the word "hello".In other words, it "learned".So it used Statistics to hear you, code to respond to you, and database technology to learn. There's no real intelligence there but it feels like it's intelligence.Multiply that by 30 years and millions of patterns and computers a million times faster and you have Alexa and Siri in today's kitchens.Ask "Siri" what gender it is.-----B) EVALUATION FUNCTIONI just mentioned about language recognition. But how does a self-driving car work?Every second it has to make a decision. Does it move forward? Does it brake? Does it swerve to avoid an accident? Does it turn left?How does it get from point A to point B?1) Google Maps. - Using GPS it knows where it is. And it puts itself on Google Maps.2) List all of the possible routes. This is a "hard" problem in the mathematical sense (there's no way for it to guess the fastest route. It has to list each route and then sort by the shortest. )But now computers are so fast what would normally be a slow decision (drive me from this corner in Piscataway, New Jersey to the capital building of Sacramento, California) now just takes seconds.3) Waze. Use Waze to eliminate the routes with too much traffic.4) Start driving.5) Statistics: Every microsecond it uses statistics to see if there is blank space or an object that must be avoided or a traffic sign that must be followed.6) Decide what to do according to the code. For each traffic sign, it has code that tells it what to do (if a sign says "Stop" it Stops for a second, uses Statistics to see if any traffic is happening on its sides (with radar and cameras to provide the images). )If there is a person standing in front of it, it might just stop.If there's traffic it didn't expect, it might trigger the program to re-route.If it's blank space it will just keep going.If there's a baby crossing the street and it has to swerve to avoid hitting it, but if swerving will cause the car to hit a truck, killing the passenger in the car, then the "AI" of the car is dependent on the ethical decisions of the programmer of the car.In other words, in every situation, it determines it's options, then uses an "evaluation function" programmed by a coder, to determine which option has the most successful outcome (move the trip forward, don't kill anyone).Eventually the evaluation function will NOT be programmed by a human coder.Instead, through thousands of experiences of other self-driving cars, the experiences plus the outcomes will all be put into a central database.When a new experience is encountered, the code will look up that experience in the database and the database will spit back the best possible outcome.The code will learn statistically what the best outcomes are of each possibly decision and change the code accordingly and send updates to all self-driving cars.-----C) TREESThe hardest game in the world is a board game called GO. With chess, if a computer can evaluate a billion possibilities a second, it can be a world champion level player.But a Go game can involve trillions of possibilities. How did Google make a program, Deep Go, to beat the world's best Go player. This was thought to be impossible.And yet Google did it.For any game, a computer program first builds a tree of possibilities. Much like a human would.A human thinks: "If I make this move in checkers, my opponent might respond with A, B, or C and then I can do D, E, or F and then my opponent can do G, H, I if I do D or it can do J, K, L if I do E and I'm never going to do F.A computer doesn't select as well as a human so it builds the FULL tree. Meaning, what are ALL of the possible moves it can do, what are ALL of the possible responses of my opponent, etc.And then it uses a programmed evaluation function to look at the leaves of the tree it built.Whichever move results in the best leaf of the tree (as determined by the evaluation function) that is the move it makes.That's how computer chess worked for decades. I'll get to the secret sauce in a second for how computers conquered chess.And then after that I'll describe how computers miraculously conquered Go.It's only a miracle until science can explain it. It's only "intelligence" until it can be coded by a programmer.D) HARDWAREEverybody thought for decades (including many Nobel Prize winners) that the best computer chess programs would be developed when scientists encoded the knowledge of the best chess players in the world into the evaluation function.How does the world champion value a position instead of a weak player?This turned out to be wrong.The MORE code in the evaluation function (i.e. the "smarter" the evaluation function was from a human perspective) the SLOWER the program.Which meant a smaller tree would be built, which meant less possibilities would be analyzed.What really allowed the programmers at IBM to build "Deep Blue" which beat Garry Kasparov in 1997 were two things.Both related to hardware.a. Computers got faster.b. First the creators of Deep Blue developed software. But then they made the software into hardware, building the logic right into the hardware infrastructure of the computer. Making the program 100x faster than it would have been.And finally, they made the evaluation function STUPID in order to use less code so the hardware could value more positions.Then, before anyone caught on to their "artificial intelligence" they retired Deep Blue right after it beat the World Champion of chess.As hardware gets faster, artificial intelligence gets "smarter".[as an aside, I once gave a date a chip that was the initial chip for “Chip Test” - the “ancestor” of what became the best chess computer, Deep Blue. She was weirded out.]----INTERLUDEWhat I just described is all the basics. You can stop now.The rest of artificial intelligence is simply combining the basics to make more advanced techniques.-----E) STATISTICS + TREERemember the TREE from computer gaming. And STATISTICS from speech recognition.Now let's go to the impossible game of Go. Google developed the program "AlphaGo" to win at Go when everyone else thought it would take another 20 to 50 years.First, remember Kai-Fu Lee who worked on speech recognition. And later developed Apple's first attempts at speech recognition in the 90s?At one point in his grad student days, he was getting tired of navy battleship commands (as one does) and decided to focus on building a program to play Othello.He ended up building the world champion of Othello.He took a lot of games, let's say a million, and put them in a database. And each position from each game, he would label, "winning" (if it was a position on the winning side) or "losing" in a massive database.He would identify several attributes of each position (how many white pieces, versus black pieces, how many corners were controlled, how many pieces were on the sides, etc).Now, if the computer was playing a brand new game, it would determine all the attributes of that position, then use Hidden Markov Analysis (remember: speech recognition) to match that position to the database.If the position pattern-matched a "winning position" then it would make the move that would lead to that winning position. If it matched a "losing position" it would not make that move.That program became the world champion of Othello.AlphaGo took it one step further.It put in the positions of millions of Go positions and did the same sort of breakdown.It used faster hardware to speed up the process.Then, once it became pretty good at GO, it played BILLIONS of games against ITSELF to put many BILLIONS of new positions into the database. In other words, it "learned".Now it was ready to play Go. It crushed the world champion------That's basically it. That's all of artificial intelligence.Let's say a bank wanted to fire all of the employees in charge of lending. And replace them by artificial intelligence.How would the bank lend money?Well, there's 100s of millions of loans already out there. And for each person who has ever borrowed money I know:- their age- where they grew up- what their job is, are they married?- are they divorced? do they have kids?- How often do they move? how have they done on prior loans like this? and I even know what they buy on Amazon and how often they fly to Las Vegas.I can put all these vectors in a database and divide them into people "most likely to pay back the loan" and people "most likely to default".Then, just like speech recognition or the Othello program above, I can use statistics to determine who I should loan money to.And if I say "no", I don't have to explain. On to the next one!---Let's say I want to fight terrorists.I already have examples of many terrorists who trained in the US and then went on to perform or attempt acts of terror.I know everything about their bank accounts. How often they transferred money. How often they traveled. How often they took out cash versus using a debit card.And so on.I can build a vector of attributes of what a terrorist bank account looks like. Then I can match new people against that database of vectors of terrorists.Believe me, every time you do a bank transfer, some AI program is out there trying to determine if you are a terrorist.----This is all that AI is.It is nothing more. It's not "intelligent" from a human sense. It's not conscious, nor will it ever be.Here's how AI has improved in the past forty years (and how it will improve the next 40):- statistics has gotten better- methods of building the trees have gotten better (this was the subject of some of my research when I was in graduate school)- hardware has gotten faster- more data is available about everything.What is changing the fastest is data. The land grab of modern society is not land, or gold, or oil.It's data.I have been invested in many companies that collect and sell data. I was an early investor (and on the board of) bit.ly, as an example. bit.ly accounts for about 2-5% of all Internet traffic.Believe me when I say, data-driven companies know how many strawberries you ate last summer.And right now that data is used mostly to target you for ads about sneakers. Or politics.But this is AI 1.0. Soon that data will be used to target your every movement, your every want, your every need.Amazon Prime won't be about delivering you what you want tomorrow. Amazon Prime Plus will be about delivering you what you want yesterday.Police 2.0 will be like the movie "Minority Report".Even art and music will be driven by AI that studies the neurochemical responses to music you like to music you don't like. And then compose accordingly.Where will humans still be unique?I don't know. Ask the humans with AI implants that enhance their brains so when they look at you they know exactly what answers will make you happy.BUT… will AI replace jobs?The answer (at least in the next decade or so…) is NO.Look at recent examples:A) Many people were worried ATM machines would replace bank tellers.Instead, the banks made so much in profits they opened up more branches than ever, creating new jobs.B) Will autonomous delivery services cost jobs.Right now there are millions of truck drivers involved in delivering goods. With autonomous delivery, less people will go shopping, more people will be required to shop in the aisles, finding products for people.Obviously this is not a high-end job. But this replaces the fact that less cashiers and drivers will be needed.Meanwhile, there will be more high-end jobs. More maintenance engineers for the cars, customer service, marketing, etc.C) Ecommerce. Branding will become less important (branding is VERY important when everyone is shopping at the big box store but advertising will have to become more clever and digital) so the millions in profits that are generated from AI will filter down to more people starting e-commerce ventures and the ancillary businesses associated with that.)Final conclusion:AI will probably create a “have” and “have not” situation, particularly as humans start to use AI to increase mental and physical capacityThis is probably a net NEGATIVE for society as the higher classes will be able to afford “super AI” capabilities, making them demi-gods to lower-classes.AI will not destroy as many jobsInstead, massive profits will be generated, which will be soaked into the economy through a rising stock market, increase in opportunities, etc.We can’t predict. ATMs didn’t destroy bank tellers. VCRs didn’t destroy movie theaters. Spotify/Pandora/etc did destroy music stores and record sales but that was replaced by growing revenues in music tours.Education needs to scale up. AI, programming, and the higher-end jobs that will be created need to be studied. College is not the place to study these opportunities. Instead: Khan Academy, Lynda, CodeAcademy, Coursera, etc should become accredited and get people ready for the opportunities that will arise.

It depends on what you mean by fast. By slower, I guess you mean top speed. F1 cars are not designed specifically for top speed.Short version:The F1 car is designed to win races at F1 tracks within strict regulations limiting power and performance. The Venom GT and Veyron don't need to be quick around a track. With no horsepower restriction, their straight-line speed is limited only by the need to be road-legal and the ingenuity of their designers.Long version:Fast, for an F1 car means getting around a specific set of short-ish closed tracks (that have quite a few corners) in the shortest time possible. At this, they are considerably faster than the Veyron or Venom.Consider the lap times from the Top Gear Test Track. Hardly perfect, but this is the only direct comparison I can think of.Bugatti Veyron 1:18.3Bugatti Veyron Super Sport 1:16.82004 Renault R24 F1 Car 0:59.0 ... in the WET!You can check out the full list of times here to see how the F1 car blows away everything else, road legal or not.List of Top Gear test track Power Lap TimesThe longest track on the F1 Calendar is usually Spa-Francorchamps at 7 km (4.35 mi) and looks like this:Although you can see a few straights, to be quick here you also need a car that can take a corner at speed.The Bugatti Veyron set its top speed on this track:The difference in scale is obvious on Google maps. The straight here is 8.7 km (5.4 mi) long. Thats longer than the longest F1 track and although it is perfectly flat, the end is not visible from the start due to the curvature of the earth!The turns at each end are banked to allow the fastest possible entry speed.Obviously the F1 car's advantage in cornering means little here.What if you remove the downforce that gives an F1 car such remarkable cornering performance? In 2006 Honda took their F1 car to the Bonneville Salt Flats.Honda F1 sets land speed records at BonnevilleThey removed the downforce-generating rear wing, gave it gearing to reach higher speeds and managed a two-way flying mile average of 397 km/h, peaking just over 400 km/h. On a shake-down test they hit 413.205 km/h without the salt slowing them down, a little quicker than the stock Veyron but some way short of the Veyron Super Sport and Venom.Why is this?Formula One does not offer a blank sheet to race car designers. The regulations strictly limit everything about an F1 car. The tradition of an open-cockpit, open wheel car is maintained, greatly increasing the aerodynamic drag. The engines are limited in size and RPM, preventing the car from getting too powerful and fast. Recent decades have seen the engine size shrink from 3.5L V8/V10/V12's, through 3.0L V10's, 2.4L V8's and now 1.6L Turbo V6.Although the Venom and Veyron need to be road legal, their engines can be as large and powerful as is practical. A 7L twin-turbo 1200hp V8 powers the Venom GT. The Veyron is motivated by an 8L quad-turbo W16 (Edit: corrected from W12 thanks to Primož Resman) of 1000 hp or 1200 hp. An F1 car would simply not be allowed to produce such outputs today.In conclusion, these cars are designed for two different types of Fast. On a long long straight, an F1 car will lose to these road cars but in their environment, nothing is quicker.To get some perspective, check out this video comparing the speed of various cars to Formula One cars. This was filmed at the famous Eau Rouge corner at the aforementioned Spa-Francorchamps track. Note that the vantage point is farther from the corner in the F1 side on the right, so they are covering more distance.Now thats what I call FAST!