#CRYPTO CONS

[ridenwithbiden]

CRYPTO CONS

Silicon Valley billionaires and crypto fans are throwing their support—and money—at former President Donald Trump.

“The Democratic Party has moved so far left that the Republican Party is now closest to the center,” Tesla CEO Elon Musk posted on X on Wednesday.

The tech bromance comes on the heels of Trump’s near-death experience and choice of J.D. Vance to be his vice presidential running mate. Musk recently promised to shovel $45 million a month into America PAC, a group that is backing the former president, the Wall Street Journal reported. Musk endorsed Trump minutes after the president survived an assassination attempt on Saturday.

In the lead-up to the endorsement, Musk and Trump had been shaping a potential administration gig for the billionaire, which would involve influencing economic policy, border security and voting integrity, according to the Journal. The two men purportedly talk on the phone multiple times a month.

America PAC’s other donors include the Winklevoss twins, billionaire Douglas Leone of Sequoia Capital, and Palantir co-founder Joe Lonsdale, who is taking part in leading the group, The New York Times reported.

Venture capital billionaires Marc Andreessen and Ben Horowitz also plan to donate to Trump, Axios reported Wednesday. On their Tuesday podcast, the pair lamented how President Joe Biden’s policies around AI and cryptocurrency have hurt start-ups in those fields.

The Biden administration has sought to rein in crypto, suing Coinbase and Binance and vetoing a bill that would have scaled back regulations. Trump, meanwhile, has said he doesn't want to lose crypto business to other countries. He plans to release a fourth collection of non-fungible tokens soon.

Trump's new running mate, Ohio Senator J.D. Vance, has been vocally critical of big tech, but he's pro crypto. He has drafted a bill to protect the industry and owns bitcoin himself. While a staunch critic of Biden, he has praised the president's Federal Trade Commission Chair, Lina Khan, who, like Vance, has been crusader against big tech.

The surge in support among the wealthy men of Silicon Valley may have helped sway Trump on Vance’s behalf—and Vance's selection may have helped win them over.

Musk and heavyweight venture capitalist David Sacks were among those who lobbied for Vance's VP selection, according to Axios. Sacks, a former PayPal executive who gave almost $1 million to a PAC supporting Vance’s 2022 Senate bid, boarded the Trump train in early June.

Peter Thiel, who co-founded PayPal with Musk and donated to Trump's previous bids, is another Silicon Valley titan who has a longstanding personal relationship with Vance. Thiel backed Vance's Senate bid with a record-breaking $15 million.

Thiel also facilitated the Vance-Trump relationship, arranging a meeting at Mar-a-Lago with the two men, as well as the president's son. Thiel told The Atlantic in 2023 that he wouldn't be giving to Trump again.

But some of Trump's earlier adopters are still chipping in. Among those who gave $1 million to America PAC last month is another PayPal co-founder, Ken Howery, the former president’s ambassador to Sweden.

[myhotmessandsoccer]

I remember asking this Latino chick on twitter who always tried to get me to cheat with her about her beloved Chelsea team who she claimed was the best soccer team in the world. She also told me watching the USWNT was something to be desired and like watching paint dry. So my question for coach Emma beings she was the coach of this all amazing team Chelsea which team is more talented.🤔

[aiartsale]

Bitcon is all about Bitcoin but with bite and some snark shot mit (mean spirited wit). Minty fresh NFTs....mmmmm. Burn after reading 🔥

[mentalbarf]

FUCK SBF "He's an awkward math nerd. He's into veganism. He has an off the chart intellect. He is a beautiful puzzle. He can parse words better than a Talmudic scholar. He was a billionaire unconcerned about material possessions." - Marc Mukasey [SBF Defense Attorney] FREE MINT on Zora Mental Barf 2024

[imageoscillite]

This isn't just the golden age of grifters, it's the age of dipshit grifters.

[crypto195]

Best Cloud Mining and Bitcoin Pool Mining Comparison in 2024

Exploring Cloud Mining and Pool Mining for Investors The choice between cloud mining and pool mining has become increasingly significant for investors aiming to maximize their returns. As the range of mining methods expands, it's essential to grasp the differences between these two popular options. This article will explore cloud mining and pool mining, outlining their features, benefits, and drawbacks to assist you in making a well-informed decision. We will also unveil the best cloud mining platform at the end of this article. So, continue reading to grasp crucial knowledge. What is Cloud Mining? Cloud mining involves renting mining hardware and infrastructure from a third-party provider. This service allows users to mine cryptocurrencies without the need to own or manage mining equipment themselves. Instead, you pay a fee to a cloud mining company, which then handles all aspects of the mining process. Pros of Cloud Mining: No Hardware Management: Avoid costly equipment and maintenance. Lower Energy Costs: Providers cover energy expenses. Ease of Use: Simple to start; just choose a plan and pay. Scalability: Adjust mining operations as needed.

To Know More- cloud mining benefits

[eltristanexplicitcontent]

PSA: Any sufficiently advanced technology is indistinguishable from magic.

Also, PSA: that magical future is here already -- it just isn't close to being evenly distributed yet -- and it's still easier to con a someone than to deliver.

[intelisync]

The Mechanics of Modular Blockchain: How It Works

Imagine a blockchain solution that grows with your startup, adapting to your evolving needs. Modular blockchain technology makes this possible by offering a flexible, scalable, and cost-effective approach to blockchain development.

Modular blockchain technology is reshaping the landscape of blockchain development by introducing a more flexible and scalable architecture. By breaking down traditional blockchain functionalities into distinct modules, startups can create customized blockchain solutions that fit their specific requirements. The primary modules execution, consensus, data availability, and settlement—work together to manage transactions, validate their accuracy, and ensure transparency.

The key benefits of modular blockchains include enhanced scalability, reduced costs, and greater adaptability. Startups can save on implementation and maintenance expenses by selecting only the modules they need. Additionally, the modular design allows for easier updates and improvements, fostering innovation and efficiency. With examples like Celestia, Dymension, and Cosmos leading the way, modular blockchain technology proves to be a game-changer for various industries.

Unlock the potential of modular blockchain with Intelisync's expertise. Our tailored development services are designed to help startups leverage modular technology for enhanced performance and security. Reach out to Intelisync today to revolutionize your blockchain infrastructure and drive Learn more....

[gemstarb]

Investigating the con that combines romance scams and crypto fraud (Mark...

[pupuseriazag]

Bestie ayuda hay gente celebrando que el gobierno le regalo 500 millones a google de nuestros impuestos para abrir un edificio y ya hay imbecil y medio diciendo que somos primer mundo por eso

[inveslo]

How to Buy and Sell Cryptocurrency?

Cryptocurrencies have gained popularity in recent years to change both finance and investment spheres. If you are a skilled investor or an enthusiastic rookie, familiarity with how to buy and sell cryptocurrencies is important.

In the course of this blog, we will provide you with a comprehensive guide about how to buy and sell crypto. We will talk about the foundations of cryptocurrency acquisition and trading, including choosing a suitable platform for crypto trade to creating safe digital wallets.

So, let’s prepare for your cryptocurrency trip with confidence!

Steps to Trade Cryptocurrency

There are various steps to trade crypto online. We’ll outline a few general steps to get you beginning here:

Step 1: Research and Select a Platform

There are several crypto platforms, each with its features, price, and list of supported coins. After examining several possibilities, decide on a platform depending on your requirements. Binance, Inveslo, and Coinbase are a few other well-known exchanges in addition to these.

Step 2: Create a Trading Account

Go to the chosen cryptocurrency trading platform’s website and create an account. It could be necessary for you to provide personal information and finish a verification process, which frequently includes bringing in identification documents.

Step 3: Enable Two-factor Authentication

As soon as your account is created, make security enhancements. Use a program like Google Authenticator to enable two-factor authentication (2FA). To protect your login information, make a strong, one-of-a-kind password and think about utilizing a password manager.

Step 4: Deposit Funds

You must add money to your wallet after setting up and protecting your account. The majority of cryptocurrency platforms accept some payment options, including credit/debit cards, bank transfers, and even other cryptocurrencies. To deposit funds in your account, follow the instructions provided by the cryptocurrency trading platform.

Step 5: Choose Pairs to Trade

Once you are done with funding your trading account, you are ready to strat buying and selling crypto. Cryptocurrencies are typically traded against other cryptocurrencies or fiat currencies such as BTC/USD and ETH/BTC. Choose the trading pairs you would like to use depending on your investment strategy and objectives.

Step 6: Place Buy or Sell Orders

You can put limit orders (set your preferred price) or market orders (buy/sell at the current market price) on the cryptocurrency trading platform. After checking the information and indicating the amount of bitcoin you wish to purchase or sell, place your order.

Step 7: Manage and Monitor Your Trades

Watch the market and monitor the results of your trades. To protect your gains, you can establish profit goals or stop-loss orders that trigger an automatic sell if the price falls below a certain threshold. Remember that the markets for cryptocurrencies are extremely volatile, So it is critical to remain knowledgeable and make wise choices.

Step 8: Withdraw Your Funds

You can start a withdrawal from your cryptocurrency trading account if you wish to transfer your cryptocurrency holdings to an external wallet for more security. Enter the required wallet address and proceed with the trading platform’s withdrawal procedure.

Suggested: How Ethereum Blockchain Works

What to Consider When Trading Cryptocurrency?

The world of cryptocurrency trading presents several difficulties, including extreme volatility, security threats, ambiguous regulations, a lack of transparency, and the possibility of losing money.

We will examine the dangers involved with purchasing and disposing of cryptocurrencies in this part. Let’s glance at them briefly.

Lack of Regulation

The trading of cryptocurrencies is still in its infancy and is not yet completely regulated in many nations. This monitoring gap leaves traders open to fraud, market manipulation, and security vulnerabilities.

Volatility

Cryptocurrency markets are highly volatile, with prices shifting dramatically over brief periods. There is a chance that this instability will result in both enormous profits and losses.

Security Risks

There are security risks while storing cryptocurrency on trading platforms or digital wallets. Platforms for trading cryptocurrencies may be subject to hacking efforts, which could lead to the loss of money.

Conclusion

The rise of cryptocurrencies in the recent past has changed the world of banking and investing. This blog provided a comprehensive overview of the processes involved in buying and selling cryptocurrencies, highlighting the importance of due diligence, safety measures as well as informed judgment.

It also highlighted the risks of crypto trading. If you know about the mentioned threats and take all necessary precautions, you can begin your cryptocurrency buy and sell journey with confidence.

Originally Published on WordPress

Source: https://inveslo.wordpress.com/2024/02/07/how-to-buy-and-sell-cryptocurrency/

[signode-blog]

The Bitcoin Chronicles: From Whitepaper to Digital Gold

The story of Bitcoin is a fascinating journey that began with the release of a whitepaper titled “Bitcoin: A Peer-to-Peer Electronic Cash System” on October 31, 2008, by an unknown person or group of people using the pseudonym Satoshi Nakamoto. The whitepaper outlined a decentralized digital currency that would operate on a blockchain, a distributed ledger technology. The idea was to create a…

[nando161mando]

An online pastor was charged in CO for a $1.3 million #crypto scam. He's released a 9-minute-long video explaining that the Lord told him to sell a cryptocurrency with no clear exit", and spend some of the proceeds on "a home remodel the Lord told us to do".

Here's a supercut.

or

[goodbreezeyeah]

Drawbacks, Disadvantages, and Cons of Central Bank Digital Currencies (CBDCs)

[mostlysignssomeportents]

What kind of bubble is AI?

My latest column for Locus Magazine is "What Kind of Bubble is AI?" All economic bubbles are hugely destructive, but some of them leave behind wreckage that can be salvaged for useful purposes, while others leave nothing behind but ashes:

https://locusmag.com/2023/12/commentary-cory-doctorow-what-kind-of-bubble-is-ai/

Think about some 21st century bubbles. The dotcom bubble was a terrible tragedy, one that drained the coffers of pension funds and other institutional investors and wiped out retail investors who were gulled by Superbowl Ads. But there was a lot left behind after the dotcoms were wiped out: cheap servers, office furniture and space, but far more importantly, a generation of young people who'd been trained as web makers, leaving nontechnical degree programs to learn HTML, perl and python. This created a whole cohort of technologists from non-technical backgrounds, a first in technological history. Many of these people became the vanguard of a more inclusive and humane tech development movement, and they were able to make interesting and useful services and products in an environment where raw materials – compute, bandwidth, space and talent – were available at firesale prices.

Contrast this with the crypto bubble. It, too, destroyed the fortunes of institutional and individual investors through fraud and Superbowl Ads. It, too, lured in nontechnical people to learn esoteric disciplines at investor expense. But apart from a smattering of Rust programmers, the main residue of crypto is bad digital art and worse Austrian economics.

Or think of Worldcom vs Enron. Both bubbles were built on pure fraud, but Enron's fraud left nothing behind but a string of suspicious deaths. By contrast, Worldcom's fraud was a Big Store con that required laying a ton of fiber that is still in the ground to this day, and is being bought and used at pennies on the dollar.

AI is definitely a bubble. As I write in the column, if you fly into SFO and rent a car and drive north to San Francisco or south to Silicon Valley, every single billboard is advertising an "AI" startup, many of which are not even using anything that can be remotely characterized as AI. That's amazing, considering what a meaningless buzzword AI already is.

So which kind of bubble is AI? When it pops, will something useful be left behind, or will it go away altogether? To be sure, there's a legion of technologists who are learning Tensorflow and Pytorch. These nominally open source tools are bound, respectively, to Google and Facebook's AI environments:

https://pluralistic.net/2023/08/18/openwashing/#you-keep-using-that-word-i-do-not-think-it-means-what-you-think-it-means

But if those environments go away, those programming skills become a lot less useful. Live, large-scale Big Tech AI projects are shockingly expensive to run. Some of their costs are fixed – collecting, labeling and processing training data – but the running costs for each query are prodigious. There's a massive primary energy bill for the servers, a nearly as large energy bill for the chillers, and a titanic wage bill for the specialized technical staff involved.

Once investor subsidies dry up, will the real-world, non-hyperbolic applications for AI be enough to cover these running costs? AI applications can be plotted on a 2X2 grid whose axes are "value" (how much customers will pay for them) and "risk tolerance" (how perfect the product needs to be).

Charging teenaged D&D players $10 month for an image generator that creates epic illustrations of their characters fighting monsters is low value and very risk tolerant (teenagers aren't overly worried about six-fingered swordspeople with three pupils in each eye). Charging scammy spamfarms $500/month for a text generator that spits out dull, search-algorithm-pleasing narratives to appear over recipes is likewise low-value and highly risk tolerant (your customer doesn't care if the text is nonsense). Charging visually impaired people $100 month for an app that plays a text-to-speech description of anything they point their cameras at is low-value and moderately risk tolerant ("that's your blue shirt" when it's green is not a big deal, while "the street is safe to cross" when it's not is a much bigger one).

Morganstanley doesn't talk about the trillions the AI industry will be worth some day because of these applications. These are just spinoffs from the main event, a collection of extremely high-value applications. Think of self-driving cars or radiology bots that analyze chest x-rays and characterize masses as cancerous or noncancerous.

These are high value – but only if they are also risk-tolerant. The pitch for self-driving cars is "fire most drivers and replace them with 'humans in the loop' who intervene at critical junctures." That's the risk-tolerant version of self-driving cars, and it's a failure. More than $100b has been incinerated chasing self-driving cars, and cars are nowhere near driving themselves:

https://pluralistic.net/2022/10/09/herbies-revenge/#100-billion-here-100-billion-there-pretty-soon-youre-talking-real-money

Quite the reverse, in fact. Cruise was just forced to quit the field after one of their cars maimed a woman – a pedestrian who had not opted into being part of a high-risk AI experiment – and dragged her body 20 feet through the streets of San Francisco. Afterwards, it emerged that Cruise had replaced the single low-waged driver who would normally be paid to operate a taxi with 1.5 high-waged skilled technicians who remotely oversaw each of its vehicles:

https://www.nytimes.com/2023/11/03/technology/cruise-general-motors-self-driving-cars.html

The self-driving pitch isn't that your car will correct your own human errors (like an alarm that sounds when you activate your turn signal while someone is in your blind-spot). Self-driving isn't about using automation to augment human skill – it's about replacing humans. There's no business case for spending hundreds of billions on better safety systems for cars (there's a human case for it, though!). The only way the price-tag justifies itself is if paid drivers can be fired and replaced with software that costs less than their wages.

What about radiologists? Radiologists certainly make mistakes from time to time, and if there's a computer vision system that makes different mistakes than the sort that humans make, they could be a cheap way of generating second opinions that trigger re-examination by a human radiologist. But no AI investor thinks their return will come from selling hospitals that reduce the number of X-rays each radiologist processes every day, as a second-opinion-generating system would. Rather, the value of AI radiologists comes from firing most of your human radiologists and replacing them with software whose judgments are cursorily double-checked by a human whose "automation blindness" will turn them into an OK-button-mashing automaton:

https://pluralistic.net/2023/08/23/automation-blindness/#humans-in-the-loop

The profit-generating pitch for high-value AI applications lies in creating "reverse centaurs": humans who serve as appendages for automation that operates at a speed and scale that is unrelated to the capacity or needs of the worker:

https://pluralistic.net/2022/04/17/revenge-of-the-chickenized-reverse-centaurs/

But unless these high-value applications are intrinsically risk-tolerant, they are poor candidates for automation. Cruise was able to nonconsensually enlist the population of San Francisco in an experimental murderbot development program thanks to the vast sums of money sloshing around the industry. Some of this money funds the inevitabilist narrative that self-driving cars are coming, it's only a matter of when, not if, and so SF had better get in the autonomous vehicle or get run over by the forces of history.

Once the bubble pops (all bubbles pop), AI applications will have to rise or fall on their actual merits, not their promise. The odds are stacked against the long-term survival of high-value, risk-intolerant AI applications.

The problem for AI is that while there are a lot of risk-tolerant applications, they're almost all low-value; while nearly all the high-value applications are risk-intolerant. Once AI has to be profitable – once investors withdraw their subsidies from money-losing ventures – the risk-tolerant applications need to be sufficient to run those tremendously expensive servers in those brutally expensive data-centers tended by exceptionally expensive technical workers.

If they aren't, then the business case for running those servers goes away, and so do the servers – and so do all those risk-tolerant, low-value applications. It doesn't matter if helping blind people make sense of their surroundings is socially beneficial. It doesn't matter if teenaged gamers love their epic character art. It doesn't even matter how horny scammers are for generating AI nonsense SEO websites:

https://twitter.com/jakezward/status/1728032634037567509

These applications are all riding on the coattails of the big AI models that are being built and operated at a loss in order to be profitable. If they remain unprofitable long enough, the private sector will no longer pay to operate them.

Now, there are smaller models, models that stand alone and run on commodity hardware. These would persist even after the AI bubble bursts, because most of their costs are setup costs that have already been borne by the well-funded companies who created them. These models are limited, of course, though the communities that have formed around them have pushed those limits in surprising ways, far beyond their original manufacturers' beliefs about their capacity. These communities will continue to push those limits for as long as they find the models useful.

These standalone, "toy" models are derived from the big models, though. When the AI bubble bursts and the private sector no longer subsidizes mass-scale model creation, it will cease to spin out more sophisticated models that run on commodity hardware (it's possible that Federated learning and other techniques for spreading out the work of making large-scale models will fill the gap).

So what kind of bubble is the AI bubble? What will we salvage from its wreckage? Perhaps the communities who've invested in becoming experts in Pytorch and Tensorflow will wrestle them away from their corporate masters and make them generally useful. Certainly, a lot of people will have gained skills in applying statistical techniques.

But there will also be a lot of unsalvageable wreckage. As big AI models get integrated into the processes of the productive economy, AI becomes a source of systemic risk. The only thing worse than having an automated process that is rendered dangerous or erratic based on AI integration is to have that process fail entirely because the AI suddenly disappeared, a collapse that is too precipitous for former AI customers to engineer a soft landing for their systems.

This is a blind spot in our policymakers debates about AI. The smart policymakers are asking questions about fairness, algorithmic bias, and fraud. The foolish policymakers are ensnared in fantasies about "AI safety," AKA "Will the chatbot become a superintelligence that turns the whole human race into paperclips?"

https://pluralistic.net/2023/11/27/10-types-of-people/#taking-up-a-lot-of-space

But no one is asking, "What will we do if" – when – "the AI bubble pops and most of this stuff disappears overnight?"

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/12/19/bubblenomics/#pop

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

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tom_bullock (modified) https://www.flickr.com/photos/tombullock/25173469495/

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