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Using a multivariable linear regression model to predict the sprint speed of players in FIFA 19

Using a multivariate linear regression model to predict the sprint speed of players in FIFA 19FIFA 19 Source: Express.co.ukI play FIFA games occasionally but classify myself as a relatively strong player who wins more often than not against other casual players. I am not a huge soccer fan in general and do not try and play a strategic game. Instead I rely heavily on player sprint speed and making unpredictable runs and turns. I often combine these skills to find and make spaces in my opponents space and dribble my way to a victory - much to the frustration of my opponent. Given this backdrop, I decided to download the FIFA19 dataset from Kaggle with the intention of predicting player sprint speed based on variables/features that I believed would best predict a player's sprint speed.Linear RegressionLinear Regression can be summed up as an attempt to model the relationship between one or multiple independent variables and a particular outcome or dependent variable. For this algorithm to be effective, there must be a linear relationship between the independent and dependent variables. Applied to data were a moderate to strong correlation exists between two or more variables it can be a very useful starting point in predicting the value of one outcome by finding the line that best fits/predicts an outcome.Y = MX + BThe math behind this is fairly simple, particularly where you are only looking at one independent variable. Y represents the outcome, or the dependent variable, while m denotes the slope, x the independent variable and b the y-intercept. Simply put, if you know the slope of the line and the value of the independent variable you can predict the outcome, assuming a linear relationship exists between x and y.In my case however, I am going to be looking at multiple independent variables therefore the formula required changes slightly.F(x) = A +(B1*X1) +(B2*X2)+(B3*X2)+(B4*X4)...+(Bn*Xn)With this formula I am assuming that there are (n) number of independent variables that I am considering. In this context F(x) is the predicted outcome of this linear model, A is the Y-intercept, X1-Xn are the predictors/independent variables, B1-Bn = the regression coefficients (comparable to the slope in the simple linear regression formula). Plugging the appropriate numbers in this formula would give me a prediction of an outcome, in this case the sprint speed of a player on FIFA19.Interacting with the dataFor this analysis I opted to use Python, downloaded the data from Kaggle uploaded it on my Google Drive, loaded up Google Colab and uploaded the data using the pandas read.csv function. After uploading the scipy, numpy and pandas libraries, I proceeded to the data clean up process.#librariesimport pandas as pdimport numpy as npimport matplotlib.pyplot as pltimport scipy.stats as statsfrom google.colab import drive#uploading datafifa_dataset = pd.read_csv('/content/gdrive/My Drive/Google Research/Learning/Kaggle Projects/FIFA19 dataset/data.csv')Data CleanupI started off with a few assumptions, I assumed that sprint speed would be largely influenced by height, weight, age, acceleration stats and possibly the ratio between a player's weight and height. Upon observation of the data set I noticed that the heights and weights were recorded in string format (e.g 5'11 and 180lbs), additionally as someone who is more accustomed to the metric system I wanted to change these measurements to centimetres and kilograms respectively.#inches to cmsfifa_dataset['Height']= fifa_dataset.Height.str.replace("'",".").apply(lambda x: float(x)*30.48).dropna()fifa_dataset['Height']= fifa_dataset['Height'].fillna(fifa_dataset['Height'].mean()).astype(np.int64)#lbs to kgsfifa_dataset['Weight'] = fifa_dataset.Weight.str.replace("lbs", "").apply(lambda x: float(x)*0.45359237).dropna()fifa_dataset['Weight'] = fifa_dataset['Weight'].fillna(fifa_dataset['Weight'].mean()).astype(np.int64)For weight, this conversion process involved splitting the string by looking for an apostrophe as a divider, replacing it with a full-stop(decimal separator) and applying a lambda function to convert the str to a float and converting it to centimetres. I converted the str to a float because I knew that the calculation would return a number that was essentially a float. After doing this I proceeded to fill all the NaN values with the mean height value in the dataframe and converted the number to an integer (under 100 rows). I made the assumption that filling in the missing values with a mean would be better for my analysis than forward filling, leaving out the NaN rows or changing them to zero. I later learnt that these columns would not be applicable to my analysis, however, I decided to include this to show the work I had to put in to clean some of the columns.def func(x): x = x.fillna(x.mean()).astype(np.int64) return xfifa_dataset[['Agility','Acceleration','Balance','Positioning','Skill Moves','BallControl','Crossing','Finishing','Reactions','SprintSpeed']] = func(fifa_dataset[['Agility','Acceleration','Balance','Positioning','Skill Moves','BallControl','Crossing','Finishing','Reactions','SprintSpeed']])After applying the same clean up to the height column, I defined a function that when applied to a column fills all NaN values with the mean of that column and converts the number to an int. After testing out which columns I would be using for my analysis, I applied this function to the relevant columnsTesting Correlation and Significance testingTo test correlation between each column and the outcome column (sprintspeed) I opted to use the spearmanr function from the scipy package. This function calculates correlation and returns both the correlation between x and y and the p-value or the probability of the significance of this correlation.#We want to test for moderate to strong correlationsdef corr_test(x): x_corr = stats.spearmanr(x, fifa_dataset['SprintSpeed']) return x_corrcorr_test(fifa_dataset[x])Using this function I ran through different columns in my dataset to determine which columns I would be using for my regression model. I opted to use columns where a moderate to strong correlation of at-least 0.50 (or under -0.50) existed. Using this as a benchmark I ended up with the columns; Agility, Acceleration, Balance, Positioning, Skill Moves, Ball Control, Crossing, Finishing and Reactions- these are the independent variables.Multivariate Linear Regression Model#multivariate linear regression#80/20 split- 20% training datafrom sklearn.linear_model import LinearRegressionfrom sklearn.model_selection import train_test_splitfrom sklearn.metrics import mean_absolute_errorfrom sklearn.metrics import accuracy_scoretrain, test = train_test_split(fifa_dataset, test_size=0.2)My machine learning algorithm (assuming you consider a linear regression model machine learning) relied heavily on the sklearn library. After importing this library, I opted to apply the 80/20 rule in splitting my data between training and test data, with 20% of the data falling under training data. I reasoned that I did not want to use more than 20% in order to get more certainty that my model could be generalised to the entire database.#independent and dependent variablesfeatures= ['Agility', 'Acceleration', 'Balance','Reactions','Positioning','Skill Moves','BallControl','Crossing','Finishing']target = 'SprintSpeed'#define model I am usingmodel = LinearRegression()#training processmodel.fit(train[features], train[target])model.fit(test[features], test[target])#mean absolute value for training datadata = train[target]predict = model.predict(train[features])training_error = mean_absolute_error(data, predict)#mean absolute value for test datatest_data = test[target]predict_test = model.predict(test[features])test_data_error = mean_absolute_error(test_data, predict_test)I went on to define the features I would be using for this model (the independent variables) and the target or the variable I sought to predict (the dependant variable) then proceeded to train the model using the linear regression model. Training involved looking at the correlation between the independent and dependant variables to make calculations that would enable the model to predict outcomes from the test data.Testing the ModelMean Absolute Error FormulaTo test the forecasting errors (loss function) in the data I calculated the mean absolute error (MAE) using the metrics module n sklearn for both the training and test data. In this formula n represents the number of errors in the data, Σ simply means summation and |yj — ŷj| refers to the absolute errors observed from the predictions. The formula sums the absolute errors and divides them by the total number of instances giving me a figure showing me what the average error between the predicted and actual sprint speed.I would ideally want the number to be as small as possible and report that figure together with my prediction success rate. I could have alternatively open to use the root mean squared error (RMSE) similar to the MAE this would return a figure showing the deviation of the predicted values from the predictions. RMSE simply finds the square root of the MAE figure (however we would square the absolute errors in this instance).#we need some metric to measure the accuracy of our regression modelfrom sklearn.metrics import r2_score#on training datatrue_value = train[target]predicted_val = model.predict(train[features])accuracy = r2_score(true_value, predicted_val)#on test datatrue_value2 = test[target]predicted_val2 = model.predict(test[features])accuracy2 = r2_score(true_value2, predicted_val2)To test the accuracy of this model I relied on the r2_score metric (coefficient of determination). The R2 score or R-Squared, measures how close the data fits to the regression model, the more the number approaches 1 the more it shows that a significant percentage of the values are explained by the linear regression model-indicating stronger prediction capability.print('This model accounts for {}% of the training data with mean data error of {}'.format(round(accuracy2*100,2), round(training_error,2)))print('This model accounts for {}% of the testing data with mean data error of {}'.format(round(accuracy*100,2), round(test_data_error,2)))####RESULT####>This model accounts for 84.96% of the training data with mean data error of 4.08 >This model accounts for 85.61% of the testing data with mean data error of 4.2As reported by my console, the prediction model accounts for 85.61% of my testing data with an average deviation of about 4.2 (the average deviation between the predicted value and actual value). According to this result if for example we make a predictions of players with a sprint speed of 90 with this model, there is a very strong probability that the actual sprint speed will on average be between 86 and 94. One issue I noticed with the predictors used is that some of the predictors had correlation with other predictors creating multicollinearity. However, from my understanding this does not have a significant effect on the prediction capability of my model.This wraps up my analysis.Feel free to send through any feedback or reach out to me on Twitter @EmmoemmUsing a multivariable linear regression model to predict the sprint speed of players in FIFA 19 was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.
Hackernoon

Billionaire Bitcoin Bull Tim Draper Has a Wild 5-Year Prediction for Cash and Crypto

Tim Draper has been one of Bitcoin’s most enthusiastic proponents. He was steadfast in his optimism even when other finance gurus thought he was crazy for giving the new-fangled crypto the time of day. Forgetting about the naysayers, Draper became about $89 million richer for sticking to his Bitcoin guns. He was steadfast while others, including JP Morgan CEO Jamie Dimon, made jokes about Bitcoin being tulips. FOMA, or simply recognizing the staying power of cryptos, JP Morgan shocked the financial community this month when it announced it would be the first major institutional bank to release its own cryptocurrency. The post Billionaire Bitcoin Bull Tim Draper Has a Wild 5-Year Prediction for Cash and Crypto appeared first on CCN
CCN

Tim Draper Predicts Only Criminals Will Use Fiat In Five Years

Bitcoin (BTC), Cryptocurrency–Bitcoin bull and billionaire investor Tim Draper has made headlines again with an interesting take on the future of cryptocurrency and fiat. On the same day that Bitcoin (BTC) nearly crested $4000, with the rest of the crypto markets experiencing a wave of green, the vocal investor made the claim that fiat is trending towards primarily criminal use. Draper, who has made high-profile claims before and is transparent in his support for Bitcoin as an investor in the digital asset, believes that BTC will be the predominant currency in five years. Compared to the  common mainstream narrative that cryptocurrency is primarily used by criminals, stemming from the storied past of The Silk Road, Draper believes that fiat will transition to the sphere of sole use by criminals. As noted by a U.S. Drug Enforcement Administration (DEA) agent in August 2018, the organization is beginning to prefer criminals use cryptocurrency over fiat due to the ease of tracking through blockchain. While typical blockchain based currencies such as Bitcoin may offer a level of anonymity in the ability to transact, the movement of capital is contained within a public ledger that can be traced for legal purposes. In the case of the DEA–and by extension Draper’s comment–blockchain provides a simultaneous security and honest-keeping record over traditional fiat. Speaking in an interview on Feb. 18 with financial news outlet Fox Business, Draper reiterated his position that Bitcoin is superior to traditional fiat, and predicted that in five years cryptocurrency will be the supreme form of currency with the latter being proven obsolete and relegated to the use of criminals. Draper also went on to state his belief that fiat in banks is less security than the value he stores through digital assets such as Bitcoin, claiming, “My bank is constantly under a hack attack,” while noting that no one has been able to hack or manipulate BTC backed by blockchain. This led Draper to go a step further, claiming that Bitcoin is substantially more secure than fiat, and generally represents a superior form of money. At one point, Draper compared exchanging Bitcoin to fiat as akin to trading gold for sea shells–an ode to the advancement that digital currencies have made in the face of their stagnant counterpart. While Draper presents an interesting scenario over criminal fiat use, the rise of Monero (XMR) and other privacy coins may disrupt that narrative. Not only do these currencies afford users the security and trust of blockchain-based transactions, but they also allow transactions to occur with complete anonymity. Some analysts have predicted that the need for privacy coins may drive the price of Monero and their like higher over the next decade, as digital assets for routine transactions such as buying a coffee become less sensationalized. However, Draper’s point to the outdated nature of fiat may have been partly represented in last week’s announcement by JPMorgan Chase to develop the JPMCoin. While JPMorgan’s new coin will not re-invent the crypto wheel, it does seek to offer an improvement in transaction speed and cost over the industry standard relying upon traditional money systems. The post Tim Draper Predicts Only Criminals Will Use Fiat In Five Years appeared first on Ethereum World News.
Ethereum World News

Tim Draper Predicts Crypto Will Rule, Only Criminals Will Use Cash in Five Years

Tim Draper Predicts Crypto Will Rule, Only Criminals Will Use Cash in Five Years Billionaire investor and known Bitcoin (BTC) bull Tim Draper argued that in five years, only criminals will use fiat as crypto becomes universally widespread. Draper made his claims in an interview with American financial news tv channel Fox Business released on […] Cet article Tim Draper Predicts Crypto Will Rule, Only Criminals Will Use Cash in Five Years est apparu en premier sur Bitcoin Central.
Bitcoin Central

XRP and Cardano (ADA) Price Analysis And Prediction

XRP and ADA Price Analysis XRP gains over 7% from its low in the last 24 hours XRP breaks resistance level of 0.030362 to achieve new highs ADA gains 13% within the last 24 hours ADA gains new high of 0.046 XRP The past 24 hours have seen XRP record a new high breaking resistance levels at 0.30362. The price became bullish in the last few hours after trading sideways since Feb 13. The bullish rally seems to find new support levels at 0.30476 with resistance levels at 0.3098. The 7-day MA rose steeply against the 21-day MA. During the last few hours, the 7-day MA has been acting as support for the bullish trends. The RSI spent the better part of yesterday ranging between 40- 60 when the markets were trading sideways. However, in the last couple of hour,s the RSI reached a high of 74 indicating that the markets were overbought. Forecast Moving forward, the price is expected to be range bound. Such a scenario would be ideal for an intra-range trading strategy with resistance at 0.3098 and support levels at 0.30484. Traders can go long once the prices bounce back from support levels (0.30484) or take a short position once the price pulls back from resistance (0.3098). ADA ADA has been bullish in the last 24 hours recording gains of over 13% from its low to get to a new high of 0.046.The currency also broke the resistance level of 0.042 to achieve its new high. ADA has been range bound for almost ten days finding resistance at 0.042 and support at 0.039. Resistance levels were broken as the bulls came calling and the currency achieved its new high seeming to find new support levels at an ascending trendline.7 day MA seems to be widening against the 21 day MA signaling that the bullish trend may still gain momentum. However, looking at the RSI, it is ranging between 40 and 60, seemingly signaling that the currency is still trading sideways. Forecast The bullish momentum is expected to continue for the foreseeable future and push the RSI to levels of over 70. The 7-day MA is expected to act as support for the bullish trend as it seeks new highs. New support levels in the near terms are expected to be at the range of 0.042-0.044. The post XRP and Cardano (ADA) Price Analysis And Prediction appeared first on ZyCrypto.
ZyCrypto

Examining the Most Overlooked Bitcoin and Cryptocurrency Market Prediction Caveats

The invention of cryptocurrencies brought the alternative way of managing our finances in a safe, convenient, decentralized way that many have accepted with great optimism. People want to have full ownership of their assets, which is impossible while third parties manage our funds for us. When you own cryptocurrencies, it is YOU who owns them and decides what to do with them, provided that you are careful with your private keys. However, while cryptos did bring a new way of managing funds, this is still quite a new and unexplored technology with a lot of flaws to it. Most of these flaws are likely not unfixable, although there are numerous issues with the system as it currently is. However, optimistic investors often tend to ignore some of the major problems, continuously claiming that the system is flawless, which can lead to losses. Ignoring the flaws is not the right way to go about them, which is why we felt the need to point out five of the major ones, even though not everyone in the crypto world wants to hear about them. 1. Crypto Experts Usually don't Know More Than you do We often hear about crypto experts giving one prediction or the other, with their opinions seemingly changing on a daily basis. This leads us to the first harsh truth, which is the fact that experts don't really know anything. Most of them are self-appointed, and while there are a few of them who may be considered actual experts, there is only a handful of them. Meanwhile, you would think that the crypto space consists of experts, as everyone has their own opinion which they try to pass on as expert advice. These “experts” emerged mostly during the time when cryptocurrencies were really big, back in 2017. Investors and traders were hungry for predictions and an investment or trading advice back then, and those who knew a bit about crypto started providing it. The majority of them came from Twitter, and their dated accounts somehow became proof that they know what they are talking about. The truth is that people still know very little about the crypto world and that it is next to impossible to predict the markets' behavior, which is why all expert predictions and opinions should be taken with a grain of salt. 2. You Being Attracted to Crypto is not a Rational Phenomenon While many probably do not want to hear this, the fact that the crypto space is still attracting interest does not really make sense from the logical point of view. Instead, its allure comes simply from our own emotions. Most people who are currently trading and investing in crypto are experiencing losses due to the bearish market, which indicates that they are only here for the dream of reaching decentralization. In other words, they are trying to make crypto a reality by force. 3. Most Positive Expert Predictions are Brought If you are following the tech news, you likely cannot find a single day without a ton of crypto-related headlines announcing, predicting, and constantly analyzing a different aspect of the crypto space. Even on social media, people are constantly posting, tweeting, and cheerleading, all in an attempt to keep cryptos on top. In a lot of cases, people are paid to do so, so that the trend would live on, which is not a phenomenon specific to cryptocurrencies. In fact, the so-called “human bots” have become increasingly popular in recent years, with people being paid to hype about pretty much anything and anyone. Due to the fact that the hype is not real, you should be really cautious when it comes to what you believe in. 4. Decentralization May not be Achievable Another rather unpleasant fact is that decentralization may end up being just a dream after all. Not because of the technical issues — we are perfectly capable of achieving it when it comes to the tech aspect. However, there is a big issue when it comes to what the people want, and what the people think they want. For example, people will say that they want freedom, authority, self-control, and alike. However, when they are at the bring of getting it, they suddenly become aware that obtaining it requires them taking the responsibility and having the discipline to maintain order. This is the part where many would get scared and turn the gift of autonomy away. After all, there is probably a reason why humans always tend to organize themselves so that there are firmly established ranks and hierarchies, instead of everyone being equal to everyone else. While there is no doubt that some people are born to rule themselves (and potentially others), the fact is that the majority does not want that kind of responsibility, and they are perfectly contempt with doing as they are told. 5. Most Crypto Projects will Undoubtedly Fail After the crypto space exploded in 2017, everyone realized that there is money to be made in the crypto trend. This is why countless new projects emerged, and while many of them already died, there are still over 2,100 living coins out there. However, most of them are weak projects that are barely keeping their heads above the water. With a situation like that, it is very likely that most of them will not make it much longer. While there are some coins that will survive, they are in the minority, while most coins were, are, and will be just a bubble that will eventually pop. According to Bitwise Asset Management’s Matt Hougan, as much as 95% of them will likely disappear in time. While others might take their place, the fact is that most of the current coins are nothing more than hype coins, and as such, they will go away when the hype dies down. This does not mean that cryptocurrencies themselves are doomed to fail, but the majority of the coins probably are, so be careful when it comes to picking projects for HODLing purposes.
Bitcoin Exchange Guide

USD/JPY Price Prediction: Trade Talks and FOMC Minutes are Huge Downside Risks; 110.25 Key Daily Support Eyed

Focus shifts to a possible FOMC hiking halt confirmation following the dovish rate decision from January. Trade talks continue in Washington, with USD pumped up on much optimism. The USD/JPY bulls have been pushing the pair higher at quite some pace, as it completed its second consecutive trading week in the green. It has gained around […] The post USD/JPY Price Prediction: Trade Talks and FOMC Minutes are Huge Downside Risks; 110.25 Key Daily Support Eyed appeared first on Hacked: Hacking Finance.
Hacked

BITCOIN $740,000 PREDICTION - Programmer explains

Bitcoin is highly important for our civilization, one of the most important aspects of Bitcoin is the fact that it's introducing triple entry accounting into the global trade. In connection to this, the CEO of one of the largest mining pools predicts Bitcoin price of 740k USD. Primedice.com - The most popular and trusted dice website - https://goo.gl/w6w28c http://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=8953732&fileOId=8953736 https://hackernoon.com/why-everyone-missed-the-most-important-invention-in-the-last-500-years-c90b0151c169 http://complexitylabs.io/triple-entry-accounting/ https://news.bitcoin.com/more-than-30-of-btc-traffic-stems-from-the-veriblock-project/ https://toshitimes.com/crypto-mining-pool-prediction-bitcoin-could-reach-740000-per-coin/ https://toshitimes.com/crypto-exchange-coinmama-hacked-450000-users-details-compromised/ https://www.ccn.com/the-232-million-ico-debacle-continues-as-tezos-community-opposes-class-action-lawsuit https://toshitimes.com/report-shows-how-facebook-creeps-on-ex-employees-and-users/ GET FULL ACCESS TO THE ACADEMY: https://academy.ivanontech.com LET’S MEET IN NEW YORK: https://www.facebook.com/events/452734075131412/ 💰 GET $10 TO BUY YOUR FIRST CRYPTO: https://www.coinbase.com/join/59d1738ff36136022bd9ee10 🏆 BUY PHYSICAL BULLION GOLD: http://www.bullionvaultaffiliate.com/ivanli/en 📈 BEST ALTCOIN EXCHANGE: https://www.binance.com/en?ref=35933746 🔐 BEST WALLET: https://www.ledger.com?r=5a56aa023b40&tracker=IOT Good Morning Crypto 🎓 LEARN SMART CONTRACT PROGRAMMING http://coding.ivanontech.com 🎓 Join my online academy https://academy.ivanontech.com 👬 Join the crypto discussion forum - https://forum.toshitimes.com 📣 Join Telegram channel https://t.me/joinchat/AAAAAE2xJE4l8xhC8MU4cg 🎤 If you would like me to speak at your conference, book me here: https://ivanontech.com #bitcoin #blockchain #ivanontech 👫👭👬Social: LinkedIn: http://linkedin.com/in/ivanliljeqvist/ Instagram: http://instagram.com/ivanontech/ Steemit: https://steemit.com/@ivanli Facebook: http://facebook.com/ivanontech/ Exclusive email list: http://eepurl.com/c0hyc9 DISCLAIMER: This is NOT financial advice. This is just my opinions. I am not responsible for any investment decisions that you choose to make. Ivan on Tech is all about cryptocurrencies and the technology behind Bitcoin, Ethereum, Litecoin, Ripple, IOTA. We also cover Bitcoin price, altcoin price, investing, analytics, different altcoins. Ivan on Tech by Ivan Liljeqvist
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Billionaire Elon Musk Lauds Bitcoin As “Quite Brilliant,” Why Isn’t Tesla Going Crypto?

While Elon Musk has yet to formally delve into the Bitcoin space, he has long been a fabled member of the crypto community. Since finding his way to the headlines of the world’s media, the Tesla chief executive’s pro-innovation mindset has struck a chord with many enamored with cryptocurrencies. In fact, some say that Musk’s unsaid raison d’etre of bettering society at large, especially by amending the world’s most harrowing issues (climate change, confinement on Earth, financial inequality), lines up with the goals held by many cryptocurrency insiders. Thus, some have even argued that Musk could be Satoshi Nakamoto. Sahil Gupta, a former intern at Musk’s second multi-billion dollar enterprise SpaceX, once infamously claimed that Musk’s brief mentionings of cryptography, economics, the C++ computing language, along with the entrepreneur overarching vision scream Satoshi. The South African-Canadian entrepreneur has done his best to keep his mouth zipped regarding his candidacy for the Satoshi title, but that hasn’t stopped him from talking about cryptocurrencies. We had @elonmusk on the latest episode of @ARKInvest's podcast! He had a few things to say about Bitcoin. "Paper money is going away and cryptocurrency is a far better way to transfer value than pieces of paper." – Elon Muskhttps://t.co/U5qOnM7nBo — Yassine Elmandjra (@yassineARK) February 19, 2019 Bitcoin Is “Quite Brilliant” While the crypto market has remained in a depressed state, save for Monday’s jaw-dropping rally, stars have begun to descend on this industry. Weeks ago, NewsBTC reported that a mass of celebrities, including the Spice Girl’s Mel B, Johnny Depp, Madonna, and Lionel Messi, had some involvement in cryptocurrency. More recently, Jack Dorsey of both Twitter and Square took to Joe Rogan to claim that the native currency of the Internet is likely to be Bitcoin. Related Reading: Twitter CEO Loves Lightning on Bitcoin: is it the Future of Fast, Instant Payments? And just on Tuesday, Elon Musk, the most well-known Silicon Valley guru, took to the New York-based ARK Invest’s “FYI” Podcast to touch on Tesla’s plans, autonomy, other innovations, such as crypto. Per The Block, who compiled his comments regarding cryptocurrencies, Musk made his comments with explicitly bullish tones. After discussing Tesla’s most recent advancements, the hosts of the podcast, the CEO and an analyst at ARK, a disruptive innovation-centric investment group, took a brief aside. They asked Musk if he agrees with Dorsey’s recent comments on Bitcoin and cryptocurrencies at large. Interestingly, Musk responded with an answer, albeit somewhat cursory. He tacitly agreed, noting that the “Bitcoin structure was (is) quite brilliant,” adding that Ethereum and “maybe some of the others” have merit too. Musk did admit that he isn’t too enamored with Bitcoin’s Proof of Work (PoW) consensus mechanism, noting that it is energy intensive. Yet, he explained that fundamentally, crypto assets are great as they bypass currency controls, especially in nations embroiled in financial and political turmoil, like Venezuela. He added that cryptocurrencies are also a “far better way to transfer value than pieces of paper,” subsequently quipping that he’s sure of this “without a doubt.” In spite of all this, he made it clear that Tesla isn’t going to foray into the crypto space in any capacity, noting that it would be a good use of his firm’s resources to prop up an offering. Musk’s abrash comments quickly elicited responses from each and every corner of the crypto space. Matt Odell, a long-time pro-Bitcoin coder and industry personality, joked that the comments “confirmed” his bias that cryptocurrencies could oust banknotes. Changpeng “CZ” Zhao of Binance noted that eventually, “[Musk] will join the brotherhood,” adding that he is unequivocally sure that the businessman will take up a crypto mantle. CZ notably called on the Tesla founder to take up the Lightning Network Trust Chain torch last week, just days after Twitter’s Dorsey openly lauded Bitcoin in dozens of tweets. Crypto Is Better Than Banknotes? While Musk made notable acknowledgments in his brief appearance on ARK’s “FYI,” what stood out to many crypto investors was his thoughts on the dichotomy between banknotes & physical cash, and crypto assets, not centralized e-money. For a brief recap, Musk simply stated that he is unequivocally sure that crypto, whether it be Bitcoin, Ethereum, or otherwise, is a “far better” medium of exchange than pieces of paper. Shocking, right? This may be deemed hearsay by pundits of the legacy world, but the world is already adopting digital mediums of exchange. Per previous reports from this outlet, Arthur Hayes of BitMEX took to his company blog to claim that platforms like WeChat Pay and AliPay have already begun to take over China’s financial system. Who’s to say that cryptocurrencies, a decentralized counterpart to these systems that tout their own currencies, cannot have a similar impact on society at large. The fact of the matter is that these digital payments systems, whether decentralized or centralized, offer benefits that cash/plastic cannot. Case in point, payments on both Bitcoin and WeChat Pay are cheap, rapid, and relatively secure. But arguably, decentralized payment ecosystems, which are non-sovereign, private, immutable, and non-censorable, are even better than their centralized peers, which is likely what Musk was touching on. Featured Image from Shutterstock Billionaire Elon Musk Lauds Bitcoin As “Quite Brilliant,” Why Isn’t Tesla Going Crypto? was last modified: February 20th, 2019 by Nick ChongThe post Billionaire Elon Musk Lauds Bitcoin As “Quite Brilliant,” Why Isn’t Tesla Going Crypto? appeared first on NewsBTC.
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In the Daily: Elon Musk Talks Bitcoin, Shanghai’s Fudan University, Xdat Exchange

In this edition of The Daily we cover some largely supportive remarks the famous entrepreneur Elon Musk has made about Bitcoin, the latest academic institution to launch a blockchain R&D center, and a new offering from Malta-based exchange Xdat. Also Read: Bank of Spain Report: Bitcoin Is a Solution for a System Without Censorship Elon Musk Talks Bitcoin The founder of Tesla and Spacex, Elon Musk, is once again making headlines about crypto. He recently went on the Ark Invest podcast to discuss the future of autonomous driving technologies. Most of the half-hour interview focused on the strategy behind his electric car company but the topic of cryptocurrency eventually popped up in the last four minutes. Musk commented: “I think the Bitcoin structure is quite brilliant. There seems like there is some merit to Ethereum as well, and obviously others. But I’m not sure if it’s a good use of Tesla resources to get involved in cryptos … We’re really just trying to accelerate the advances of sustainable energy. One downside of Bitcoin is … computationally it’s quite energy intensive. There has to be some kind of constraint on the creation of crypto. It’s very energy intensive to create the incremental bitcoin at this point … It bypasses currency controls. Paper money is going away, and crypto is a far better way to transfer value than pieces of paper. That’s for sure.” Shanghai’s Fudan University Launches Research Center Shanghai’s Fudan University has become the latest academic institution to launch a blockchain R&D center. Founded in 1905, Fudan is one of the most prestigious and selective schools for higher learning in China. The Shanghai Blockchain Engineering Technology Research Center is tasked with carrying out basic research in the field, developing demo applications in collaboration with the broader industry, and training talent to serve Shanghai’s economic development. Last month the University of California, Berkeley announced the formation of its own blockchain-focused startup accelerator program, the Berkeley Blockchain Xcelerator. This program is meant to help aspiring entrepreneurs create high-value ventures in the blockchain space with industry guidance from Silicon Valley. Xdat Exchange Lists 18 Trading Pairs Xdat, a new Malta-based cryptocurrency trading exchange, has announced the listing of 18 trading pairs. These comprise ETH/BTC, BCH/BTC, EOS/BTC, ETC/BTC, XRP/BTC, DASH/BTC, LTC/BTC, BTC/ETH, BCH/ETH, EOS/ETH, ETC/ETH, XRP/ETH, DASH/ETH, LTC/ETH, BTC/TUSD, ETH/TUSD, BTC/EURO, and ETH/EURO. The company has further plans to add other pairs over time. The exchange is compliant with Maltese regulations for KYC and AML procedures and caters to both retail and institutional investors. Its fiat gateway allows users to deposit funds in 12 major currencies: USD, GBP, JPY, HKD, CHF, AUD, NOK, SEK, DKK, CZK, PLN, and HUF. This selection is meant to eliminate the need for involvement of a foreign bank for the supported options and allows users to work solely with Xdat’s bank. “Xdat is on a mission to address the key problems of existing exchanges … including lack of flow of new capital, lack of trust, no approach for mass adoption, and high fragmentation,” said CEO Prashanth Swaminathan. “Our aim is to bring crypto to all. To that end, we will be working closely with our community and using their support and feedback to make our interface more user-friendly and trading as streamlined as possible.” What do you think about today’s news tidbits? Share your thoughts in the comments section below. Images courtesy of Shutterstock. Verify and track bitcoin cash transactions on our BCH Block Explorer, the best of its kind anywhere in the world. Also, keep up with your holdings, BCH and other coins, on our market charts at Satoshi’s Pulse, another original and free service from Bitcoin.com. The post In the Daily: Elon Musk Talks Bitcoin, Shanghai’s Fudan University, Xdat Exchange appeared first on Bitcoin News.
Bitcoin News

Elon Musk Praises 'Brilliance' Of Bitcoin And Ethereum, But Clash With Tesla's Energy Stance

Main Street seems to be giving cryptocurrency a second look. Last week, Jamie Dimon and JPMorgan Chase & Co. (NYSE: JPM) announced an investment in JPM Coin, which will become the first digital token provided by a U.S. bank. This week, Tesla Inc (NASDAQ: TSLA) CEO Elon Musk lent cryptocurrency additional validation. “Paper money is going away, and crypto is a far better way to transfer value than pieces ...Full story available on Benzinga.com
Benzinga

Elon Musk Calls Bitcoin "Brilliant" | Here's Why He's Optimistic

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