The Top 20 AI Cryptocurrencies For 2024 (Part 1)

Posted on by Werner

Introduction 

AI cryptocurrencies, as we explained in our last article, have really come to mainstream attention in 2023, at least for cryptocurrency enthusiasts,  following the breakthrough of popular large language model (LLM) such as OpenAI’s ChatGPT and the image generator Midjourney. In addition, we also had the Summer of Trading Bots this year.

While some experts like DeFi pundit Andre Cronje believe that artificial intelligence and blockchain technology (presently) shouldn’t mix, there is a growing cohort of promising AI projects that integrate both blockchain and cryptocurrency technology on chains like Ethereum and Solana in order to sustain and grow their ecosystems. 

Mindplex Magazine is excited about the use of artificial intelligence in the world of Web3 and cryptocurrency, and this article will be the first in a series that focuses on identifying top AI cryptos. 

With both AI and Web3 innovation expected to continue its ascent next year, here are five of the best AI cryptocurrency projects for 2024:

Credit: Tesfu Assefa

1. SingularityNET (AGIX): The AI Marketplace

Name
SingularityNET

Ticker
AGIX

Year Founded & Team

Founded in 2017 by Ben Goertzel (CEO)

Institutional Investors

Kosmos Ventures, Fundamental Labs, LDA Capital, Elizabeth Hunker, Zeroth.AI

What is SingularityNET?

SingularityNET is a decentralized platform that enables users to buy and sell artificial intelligence (AI) services. The platform uses blockchain technology to create a marketplace where AI service providers can offer their services to artificial intelligence and blockchain users.

Main Purpose

To provide a secure and transparent way for users to buy and sell high-quality AI services.

What Are Its Use Cases?

SingularityNET is basically a one-stop shop hub for all things AI. You can build new AI apps, carry out artificial intelligence research, and even launch your project into the real world. It’s like a marketplace where you can find, mix, and match various AI services to meet your unique needs.

How It Utilizes AI:

SingularityNET’s platform isn’t just about offering artificial intelligence services; it also uses machine learning to make your life easier. It helps you discover services that fit your needs, ensures you’re getting a fair price, and even checks the quality of the service you’re using.

Why SingularityNET Is Important?

SingularityNET democratizes AI usage for everyone. It does this by connecting developers to users to sell and buy AI services in a secure and transparent way. By making AI marketplaces more efficient and fair, it helps to bring the cost of machine learning down and raise its impact. 

What is the AGIX token used for? 

The AI crypto token AGIX helps SingularityNET manage transactions, govern its DAO and enable global access to artificial intelligence services. The token works across multiple chains like Cardano and Ethereum, and AGIX holders can stake their tokens with interest to provide platform liquidity.

Chains: Ethereum and Cardano
Fully diluted market cap: $358 million (Oct 2023)

2. The Graph: The AI Librarian

Name
The Graph

Ticker
GRT

Year Founded & Team

The Graph was founded in 2018 by Yaniv Tal, Brandon Ramirez, and Jannis Pohlmann, and in December 2020 it launched its mainnet.

Institutional Investors

Early investors included Launch Code Capital, Ganesh Kompella andFuture/Perfect Ventures.

Project Definition

Think of The Graph as a super-smart librarian for blockchain data. It sorts and organizes this data into neat categories called subgraphs. This helps developers and analysts find exactly what they need, whether they’re working on digital currency exchanges, virtual collectibles, or other blockchain-based projects.

Main Purpose

In simple terms, The Graph aims to make the messy world of blockchain data a whole lot easier to navigate through the use of artificial intelligence. If you’re looking to build a decentralized app (dApp) or just trying to analyze blockchain data, this platform is your go-to resource.

Use Cases

Primarily, The Graph is a big help in two areas: building dApps and researching blockchain data. Developers get a smoother way to integrate blockchain data into their apps, while researchers get a more streamlined method to sift through and analyze the data they need.

How it Utilizes AI:

AI plays a handy role here. It’s like the assistant librarian, helping you find the most relevant and high-quality subgraphs. It’s also the pricing guru, making sure you’re not overpaying for the data you’re after. Overall, machine learning is used to enhance The Graph’s functionality, ensuring the info you get is both reliable and fairly priced.

Why should you care about The Graph?

Because it’s essentially making blockchain data more approachable and user-friendly. Thanks to its AI features, it’s an invaluable tool for anyone wanting to build dApps or analyze blockchain data. It’s smoothing the path toward wider adoption of blockchain technology, making life easier for developers and data nerds alike.

What is the GRT token used for?

The Graph’s GRT token is a machine-learning cryptocurrency that’s used for staking, delegating, contributing to network governance, and payment to network participants.

Chains: Ethereum, Solana, Avalanche and more
Fully diluted market cap: $922 million, with infinite token supply (Oct 2023)

3. Fetch.AI (FET): The AI Agency

Name
Fetch.AI

Ticker
FET

Year Founded & Team

Founded in 2017 by Humayun Sheikh (CEO), Toby Shorin (CTO), and AJ Gordon (COO)

Institutional Investors

Fetch.AI raised $75m through investors like Outlier Ventures, GDA Group, BitGet and DWF Labs.

Project Definition

Fetch.AI is a game-changer in a few areas. It’s making supply chains smarter by automating stuff like keeping track of inventory and filling orders through the use of autonomous agents. If you’re into the Internet of Things (IoT), it’s also useful there—managing how devices collect and share data. Plus, it gives people a way to monetize their data.

How it Utilizes AI:

First off, Fetch.AI gives you the tools you’d need to build one of these smart agents. Once you’ve built one, it helps you deploy it to do whatever job it was designed for. And it doesn’t stop there; it uses artificial intelligence to make sure a bunch of these agents can work together efficiently to reach common goals.

Why It’s Important?

Fetch.AI is making businesses run smoother by automating a lot of their tasks. Because it’s all built on AI, it’s leveling up the marketplace for these autonomous agents, making this cool tech more available and cheaper for everyone.

What is the FET token used for? 

Fetch.AI’s FET is an artificial intelligence cryptocurrency used as a utility token for the Fetch ecosystem and network transaction fees. FET is required to find, create, deploy, and train autonomous economic agents and is essential for smart contracts, oracles, and transactions.

Chains: Ethereum, BNB Chain, and Cosmos
Fully diluted market cap: $267 (Oct 2023)

4. Ocean Protocol (OCEAN): The AI Data Merchant

Name
Ocean Protocol

Ticker
OCEAN

Year Founded & Team

Founded in 2017 by Trent McConaghy (CEO), Bruce Pon (CTO), and Brian Singer (COO)

Institutional Investors

Ocean Protocol has 20 institutional investors including Outlier Ventures, Amino Capital and Blockchain Coinvestors

Project Definition

Ocean Protocol is like an online marketplace, but specifically for data. The Singapore-based project uses the security of blockchain to help people buy, sell, and share data safely. It puts data owners in the driving seat, letting them decide who gets to access their data.

Main Purpose

The big idea here is to give people a safe and clear-cut way to deal with data. Whether you’re buying, selling, or just looking to share, it’s all above board and secure.

Use Cases

So what can you do with Ocean Protocol? A lot, actually. If you’re a business or a researcher looking to team up and share data, then this is your playground. Got valuable data? You can sell it here. If you’re on the hunt for very specific data, Ocean Protocol can help you find it.

How Ocean Protocol Wields AI:

The Ocean platform uses AI to make their user experience a case of plain sailing. It weeds out low-quality data so you’re only dealing with the good stuff. Plus it uses artificial intelligence to hook you up with the data that suits your needs and even helps to set a fair price for the data you’re interested in.

Why It’s Important?

Why does any of this matter? Well, Ocean Protocol is making the data world a better place. It’s more secure and transparent, so people are more willing to share. And thanks to AI, it’s also super efficient. This is great news for everyone from researchers to everyday data owners who want to unlock the value of their data.

What is the OCEAN token used for? 

The OCEAN token allows users to buy and sell data tokens and services, participate in governance, or stake within the Ocean Protocol ecosystem. 

Chains: Ethereum ERC-20 token
Fully diluted market cap: $450 (Oct 2023)

5. Cortex (CTXC): The AI Garden

Name
Cortex

Ticker
CTCX

Year Founded & Team

Founded in 2017 by Li Tian (CEO), Li Mu (CTO), and Jianping Chen (COO)

Institutional Investors

Cortex has 9 institutional investors including FundamentalLabs, IOSG Ventures, and Global Blockchain Innovative Capital.

Project Definition

Cortex uses smart contracts to facilitate transactions and ensure fairness and transparency in the AI marketplace. Think of Cortex as a communal garden for AI—anyone can come in, plant a seed (an AI model), nurture it, and sell the fruits. All of this happens on a decentralized blockchain, meaning it’s not controlled by any single entity.

Main Purpose

The core mission of Cortex is to make AI as accessible as Wi-Fi in a coffee shop. By offering a decentralized space to create, run, share, and even make money off artificial intelligence models and build AI-infused decentralized apps (dApps), it’s breaking down the ivory towers that often make AI seem unattainable for regular folks.

Use Cases

Cortex is a jack-of-all-trades when it comes to AI. Whether you’re a developer, a researcher, or someone looking to make a buck off your AI model, Cortex serves as your one-stop shop.

How it Utilizes AI:

Here’s where it gets meta—Cortex uses machine learning to make its AI marketplace better. If you’re looking for a specific AI model, its algorithms will match you up. And just like an auctioneer, it dynamically sets the prices based on what’s in demand. Plus, it makes sure whatever you’re choosing is up to snuff quality-wise.

Why It’s Important?

In a nutshell, Cortex is almost like the Robin Hood of AI. It’s making sure that AI technology isn’t just for the elite, but for everyone who wants in on it. By offering a decentralized, open platform for artificial intelligence, it’s tearing down the walls that have traditionally kept people out of this exciting field.

What is the CTCX token used for? 

The CTXC token is an ERC-20 asset and utility token for the Cortex platform, which is focused on AI and machine learning. It is used to pay for AI services, incentivize developers, and participate in the governance of the platform.

Chains: Ethereum ERC-20 token
Fully diluted market cap: $36 (Oct 2023)

Let us know your thoughts! Sign up for a Mindplex account now, join our Telegram, or follow us on Twitter. 

Digital Realms: The War for Sovereignty in Cyberspace

Posted on by SB Fisher

The internet is the infrastructure that supports our economy and society. Whoever controls it controls the world. Whoever can censor it, deny access, and control its output controls society. The internet is a permissionless network with countless participants, but nevertheless access to it has agglomerated towards centralised entities, whose influence grows by the day. Privacy is now a relic and your access to the internet is less assured than you might think. The war for cyberspace hasn’t just begun – it’s been raging for decades, and the war over the digital realm is no less vital than those waged in the real.

Erecting Digital Walls

The Great Firewall of China, the tongue-in-cheek name given to China’s mass surveillance, restriction, and gatekeeping of the internet has for decades now inhibited its citizens’ access to data. Russia recently followed suit. Societies on the totalitarian end of the spectrum want more than anything to keep the internet under their control, and deny access to global information. 

It’s easy to see why. The internet, like communication technologies before it, lets societies communicate and distribute information en masse without oversight of the elite. Remember that the printing press was heavily censored for centuries almost as soon as it was created, although in the end it didn’t stop the Lutherian reformation and the messages of the newly minted protestant movement being distributed in secret, smuggled under the cowls of renegade preachers.

Yet corporate America has its own issues with free internet access, with net neutrality under siege from ISPs who would like to discriminate and levy fees based on access it, or what they are accessing (although in fairness to the USA, their surrendering ICANN’s control of the DNS system to a multi-stakeholder model was a major move towards ‘decentralisation’ of the internet). 

Meanwhile, the EU panics about the US-led cartel in cloud computing, and the fact that the majority of the world’s data is held in massive data farms controlled by US techopolies and routed through Amazon, Google, and Microsoft’s services – data used by national governments to service their own ends, or wielded by corporations who finally rip off the fig-leaf of social conscience (remember that Google stripped ‘Don’t Be Evil’ from its corporate manifesto). 

How AI Data Scouring Leads to Dystopia

The advance of AI is central to the current hubbub of concern over all of this. Mass harvesting of data is useless without appropriate indexing and, as anyone who uses Windows can tell you, even searching a hard drive for a file can be a difficult task. No matter how many data crunchers you put to the task, and how powerful your indexing software is – there is simply too much data to reliably capture, store and output in any meaningful way. 

Command-and-control technologies like this are still in their infancy, despite decades of research. Yet neural nets trained to harvest innocuously-generated data lead to a dystopian future, one where you can say ‘Hi DataGPT, please look up [John Maguire], give me a three-paragraph profile on who he is, and a verdict on whether he is an enemy of the state’. To think governments won’t use it is a naive fallacy. In a decade, getting caught for speeding might have the cop asking his AI about you, and what you’ve been up to, before he decides whether he should wave you on or shoot you down. 

Credit: Tesfu Assefa

A Return to the Original Internet

The internet was originally dreamed up as a fully decentralised network, built to withstand the possible infrastructure-annihilating shocks of war or catastrophe. Over time, commercialisation crept in, and centralisation with it. Rather than accessing any given server, instead people accessing through one ‘node’, that of the ISP. 

That was Web 1.0 but, in some ways, Web3 is an attempted return the prelapsarian state first envisaged by the creators of the early internet, where activities and services are run on a decentralised set of nodes and are permissionless, trustless, and free (in an access sense) – forever, with no one able to revoke access, and no great firewalls being erected and – in an ideal world – with pseudonymous or anonymous privacy maintained.

Of course, Web3 currently needs the infrastructure rails of the ‘old internet’ to function. Yet as decentralised scalability improves, there is perhaps a future in which an internet exists which no nation state can colonise, where privacy is retained, and which enshrines the rights of the individual. Excitement over crypto starts with the power of trustless decentralisation, with tokens that give you the right to wander these digital realms without fear.

Let us know your thoughts! Sign up for a Mindplex account now, join our Telegram, or follow us on Twitter. 

Middle Class Precariat: The Obsolescence of the Intelligent Workforce

Posted on by SB Fisher

Is your job safe? Are you sure? In recent times, journalists around the world are facing mass layoffs in the wake of the generative AI boom. Following Buzzfeed’s lead, even traditional new organisations like Murdoch’s News Corp are using AI to mass produce their content. 

To some, this widespread cull of the journalistic class in traditional media is a necessary casualty in the march to the Singularity. If AI can do the job at 70% of the quality but 1% of the cost, then for any media CEO, it makes sense. Machines don’t go on strike, they don’t require breaks, and they never go home after a hard day at the office. 

Modern content and consumption habits are increasingly formulaic. Ad-driven sites spurn quality in favour of clickbait dopamine, driving communication to become ever more bitesize – and become something a computer program can handle. With language models among the first neural networks to make a breakthrough, the writers were among the first in front of the robot firing squad. Yet as generative AI develops, they won’t be the last.

Just The Latest Panic?

Technology is a labour-saving device, and the efficiency savings should, in theory, lead to a more wealthy, more liberated society. If we can get technology to drastically save time and effort on essential activities, then – theoretically – everyone should have more free time, more leisure, and more opportunity to create wealth or art on their own terms. 

They said that about the plough, they said it about washing machines, neither which turned out to be wholly true. But they absolutely didn’t say it about industrial looms, or automobile production. ‘Once a generation we have a near panic [that] technology is destroying jobs’, says Professor Richard Cooper, and he’s right. Historically though, new jobs emerged in the vacated space. 

Is AI just the latest panic? This time, the fear is different. A general intelligence won’t just take over one field of work, but all of them. Generative AI is the most generalist labour-saving technology ever conceived. The annihilation of the content journalist class is only the beginning. First they came from the writers. Then they came for the graphic designers. Then they come for you.

The Two Paths 

So which is it? Will AI finally unlock an abundant life of leisure, or consign humanity to a new serfdom? Where is our Neo-Luddite movement? There are two paths. One, where AI just augments current jobs, piloted by skilled humans, boosting efficiency and output, leading to broad wealth creation, or even unlocking new talent where before the barriers to entry were too high. A virtuoso game designer who was never able to code well may suddenly find their visions easy to enact. This path requires an orderly, fair, consultative transition about the integration of AI agents into our economic workforce.

Capitalism is rarely that careful. The key aspect of this economic meteor is how AI agents may take over large areas of the labour force in one short, brutal blow. If it’s just the graphic designers who lose out, perhaps they can retrain. But if 25% or 50% of middle class jobs get obliterated in one fell swoop? The potential stress on society could lead to far more than widespread poverty, it could lead to revolution. Society exists based on a treaty between the have and the have-nots, a line constantly fought over in politics and, at times of strife, the battlefield. If huge parts of society suddenly become ‘useless’ to the political and social economy, it may not be them who have to change, but society itself; such change rarely happens without violence or upheaval.

Credit: Tesfu Assefa

An ‘Organic’ Tariff

There is hope. We may see a turn back to ‘organic’ work taking on its own value-add, the same way that homespun crafted products often fetch a higher price than factory-made products. Yes, an AI may produce superior, more complex, and more technically adept work at any given task, but it may lack that ‘human’ touch. Right now, with the current state of AI, this unheimlich, or uncanny, valley is quite easy to spot, and often induces aversion in observers. 

Over time, it may become ever more imperceptible. In the case of sectors firmly in the crosshairs, like clerical work, it never mattered in the first place. Yet the hope of an artisan society, an economy powered by human creativity and in which AI allows us to meet our basic needs while we focus on what makes us happy and fulfilled, is too utopian a view in a world where the processing power that fuels AI agents (and the code that runs them) is in the clutches of a few corporations.

Things Will Fall Apart Fast

AI needs to benefit all of us. To do that, we all need a stake in it. If we let our rapacious capitalist tendencies as a society run too long without safeguards on the development of AI – we may find wealth inequality, aided and abetted by AI agents working for zaibatsus, becomes too extreme too quickly to fix. We are sleepwalking toward a nightmare society, too enthralled by the promethean fire to notice that it’s burning everything.

Let us know your thoughts! Sign up for a Mindplex account now, join our Telegram, or follow us on Twitter. 

The Rise of AI Cryptocurrencies: How Machine Learning is Reshaping The Crypto Industry

Posted on by Werner

Artificial Intelligence (AI) tools like OpenAI, and blockchain-powered networks like Ethereum have shaped the first few years of the 2020s, leveraging the power of Big Data, decentralized computing and network effects to disrupt a multitude of industries and reshape economic, social, and even environmental issues for better or worse.

The cryptocurrency revolution aims to transform finance through blockchain technology. Now, artificial intelligence (AI) is supercharging crypto with sophisticated machine learning algorithms. 

Where AI and blockchain intersect, they unlock a new wealth of possibilities for users, bolstered by AI’s productivity gains, blockchain’s security and its transparent and immutable participation trophies of cryptocurrency and non-fungible tokens (NFTs).

The appeal is easy to understand: AI offers real solutions to major challenges like security, scalability, and accessibility. And the industry is taking note, with more and more blockchain projects appearing that integrate machine learning into their DNA. 

This new breed of AI cryptocurrencies are rising from the wasteland of 2022’s crypto bear market to leverage AI for optimized transactions, predictive analytics, automated trading, and more. 

So the big question is, can AI-enhanced digital assets really unlock crypto’s true capabilities? Or will artificial intelligence’s data privacy issues drag virtual assets down with it to regulatory purgatory? Let’s check what all the hype’s about.

What Are AI Cryptocurrencies? 

AI cryptocurrencies are tokens that power AI-related blockchain platforms such as The Graph (the biggest AI crypto by market cap) and SingularityNET, arguably the most high-profile AI crypto project. 

In most cases, these tokens serve either as a means of payment for transactions, or as rewards for participants on the AI platform, or as a way of giving governance rights to holders. 

It’s important to note that not all cryptocurrency or blockchain projects which use AI in their systems have a token. 

How AI Cryptos Work

AI cryptocurrency projects use machine learning algorithms to make core crypto features smarter. They sift through huge datasets to offer a more personalized and improved user experience.

These AI coins are special types of crypto assets. They use artificial intelligence to make things better for everyone – whether it’s making your user experience smoother, scaling up the network, or tightening security.

And it’s not just about enhancing existing features; these coins are fueling new kinds of AI-focused projects. From decentralized marketplaces like SingularityNET to future market predictions and even managing your crypto portfolio like SingularityDAO, these AI coins are here to transform every inch of the digital financial landscape. Who and how will be addressed in a later article in our Crypto AI series. 

The Top Five AI Cryptocurrency Projects in 2023

You want names? OK OK. Here are five cool crypto projects that are leveraging artificial intelligence right now. We’ll cover more in our next article. 

  1. SingularityNET (AGIX) 

Founded by well-known AI researcher Ben Goertzel, SingularityNET is a decentralized AI-focused blockchain that allows anyone to monetize or utilize AI services. In its own words it’s building the next generation of decentralized AI and its network is powered by its AGIX token. SingularityNET has a blossoming ecosystem of partners and supported projects, such as Cardano and (yours truly) Mindplex. 

  1. Fetch.ai (FET) 

Fetch.ai is building an AI-powered blockchain to enable autonomous smart infrastructure. The open-access decentralized network allows devices to transact and share data via AI agents, with use cases across smart cities, supply chains, healthcare, and more. 

  1. Numerai (NMR)

Numerai is playing a numbers game, as its name suggests. It crowdsources machine learning for stock market predictions, and encrypts and anonymizes datasets to organize data science competitions among its community of data scientists. Winners are rewarded in NMR tokens based on the accuracy and predictive power of their models.

  1. Matrix AI Network (MAN) 

Matrix AI Network leverages AI to optimize blockchain architecture. The Intelligent Contracts and Intelligent Services chains allow smart contracts and machine learning models to interact seamlessly.

  1. Ocean Protocol (OCEAN)

This project focuses on data sharing, aiming to make datasets available for AI development without compromising on privacy. 

Benefits and Challenges of AI Cryptocurrencies 

Sorry Bitcoin: AI-injected digital assets deliver many advantages over traditional cryptocurrencies. Such as: 

They’re more efficient 

By automating manual processes, AI reduces costs and errors. Through the use of smart contracts, users also eliminate intermediaries, reducing another source of friction.

They’re more secure 

AI algorithms provide adaptive defense, and better threat detection against increasingly sophisticated cyberattacks. 

They can be personalized

AI analyzes trends and patterns to tailor solutions to each user. This provides a better customer experience.

They’re faster and more scalable 

AI optimizes protocols and transactions, increasing throughput, which translates to faster payments and high network capacity.

It’s not all a case of OK Computer though.

What are the biggest challenges for AI cryptos? 

Complexity and Cost

Sophisticated AI models require advanced expertise and resources, which many of today’s crypto projects, hamstrung by a long bear market, have in short supply. 

Data Privacy 

AI’s lifeblood is abundant user data. With Web2’s previous data exploits still fresh in the mind of consumers and regulators, this raises ethical concerns around consent and surveillance. And scanning people’s eyeballs isn’t providing good optics either, so to speak.

Energy Use

Training complex machine learning models uses a lot of computing power, which is a big no-no nowadays. Couple this with the general misconceptions over Bitcoin’s proof-of-work footprint, and it’s not a good look, even if most DeFi chains are environmentally-friendly proof-of-stake chains. 

Regulation

Laws have not kept pace with the rapid pace of AI and crypto development. Legislation for AI and crypto is in the pipeline that could put the brakes on the growth of both sectors. 

Credit: Tesfu Assefa

How is AI applied in Crypto? 

Let’s now look at some of the most popular current trends of utilizing AI in crypto:

AI in Decentralized Finance (DeFi) 

  1. Automated Crypto Trading 

As we covered in a previous article, AI-powered crypto trading bots have risen to prominence in 2023 due to their ability to automate the buying and selling of trading and investment positions based on technical indicators. 

AI bots can analyze market data, identify trends, and execute trades faster (sniping) and more efficiently than humans. Recently a Cointelegraph journalist took on an AI bot in a trading competition and lost. 

  1. Predictive Analytics

AI analyzes historical patterns in crypto prices, demand, and volatility. This powers price forecasting and predictive investment algorithms.

  1. Security 

AI algorithms can detect anomalies and cyberthreats. Then they adapt cyberdefenses, like in Numerai’s cryptographic security protocol.

  1. AI-driven DAOs: 

AI tokens are already used to fuel decentralized autonomous organizations (DAOs) and their applications, such as AI-powered trading algorithms and decentralized AI marketplaces. AI tools can optimize and speed up many DAO tasks, such as making proposals, summarizing governance decisions, transferring assets, and attracting new members.

  1. Fraud Detection

By learning normal user behavior patterns, AI can identify suspicious activities like ransomware attacks, hacking, and money laundering.

  1. Transaction Optimization 

AI can fine-tune transactions and protocols to enhance speed, cost, scalability, privacy, and other parameters.

  1. Personalization 

Analyzing user data allows AI cryptocurrencies to offer curated, tailored recommendations on investments, trades, and DeFi applications.

AI in Crypto Mining

AI presents solutions to enhance mining processes by improving algorithms, offering real-time data insights, and suggesting advanced hardware. Crypto mining uses powerful computational resources and specialized hardware to solve complex mathematical problems – whereas AI has a different set of hardware requirements.

Future Trends of AI in Crypto

Looking ahead, AI will likely evolve in tandem with blockchain infrastructure and aid its growth.

Here are four emerging trends:

AI-powered DeFi: Personalized and Efficient

DeFi is no longer just about simple transactions. With AI on board, DeFi are now your personal financial advisors, offering automated trading, advanced credit assessments, and tailor-made recommendations. 

AI Oracles: Bridging Real and Digital Worlds

AI Oracles go beyond regular data feeds; they intelligently enable AI systems to bring real-world data into smart contracts, bridging the gap between crypto and the real world.

Autonomous Agents: The Smart Brokers

Think of AI agents as your switched-on personal financial planners. They represent you in DeFi transactions, adapting to market changes and aiming to boost your returns.

Embedded AI: The Evolution Ahead

In the future, AI won’t just be an add-on; it’ll be part of the blockchain’s DNA. Embedded AI will perform a myriad of tasks such as improving transaction validation and enhancing security.

Endnote

While AI has taken a lot of limelight and lucre away from blockchain and crypto since its explosive rise in 2023, it should be viewed as a long-term ally that compliments instead of competes against digital asset technology. Its convergence with blockchain technologies has given rise to numerous promising AI crypto projects that will thrive over the coming decade. 

The benefits are easy to see: machine learning can make blockchains faster, cheaper, and more accessible, while AI cryptocurrencies are poised for mass adoption as the technology improves. 

Harnessing AI’s potential while addressing ethical concerns will be critical in democratizing DeFi and Web3’s realms. If that balance can be met, AI can transform crypto as limitlessly as it can transform other fields.

Let us know your thoughts! Sign up for a Mindplex account now, join our Telegram, or follow us on Twitter. 

A.I. in the Newsroom

Posted on by Joyce Pavia Hanson

Goodbye to the Byline? How A.I. May Change Authorship in News

In the world of print journalism, a byline is a coveted commodity. For journalists, it’s recognition of the hard work that goes into developing and writing a solid story. It’s no secret that reporters rely on editors, fact checkers, proofreaders, and automated spelling and grammar programs  for support in producing articles – that’s part of the process. 

But what happens when reporters use Artificial Intelligence (A.I.) to do more – such as produce paragraphs of content for their stories? Will reporters and news outlets disclose what is being produced by machines versus humans? Should the byline change to acknowledge A.I. generated content? 

A.I. Makes Inroads in the Newsrooms

Much has been written recently about the ability of machines and software programs to generate news articles. Tools such as QuillBot, ChatGPT and dozens more can create or paraphrase content. Many print and digital news organizations, faced with economic realities in today’s marketplace, have been quick to adopt A.I. 

News outlets have acknowledged the use of A.I. to generate (non-bylined) stores. The Associated Press states it was among the first news organizations to use AI in the newsroom: “Today, we use machine learning along key points in our value chain, including gathering, producing and distributing the news.”

“Roughly a third of the content published by Bloomberg News uses some form of automated technology,” The New York Times said in its 2019 article, “The Rise of the Robot Reporter.”

And in July, The New York Times reported that Google was testing a new tool called “Genesis” that generates news stories. “Google is testing a product that uses artificial intelligence technology to produce news stories, pitching it to news organizations including The New York Times, The Washington Post and The Wall Street Journal’s owner, News Corp, according to three people familiar with the matter.” 

As A.I. tools continue to be explored and adopted by reporters and the news media, some organizations have been sounding the alarm about the overall impact on the quality of newswriting and reporting created by automated systems. Inaccurate data, bias, and plagiarism – which have happened in human-generated stories – have also been uncovered in A.I. generated content.  

The most recent example of A.I. gone awry in a newsroom occurred last year at CNET. The news outlet issued corrections to more than half of 70 articles created by A.I. for its Money section. The articles, including many “how to” stories, were plagued by inaccuracies and plagiarism.

After correcting the articles, CNET announced it was changing its policies on the use of A.I. in generating news.

“When you read a story on CNET, you should know how it was created,” said Connie Guglielmo, former CNET Editor in Chief in her January 25 blog post. “We changed the byline for articles compiled with the AI engine to “CNET Money” and moved the disclosure so you don’t need to hover over the byline to see it. The disclosure clearly says the story was created in part with our AI engine. Because every one of our articles is reviewed and modified by a human editor, the editor also shares a co-byline. To offer even more transparency, CNET started adding a note in AI-related stories written by our beat reporters letting readers know that we’re a publisher using the tech we’re writing about.” 

(Guglielmo took on a new role in CNET following the A.I. debacle. She is now senior vice president on A.I. strategy.)

Many credible news outlets are letting readers know they are aware of the potential for A.I generated text to include bias and what actions they are taking to avoid it.

“We will guard against the dangers of bias embedded within generative tools and their underlying training sets,” The Guardian’s editor US Editor Betsy Reed states. “If we wish to include significant elements generated by AI in a piece of work, we will only do so with clear evidence of a specific benefit, human oversight, and the explicit permission of a senior editor. We will be open with our readers when we do this.”

Just last week, the Associated Press issued new guidance for use of A.I. in developing stories. “Generative AI has the ability to create text, images, audio and video on command, but isn’t yet fully capable of distinguishing between fact and fiction,” AP advises.

“As a result, AP said material produced by artificial intelligence should be vetted carefully, just like material from any other news source. Similarly, AP said a photo, video or audio segment generated by AI should not be used, unless the altered material is itself the subject of a story.”

Credit: Tesfu Assefa

Use of A.I. as a Tool, Not a Replacement for Human-Generated News

In some ways, the failed experiment at CNET supports the use of A.I. as a compliment to human reporting. Proponents cite the ability of A.I. to take the burden of mundane tasks off reporters and editors, increasing productivity and freeing up time to do what humans do best.

“Social Perceptiveness, Originality, and Persuasion” are cited as the human qualities that would be difficult for A.I. to replicate in newswriting and reporting, according to the website calculator “Will Robots Take My Job.” (Journalists are shown to be at a “Moderate Risk” of 47% of losing their jobs to automation, the site said.)

The new Google tool is designed to do just that, a company spokesperson said to the news outlet Voice of America.

“Our goal is to give journalists the choice of using these emerging technologies in a way that enhances their work and productivity,” the spokesperson said. “Quite simply these tools are not intended to, and cannot, replace the essential role journalists have in reporting, creating and fact-checking their articles.”

That philosophy may sit well with readers, as shown by a recent Pew Research Poll. When asked if A.I. in the newsroom was a major advance for the media, many didn’t see the value.

“Among Americans who have heard about AI programs that can write news articles – a use closely connected with platforms such as ChatGPT – a relatively small share (16%) describe this as a major advance for the news media, while 28% call it a minor advance. The largest share (45%) say it is not an advance at all,” the survey said.

Will Today’s Byline Become Extinct?

As A.I. becomes mainstreamed into the print reporting world, news outlets are faced with choices on how to acknowledge the origins of their content. Will reporters who use A.I. text in their stories acknowledge its source in their byline (‘By York Smith, and Genesis’)? Will they add a credit line at the end of the article? Or will A.I. generated sentences be considered just another tool in the hands of reporters and editors? 

A definitive answer may not be available yet. But credible news outlets that maintain the value of transparency will help the media develop a new industry standard in the world of machine learning.

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Old Money, New Game: Does Institutional Money Spell the End of Web3?

Posted on by SB Fisher

Big money – smart, dumb, and everything in between – is coming to Web3. The increasingly likely prospect of a spot Bitcoin ETF is a milestone in crypto’s final acceptance by the mainstream. Adoption is coming: a word that fuels the dreams of bedroom miners who have for years waited for the wider world to catch on to crypto’s promise.

For many, adoption is something to be fervently wished for, the final ratification of crypto’s potential. For others, it spells the end of crypto’s status as an alternative asset class, a death knell for the underground financial resistance that crypto historically represented.

Bitcoin: Always an Alternative

Bitcoin’s creation was predicated on being an alternative to big money. The first block in the entire chain contains a cryptic jab at central banks: “The Times 03/Jan/2009 Chancellor on brink of second bailout for banks.” The most recent bull run, although powered by stimulus checks and everyone having too much time on their hands, was built on the belief that Bitcoin and cryptocurrencies can be a store of value – a trustless hedge against the rampant money printing of central banks with levers operated by shady politicos funded by corporations keen to see their share price rise. I’m not suggesting this narrative is true or false, but it certainly fed the meteoric rise in crypto asset prices in 2020 and 2021.

Fifteen years of 0% interest and quantitative easing have made everyone’s money mean less (and everyone’s ownership mean more). Crypto represented a resistance to this. Almost since its inception, crypto has been seen as a chance for the little guy to make it, for Millenials and Gen Z (who are far more likely to be invested in crypto) to overturn the Boomers’ hoarded wealth and have a chance at replicating the stable, successful accumulation of their forebears, for those operating outside the standard rails of society to hold, store, and gain wealth. To let les miserables get involved in playing the game.

What ETFs Will Do To Crypto

The Securities and Exchange Commission (SEC) former chair’s statement that a spot Bitcoin ETF is ‘inevitable’ is, to some, a cause for sadness as well as celebration. Make no mistake, a Bitcoin ETF will open the doors for institutional money to get into crypto. ETFs (exchange traded funds) are a gold standard for institutional investors. Let’s talk about the positives first.

An ETF is a regulated mutual fund, professionally managed, that pays out dividends to shareholders based on its basket of securities. Unlike mutual funds, ETFs can be listed on a stock exchange, and are freely fungible for other cash or stocks. Most crucially, ETFs are an investment instrument that would not break fiduciary responsibility for pension funds, hedge funds, public businesses, or any other large institution who wants to hold crypto on their balance sheet and be exposed to crypto’s upside.

Upsides could be enormous if, as expected upon ETF ratification, institutions begin piling into crypto, as a method of diversifying their massive portfolios. The ‘$15 Trillion earthquake’ has the potential to send crypto not just to the moon, but to Oort Cloud. What about this is sad at all? Won’t everyone benefit? Well, yes, those who hold crypto will financially benefit – a lot.

Credit: Tesfu Assefa

A Requiem For Web3

The sadness is perhaps more philosophical, less practical. They worry that on the grandest scale, the cat will be out of the bag. Old money – banks, institutions, pension funds, Wall Street – these will become the primary drivers of the crypto market once crypto ETFs go live. The fun underground culture of Discord announcement parties, acid-mediated 125× Binance longs, Pepe-meme punts on shitcoins, and community-led price action with groundswell social campaigning will be completely swamped by the ticker tape tapestry of Bloomberg-reading MBA suits pumping tsunamis of money around the market or letting an algorithm HFT for them. Crypto will no longer be an alternative asset class, but just an asset class: regulated, controlled, and milled by the ancient financial machine that plunders all our tomorrows.

A New Financial System For Everyone

The hope, of course, is that crypto actually presents the opportunity for a fundamental change to the old systems. Ethereum (itself the subject of an ETF application) has, through its programmable smart contracts, the potential to act as an alternative financial substrate – one that is decentralised, trustless, and censorship resistant. One that levels the playing field and lets everyone ‘play up, play up, and play the game.’ It won’t just be Old Money buying into these assets, but these assets will form a new foundation on which the financial world can thrive – one that is permissionless and (at least nominally) fair, governed by smart contracts and regulated by all. Old Money might be entering the new game, but at least this time everyone gets a chance to join in.

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Understanding EIP-4844: Ethereum’s Proto-Danksharding Upgrade for Layer-2s

Posted on by Werner

Introduction

Ethereum is drawing closer to another upgrade in Q4 of 2023 which will have a transformative effect on its whole ecosystem.

The Cancun-Deneb (Or Dencun) upgrade will feature the important EIP-4844 protocol, designed to boost Ethereum’s competitiveness and the performance of its slew of layer-2 scaling chains.

Also known as Proto-Danksharding, in honor of two of its researchers, Proto Lambda and Dankrad Feist, EIP-4844 is a part of the broader Ethereum Improvement Proposal protocol, which allows for the introduction of new features to its network. 

It was conceived by Ethereum co-founder Vitalik Buterin (who recently shared his vision of three transitions needed to scale the network) along with a team of developers with the primary objective of lowering gas fees, particularly for layer-2 rollup solutions such as Optimism, Arbitrum, and zkSync Era, without compromising on the network’s decentralization. 

But what exactly is EIP-4844, and why is it so crucial for the future of Ethereum and the development of Web3? Let’s take a closer look. 

Sharding vs Danksharding vs Proto-danksharding

To fully grasp the impact of EIP-4844, it’s essential to understand what sharding and danksharding are. 

  • Sharding is a long-time end goal for Ethereum that dates back all the way to the 2018 Casper roadmap. It involves partitioning a blockchain network into smaller units, known as ‘shards,’ to improve transaction throughput and reduce network congestion. To get there though, some preliminary steps are needed.
  • Danksharding is a new architectural approach that relies on data blobs to scale the Ethereum blockchain. It’s a complex process that will be implemented in phases, with EIP-4844 serving as the initial step.
  • In the words of Vitalik Buterin, proto-danksharding provides the “scaffolding” for future sharding upgrades. It implements most of the logic required for danksharding without actually initiating sharding.

What is EIP-4844?

In short, EIP-4844, or Ethereum Improvement Proposal 4844, aims to enhance scalability by exponentially lowering gas fees on layer-2 rollups through innovative blob-carrying transactions. Yes, you read that correctly. 

Interestingly, EIP-4844 is a temporary fix – until sharding is fully supported on Ethereum and solves scaling. EIP-4844 introduces a new way to split transaction information, such as verification rules and transaction formats, without the need for full sharding.

What Are Shard Blob Transactions?

One of the most groundbreaking features of EIP-4844 is the introduction of a new transaction type known as “blob transactions”. These transactions allow for data blobs to be temporarily stored in the beacon node.

Blobs are essentially data packages around 125kB in size. Compared to regular transactions, blob transactions are cheaper to execute, but they are not accessible to the Ethereum Virtual Machine (EVM).

Scalability and Data Bandwidth

The data bandwidth for a slot in proto-danksharding is capped at 1 MB, a significant reduction from the previous 16 MB, which is a massive change aimed at alleviating Ethereum’s well-known scalability issues. The EIP-4844 update does not affect gas usage for standard Ethereum transactions.

Credit: Tesfu Assefa

Why is EIP-4844 A Game-Changer For Ethereum and L2s?

High gas fees have been a significant barrier to Ethereum’s mass adoption, as any DeFi user will tell you. People who tried to trade on Uniswap or flip NFTs during 2021s wild bull run (with its record-high ETH gas fees) can attest that some transactions cost hundreds of dollars in fees. Network fees on any blockchain can skyrocket when on-chain activity increases, making the network expensive and inaccessible for many users.

The advent of layer-2 side chains that use optimistic and zero-knowledge (ZK) rollup technology to compile transaction batches has done a lot to alleviate the pressure on Ethereum’s mainnet. The Optimism chain was presented in March 2022 by Proto Lambda with claims that it could potentially lower L2 transactions by up to 100x. But as things stand, when network usage and congestion soar, transactions still get unacceptably pricey.

EIP-4844 aims to be a game-changer by significantly reducing transaction fees and increasing throughput. Yet it’s only a stop-gap measure until the full implementation of data sharding, which would add around 16 MB per block of dedicated data space for rollups to use.

The Future of Ethereum and Rollups

With so much building happening on Ethereum due to its stable infrastructure and proven security, it’s no surprise that Buterin believes that the future of scaling the world’s first smart contract network will revolve around these rollup chains. Proto-danksharding is a pivotal stop on this roadmap. 

Post-implementation, users can expect faster transactions and lower fees, which will enhance Ethereum’s competitiveness in the blockchain sector, and help it to stretch its massive lead over rival layer-1s such as “ETH killers” like Solana, Cardano, and EVM-compatible chains such as Avalanche and BNB Smart Chain. These chains have also all been plagued with their own development setbacks from time to time. 

Conclusion

EIP-4844, or Proto-Danksharding, is more than just a not-so-catchy name; it’s a pivotal upgrade that promises to address some of Ethereum’s most pressing issues. From reducing layer-2 gas fees to paving the way for full sharding, this proposal is another worthy milestone on the road to Ethereum’s final state as the world’s computer.

The scheduled rollout in Q4 2023 should hopefully go through without any major surprises, if the network’s last few upgrades are anything to go by. Sailing was rarely smooth for any update prior to 2020’s Beacon Chain fork (2019’s Constantinople fracas comes to mind), but the ones after all breezed through with flying colors, giving ETH users and developers much-needed confidence. Let’s hope the Dencun update provides more of the same. 

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The Singularity Obsessed AI Hacker in Antero Alli’s Last Film Blue Fire is Only The Beginning

Posted on by RU Sirius

I suppose the way to get Mindplexians interested in Antero Alli – author, theater producer, experiential workshop leader and film director – is through his ties to Timothy Leary and Robert Anton Wilson starting back in the 1980s, where that pair were advocating transhumanist slogans like Space Migration, Intelligence Increase, Life Extension.

But the reality is that Alli has carved his own path as a writer, a thinker and director. And as he slowly exits corporeality, it’s his film oeuvre that most fascinates me.  

I recently spent a day watching several of his films and it struck me that I was looking at part of  an entire body of work that has been largely neglected by those writing about and advocating for indie films. Alli’s films may be about to be discovered. They certainly deserve substantial notice. There are hours of enjoyment and intrigue awaiting viewers.

And while enough of his films enclose neo-tech tropes like VR and AI to cause one or two commentators to toss out the buzzword “cyberpunk,” these are all ultimately human stories leaning on depth psychology, Jungian symbolism, dreams and real experience.

In the preview for his latest film (and most likely his last) ‘Blue Fire’, Alli highlights the Singularity.

The central protagonist is an underground singularity-obsessed AI hacker. Scenes show male computer-freak social awkwardness, unrequited male obsession with a woman and a bad Salvia Divinorum trip (been there). Ultimately ‘Blue Fire’ is not a film about AI or the personalities of underground hacker archetypes. It’s a film about human connections — connections made but mostly connections missed.

I interviewed Antero Alli by email.

R.U. Sirius: Since Mindplex readers probably aren’t familiar with your work, what would you say is the theme or project or search that runs through all of your work that includes books, theater, experiential workshops and film, including the most recent one we’re discussing today?

Antero Alli: The silver thread running through most everything I’ve put out to the public since 1975 – my books, films, theatre works, Paratheatrical experiments – reflects my ongoing fascination with how our diurnal earth-based realities are impacted in meaningful ways by our nocturnal dreams and related astral or out-of-body events. I have felt compelled to share these visions through the Art of words, images, and human relations. All this obsession started back in 1975 when I endured a spontaneous out-of-body experience at the age of 23. I say endured since the experience itself was traumatic and a massive shock to my concept of identity. I was no longer able, in all honesty, to identify as a physical body after being shown more truth when seeing and knowing myself as a light body, an electric body, cased within the physical body. No drugs were involved. The only condition I can relate it to was exhaustion from an intense theatre rehearsal that evening. All my films are oneiric docufictions, where real life experiences are camouflaged and spun by my feral poetic imagination.

Credit: Antero Alli

RUS: We met when we were both working and playing with the ideas of Timothy Leary and Robert Anton Wilson. To the extent that their ideas are likely of interest to the mostly technophile readers of Mindplex, they would be attracted to the technotopian ideas they advocated like SMI²LE and evolutionary brain circuits as opened by drugs and technology, and then Leary’s later advocacy of cyberpunk and the digital revolution. How do you see your own work in relationship to these tropes?

AA: My contribution to the legacies of Timothy Leary and Robert Anton Wilson is demonstrated through my thirty-year era of working with The Eight-Circuit Brain model. This started in 1985 with the publication of my first 8-circuit book, ‘Angel Tech’, updated and expanded in 2009 with ‘The Eight Circuit Brain: Navigational Strategies for the Energetic Body’. (Both books are still in print at The Original Falcon Press.) My approach is somatic and experience-oriented, rather than theoretical or philosophical. I relate the eight-circuit model as a diagnostic tool to track and identify multiple states of consciousness and eight functions of intelligence that can be accessed as direct experience through ritual, meditation, and trigger tasks. This embodiment bias sets my circuit work apart from Leary’s more theoretical approach and Wilson’s use of multiple systems theory to expand the eight-circuit playing field. Between the three of us, I think we cover the bases pretty well.

RUS: The dramatic persona in Blue Fire is an underground AI hacker… seemingly a singularitarian. How did you conceive of this character? Was he based on someone or a composite or a pure imagining?

AA: The AI-coder Sam, played by Bryan Smith, was inspired in part by the actor — a singular personality with a dynamic physical sensibility and this very pure kind of cerebral charisma, a complexity that I felt could brilliantly serve the film. I was also intrigued and inspired by the subculture of coders that I discovered talking with a few of my friends, AI freaks and serious hackers, who shall remain anonymous.

RUS: Without giving up too much of the plot, the other protagonists are a relatively normal nice seemingly-liberal couple. The dynamic between could be read as a contrast between neurotypicals and neuro-atypicals, In this case the atypical doesn’t do very well but is perhaps a catalyst for putting the typicals through some changes. Would you read it that way?

AA: The so-called typical couple are not lovers or married or in any kind of romantic involvement; nowhere in their dialogue mentions or indicates that. What is clear is that she is a student in the college-level Psychology 101 that he teaches. They form a bond over their shared interest in dreams, a bond that deepens into a troubling mentorship. All three characters act as catalysts for each other in different ways. Much of this starts in their nocturnal dreams and how their daily discourse is impacted by these dreams. This daytime-dreamtime continuum continues as a thread throughout most of my films.

RUS: Again, not giving up too much, the hacker dude smokes some salvia divinorum… and based on my own experiences, you got that right in the sense that it’s often an uncomfortable high. I’ve referred to it as “naggy”. People who want to be happy about being in disembodied cyberspace should probably make ketamine their drug of choice (I’m just chattering here but welcome you chattering back) or even LSD rather than a plant. McKenna used to believe that with plant psychedelics there’s someone or something in there… kind of another mind with something to impart to the imbiber. Any thoughts on this or thoughts on minds other than our own here on earth and what they can teach us?

AA: I knew Sam, the A.I. coder, had a drug habit, but didn’t know at first what drug would be the most indicative of this native state in mind. What drug would he gravitate towards? What drug amplifies his compartmentalizing, highly abstract, and dissociative mindset? After smoking salvia several times, it seemed like a good fit (not for me but for Sam). By the way, I don’t make my films to school the audience or teach them anything. It would be a mistake to also view any of the characters in my films as role models, unless your Ego Ideal includes flaws, shortcomings, and repressed Shadow material. Though ‘Blue Fire’ revolves around Sam’s AI coding, this is also not a story about AI but how AI acts on Sam’s psyche. Like my other films, I explore human stories planted in extreme circumstances or situations where people face and react to realities beyond their control or comprehension.


RUS: Aside from AI, virtual reality pops up in some of your work, and the language of hacking occurs here and there. But I don’t think your work would be categorized as cyberpunk or even sci-fi. What role would you say fringe tech and science play in your films?

AA: The fringes of tech and science play a role in those films – their presence amplifies the human story or shows the viewer a new context or way of seeing how the characters interact with tech and science. This keeps me and my films honest, as I’m no techie or science nerd. My deep background in theatre and ritual (Paratheatre) has slam-dunked me into the deeper subtext of human relations and how this interacts with the transpersonal realms of archetypes and dreams.

RUS: I’m feeling a little claustrophobic making what I suspect might be your last or one of your last interviews just about Blue Fire as directed at the Mindplex audience. If you’re up to it, why don’t you hit the world with your parting shot, so to speak. A coda? A blast of wisdom? A great fuck-all? A kiss goodbye? Whatever you feel. And thanks for being you.

AA: I’m feeling a bit claustrophobic about answering your question. I get that others sometimes think of me as this fount of wisdom – which humors me to no end. I suppose whatever ‘wisdom’ has been born in me, it’s come from making many mistakes and errors of judgment that I have felt compelled to correct as soon as possible, if only because I hate the dumbdown feeling of making the same mistake more than once. This self-correction process vanquished any existing fear of making mistakes, in lieu of an excitement for making new mistakes – defining my creative approach to most everything I do as experimental. Everything starts out as an experiment to test the validity of whatever idea, plan, or theory I start with. Sometimes I’m the boss and sometimes the situation is the boss.

No fuck alls, no kisses goodbye, no regrets. I remain eternally grateful to have lived an uncommonly fulfilling life by following and realizing my dreams. At 70, this has proven a great payoff during my personal end times (I was diagnosed with a terminal disease and don’t know my departure date).

BLUE FIRE Official site

https://www.verticalpool.com/bluefire.html

Antero Alli Films online

https://www.verticalpool.com/dvd.html

9/21 Portland premiere

Purchase Advance Tickets

Sept. 22 – YouTube Premiere

Sept. 26 – New York Premiere

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System Shocks: The Perils of Corporate AI

Posted on by Daniel Dob

Do you want to be a paperclip? This isn’t a metaphor, rather a central thesis of Nick Bostrom’s harbinger book Superintelligence. In it, he warns of the calamity lurking behind poorly thought out boot up instructions to AI. An AI tasked with the rather innocuous goal of producing paperclips could, if left unchecked, end up turning every available mineral on earth into paperclips and, once completed, set up interstellar craft to distant worlds and begin homogenising the entire universe into convenient paper organisers.

Horrifying? Yes. Silly? Not as much as you may think. Bostrom’s thought experiment strikes directly at a core problem at the heart of machine learning. How do you appropriately set goals? How do you ensure your programming logic inexorably leads to human benefit? Our promethean efforts with AI fire is fraught with nightmare fancies, where a self-evolving, sentient machine takes its instructions a little too literally – or rewrites its failsafe out entirely. Skynet’s false solution is never too far away and – to be fair to literary thinkers, AI builders, and tech cognoscenti – we have always been conscientious of the problem, if not necessarily the solutions.

Learning Machines Require Resources

The thing is, machine learning is not easy to research. You need insane processing power, colossal datasets, and powerful logistics – all overseen by the brightest minds. The only entities with the unity of will to aggressively pursue AI research are the corporations, in particular the tech giants of Silicon Valley. Universities make pioneering efforts, but they are often funded by private as well as public grants, with their graduates served up the conveyor belt to the largest firms. In short, any advances in AI will likely come out of a corporate lab, and thus its ethical construction will be mainly undertaken in the pursuit of profit.

The potential issues are obvious. An advanced AI with access to the internet, poorly defined bounds, capital to deploy, and a single goal to advance profit for its progenitor organisation could get out of hand very quickly. A CEO, tasking it one evening, could wake up in the morning to find the AI has instigated widespread litigation against competitors and shorted bluechip stocks in their own sector at vast expense for a minor increase in balance sheet profit – that is a best case scenario. Worst case – well, you become a paperclip.

The Infinitely Destructive Pursuit of Profit 

Capitalism’s relentless profit incentive has been the cause of global social traumas the world over. From environmental desecration for cheaper drinking water, to power broking with user’s data staining politics, the general ruination of public services by rentier capitalists ransacking public infrastructure and pensions for fast profit is a fact. For sure, capitalism ‘works’ as a system – in its broadest conception, and yes, it does a great job of rewarding contribution and fostering innovation. Yet we all know the flaw. That single, oppressive focus on ever increasing profit margins in every aspect of our lives eventually leads to a race to the bottom for human welfare, and hideous wealth inequality as those who own the means of production hoard more and more of the wealth. When they do, social chaos is never far behind. The way that capitalism distorts and bends from its original competition-focused improvement into a twisted game of wealth extraction is just a shadow of what would occur if an AI takes the single premise of profit and extrapolates the graph to infinity. Corporate entities may not be the proper custodians of the most powerful technologies we may ever conceive, technologies that may rewrite society to their own ends.

Credit: Tesfu Assefa

A Likely Hegemony; Eternal Inequality

This may sound like extreme sci-fi fear mongering. A tech junkie’s seance with the apocalypse. So let’s consider a more mundane case – whoever has AI has an unassailable competitive advantage that, in turn, gives them power. Bard, ChatGPT, and Bing are chatbots, but there are companies who are working on sophisticated, command and control AI technologies. AIs that can trawl CCTV databases with facial recognition. AIs that can snapshot credit and data of an individual to produce a verdict. AIs that can fight legal cases for you. AIs that can fight wars. The new means of production in a digital age, new weapons for the war in cyberspace, controlled by tech scions in glass skyscrapers.

If these AIs are all proprietary, locked in chrome vaults, then certain entities will have unique control over aspects of our society, and a direct motive to maintain their advantage. Corporate AIs without checks and balances can and will be involved in a shadow proxy war. For our data, our information, and our attention. It’s already happening now with algorithms. Wait until those algorithms can ‘think’ and ‘change’ (even if you disallow them a claim to sentience) without management’s approval. It won’t be long before one goes too far. Resources like processing power, data, and hardware will be the oil of the information age, with nation states diminished in the face of their powerful corporations. A global chaebol with unlimited reach in cyberspace. Extreme inequality entrenched for eternity.

The Need for Open-Source AI

There is an essential need, therefore, for open-source access to AI infrastructure. Right now, the open-source AI boom is built on Big Tech handouts. Innovation around AI could suffer dramatically if large companies rescind access to their models, datasets and resources. They may even be mandated too by nation states wary of rival actors stealing advances to corrupt them to nefarious ends. 

Yet just as likely, they will do so afraid of losing their competitive advantage. When they do, they alone may be the architects of the future AIs that control our daily lives – with poorly calibrated incentives that lack social conscience. We’ve all seen what happens when a large system’s bureaucracy flies in the face of common sense, requiring costly and inefficient human intervention to avert. What happens when that complex system is the CEO, and its decisions are final? We’ve seen countless literary representations, from GlaDos to Neuromancer’s Wintermute to SHODAN, of corporate AIs run amok – their prestige access to the world’s data systems, the fuel for their maniacal planning. When the singularity is born, whoever is gathered around the cradle will ordain the future. Let’s all be part of the conversation. 

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Digital Title Deeds: Ownership for a Virtual Generation or Commodified Engagement?

Posted on by SB Fisher

NFTs are, by now, old news. No single aspect of crypto has been more derided than the ‘million dollar jpegs’ which headlined the last crypto bullrun. Around coffee tables, bars, and Discords all over the world, snide remarks about the utter insanity of the modern market reigned supreme. To many, the idea that a duplicable image of an Ape could set you up for life was cause for bemusement, anger, and not the least bit of jealousy. 

Has this modern speculative capitalism gone mad? Was it the outrageous excess of the crypto-minted tech bros’ 1% indulging themselves in the new ‘roaring 20s’ of the 21st century amid a backdrop of pandemic and war? Or was someone, somewhere, actually on to something: that the dizzying prices and speculative excess was a harbinger of a newly consecrated form of online ownership and digital demesnes that would lead to a new concept of cyberspace.

The answer, of course, is that all three are true. Though the positive narrative has, to date, almost been entirely sunk by the precipitous, and in some cases hilarious, losses that early NFT ‘investors’ suffered. All gold rushes bring charlatans, and nowhere was this more acute in the insane pell mell towards the jackpot that occurred as literally anyone with a few thousands dollars and a basic concept of programming, blockchain or otherwise, could spin up a brand new NFT collection, promising insane gains, ambitious roadmaps, and eternal friendship among the community. The barrier to entry was near-zero, and the market was hungry for every new ape collection that rolled off the bedroom CEO production line. A lot of people – mainly the young – made a lot of money.

Everyone else lost everything. Very few projects ever grew beyond the initial launch. Leaders collected the minting fees and promptly stopped working, realising perhaps innocently, perhaps not, that the roadmaps they had set out would be difficult even for Apple to execute in the timeframes spoken about. Discords turned feral as thousands of users realised a 14 year old, perfectly innocently, had sold them a few pictures of whales to test his skills with Rust, with zero plans to do anything else for the project. It was just a hobby to make a few dollars. 

Credit: Tesfu Assefa

Yet even without a roadmap, communities wrote one in their heads. This was going to be the latest craze, the keys to a better virtual future where whale-owners would walk tall in the new halls of cyberspace, a chance to pay off the mortgage. How dare this 14 year old kid rob us of that future they’d already dreamed they were in. Scammer, I can doxx you! I know where you live!

How did this happen? What is it about those jpeg apes that so seized the cultural imagination? Yes, there were an incredible amount of push factors – Covid, quantitative easing, stimulus, lockdown, BTC’s massive gains creating crypto-related mania. But there must have been more – what was the pull?

First, they’re not jpegs. The picture associated with an NFT is not truly the NFT itself. An NFT is a token created (‘minted’) by a smart contract that has certain information on it (like pointing to a webhost hosting a jpeg), is completely unique (even if duplicates are made, each NFT would still a specific blockchain signature), and has an owner ascribed to it (usually the person sending tokens to the smart contract to make it execute its creation function. The NFT’s information, the transaction that created it, and the current ownership is all publicly visible, irrefutable, and benefits its blockchain’s security, making fraud impossible without breaking the network entirely.

This means that we’d finally figured out a way to record digital ownership, and thus digital items, which due to their reproducibility had very little worth, but could suddenly have a lot. It started with art, but games quickly realised they could consecrate ownership over their in-game assets to players, creating cooperative gaming experiences. Ownership of the first digital ‘printing’ of your favourite artist’s new album having kudos. The ability for vibrant secondary economies to spring up around their favourite talent as users could trade NFTs with one another, or sell them. NFTs created a whole new economy to be exploited where there was none before. And boy, was it exploited. Influencers, artists, and anyone with a following could create new engagement models using NFTs, with bespoke experiences attached. At time of writing, Cristiano Ronaldo’s instagram bio asks his 600m followers to join him on his NFT journey, and bid for NFTs in open auction for a chance to meet the man himself.

What’s wrong with a ticket though? Just tell me why an ape picture is worth millions. Well, the reason is, as with so many new technologies, is the possibilities. Bitcoin, Ethereum, Solana, Cosmos – whichever – blockchains by their nature are designed to be permanent, digitally-native operating systems for our future. An NFT bought in 2017 will keep its functionality for eternity. It can’t be erased from the blockchain, or from time. 

That means that should, in the future, a new business, say, declare that the only way to buy the first release of their hot new product is by owning said NFT, it would be easy for them to borrow the operation security of the blockchain and create instant exclusive access to whatever ‘club’ of people they those at near-zero outreach cost. Membership of said clubs would be powerful, digital cartels impossible to access except through the NFT and the key it provides. Or a blockchain game grows and develops a powerful online community over a decade. The first NFTs of in-game assets would be priceless, and nothing would stop developers engineering new functionality for them over time. Only a fool would suggest that we are not becoming ever more cyberised as history advances, so why wouldn’t the first digital artefacts – the first time we can truly declare failsafe ownership of a digital asset – have value? 

As alluded to, all of that is decades hence. NFTs have been mooted for use in retail, supply chains, schools but, as ever, the integrative technology to make that happen and make it useful has a long way to go. Those most in the know are too busy getting rich, or at least were, to truly focus on advancing NFTs as a useful digital technology. Now, as almost every project suffers on the wind-down from mania, perhaps it’s time to take stock of what digital ownership could truly give us. As a blaze of stimuli, images, and simulacra race past us in virtual headsets, NFTs just give us something to hold on to.

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