Daily Archives: September 16, 2021

Bitcoin Transaction Fees Hit One-Year Lows, How Does This Affect The Price? – NewsBTC

Posted: September 16, 2021 at 6:47 am

Bitcoin transaction fees are usually an indication of how holders are moving their coins around. When the network gets congested due to a high number of transactions, the transaction fees go up, indicating a high volume of traffic on the network. Transaction traffic usually is high around bull markets when the price of the digital asset is up. Usually leading to a sell-off as investors try to take profits.

Related Reading |Bitcoin Suffers As Mid Caps Cryptos Establish Market Dominance With Wide Margin

One thing, this recent bull market has been anything but usual. So many things that are normal around bull markets have not happened with this bull market. An example is the declining reserves on exchanges. Bitcoin going up would often trigger an increase in the exchange reserves with the bull market, which happens because investors are trying to sell off their coins. This bull market, however, has shown the opposite. Exchange reserves have plummeted, and along with it, bitcoin transaction fees are at one-year lows, indicating that investors are carrying out fewer transactions on the blockchain.

The current climate for bitcoin transaction fees has been at levels not seen since last year. The fees which had spike following the great miner migration out of China have now dropped back to pre-2021 levels. Competition for block space due to the reduced hashrate had seen the transaction fees of bitcoin go up by about 50% in July of 2021. But as miners have come back online and the hashrate has picked up, fees on the network have dropped again.

Related Reading |MicroStrategy Deepens Its Crypto Bet With Another $240 Million Spent On Bitcoin

Current network activity shows that there is now less demand for block space on the blockchain. This is unique in the fact that during bull markets, demand for block space is usually at its highest. The last couple of bull markets have all shown similar trends. Bitcoin transaction volumes have spiked in previous bulls, leading to higher demand for block space, leading to higher transaction fees.

Presently, the average transaction fee for bitcoin transactions sits at $3. Average transaction fees have not been this low since October last year when the average fee was $3. Comparing this to April, when the bull market was in full force, the average transaction fee had been $61. Competition for block space was high as investors moved their assets around.

The price of the digital asset, like any other asset, is tied to the demand for the asset. Given the current transaction fees and transaction volumes, this shows that investors are not moving too much of their digital assets around. Hence, it points towards more hold sentiment amongst investors. This could spell the continuation of the bull market. Maybe one last bull run before the market finally gives in to the bears.

Related Reading |New To Bitcoin? Learn To Trade Crypto With The NewsBTC Trading Course

Hold sentiment has always been important when it comes to the price of the digital asset. This shows that bitcoin investors are more inclined to buy more coins instead of selling their existing stash. Thus creating scarcity in the market, which is evidenced by the decreased exchange reserves, which have also hit one-year lows. Scarcity inadvertently leads to a higher value for an asset. Playing to the basic laws of economics.

The price of bitcoin is currently above $48,000. A successful test of the $48,000 resistance point had seen the asset climb $400 above this, before losing hold and falling back below this crucial point. Indicators still show a positive upward trend in the price of the asset. Possibly a green close by the end of the midweek trading day.

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Bitcoin Transaction Fees Hit One-Year Lows, How Does This Affect The Price? - NewsBTC

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Ark Invest to split 60% Bitcoin, 40% Ether as confidence in ETH grows dramatically – Cointelegraph

Posted: at 6:47 am

Cathie Wood, CEO of Ark Invest, has doubled down on her prediction that the price of Bitcoin (BTC) will grow tenfold in the next five years and said the growth of decentralized finance (DeFi), nonfungible tokens (NFT) and the Ethereum 2.0 upgrade has massively increased Arks confidence in Ethers (ETH) future.

Woods prediction has Bitcoins value to have hit almost $500,000 by 2026. She said that Ark Invests future exposure to crypto was likely to be around 60% Bitcoin and 40% Ether.

Wood made the comments Monday during a live stream at the SALT Conference in New York.

Her BTC price thesis is based on more companies adding Bitcoin to their balance sheets and institutional investors allocating around 5% of their portfolios toward Bitcoin or other cryptos.

In her view, Bitcoin still remains the default currency of the crypto space, with El Salvador deeming it legal tender and other countries ofCentral America signaling they may follow soon.

But she said Ether is becoming more and more attractive as an investment thanks to the explosion in developer activity related to NFTs and DeFi.

Im fascinated with whats going on in DeFi, which is collapsing the cost of the infrastructure for financial services in a way that I know that the traditional financial industry does not appreciate right now, she said.

Ark Invest manages several actively exchange-traded funds with a focus on disruptive innovation. It has significant investments in Coinbase and shares in the Grayscale Bitcoin Trust, and Wood has spoken frequently about her enthusiasm for Bitcoin.

Related: Bitcoin bull run sparks $180K BTC price prediction ahead of institutional fireworks

Wood said that from past experience, she believed no regulator, including new United States Securities and Exchange Commission Chair Gary Gensler, would want to be blamed for preventing the next big tech breakthrough.

Wood believes the SECs threats to pursue legal action against Coinbase regarding the launch of a stablecoin yield product highlights that the crypto ecosystem is developing faster than the regulators have been able to keep up with.

In her view, Coinbase shouldnt be especially worried. Wood highlighted how in October 2019,Canada's largest Bitcoin and digital asset fund managerreceived a favorable ruling from the Ontario Securities Commissionto offer a publicly traded Bitcoin fund.

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Ark Invest to split 60% Bitcoin, 40% Ether as confidence in ETH grows dramatically - Cointelegraph

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Senegalese Bitcoin Developer: Bitcoin Is A Weapon To Fight Oppression – Bitcoin Magazine

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Fod Diop, a Bitcoin and Lightning developer from Senegal, has recently shared his thoughts on why Bitcoin is so important to billions of people worldwide that are still victims of monetary colonialism. The developer highlighted the central role that Bitcoin's open-source technology could play in providing financial sovereignty to those in the developing world.

"Today, people like myself have the means and the power to fight, and there has never been a time in the world like that until Bitcoin came in 2008," Diop told Reason. "Everything is possible actually, because money is everything."

Diop was accepted to Emporia State University in Kansas to study engineering and play basketball as a high school senior in Senegal. His father had saved just enough money for his tuition, but before enrolling, their savings were cut in half overnight due to a deal spearheaded by the International Monetary Fund (IMF) and France. To this day, the IMF and the French government still control the currency of 15 African countries.

"If you are in a country where your money might be devalued on the whim of other nations interfering with the local economy, storing your money in Bitcoin might be a better deal to preserve your wealth," said Diop.

Bitcoin didn't exist when the CFA franc, which had been pegged to the French franc for Diop's entire life at 1 to 50, got devalued to 1 to 100 in 1994 after France conceded to pressure from the IMF and the World Bank.

"The cruel irony was that the economic fate of millions of Senegalese was completely out of their own hands. No amount of protest could overthrow their economic masters," wrote the Human Rights Foundation's Alex Gladstein for Bitcoin Magazine in "Fighting Monetary Colonialism with Open-Source Code," an article that also recounts Diop's story.

The Senegalese Bitcoin developer echoed Gladstein's remarks to Reason, saying that "the local people felt robbed, because their purchasing power was cut in half overnight," and there was nothing they could do about it. It wasn't until Diop encountered Bitcoin that he started to glimpse how his people could fight monetary colonialism.

"When I read the [Bitcoin] white paper I said, this is a weapon for us to fight oppression. I feel like maybe governments are still threatened, but to me, open source technology is just beautiful," Diop said.

Bitcoin's open-source technology, along with the scaling and empowerment brought by Lightning, gives citizens worldwide the very weapons they need to fight the oppressor and reclaim their monetary independence.

"I believe that our work is so important that we have to do it no matter what the consequences are," said Diop. "You can leverage this open source technology to fight the oppressor, so why not use it?"

Indeed, the Senegalese developer has been doing just that. In July, Diop announced the launch of Bitcoin Developers Academy to teach students how to build Bitcoin applications from the ground up using the Rust programming language.

Empowered by open-source code and an antifragile peer-to-peer monetary network that cannot be debased or controlled by third parties, Diop, his students, and millions of others are now able to regain sovereignty over their financeswhether the IMF and the World Bank like it or not.

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What Is the ‘Golden Cross,’ and Why Are Bitcoin Investors Obsessed With It? – Money

Posted: at 6:47 am

For many Bitcoin investors theres nothing better than looking at a price chart and seeing the vaunted golden cross. At the same time, its dark twin, the death cross, can strike fear into the YOLO-est of hearts.

While cryptocurrency is new, studying price charts -- looking for patterns in graphs of up and down movements -- is one of the oldest (and oddest) trading strategies on Wall Street. Its also one of the most controversial, with advocates swearing price patterns contain valuable information, but many others dismissing the practice as investings equivalent to tarot cards or astrology.

Whatever they think of technical analysis, strategists say followers of Bitcoin markets cannot ignore the hype around a pattern thats forming on Bitcoin charts called the golden cross. Chatter about the indicator on specialist Web sites such as CoinDesk and Cointelegraph could catalyze more upward momentum, if only as a self-fulfilling prophecy.

Cryptocurrencies trade extremely technical because what else are they going to trade on? says Mark Arbeter, who publishes a newsletter analyzing the charts of a variety of indexes and securities. You cant pick up an annual report, a quarterly report...any kind of freaking report and do a fundamental analysis of this stuff.

Ever since Charles Dow compiled the Dow Jones Transportation Average in 1884, investors have sought to decipher broader trends in financial markets by charting prices and other indicators such as trading volume and price moving averages. Based on these indicators, technical analysts draw trend lines over price charts in an attempt to identify turning points. These points are broadly categorized as "support," spots where bounces tend to happen during selloffs; "resistance," spots where rallies tend to peter out; and "breakouts" or "breakdowns," spots where momentum should accelerate in one direction or another.

The most widely tracked chart trends in cryptocurrencies are moving averages, momentum indicators, which basically measure the speed of the up-trend or the down trend, says. Arbeter. There are simple and exponential versions of moving averages, with the latter giving more weight to recent prices. But the concept is the same: Take the daily prices of a security, index, commodity, or digital currency over a chosen period, add them all up and divide by the number of trading sessions.

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The chart lines tracking moving averages that form both the bullish golden cross and the bearish death cross trace the simple 50-day and the 200-day moving averages of a stock or cryptocurrency over an extended period of time.

The death cross, recorded by Bitcoin in July, indicates that the short-term trend expressed by the 50-day moving average line had accelerated downward by crossing below the long-term trend line, the 200-day moving average. This event was supposed to herald a breakdown of the long-term upward trend that began in March 2020. (As it turned out, Bitcoin began a new rally in late July.)

The golden cross is the bullish flipside, and happens when the 50-day moving average breaks above the 200-day moving average. Bitcoin was on the cusp of recording a golden cross as recently as Sept. 6, when, according to crypto Web site CoinDesk, the 200-day moving average was around $46,100 and the 50-day was about to move above that, following a string of closes above $50,000. As it happened, Bitcoin prices retreated the second week in September. It would have been the first time the golden cross has happened on a bitcoin chart in more than a year, suggesting a break-out to a more dramatic rally, according to technical analysts.

There are so many traders and algorithms, following the 50-day and 200-day moving averages on the Standard & Poors 500 that theres almost always a market reaction -- a series of rebounds in bear markets, or a series of short-term corrections in bull markets -- when either one is tested, says Arbeter, who has followed stock charts since he started on Wall Street the week before the crash known as Black Monday, October 19, 1987.

If you go back in time 100 years and look at uptrends in major indices, youll see the 50-day worked even back thenits just something that people pay attention to, says Arbeter.

On the wild bitcoin chart, however, the indicators are less reliable, Arbeter says. The "death cross" in July marked the end of the downward trend rather than an intensification of it.

For newcomers, the golden cross could still be a reassuring momentum signal, says Edward Moya, senior market analyst at OANDA Group, which specializes in another market where charts carry a lot of sway foreign exchange. Moya would see a move of the 50-day moving average above the 200-day as a signal that short-term upward momentum is strengthening, reducing chances of a sudden collapse in the short term.

With bitcoin, where you could see 20% plunges out of nowhere, and extreme drawdowns of over 50%...the golden cross pretty much alleviates the concerns that you're trying to catch a falling knife during one of those panic-selling frenzies, says Moya.

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What Is the 'Golden Cross,' and Why Are Bitcoin Investors Obsessed With It? - Money

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Bitcoin’s First Week in El Salvador: App Problems and Regulatory Uncertainty – The Street Crypto: Bitcoin and cryptocurrency news, advice, analysis…

Posted: at 6:47 am

For all the excitement surrounding Bitcoin in El Salvador, its first week has been plagued with app errors, vague regulations and a lack of public education on cryptocurrencies and blockchain technologies.

After President Nayib Bukele announced plans to introduce Bitcoin as legal tender over a live stream at the Bitcoin 2021 conference in June, the law was approved days later. That kicked off a three-month period for businesses to make themselves compliant by the time the law took effect Sept. 7.

During that period, the government rushed to roll out the Chivo wallet app, launched it right before the Bitcoin law took effect and is still battling service issues. The president and Congress also added a new article to the Bitcoin Law that said people and businesses without access to the technologies that allow them to carry out transactions in bitcoin are excluded from the obligation to accept it but did not specify how to apply for such an exemption.

Even with all the hiccups, Nolvia Serrano, the San Salvador-based chief marketing officer at fintech startup BlockBank, says reports about widespread protests in opposition to Bitcoin adoption have been exaggerated.

Im not saying everyone wants it. Im sure, absolutely, there are a lot of people who dont want Bitcoin, she said. But [people outside El Salvador] miss that this is political. The protests have been more about the president trying to have two terms in power. So there are all of these mechanics and dynamics in the country that explain whats really happening.

Whats more, she said, is that legitimate concerns are getting drowned out by Bukeles political rivals who dont themselves have a solid grasp on how Bitcoin works.

There are so many concerns that are legitimate, in my opinion for example, the volatility of Bitcoin. But there's also other information that's been spread by the opposition that's not correct, Serrano said. I was listening to the executive director [Leonor Selva] of the Association of Private Enterprises in El Salvador, and she was comparing Bitcoin to holding a piece of paper that says this is $5 which is completely not the case.

Thats why one of her most pressing concerns about Bitcoin has been the lack of public education. Working at a fintech company means shes well-versed in cryptocurrencies and understands the inherent risks of using them. But she worries the unbanked Salvadorian population, upwards of 70%, by one estimate, hasnt been given much guidance.

The hands-on approach used by the founders of Bitcoin Beach, however admirable, has been difficult to scale.

On the Sept. 11 when there was a big celebration of the Bitcoin, they came. They were not even having parties or anything, Serrano said. They were just helping all the lines of people trying to download their wallets.

Even with help, signing up for the Chivo wallet has been a struggle.

Fernando Argumedo, a San Salvador-based attorney at Central Law, practices corporate law. He focuses mainly on intellectual property, technology and data privacy.

Hes been unable to download the app on either of his two cell phones or his tablet. Even if he could, Argumedo said one of his main complaints about Chivo has been its privacy policy. It says by using the app, users consent to share their data with other institutions or related companies, as permitted by law.

That kind of vague disclaimer has given him and others pause, mainly because there isnt legal clarity on what can be shared or with whom.

Argumedo said there was a Congress-approved data privacy bill that Bukele rejected earlier this year. But while Bukele has been the incumbent for two years, the new assembly which is now politically aligned with his party took office in March. And so far theres been no indication that the new legislators will update and resubmit the data protection law for presidential approval.

Considering this, we don't have a specific act or regulation for you to understand how your data is going to be treated, Argumedo said. So that's a specific concern for people who are more worried about their data and privacy.

There are alternatives to Chivo. Jack Mallers Strike, once thought to be the heir apparent to the government-sponsored wallet, is among them.

Strike is a viable option because it started operating in El Salvador before the Bitcoin law went into effect. For existing apps and financial institutions, the government has issued guidance on how to comply with Bitcoin regulations. For newcomers, its not clear how to enter the market.

For new companies that want to provide new services related to Bitcoin, Argumedo said, those rules are still yet to be released.

Another complaint about Chivo has been the fact that its structured like a private company, but funded with public money. There was no government contractor process that solicited bids from companies. And, so far, there appears to be no government official who will be accountable for it.

Argumedo said businesses who do want to use the app have had issues creating accounts. The app specifies that business accounts should be created by a companys legal representative. That becomes an obstacle when a companys legal team is based in another country, he said.

These are people who have a resident card, they have a passport, but they are not able to create an account because they don't have Salvadorian Unique Identification, he said, so that's another concern.

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Bitcoin's First Week in El Salvador: App Problems and Regulatory Uncertainty - The Street Crypto: Bitcoin and cryptocurrency news, advice, analysis...

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Retail Investors Will Drive A $1 Million Bitcoin Price – Bitcoin Magazine

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To HODL bitcoin is to love bitcoin. And love, being the primary experience which we were set upon this earth for, should be spread like pollen in the wind.

If you truly love the people around you, you need to be educating them about bitcoin. Every single time a negative event occurs that is a direct result of the fiat standard that we live in, they must be reminded of this. Knowledge is power, and in a society with a crumbling monetary system, power is key to maintaining stability for your loved ones.

A major benefit of bitcoin is its ability to show its merits through reward, thus encouraging those who own bitcoin to become even more aware of these merits. Gathering knowledge through podcasts, articles and communication is central to many bitcoiners journeys in the space but this knowledge shouldnt be held to oneself.

Upon understanding bitcoin, the responsibility to share, promote and defend it must be ingrained within the Bitcoiner. Amidst the fires of confusion and chaos, we can be bastions of truth and direction. With purpose, retail investors can simply demonstrate the positive feedback loop of continued investment and growth in bitcoin. Those interested in humanitarian benefits have a vast world of information to discover. And for technology lovers, there are limitless possibilities of what could be built with bitcoin.

But in the end, it is incumbent upon those already orange-pilled to convey the message of bitcoin to others. It takes a concerted effort to reach out, educate and empower those who simply havent been reached yet. And with this effort, we can truly bring bitcoin to the masses, increasing adoption and driving the price of bitcoin higher. This in turn will bring even further interest, as the self-rewarding loop known as number go up technology continues to drive us towards hyperbitcoinization.

Retail investors have the ability to drive us to a $1 million bitcoin price all the sooner through their efforts to show bitcoin to others or bitcoin will simply show itself.

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Retail Investors Will Drive A $1 Million Bitcoin Price - Bitcoin Magazine

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Here Are Three Things That Must Happen for Bitcoin To Make New All-Time Highs, According to Crypto Analyst … – The Daily Hodl

Posted: at 6:47 am

Popular crypto analyst Nicholas Merten of DataDash is looking for three key components to fuel Bitcoins bull run towards new all-time highs.

In a recent Bitcoin update, Merten tells his 470,000 YouTube subscribers that Bitcoin (BTC) has been trading near a key level of ascending support and resistance around $43,500 that he wants to see the top crypto asset hold before establishing new highs.

The first thing we wanna see here is multiple retests of this previous line of resistance in order to solidify as support

It always tends to be that we test a certain range of support multiple times. And the reason for this is because its a test between whos in charge. Is it the bulls or the bears? Is it the buyers in this case? Are they buying more than the sell-side? Or vice versa, is the sell-side pressure outweighing any potential new buyers coming in?

As for the second step, he wants to see Bitcoin begin forming higher lows and higher highs after it solidifies new support levels.

Step number two is setting in higher lows and higher highs. Now, this can happen simultaneously with testing the support range, but its usually going to happen afterward because were gonna be testing this line multiple times.

Lastly, Merten is looking for a breakout past Bitcoins previous all-time high of $64,000 to see further continuation.

The third step, which I know might seem kind of obvious, is not only inevitably breaking past the broader-term relative highs, but eventually setting up the stage and continuing trend number two of setting those higher lows and higher highs where we eventually break above the previous all-time highs.

And the reason Im talking about this third step as a quite significant one is because its not an easy challenge. Breaking through all-time highs can generally take a pretty long period of time.

He flashes back to November 2020 when Bitcoin was trading just under its previous 2017 all-time high of $20,000, highlighting that BTC went through multiple pullbacks for about a month before finally breaking out.

As for the future, Merten is predicting the end of this year or the beginning of 2022 for BTC to climb towards new all-time highs.

Generally speaking, were looking for a potential breakout above those previous all-time highs in December of 2021, or January of 2022. I think thats a reasonable time frame.

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Here Are Three Things That Must Happen for Bitcoin To Make New All-Time Highs, According to Crypto Analyst ... - The Daily Hodl

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This needs to happen before Peter Schiff will buy Bitcoin (BTC) – CryptoSlate

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This needs to happen before Peter Schiff will buy Bitcoin (BTC)

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Schiff explains what it would take for him to change his mind on Bitcoin.

Samuel Wan September 16, 2021 at 2:00 am UTC 2 min read

Its no secret that gold-bug Peter Schiff loathes Bitcoin.

But, to his credit, he still ponders the arguments and is active in debating the issue.

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Artificial Intelligence – Overview

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Since the invention of computers or machines, their capability to perform various tasks went on growing exponentially. Humans have developed the power of computer systems in terms of their diverse working domains, their increasing speed, and reducing size with respect to time.

A branch of Computer Science named Artificial Intelligence pursues creating the computers or machines as intelligent as human beings.

According to the father of Artificial Intelligence, John McCarthy, it is The science and engineering of making intelligent machines, especially intelligent computer programs.

Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.

AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.

While exploiting the power of the computer systems, the curiosity of human, lead him to wonder, Can a machine think and behave like humans do?

Thus, the development of AI started with the intention of creating similar intelligence in machines that we find and regard high in humans.

To Create Expert Systems The systems which exhibit intelligent behavior, learn, demonstrate, explain, and advice its users.

To Implement Human Intelligence in Machines Creating systems that understand, think, learn, and behave like humans.

Artificial intelligence is a science and technology based on disciplines such as Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering. A major thrust of AI is in the development of computer functions associated with human intelligence, such as reasoning, learning, and problem solving.

Out of the following areas, one or multiple areas can contribute to build an intelligent system.

The programming without and with AI is different in following ways

In the real world, the knowledge has some unwelcomed properties

AI Technique is a manner to organize and use the knowledge efficiently in such a way that

AI techniques elevate the speed of execution of the complex program it is equipped with.

AI has been dominant in various fields such as

Gaming AI plays crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where machine can think of large number of possible positions based on heuristic knowledge.

Natural Language Processing It is possible to interact with the computer that understands natural language spoken by humans.

Expert Systems There are some applications which integrate machine, software, and special information to impart reasoning and advising. They provide explanation and advice to the users.

Vision Systems These systems understand, interpret, and comprehend visual input on the computer. For example,

A spying aeroplane takes photographs, which are used to figure out spatial information or map of the areas.

Doctors use clinical expert system to diagnose the patient.

Police use computer software that can recognize the face of criminal with the stored portrait made by forensic artist.

Speech Recognition Some intelligent systems are capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in humans noise due to cold, etc.

Handwriting Recognition The handwriting recognition software reads the text written on paper by a pen or on screen by a stylus. It can recognize the shapes of the letters and convert it into editable text.

Intelligent Robots Robots are able to perform the tasks given by a human. They have sensors to detect physical data from the real world such as light, heat, temperature, movement, sound, bump, and pressure. They have efficient processors, multiple sensors and huge memory, to exhibit intelligence. In addition, they are capable of learning from their mistakes and they can adapt to the new environment.

Here is the history of AI during 20th century

Karel apek play named Rossum's Universal Robots (RUR) opens in London, first use of the word "robot" in English.

Foundations for neural networks laid.

Isaac Asimov, a Columbia University alumni, coined the term Robotics.

Alan Turing introduced Turing Test for evaluation of intelligence and published Computing Machinery and Intelligence. Claude Shannon published Detailed Analysis of Chess Playing as a search.

John McCarthy coined the term Artificial Intelligence. Demonstration of the first running AI program at Carnegie Mellon University.

John McCarthy invents LISP programming language for AI.

Danny Bobrow's dissertation at MIT showed that computers can understand natural language well enough to solve algebra word problems correctly.

Joseph Weizenbaum at MIT built ELIZA, an interactive problem that carries on a dialogue in English.

Scientists at Stanford Research Institute Developed Shakey, a robot, equipped with locomotion, perception, and problem solving.

The Assembly Robotics group at Edinburgh University built Freddy, the Famous Scottish Robot, capable of using vision to locate and assemble models.

The first computer-controlled autonomous vehicle, Stanford Cart, was built.

Harold Cohen created and demonstrated the drawing program, Aaron.

Major advances in all areas of AI

The Deep Blue Chess Program beats the then world chess champion, Garry Kasparov.

Interactive robot pets become commercially available. MIT displays Kismet, a robot with a face that expresses emotions. The robot Nomad explores remote regions of Antarctica and locates meteorites.

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The responsibilities of AI-first investors – TechCrunch

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Ash Fontana, a managing director at Zetta Ventures, is the author of The AI-First Company: How to Compete and Win with Artificial Intelligence.More posts by this contributor

Investors in AI-first technology companies serving the defense industry, such as Palantir, Primer and Anduril, are doing well. Anduril, for one, reached a valuation of over $4 billion in less than four years. Many other companies that build general-purpose, AI-first technologies such as image labeling receive large (undisclosed) portions of their revenue from the defense industry.

Investors in AI-first technology companies that arent even intended to serve the defense industry often find that these firms eventually (and sometimes inadvertently) help other powerful institutions, such as police forces, municipal agencies and media companies, prosecute their duties.

Most do a lot of good work, such as DataRobot helping agencies understand the spread of COVID, HASH running simulations of vaccine distribution or Lilt making school communications available to immigrant parents in a U.S. school district.

However, there are also some less positive examples technology made by Israeli cyber-intelligence firm NSO was used to hack 37 smartphones belonging to journalists, human-rights activists, business executives and the fiance of murdered Saudi journalist Jamal Khashoggi, according to a report by The Washington Post and 16 media partners. The report claims the phones were on a list of over 50,000 numbers based in countries that surveil their citizens and are known to have hired the services of the Israeli firm.

Investors in these companies may now be asked challenging questions by other founders, limited partners and governments about whether the technology is too powerful, enables too much or is applied too broadly. These are questions of degree, but are sometimes not even asked upon making an investment.

Ive had the privilege of talking to a lot of people with lots of perspectives CEOs of big companies, founders of (currently!) small companies and politicians since publishing The AI-First Company and investing in such firms for the better part of a decade. Ive been getting one important question over and over again: How do investors ensure that the startups in which they invest responsibly apply AI?

Lets be frank: Its easy for startup investors to hand-wave away such an important question by saying something like, Its so hard to tell when we invest. Startups are nascent forms of something to come. However, AI-first startups are working with something powerful from day one: Tools that allow leverage far beyond our physical, intellectual and temporal reach.

AI not only gives people the ability to put their hands around heavier objects (robots) or get their heads around more data (analytics), it also gives them the ability to bend their minds around time (predictions). When people can make predictions and learn as they play out, they can learn fast. When people can learn fast, they can act fast.

Like any tool, one can use these tools for good or for bad. You can use a rock to build a house or you can throw it at someone. You can use gunpowder for beautiful fireworks or firing bullets.

Substantially similar, AI-based computer vision models can be used to figure out the moves of a dance group or a terrorist group. AI-powered drones can aim a camera at us while going off ski jumps, but they can also aim a gun at us.

This article covers the basics, metrics and politics of responsibly investing in AI-first companies.

Investors in and board members of AI-first companies must take at least partial responsibility for the decisions of the companies in which they invest.

Investors influence founders, whether they intend to or not. Founders constantly ask investors about what products to build, which customers to approach and which deals to execute. They do this to learn and improve their chances of winning. They also do this, in part, to keep investors engaged and informed because they may be a valuable source of capital.

Investors can think that theyre operating in an entirely Socratic way, as a sounding board for founders, but the reality is that they influence key decisions even by just asking questions, let alone giving specific advice on what to build, how to sell it and how much to charge. This is why investors need their own framework for responsibly investing in AI, lest they influence a bad outcome.

Board members have input on key strategic decisions legally and practically. Board meetings are where key product, pricing and packaging decisions are made. Some of these decisions affect how the core technology is used for example, whether to grant exclusive licenses to governments, set up foreign subsidiaries or get personal security clearances. This is why board members need their own framework for responsibly investing in AI.

The first step in taking responsibility is knowing what on earth is going on. Its easy for startup investors to shrug off the need to know whats going on inside AI-based models. Testing the code to see if it works before sending it off to a customer site is sufficient for many software investors.

However, AI-first products constantly adapt, evolve and spawn new data. Some consider monitoring AI so hard as to be basically impossible. However, we can set up both metrics and management systems to monitor the effects of AI-first products.

We can use hard metrics to figure out if a startups AI-based system is working at all or if its getting out of control. The right metrics to use depend on the type of modeling technique, the data used to train the model and the intended effect of using the prediction. For example, when the goal is hitting a target, one can measure true/false positive/negative rates.

Sensitivity and specificity may also be useful in healthcare applications to get some clues as to the efficacy of a diagnostic product: Does it detect enough diseases enough of the time to warrant the cost and pain of the diagnostic process? The book has an explanation of these metrics and a list of metrics to consider putting in place.

We can also implement a machine learning management loop that catches models before they drift away from reality. Drift is when the model is trained on data that is different from the currently observed data and is measured by comparing the distributions of those two data sets. Measuring model drift regularly is imperative, given that the world changes gradually, suddenly and often.

We can measure gradual changes only if we receive metrics over time, sudden changes can be measured only if we get metrics close to real time, and regular changes are measurable only if we accumulate metrics at the same intervals. The following schematic shows some of the steps involved in a machine learning management loop so that we can realize that its important to constantly and consistently measure the same things at every step of the process of building, testing, deploying and using models.

The issue of bias in AI is a problem both ethical and technical. We deal with the technical part here and summarize management of machine bias by treating it in the same way we often manage human bias: With hard constraints. Setting constraints on what the model can predict, who accesses those predictions, limits on feedback data, acceptable uses of the predictions and more requires effort when designing the system but ensures appropriate alerting.

Additionally, setting standards for training data can increase the likelihood of it considering a wide range of inputs. Speaking to the designer of the model is the best way to reach an understanding of the risks of any bias inherent in their approach. Consider automatic actions such as shutting down or alerting after setting these constraints.

Helping powerful institutions by giving them powerful tools is often interpreted as direct support of the political parties that put them into power. Alignment is often assumed rightly or wrongly and carries consequences. Team members, customers and potential investors aligned with different political parties may not want to work with you. Media may target you. This is to be expected and thus expressed internally as an explicit choice as to whether to work with such institutions.

The primary, most direct political issues arise for investors when companies do work for the military. Weve seen large companies such as Google face employee strikes over the mere potential of taking on military contracts.

Secondary political issues such as personal privacy are more a question of degree in terms of whether they catalyze pressure to limit the use of AI. For example, when civil liberties groups target applications that may encroach on a persons privacy, investors may have to consider restrictions on the use of those applications.

Tertiary political issues are generally industrial, such as how AI may affect the way we work. These are hard for investors to manage, because the impact on society is often unknowable on the timeline over which politicians can operate, i.e., a few years.

Responsible investors will constantly consider all three areas military, privacy and industry of political concern, and set the internal policy-making agenda short, medium and long term according to the proximity of the political risk.

Arguably, AI-first companies that want to bring about peace in our world may take the view that they eventually will have to pick a side to empower. This is a strong point of view to take, but one thats justified by certain (mostly utilitarian) views on violence.

The responsibilities of AI-first investors run deep, and rarely do investors in this field know how deep when theyre just getting started, often failing to fully appreciate the potential impact of their work. Perhaps the solution is to develop a strong ethical framework to consistently apply across all investments.

I havent delved into ethical frameworks because, well, they take tomes to properly consider, a lifetime to construct for oneself and what feels like a lifetime to construct for companies. Suffice to say, my belief is that philosophers could be better utilized in AI-first companies in developing such frameworks.

Until then, investors that are aware of the basics, metrics and politics will hopefully be a good influence on the builders of this most powerful technology.

Disclaimer: The author is an investor in two companies mentioned in this article (HASH and Lilt) through a fund (Zetta), where he is a managing partner.

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The responsibilities of AI-first investors - TechCrunch

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