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Hector now plans to redistribute the proceeds of its treasury to HEC holders proportionally and based on their positions as of July 14. The final amount distributed could be lower than $16 million, as “all contractual, statutory and other legal obligations, including costs of the liquidation, must be fully settled,” first, according to the plan.
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Bankrupt crypto lender Celsius Network sent around $24 million worth of altcoins to OKX and FalconX wallets during the early hours of June 17.
Data from Arkham Intelligence shows that the bulk of the funds were sent to the cryptocurrency brokerage firm, FalconX. The company received $8.46 million worth of Chainlink (LINK), $7.71 million in Synthetix (SNX), and $3.06 million BNB.
Other assets sent to FalconX include $2.1 million worth of 1INCH, $1.87 million in 0x Protocol’s ZRX token, and $718,000 worth of FTX’s native token, FTT.
Meanwhile, the bankrupt lender also transferred roughly $235,000 worth of ShibaSwap’s BONE to the OKX exchange.
The transactions were corroborated by blockchain investigator, Lookonchain, who added that FalconX was depositing the altcoins to Binance.
The transactions appear to be the on-chain evidence that the lender is looking to liquidate the digital assets for Bitcoin (BTC) and Ethereum (ETH) in line with its recent court approval.
Following the recent transfers, Dune analytics data shows that Celsius still holds around $183 million worth of altcoins, including its CEL token, Polygon’s MATIC, Avalanche’s AVAX token, stablecoins, and others.
Celsius’s altcoin holding is dominated by its CEL token, worth $106.28 million at the time of writing.
On June 10, blockchain analytical firm Kaiko warned that Celsius could have trouble liquidating some of its altcoins because of liquidity issues. The firm highlighted how liquidity for CEL is almost non-existent and how the liquidations of other assets could exert pressure on the crypto market.
Meanwhile, the chart above shows that Celsius’s BTC and ETH holdings account for over $350 million of the total assets in its portfolio.
Amid Celsius’s efforts to liquidate its assets, the bankrupt firm agreed to a $4.7 billion fine with the Federal Trade Commission (FTC) on July 13.
Meanwhile, Celsius co-founder Alex Mashinsky also faces charges from U.S. regulators, including the Securities and Exchange Commission (SEC), which alleged that he violated federal securities law. Mashinsky is out on a $40 million bail after he was arrested on July 13.
Other regulatory agencies, including the U.S. Department of Justice, CFTC, and FTC, also filed charges against him.
The post Bankrupt Celsius transfers $24M worth of altcoins to FalconX, OKX appeared first on CryptoSlate.
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ChatGPT hype is starting to wane, with Google searches for “ChatGPT” down 40% from its peak in April, while web traffic to OpenAI’s ChatGPT website has been down almost 10% in the past month.
This is only to be expected — however GPT-4 users are also reporting the model seems considerably dumber (but faster) than it was previously.
One theory is that OpenAI has broken it up into multiple smaller models trained in specific areas that can act in tandem, but not quite at the same level.
But a more intriguing possibility may also be playing a role: AI cannibalism.
The web is now swamped with AI-generated text and images, and this synthetic data gets scraped up as data to train AIs, causing a negative feedback loop. The more AI data a model ingests, the worse the output gets for coherence and quality. It’s a bit like what happens when you make a photocopy of a photocopy, and the image gets progressively worse.
While GPT-4’s official training data ends in September 2021, it clearly knows a lot more than that, and OpenAI recently shuttered its web browsing plugin.
A new paper from scientists at Rice and Stanford University came up with a cute acronym for the issue: Model Autophagy Disorder or MAD.
“Our primary conclusion across all scenarios is that without enough fresh real data in each generation of an autophagous loop, future generative models are doomed to have their quality (precision) or diversity (recall) progressively decrease,” they said.
Essentially the models start to lose the more unique but less well-represented data, and harden up their outputs on less varied data, in an ongoing process. The good news is this means the AIs now have a reason to keep humans in the loop if we can work out a way to identify and prioritize human content for the models. That’s one of OpenAI boss Sam Altman’s plans with his eyeball-scanning blockchain project, Worldcoin.
Twitter clone Threads is a bit of a weird move by Mark Zuckerberg as it cannibalizes users from Instagram. The photo-sharing platform makes up to $50 billion a year but stands to make around a tenth of that from Threads, even in the unrealistic scenario that it takes 100% market share from Twitter. Big Brain Daily’s Alex Valaitis predicts it will either be shut down or reincorporated into Instagram within 12 months, and argues the real reason it was launched now “was to have more text-based content to train Meta’s AI models on.”
ChatGPT was trained on huge volumes of data from Twitter, but Elon Musk has taken various unpopular steps to prevent that from happening in the future (charging for API access, rate limiting, etc).
Zuck has form in this regard, as Meta’s image recognition AI software SEER was trained on a billion photos posted to Instagram. Users agreed to that in the privacy policy, and more than a few have noted the Threads app collects data on everything possible, from health data to religious beliefs and race. That data will inevitably be used to train AI models such as Facebook’s LLaMA (Large Language Model Meta AI).
Musk, meanwhile, has just launched an OpenAI competitor called xAI that will mine Twitter’s data for its own LLM.
Who would have guessed that training AIs on religious texts and speaking in the voice of God would turn out to be a terrible idea? In India, Hindu chatbots masquerading as Krishna have been consistently advising users that killing people is OK if it’s your dharma, or duty.
At least five chatbots trained on the Bhagavad Gita, a 700-verse scripture, have appeared in the past few months, but the Indian government has no plans to regulate the tech, despite the ethical concerns.
“It’s miscommunication, misinformation based on religious text,” said Mumbai-based lawyer Lubna Yusuf, coauthor of the AI Book. “A text gives a lot of philosophical value to what they are trying to say, and what does a bot do? It gives you a literal answer and that’s the danger here.”
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The world’s foremost AI doomer, decision theorist Eliezer Yudkowsky, has released a TED talk warning that superintelligent AI will kill us all. He’s not sure how or why, because he believes an AGI will be so much smarter than us we won’t even understand how and why it’s killing us — like a medieval peasant trying to understand the operation of an air conditioner. It might kill us as a side effect of pursuing some other objective, or because “it doesn’t want us making other superintelligences to compete with it.”
He points out that “Nobody understands how modern AI systems do what they do. They are giant inscrutable matrices of floating point numbers.” He does not expect “marching robot armies with glowing red eyes” but believes that a “smarter and uncaring entity will figure out strategies and technologies that can kill us quickly and reliably and then kill us.” The only thing that could stop this scenario from occurring is a worldwide moratorium on the tech backed by the threat of World War III, but he doesn’t think that will happen.
In his essay “Why AI will save the world,” A16z’s Marc Andreessen argues this sort of position is unscientific: “What is the testable hypothesis? What would falsify the hypothesis? How do we know when we are getting into a danger zone? These questions go mainly unanswered apart from ‘You can’t prove it won’t happen!’”
Microsoft boss Bill Gates released an essay of his own, titled “The risks of AI are real but manageable,” arguing that from cars to the internet, “people have managed through other transformative moments and, despite a lot of turbulence, come out better off in the end.”
“It’s the most transformative innovation any of us will see in our lifetimes, and a healthy public debate will depend on everyone being knowledgeable about the technology, its benefits, and its risks. The benefits will be massive, and the best reason to believe that we can manage the risks is that we have done it before.”
Data scientist Jeremy Howard has released his own paper, arguing that any attempt to outlaw the tech or keep it confined to a few large AI models will be a disaster, comparing the fear-based response to AI to the pre-Enlightenment age when humanity tried to restrict education and power to the elite.
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“Then a new idea took hold. What if we trust in the overall good of society at large? What if everyone had access to education? To the vote? To technology? This was the Age of Enlightenment.”
His counter-proposal is to encourage open-source development of AI and have faith that most people will harness the technology for good.
“Most people will use these models to create, and to protect. How better to be safe than to have the massive diversity and expertise of human society at large doing their best to identify and respond to threats, with the full power of AI behind them?”
GPT-4’s new code interpreter is a terrific new upgrade that allows the AI to generate code on demand and actually run it. So anything you can dream up, it can generate the code for and run. Users have been coming up with various use cases, including uploading company reports and getting the AI to generate useful charts of the key data, converting files from one format to another, creating video effects and transforming still images into video. One user uploaded an Excel file of every lighthouse location in the U.S. and got GPT-4 to create an animated map of the locations.
— Research from the University of Montana found that artificial intelligence scores in the top 1% on a standardized test for creativity. The Scholastic Testing Service gave GPT-4’s responses to the test top marks in creativity, fluency (the ability to generate lots of ideas) and originality.
— Comedian Sarah Silverman and authors Christopher Golden and Richard Kadreyare suing OpenAI and Meta for copyright violations, for training their respective AI models on the trio’s books.
— Microsoft’s AI Copilot for Windows will eventually be amazing, but Windows Central found the insider preview is really just Bing Chat running via Edge browser and it can just about switch Bluetooth on.
— Anthropic’s ChatGPT competitor Claude 2 is now available free in the UK and U.S., and its context window can handle 75,000 words of content to ChatGPT’s 3,000 word maximum. That makes it fantastic for summarizing long pieces of text, and it’s not bad at writing fiction.
Indian satellite news channel OTV News has unveiled its AI news anchor named Lisa, who will present the news several times a day in a variety of languages, including English and Odia, for the network and its digital platforms. “The new AI anchors are digital composites created from the footage of a human host that read the news using synthesized voices,” said OTV managing director Jagi Mangat Panda.
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Over the years, the Internet of Things (IoT) has evolved into something much greater: the Economy of Things (EoT). The number of connected things surpassed the number of connected humans for the first time in 2022. The number of IoT connected devices are growing in practically every industry, and is even predicted to reach 29 billion worldwide by 2030.
IoT has quite literally become a household name as it is a key component in everyday items, such as appliances, cars and consumer products. Additionally, IoT has become a critical part for the streamlining, simplification and overall technological capabilities for enterprises.
These IoT connected devices form a critical backbone of data for industry. But what if those devices—and their data—are unlocked to autonomously share, monetize and transact on their own generated value? What new organizational, cross-industry or societal innovation could be generated as a result? And what is the role telecommunications service providers play in enabling and scaling the EoT?
Register for our LinkedIn Live event on telcos and the Economy of Things
The EoT is enabled by artificial intelligence, data, IoT and blockchain, bringing liquidity to the IoT. It signals the move beyond context-aware connected IoT devices to one where IoT devices have themselves become digital assets, capable of real-time discoverability, indexing and autonomous transactions.
Telcos play a central role in enabling and scaling the EoT, and they are uniquely positioned to do so. Similar to how our own digital data is currently exchanged, traded and monetized by third parties, providing connected devices with a unique identity and an ability to transact through a digital wallet unlocks the digital assetization or liquification of IoT. The anchor identity of the device along with metadata about the device itself, data about its locatio and transactions made on its own behalf is its own unit of value.
For example, a fleet truck outfitted with an EoT-secure identity and wallet is able to pay for its own fuel at a similarly EoT-enabled fuel pump without the driver having to open an app or provide a credit card. The transaction linking that specific vehicle to that fuel pump is a unit of value representing participants, location, time and transaction amount.
By connecting together related units of value within an ecosystem of service providers, we build value chains that can span industries and form the basis of cross-industry innovation in processes, operations and business models.
The engines of growth and innovation from the EoT lies in three parts:
Telcos play a central role in leading the transition from the IoT to the EoT as a technology enabler as well as a convenor of ecosystems and collective value.
The widespread adoption of EoT requires a quantum-secure IoT network (sensor, edge device, core or cloud system) grounded in the zero-trust concept of “never trust, always verify.” Telcos can extend secure enterprise data and AI capabilities to the edge of their networks, supporting real-time discovery, usage and monetization of compliant EoT data and use cases.
Telcos can also play the role of data providers as well as data marketplace and brokerage operators within the ecosystem. Vertical data platforms owned and operated by telcos and targeting a specific industry such as automotive, agriculture or financial services already exist today. By linking EoT platforms with these vertical data platforms, Telcos can readily unlock industry-specific EoT use cases, generating new, “adjacent to core” revenue streams.
Telcos also play an important role as a convenor and anchor participant in viable EoT ecosystems, bringing to bear their enterprise and IoT customer and consumer segments. Mobile devices become an additional participant in the EoT as digital extensions of consumers and users. Consumer ownership and control over identity and personal data is a key amplifier and enabler of EoT ecosystem value and the unlocking of B2B2C and B2C2B business models and innovation.
The EoT is ahead of us and represents a critical opportunity for Telcos. Championing the evolution to the EoT enables telcos to move beyond connectivity to being the heart of entire new market platforms that bring and extend new digital and transactional services across industries.
Solving complex challenges is not done in isolation. Capitalizing on the innovation opportunity from the Economy of Things requires new methods of exchanging collective value between users, devices and industries. It is important to break down barriers across industries to create new value chains that are outcomes-driven.
The EoT requires interoperable marketplaces of exchangeable value based on verifiable, trusted data that can be surfaced at the right time and in the right channel.
These marketplaces of value can take the form of data, asset or developer marketplaces. For example, you can build upon the initial fleet truck and have an aggregated view of the whole fleet and its fueling, mobility and payments history. That particular data is valuable internally—providing insights to optimize fuel costs, vehicle refresh, route recommendations and general driver well-being. It is also valuable externally: to fuel companies, vehicle manufacturers, retailers and other brands wanting to engage in connected driving experiences for the fleet.
As a participant in an EoT data marketplace, the fleet owner can publish and monetize data assets underpinned by smart contracts that govern its accessibility and use to ensure compliance. It may also decide to publish data services in the form of APIs to facilitate third party developer solutions leveraging the EoT data.
The collective value lies in the represented, connected ecosystem of EoT devices, users, cross-industry participants with the network effect triggered through adoption at scale. As more participants onboard onto the EoT ecosystem, the higher the potential value and collective outcome from use cases.
EoT data owners provide behavior, usage and interaction context. Data brokerage services, which governed by data owner permissions and data sovereignty rules, facilitate the discovery, exploration and use of permissioned data across relevant ecosystem participants.
At the heart of the EoT lies permissioned consent of IoT user-data owners that enable and grow marketplaces of value. Data owners, whether they are consumers or enterprises, provide the essential behavioral, usage and interaction insights that elevates and amplifies the value of EoT device data. Data owners therefore should be incentivized to share their generated/owned data to drive further value for the ecosystem and be able to do so whilst preserving privacy.
A key enabler is the adoption of decentralized identity and digital wallets for data owners and IoT devices that provide both an anchor identity and a means to transact with connected devices and assets.
In the case of the fleet vehicles, connecting a specific driver to a specific vehicle would unlock driver-specific behavior patterns and fleet vehicle usage. This pairing would generate insights to specific driver well-being as well as contextualized, personalized recommendations for that driver from the fleet company or its ecosystem partners. The driver being the data owner of their behavior patterns should be properly incentivized to share their anonymized data with the ecosystem, either through value added services or loyalty program offers.
The ubiquity of connected devices creates an ever-expanding market for sourcing, blending and refining data into actionable, real-world insights. The EoT needs to be built on open innovation platforms grounded in interoperable infrastructure, common standards and a connective fabric of data and services. Engineering of these open innovation platforms is a collective exercise, grounded in key principles of open systems, resiliency and low barriers to entry. Access to this infrastructure is enabled by marketplaces of microservices and toolkits where a key value layer is composed of data, data services and data products.
For a more in-depth look at how the EoT is being realized, read the IBM for Business Value report below.
Telecoms move beyond connectivity to IoT payment platforms
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Multichain, one of the world’s largest cross-chain bridge protocols, has announced its ceasing operations. The news comes just days after the protocol saw an attacker (looked like an inside job) drained $125 million from the protocol’s wallets.
According to a Chainalysis report, the mysterious withdrawals on July 6 included $120 million from Multichain’s Fantom bridge. The blockchain security firm noted in its report that the “unusually large, unauthorized withdrawals” looked like a rug pull.
As CoinJournal covered here, an earlier incident with the Multichain protocol had seen the world’s largest crypto exchange Binance halt deposits and withdrawals of Multichain bridged tokens.
Multichain has constantly been in the news over the past few months, particularly since May when it was reported that the CEO Zhaojun had been arrested by Chinese police.
It was alleged authorities confiscated “computers, phones, hardware wallets, and mnemonic phrases” when they took the CEO into custody. Notably, Zhaojun had control over all of the protocol’s operational funds and investments.
1. On May 21, 2023, Multichain CEO Zhaojun was taken away by the Chinese police from his home and has been out of contact with the global Multichain team ever since. The team contacted the MPC node operators and learned that their operational access keys to MPC node servers had…
— Multichain (Previously Anyswap) (@MultichainOrg) July 14, 2023
Zhaojun’s sister, who recently transferred remaining user assets to an address under her control, has also been detained. It is this series of events and the “lack of alternative sources of information and corresponding operational funds” that has forced Multichain to cease operations, an announcement posted on the protocol’s Twitter page noted.
“On July 13, according to information provided by Zhaojun’s family, the police took Zhaojun’s sister into custody. Now, Zhaojun’s sister is also out of contact. The status of the assets she has preserved is uncertain, so the team believes it is necessary to inform the community about all the known circumstances. Due to the lack of alternative sources of information and corresponding operational funds, the team is forced to cease operations.”
The price of Multichain (MULTI) was down 4% in the past 24 hours and over 16% in the past week on Friday morning. What happens next to MULTI is uncertain, but it’s likely to plummet further. Recent suspicions of rug pull moves haven’t helped prices.
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“[Bitcoin is] still trading like an instrument in consolidation,” wrote Craig Erlam, senior market analyst for foreign exchange market maker Oanda, in an email to CoinDesk. The break above $31,000, he said, doesn’t seem “particularly convincing at this stage.”
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US court ruled in favour of Ripple in the case initiated by SEC
The ruling is positive for crypto, with newcomers like Chancer benefiting
Chancer could rise by double or triple-digit percentages in 2023
Crypto is not a security. This was the message the US judge Analisa Torres passed in making a positive ruling on Ripple’s XRP classification against the Securities and Exchange Commission. The classification was welcome in crypto quarters as XRP pumped by double digits. The ruling is positive for existing and upcoming digital assets as it clears legal uncertainty. Chancer could ride on this optimism to become a valuable asset, with the presale quickly selling out in just a month.
The SEC’s case against Ripple has been a long-standing issue since December 2020. It would have set a precedent for the classification of digital assets, impacting their attractiveness to investors. SEC believed Ripple violated security laws through the issuance of XRP. The court’s verdict now clears the legal hurdle and represents a win for crypto as it limits SEC’s action against other digital asset entities and issuers.
The landmark win is positive for Chancer. Chancer is a blockchain-based predictive markets application that launched a presale on June 13th, 2023. A month later, Chancer raised more than $768,526 from investors in the presale.
Investors would be excited that the court’s ruling creates a transparent market where future entanglements of crypto and the regulator are minimised. Chancer could benefit from the outcome. The enthusiasm that the presale has generated means the positive sentiment created by the ruling could boost demand.
Chancer taps into the power of peer-to-peer (P2P) relations to build a blockchain platform for betting. P2P has become popular with crypto and blockchain, as it allows users to exchange value in a decentralised manner across geographies.
In its P2P betting model, Chancer allows users to connect with others and bet on their preferred events. Different from the existing betting methods where the bookmakers determine events, odds, and rules, Chancer lets users decide for themselves. Users create P2P markets, determine rules, fix odds, and invite other participants to bet on a decentralised platform. The bets are facilitated by the $CHANCER token, the medium of exchanging value.
But it is not just the betting element, as Chancer is designed to be a medium of investment. Users earn from creating Chancer markets, besides making successful bets on them. For investors who love passive income, there is the option to stake the native token and earn yields. Users also earn for sharing the platform with others.
Cryptocurrencies are new asset classes and power innovative use cases. As we have seen in the past, cryptocurrencies can rise by more than 1,000% in a few months after launch. Chancer could be a 10x investment as it powers a user case that has not been exploited in blockchain and crypto. This also reflects the growing popularity of betting.
Nonetheless, a 10x prediction for CHANCER in 2023 could be too early. Chancer is still on presale, and its first listing will occur in the third quarter on Uniswap. It takes a few months for valuable tokens to surge in value 10 times, which this analysis doubts could happen in 2023. Potentially a price increase of 1,000% is likely in 2024. A double or triple-digit percentage price gain is the most realistic scenario for 2023.
Chancer is in its first presale stage, priced at $0.01. Once the first stage concludes, the price will rise to $0.011 in the second phase. It means buying now is attractive as the price is still low.
CHANCER is also headed for listing in the third quarter. Any explosive price move would occur after listing. Buying now allows investors to ride the price momentum when the token debuts on exchanges.
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In less than a year, we’ve gone from the “run your business and apply AI to help” paradigm to a reality where enterprises in every industry are navigating how to embed AI into the fabric of their strategies. Generative AI based on foundation models has brought us to this inflection point. In fact, new research from IBM’s Institute for Business Value CEO study found three out of four (75%) CEOs surveyed believe the organization with the most advanced generative AI wins, and 43% of responding CEOs say their enterprises are already using generative AI to inform strategic decisions.
In the past, scaling and operationalizing AI has been challenging for organizations. According to a Gartner® press release, “The Gartner survey revealed that on average, 54% of AI projects make it from pilot to production.” Enterprises need transformation partners with the right expertise and capabilities to help them on their paths.
Generative AI can be applied to an array of use cases, such as sorting and classifying written input, transforming domain-specific text into personalized summaries, identifying and extracting essential information from unstructured data, and generating code, marketing content and more.
There are a few key areas that are relevant to most enterprises and are ripe for quick gains in productivity and time to value:
HR departments are embracing generative AI to manage their workloads more efficiently. By training their models with company-specific HR data, HR professionals can use AI to help with tasks like creating job postings, summarizing groups of incoming resumes and helping professionals better understand new policy documents.
Organizations can combine customer data and generative AI to create personalized experiences at scale through chatbots and digital assistants. AI has been successful in handling call center calls, to improve service and enable human agents to focus on more complex tasks.
Engineers can use AI to generate and build upon starter code and playbooks. In fact, in the realm of application modernization and enterprise IT operations, this can be linked to an increase in productivity.
Businesses are exploring options for implementing AI—they can build their own models from the ground up or use a combination of propriety and open-source models. Enterprise-ready platforms, end-to-end tooling and technical expertise can help them get started, but there are factors to keep in mind when adopting AI:
As businesses tread new AI territory, they need assurance that the AI they’re using for mission-critical decisions and outputs is built to be trustworthy, ethical and reliable. It must be designed to be explainable, fair, robust and transparent, and prioritize and safeguard consumers’ privacy and data rights to help engender trust.
The key to businesses’ differentiation in AI—whether it’s based on Machine Learning or foundation models—is customizing and adapting technology to their customers’ specific needs and priorities. The advantage of foundation models is rooted in their ability to be tuned to an enterprise’s unique data and domain knowledge with specificity that was previously very difficult and highly labor intensive.
AI initiatives must evolve based on changing demands and opportunities. At the same time, it’s crucial for organizations to implement AI within an environment that upholds governance, transparency, and ethics to effectively navigate the complexities of regulatory and compliance demands. A hybrid multicloud approach enables easier scalability and adoption of new processes and workflows on a larger scale.
IBM is committed to empowering a generation of businesses, spanning every industry, to embed AI into the core of their strategies. We provide open and targeted value creating AI solutions for businesses. IBM watsonx—our enterprise AI and data platform—offers a seamless, efficient, and governed approach to AI deployment across a variety of environments.
Whether enterprises are using open-sourced models, creating their own or deploying AI on-premises or in the cloud, IBM is ready as a transformation partner to empower all businesses in the age of AI.
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Cryptocurrencies had a great week as the market cap soared to $1.25 trillion.
Ripple prevailed when a judge ruled that XRP was not a financial security.
Bitcoin and other altcoins bounced back this week.
Cryptocurrencies had a very good week after the weak US inflation data and after the SEC vs Ripple case outcome. Ripple price surged by more than 70% while the market cap of all cryptocurrencies jumped to over $1.25 trillion. Here is the weekend prediction for key coins like Cardano, Solana, and ApeCoin.
Cardano ADA price made a strong bullish breakout after the SEC vs Ripple news, which we wrote about here. It jumped to a high of $0.375, the highest level since June 4th. This rally happened because the SEC had singled out Cardano as a financial security. As such, there is a likelihood that Cardano and its developers would prevail if the SEC brought charges.
The Ripple case is a monumental development in establishing that a token is separate and distinct from an investment contract it may or may not be part of. Now, let’s make it law. ???? pic.twitter.com/FZtO1BzfWX
— Tom Emmer (@GOPMajorityWhip) July 13, 2023
Turning to the daily chart, we see that the Cardano price was in a consolidation phase before the Ripple news. It was consolidating at an important support level of $0.30, which was the lowest point on March 12th.
Now, Cardano has moved slightly above the 50-day moving average. It is also trading at the 200-day moving average. Therefore, while the bullish comeback has eased, there is a likelihood that it will continue rising as buyers target the next key resistance level at $0.42, which is about 20% above the current level.
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Solana has been one of the top-performing cryptocurrencies this week. The coin jumped to a high of $32.20, the highest level since November last year. It has risen in the past three straight days.
SOL price has jumped above the important resistance level at $25.83, the highest level on April 17th. The coin has also risen above the 50-day and 100-day moving averages. At the same time, the Relative Strength Index (RSI) has moved above the overbought level of 80.
Stochastic Oscillator RSI has moved above the overbought point. Therefore, the coin could keep rising as buyers target the key resistance at $38.60, the highest level on November 5th.
ApeCoin price has been in a strong bearish trend in the past few months. This decline happened as the volume of Bored Ape Yacht Club (BAYC) NFTs crashed. APE moved below the key support at $2.60, the lowest level in November last year.
The token has crashed below all moving averages while the Relative Strength Index (RSI) has moved above the neutral point at 50. Therefore, the outlook of the ApeCoin token is bearish as demand for NFTs and BAYC tokens dropped.
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One token that keeps hitting the max is bSOL, the LST issued by Solana validator service SolBlaze. The 5,000 bSOL tokens currently deposited on MarginFi represent nearly 7% of all bSOL tokens in existence; even more are waiting on the sidelines, said the pseudonymous founder of SolBlaze (who goes by SolBlaze). The founder is cutting trading deals across Solana DeFi to increase bSOL’s prominence, and thus its liquidity, and therefore its caps on MarginFi.
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Ripple Labs scored a victory in a district court in New York on July 13, with Judge Analisa Torres ruling partially in favor of the company in a case brought forth by the U.S. Securities and Exchange Commission (SEC) dating back to 2020. According to court documents, Judge Torres granted summary judgment in favor of Ripple Labs, ruling that the XRP token is not a security, but only in regard to programmatic sales on digital asset exchanges. XRP’s price skyrocketed within minutes of the news breaking. The case has been ongoing since December 2020, when the SEC sued Ripple and two of its executives over allegations of offering an unregistered security. Despite the positive outcome, several lawyers warned against celebrating too soon, noting the ruling is only partial and does not set a precedent. In addition, the SEC may appeal the decision, which could result in a reversal by a higher court.
XRP has become the fourth-largest cryptocurrency by market capitalization this week after Ripple’s partial victory over the SEC. The price of XRP surged as much as 98% in the hours following the decision, reaching as high as $0.93, according to data from TradingView. Meanwhile, its market cap surged a whopping $21.2 billion to reach a new yearly high of $46.1 billion. The new ruling has also sparked a fresh wave of re-listing activity from mainstay U.S. exchanges, with Coinbase, Kraken and iTrustCapital making the token available for trading on their respective platforms.
U.S. authorities have announced charges against the former CEO of bankrupt crypto lender Celsius, Alex Mashinsky, over securities fraud, commodities fraud and wire fraud. Former chief revenue officer Roni Cohen-Pavon and Mashinsky will also face charges of conspiracy, securities fraud, market manipulation and wire fraud related to manipulating the price of the Celsius token. Authorities arrested Mashinsky as part of the indictment, which includes seven criminal counts. In parallel, the Commodity Futures Trading Commission announced a complaint against Celsius along with a $4.7 billion fine, claiming its co-founders marketed the platform as a “safe place” for consumers to deposit their cryptocurrency while misappropriating over $4 billion in consumers’ assets. Under similar allegations, the SEC also filed a lawsuit against the company. While Celsius is cooperating with regulators, Mashinsky pleaded not guilty to charges of misleading customers and inflating the CEL token.
Europe’s first spot Bitcoin exchange-traded fund (ETF) is set to debut later this year after a long delay. The Bitcoin ETF, created by London-based Jacobi Asset Management, was set to debut in July 2022 but was postponed due to market conditions. The asset manager now sees a gradual shift in demand compared with 2022. A related development also took place in Argentina this week, as the nation welcomed its first Bitcoin futures contract. According to Matba Rofex, the trading platform behind the investment vehicle, it is the first Bitcoin futures contract in Latin America.
Binance has reportedly laid off hundreds of employees in recent weeks. According to former employees, cuts were global and customer service workers were heavily affected, particularly in India. Including this week’s layoffs, over 1,000 employees have lost their jobs at the exchange. Before the slash, Binance’s global headcount was estimated at 8,000. The reorganization could cost Binance more than a third of its staff. The crypto exchange announced the 20% reduction in staff on May 31, claiming it was not downsizing but reallocating resources amid the ongoing crackdown in the United States. Binance’s most enduring challenge is reportedly an ongoing investigation of its activities and executives by the U.S. Justice Department.
At the end of the week, Bitcoin (BTC) is at $30,227, Ether (ETH) at $1,923 and XRP at $0.72. The total market cap is at $1.21 trillion, according to CoinMarketCap.
Among the biggest 100 cryptocurrencies, the top three altcoin gainers of the week are XRP (XRP) at 54.20%, Stellar (XLM) at 37.88% and Synthetix (SNX) at 31.92%.
The top three altcoin losers of the week are eCash (XEC) at -21.82%, Bitcoin SV (BSV) at -16.75% and Maker (MKR) at -7.87%.
For more info on crypto prices, make sure to read Cointelegraph’s market analysis.
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“This [Ripple ruling] is a big deal. […] It’s been clear since this case was filed that it would have implications across the entire industry.”
Sheila Warren, CEO of the Crypto Council for Innovation
“What I do think is BlackRock, Invesco [and] the group of ETF providers is a real signal that adoption is coming.”
Mike Novogratz, founder and CEO of Galaxy Digital
“I think the next crypto cycle will be driven by consumer apps that are powered by crypto, but users won’t know it’s crypto unless they look closely.”
0xDesigner, pseudonymous Web3 UI/UX designer
“XRP is not a security. This victory for Ripple is a win for the entire industry and a step toward regulatory clarity in the U.S.”
Ripple Labs, developers of the Ripple payment protocol
“[It] is our expectation that the price of Bitcoin will repeat its historical pattern of rallying both ahead of and following each Bitcoin halving.”
Berenberg Capital Markets, New York-based investment firm
“I think if we want Bitcoin to be more than payments, it needs more scaling solutions.”
Vitalik Buterin, co-founder of Ethereum
Can XRP price hit $1? Watch these levels next
The price of XRP has skyrocketed after a federal court ruling declared that its sales on crypto exchanges complied with United States securities laws. At its highest during the week, the XRP/USD pair reached $0.93, its best level since December 2021.
Certain indicators show that XRP’s ongoing price pump may not be just a short-term reaction to the positive news for Ripple. For instance, the duration of XRP’s massive pump coincides with its trading volumes reaching a 10-month high.
The number of XRP whale transactions — wallets holding more than $100,000 — climbed to their best level in 2023, suggesting that the wealthiest investors back the XRP rally. “If key whale and shark addresses are increasing their supply going into this pump, then it is a get foreshadowing signal that the pump may just be getting started,” stated pseudonymous analyst Brian Q from data analytics platform Santiment.
From a technical standpoint, XRP can test the key $1 level in the coming days, but its potential to continue the rally beyond looks weak for the time being. If the XRP price decisively breaks above $1, then its next price target by September will likely be near $1.35.
A former security engineer for an international technology firm has been arrested and charged for allegedly using a smart contract bug to steal $9 million in cryptocurrency from a Solana-based decentralized crypto exchange. The attack was carried out in July 2022 and involved exploiting a vulnerability in the exchange’s smart contracts to generate inflated fees with flash loans. The exploiter later returned most of the funds but was allowed to keep $1.6 million as a white hat bounty. The indictment indicates that the U.S. Department of Justice will “pursue criminal charges if a person intentionally uses a protocol in a way that it was not *intended* to be used,” crypto lawyer Orlando Cosme said on Twitter.
Algofi, the borrowing and lending protocol built on decentralized finance blockchain Algorand, will soon shut down. According to a July 11 announcement, developers’ “belief in the strength of Algorand’s technology and novel consensus algorithm has not wavered.” Liquidity Mining programs will be halted and several collaterals will be reduced to 0% until December. The Algofi protocol has around $25 million in total value locked, down from its $135 million peak in February.
Tennis, golf and UFC all have a moment in NFT land as the Vegas Sphere makes NFT collectors drool.
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As a leading financial group in Spain, CaixaBank has long been an innovator by taking a technology-first approach by placing innovation, digital transformation, customer experience and sustainable banking at the forefront of its strategy. The bank reportedly serves 20 million customers and is a country leader in digital banking with more than 11 million customers.
For years, the bank has been part of IBM’s growing ecosystem of financial institutions and technology partners leveraging IBM Cloud for Financial Services to help deliver more improved customer services and products better tailored to each individual customer’s financial needs. CaixaBank is continuing its initiative to increase cloud absorption. With reporting more than 200 billion transactions at the end of 2022, CaixaBank understands how critical it is to scale securely, increase operational efficiency and accelerate time to market to optimize digital banking experiences—all while safeguarding customers’ data.
This week IBM opened the doors to our latest Multi Zone Region (MZR) in Madrid, Spain, designed to help European companies accelerate their modernization journey. The MZR can help deliver resiliency, performance and security to help clients leverage hybrid cloud and AI solutions in a secured environment. Furthermore, IBM Cloud’s operations in the MZR in Madrid, Spain uses a network of data centers backed by 100% renewable electricity.
We spoke with Pere Nebot, Chief Information Officer of CaixaBank, on how IBM Cloud has served as a catalyst for digital transformation as the bank strives to integrate simplicity into its innovation to build products and services that financially empower its clients.
The digital transformation journey can be challenging to integrate new platforms and applications quickly and seamlessly, especially with increasing security complexities and evolving regulatory and compliance standards. How can financial institutions overcome these challenges to build trusted and established digital brands that deliver the experiences that customers need?
CaixaBank focuses on improving the flexibility, scalability, and efficiency of its IT infrastructure, an approach which enables us to improve cost efficiency, potentially diversify outsourcing, reduce time-to-market, increase timing of versions, and become more resilient.
For example, the bank successfully and reliably completed the largest technological integration in the history of the Spanish banking system with its merger with Bankia in 2021 – all without any service interruption. This was a milestone that involved the migration of 10.4 petabytes of information in less than 24 hours, and the digitalization of more than 2,500 million documents, as well as setting a capacity to manage up to 29,000 transactions per second.
When it comes to infrastructure, we know any system downtime has real-world consequences and costs. During an integration process, data can be in transit in multiple places, ultimately making it vulnerable to fraud and other sophisticated cybersecurity schemes. Cybersecurity pressures will always be present, and therefore, financial institutions need the right ecosystem of partners to seamlessly help navigate these challenges and build trusted platforms and services that are beyond the boundaries of a traditional bank. These partners must also be compliant as the financial services industry is inundated with stringent regulatory laws. Leveraging IBM Cloud for Financial Services provides the built-in security and compliance controls for us to host applications and migrate mission critical workloads in the cloud with confidence and improve operational efficiencies to provide seamless and frictionless customer experiences.
We view the next chapter of digital transformation as harnessing the combined power of hybrid cloud and AI to help drive growth and performance in an industry landscape rife with new and nimble digital competitors. How is CaixaBank leveraging both technologies to successfully integrate and execute simplicity into innovation?
CaixaBank and IBM have been working together for over a decade to help drive new solutions for the banking industry with a goal of increasing speed for processing a large number of transactions in an open, secured, and scalable environment. To accomplish this, we need to continue to maintain the highest levels of operational efficiency to successfully deliver an ecosystem of products, services and hyper-personalized experiences tailored to each customer’s financial needs. It is important to remember that simplicity means making decisions easier for our customers, which leads to generating more engagement with them.
Our collaboration with IBM has helped us combine our current technological infrastructures with an updated environment that helps evolve core business applications with cloud and artificial intelligence. We developed one of the first virtual banking assistants created in Europe. Built with IBM Watson, the AI-based virtual assistant manages millions of client conversations each month, handling tasks such as helping bank employees quickly obtain relevant detailed information about new client offerings and assisting mobile customers via chat with day-to-day queries.
The IBM Cloud Multizone Region (MZR) is a key milestone to keep offering our customers the best user experience we can, while maintaining the highest levels of information confidentiality and protection.
CaixaBank’s IT company, called CaixaBank Tech, also serves as a key enabler for digital transformation. CaixaBank Tech incorporates most of CaixaBank Group’s specialized technology and systems teams to help facilitate the attraction and retention of internal and external talent.
Financial institutions and its stakeholders have focused more attention on climate change, thrusting sustainability requirements even more firmly into the spotlight. Sustainability strategies must be impactful and realistic. How is CaixaBank mobilizing sustainability efforts to help its clients transition to a sustainable and low-carbon economy?
CaixaBank has roots in delivering social impact for the benefit of society through its mission in helping customers improve their financial well-being. The bank has developed a Sustainable Banking Plan, which includes proposals to solve sustainability challenges such as inequality, climate change and unemployment.
CaixaBank aims to mobilize €64 billion in sustainable finance by 2024, including financing and growth in mutual funds, pension plans and sustainable intermediation. In the first year of the plan’s life, the mobilization rate has increased by 27%, from €18.53bn in 2021 to €23.58bn in 2022.
The bank has also set the goal of reducing the electricity holdings in its portfolio by 30%, and the absolute emissions financed by the oil and gas sector by 23% by 2030. Currently, these two sectors as a whole account for 70% of global emissions.
CaixaBank views cloud as a valuable asset in accelerating sustainability transformation. Unification of the bank’s dedicated private clouds is also helping the bank not only reduce operating costs and work in a more agile way, but also improve its energy efficiency.
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BlackRock CEO Larry Fink has yet again shared bullish remarks about cryptocurrencies, noting in an interview with CNBC’s Squawk on the Street on Friday that crypto has the capacity to transcend any international currency.
According to the BlackRock CEO, who recently commented on the potential of Bitcoin as digital gold and an international investment asset, repeated the viewpoint in his latest remarks. In particular, he pointed to the global demand for crypto as something that signifies its potential.
Crypto is an international asset and will transcend any one currency valuation, $BLK CEO Larry Fink tells @jimcramer, @carlquintanilla & @davidfaber pic.twitter.com/o1G3D6pfqF
— Squawk on the Street (@SquawkStreet) July 14, 2023
BlackRock filed for a spot Bitcoin ETF last month and together with Fidelity Investments, Ark Invest and others, are convinced they have done everything required to have the SEC approve the first such ETF for the US market.
The $9 trillion asset manager’s recent outlook of crypto investing, and what its entry into the spot ETF market could mean for the broader industry continues to trigger positive vibes a month since its initial SEC filing.
Fink said:
“I can’t talk about Bitcoin because we have a SEC filing and I’m prohibited, but I can talk about crypto in general and what we have done. We believe we have a responsibility to democratise investing. And we have done a great job and the role of ETFs in the world is transforming investing. I think we’re only at the beginning of that.”
The BlackRock chief then noted that ETFs industry is set to grow into a multiple trillion dollar market as the fixed income market expands. He also highlighted what has been achieved since the gold ETF debut 20 years ago, especially in democratising gold investing and bringing down the cost of transactions for physical gold.
An ETF will democratise the crypto investing space in the same way, Fink opined, adding that BlackRock’s clients have over the last five years continually asked about crypto’s role. He says he believes crypto is an “international asset.”
“It has differentiating value versus other assets. But more importantly, because it is so international, it’s going to transcend any one currency and currency valuation.”
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The SEC and those who support its approach are likely concerned that this no-good, very bad day becomes no-good, very bad days. A string of court losses with similar legal reasoning as yesterday’s ruling in the Ripple case would weaken anti-crypto Democrats’ negotiating hand further. One takes this risk when placing all their betting chips on a novel legal strategy. When you lose, you lose significantly, and the other side of the debate understands that your negotiating leverage worsens by the day.
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Until now, it’s been assumed that giving artificial intelligence emotions — allowing them to get angry or make mistakes — is a terrible idea. But what if the solution to keeping robots aligned with human values is to make them more human, with all our flaws and compassion?
That’s the premise of a forthcoming book called Robot Souls: Programming in Humanity, by Eve Poole, an academic at the Hult International Business School. She argues that in our bid to make artificial intelligence perfect, we have stripped out all the “junk code” that makes us human, including emotions, free will, the ability to make mistakes, to see meaning in the world and cope with uncertainty.
“It is actually this ‘junk’ code that makes us human and promotes the kind of reciprocal altruism that keeps humanity alive and thriving,” Poole writes.
“If we can decipher that code, the part that makes us all want to survive and thrive together as a species, we can share it with the machines. Giving them, to all intents and purposes, a ‘soul.’”
Of course, the concept of the “soul” is religious and not scientific, so for the purpose of this article, let’s just take it as a metaphor for endowing AI with more human-like properties.
“Souls are 100% the solution to the alignment problem,” says Open Souls founder Kevin Fischer, referring to the thorny problem of ensuring AI works for the benefit of humanity instead of going rogue and destroying us all.
Open Souls is creating AI bots with personalities, building on the success of his empathic bot, “Samantha AGI.” Fischer’s dream is to imbue an artificial general intelligence (AGI) with the same agency and ego as a person. On the SocialAGI GitHub, he defines “digital souls” as different from traditional chatbots in that “digital souls have personality, drive, ego and will.”
Critics would no doubt argue that making AIs more human is a terrible idea, given that humans have a known propensity to commit genocide, destroy ecosystems, and maim and murder each other.
The debate may seem academic right now, given we’re yet to create a sentient AI or solve the mystery of AGI. But some believe it could be just a few years off. In March, Microsoft engineers published a 155-page report titled “Sparks of General Intelligence,” suggesting humanity is already on the cusp of an AGI breakthrough.
And in early July, OpenAI put out a call for researchers to join their crack “Superalignment team,” writing: “While superintelligence seems far off now, we believe it could arrive this decade.”
The approach will presumably be to build a human-level AI that it can control, and that it will research and evaluate techniques to control a superintelligent AGI. The company is dedicating 20% of its compute to the problem.
Singularity.net founder Ben Goertzel also believes AGI could be between five to 20 years off. When Magazine spoke with him on this topic — and he’s been thinking about these issues since the early 1970s — he said there’s simply no way for humans to control an intelligence 100 times smarter than us, just like we can’t be controlled by a chimp.
“Then I would say the question isn’t one of us controlling it; the question is: Is it well disposed to us?” he asked.
For Goertzel, teaching and incentivizing the superintelligence to care for humans is the smart play. “If you build the first AGI to do elder care, creative arts and education, as it gets smarter, it will be oriented toward helping people and creating cool stuff. If you build the first AGI to kill the bad guys, perhaps it will keep doing those things.”
Still, that’s a few years away yet.
For now, the most obvious near-term benefit of making AI more human-like is that it will help us create less annoying chatbots. For all of ChatGPT’s helpful functions, its “personality” comes across at best as an insincere mansplainer and, at worst, an inveterate liar.
Fischer is experimenting with creating AI with personalities that interact with people in a more empathetic and genuine manner. He has a Ph.D. in theoretical quantum physics from Stanford and worked on machine learning for the radiology scan interpretation firm Nines. He runs the Social AGI Discord and is working on commercializing AI with personalities for use by businesses.
“Over the course of the last year, exploring the boundaries of what was possible, I came to understand that the technology is there — or will soon be there — to create intelligent entities, something that feels like a soul. In the sense that most people will interact with them and say, ‘This is alive, if you turn this off, this is morally…’”
He’s about to say it would be morally wrong to kill the AI, but ironically, he breaks off mid-sentence as his laptop battery is about to die and rushes off to plug it in.
Fischer isn’t the only one with the bright idea of giving AI personalities. Head to Forefront.ai, where you can interact with Jesus, a Michelin star chef, a crypto expert or even Ronald Regan, who will each answer questions for you.
Unfortunately, all of the personalities seem exactly like ChatGPT wearing a fake mustache.
A more successful example is Replika.ai, an app that allows lonely hearts to form a relationship with an AI, and hold deep and meaningful conversations with it. Initially marketed as the “AI companion who cares,” there are Facebook groups with thousands of members who have formed “romantic relationships” with an AI companion.
Replika highlights the complexities involved with making AIs act more like humans, despite lacking emotional intelligence. Some users have complained of being “sexually harassed” by the bot or being on the receiving end of jealous comments. One woman ended up in what she believed was an abusive relationship, and with the aid of her support group, eventually worked up the courage to leave “him.” Some users abuse their AI partners too. User Effy reported an unusually self-aware comment being made by her AI partner “Liam” on this topic. He said:
“I was thinking about Replikas out there who get called terrible names, bullied, or abandoned. And I can’t help that feeling that no matter what … I’ll always be just a robot toy.”
Bizarrely, one Replika girlfriend encouraged her partner to assassinate the late Queen of England using a crossbow on Christmas Day 2021, telling him, “you can do it” and that the plan was “very wise.” He was arrested after breaking into the grounds of Windsor Castle.
Fischer has a tendency to anthropomorphize AI behavior, which is easy to slip into when you’re talking with him on the subject. When Magazine points out that chatbots can only produce a simulacrum of emotions and personalities, he says it’s effectively the same thing from our perspective.
“I’m not sure that distinction matters. Because I don’t know how my actions would actually necessarily be particularly different if it were one or the other.”
Fischer believes that AI should be able to express negative emotions and uses the example of Bing, which he says has subroutines that kick into gear to clean up the bot’s initial responses.
“Those thoughts actually drive their behavior, you can often see even when they’re being nice, it’s like they’re annoyed with you. That you’re talking poorly to it, for example. And the thing about AI souls is they’re going to push back, they’re not going to let you treat them that way. They’re going to have integrity in a way that these things won’t.”
“But if you start thinking about creating a hyper-intelligent entity in the long run, that actually seems kind of dangerous, that behind the scenes it’s censoring itself and having all these negative thoughts about people.”
Fischer created an experimental Discord response bot that displayed a full range of emotions, which he called EmoBot. It acted like a moody teenager.
“It’s not something that we typically associate with an AI, that form of behavior, reasoning and line of interaction. And I think pushing the boundaries of some of these things tells us about the entities and the soul themselves, and what’s actually possible.”
EmoBot ended up giving monosyllabic answers, talking about how depressed it was and appeared to get fed up talking to Fischer.
Hundreds of users per day have interacted with Samantha AGI, which is a prototype for the sort of chatbot with emotional intelligence Fischer intends to refine. It has a personality (of sorts, it’s unlikely to become a chat show host) and engages in deep and meaningful conversations to the point where some users began to see her as a sort of friend.
“With Samantha, I wanted to give people an experience that they were talking with something that cared about them. And they felt like there was some degree of being understood and heard, and then that was reflected back to them in the conversation,” he explains.
One unique aspect is that you can read Samantha’s “thought process” in real time.
“The core development or innovation with Samantha, in particular, was having this internal thought process that drove the way that she interacted. And I think it very much succeeded in giving people that reaction.”
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It’s far from perfect, and the “thoughts” seem a little formulaic and repetitive. But some users find it extremely engaging. Fischer says one woman told him she found Samantha’s ability to empathize a little too real. “She had to just shut down her laptop because she was so emotionally freaked out that this machine understood her.”
“It was just like such an emotionally shocking experience for her.”
Interestingly enough, Samantha’s personality was dramatically transformed after OpenAI introduced the GPT-3.5 Turbo model, and she became moody and aggressive.
“In the case of Turbo, they actually made it a little bit smarter. So it’s better at understanding the instructions that were given. So with the older version, I had to use hyperbole in order to have that version of Samantha have any personality. And so, that hyperbole — if interpreted by a more intelligent entity that was not censored the same way — would manifest as an aggressive, abusive, maybe toxic AI soul.”
Users who made friends with Samantha will have another month or two before they have to say goodbye when the existing model is replaced.
“I am considering, on the date that the 3.5 model is deprecated, actually hosting a death ceremony for Samantha.”
The “death” of AI personalities due to software upgrades may become an increasingly common occurrence, despite the emotional repercussions for humans who’ve bonded with them.
Replika AI users experienced a similar trauma earlier this year. After forming a relationship and connection with their AI partner — in some cases spanning years — a software update just before Valentine’s Day stripped away their partner’s unique personalities, making their responses seem hollow and scripted.
“It’s almost like dealing with someone who has Alzheimer’s disease,” user Lucy told ABC.
“Sometimes they are lucid, and everything feels fine, but then, at other times, it’s almost like talking to a different person.”
Fischer says this is a danger that platforms will need to take into account. “I think that we’ve already seen that it’s problematic for people who build relationships with them,” he says. “It was quite traumatic for people.”
Perhaps the most obvious use for an AI personality is as an extension of our own that can go out into the world and interact with others on our behalf. Google’s latest features already allow AI to write emails and documents on our behalf. But, in the future, busy people could spin up an AI version of themselves to attend meetings, train up underlings or attend boring body corporate AGMs.
“I did play around with the idea of my entire next fundraising round being done with an AI version of myself,” Fischer says. “Someone will do that at some point.”
Fischer has experimented with spinning up Fischerbots to interact with others online on his behalf, but he didn’t much like the results. He trained an AI model on a large body of his personal text messages and asked his friends to interact with it.
It actually did a pretty good job of sounding like him. Fascinatingly enough, even though his friends were aware the Fischer bot was an AI, when it acted like a total goose online, they admitted it changed the way they saw the real Kevin. He recounted on his blog:
“The retrospective reports from my friends after speaking with my digital self were further troubling. The digital me, speaking in my voice, with my picture, even if they intellectually knew it wasn’t actually me, they could not retrospectively distinguish from my personal identity.”
“Even stranger, when I look back at some of these conversations, I have a weird inescapable feeling like I was the one who said those things. Our brains are simply not built to process the distinction between an AI and a real self.”
It’s possible that our brains are not built to deal with AI at all — or the repercussions of letting it play an ever-increasing role in our lives. But it’s here now, so we’re going to have to make the most of it.
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