Welcome back, everybody. It’s been another exciting week in crypto, and we’re pleased to bring you the next edition of Moralis Research. Today, we will be interested in getting your feedback on the content of these reports. Please take a few minutes to give us your feedback here.
This week, we continued to see Operation Choke Point in play as The Federal Deposit Insurance Corporation has stated that prospective purchasers of Signature Bank would have to stop doing business with crypto. Bidders with existing banking charters can review the bank’s financials before submitting an offer.
Signature Bank and Silicon Valley Bank collapsed, and the federal government stepped in to protect depositors. The collapse of major banks like Silicon Valley Bank has disrupted the industry, and other banks are at risk.
The Federal Reserve had to ease the ongoing liquidity crisis in the country. Its emergency loan program is expected to bring $2 trillion worth of funds into the U.S. banking system. While top banks have a sizable share of the $3 trillion reserves in the U.S. financial system, the Fed’s quantitative tightening and rate rises are blamed for tighter liquidity. Speculations that the Fed may forego raising interest rates next week to stabilize the banking industry have caused the two-year Treasury bond yield to fall.
Overall, It’s a bad week for banks and lenders, with First Republic Bank being the only one to avoid the same fate as Silicon Valley Bank and Signature Bank. The collapse of major banks has caused disruptions in the industry, and the Federal Reserve is taking action to ease the ongoing liquidity crisis.
We’ll always provide you with our research to help with your education. We’ll keep close track of the main developments and evolution of the niches in blockchain so that you get the best of the new knowledge. When you’ve finished reading your report, please remember to fill out the feedback form, your feedback is valued, and we’re always open to suggestions.
Friday 17th of March | 09:30 UTC
For those new to my analysis, I do trend trading over long timeframes.
Global tech only has two outcomes: Giant success or catastrophic failure. Tech either does a 100x or goes to zero, with little in-between. Before reaching either end point, the asset price will trend for extended periods.
My process aims to give exposure during those periods of established trends. That way I can enter with more capital for any given risk, compared to a hold only approach. I don’t try to catch tops or bottoms. I don’t worry about intraday movements. My style of analysis is not suitable for day traders or range traders. When it comes to tech, the big gains come from catching big moves over long periods of time.
This is an analysis at one moment in time. Market structure can change in an instant. When presented with new information, I will adjust my opinion accordingly. Technical analysis of historical data is not a prediction of the future. It is a tool that can aid in finding setups for favorable risk-reward and points of invalidation.
FOR GENERAL INFORMATION PURPOSES ONLY, NOT FINANCIAL ADVICE.
All information presented in this report references an opinion of the author and is for general information purposes only. You must not construe any information presented as legal, tax, investment, financial, or other advice. Nothing presented constitutes a solicitation, recommendation, endorsement, or offer to buy or sell financial instruments. I am not a licensed financial advisor or registered investment advisor. For financial or investment advice, seek a duly licensed professional in your jurisdiction, who can take your specific situation into account. Past performance does not indicate future results. You are always at risk of losing all invested funds. I don’t give advice to buy or sell specific assets. The education and software tools are timeless and generic for any asset. Rather than relying on subjective market opinions, I apply the principles of technical analysis formulated in 1930s on historical charts. Anyone can apply the same process and get the same result. Technical Analysis does not predict the future. It is a tool to find setups for controlled risk/reward. Larsson Line does not predict the future. It is a mathematical formula for trend expression. My objective with this report is to help you reflect on your own analysis, not to replace it.
Disclosure: I hold Bitcoin and Ethereum exposure through company ownership and in my personal capacity, as ETP price tracker certificates through my bank.
In this overview we are using Metamask, the most popular Web3 wallet and ID system. Alternative methods do exist but are not explained in this overview. For a more detailed tutorial navigate to Moralis Blog.
Bitcoin dominance remains range bound, as drawn below.
A range can break out in either direction and it’s usually a mistake to try to guess in which direction, before it has actually happened.
At one point it will, and that will be my clue for how to position myself between BTC and alts for the next major move of the markets.
The chart is here shown with 3 day candles.
Once downloaded and installed, we are presented the option to [Get Started].
Once downloaded and installed, we are presented the option to [Get Started].
Once downloaded and installed, we are presented the option to [Get Started].
Next we must specify a password for our wallet, this password will be used when signing transactions (we specify a password and agree to terms in order to continue). This is not a private key.
Next, the wallet displays an instructional video on seed key security. The video is highly recommended for new users, or anyone generating a seed for the first time.
Selecting the [Next] button, prompts the generation of a new seed phrase, a related warning is displayed.
After revealing our seed phrase and storing it securely, the [Next] button becomes selectable. Proceeding from here, we are asked to confirm the phrase as a final security check, to make sure that you have stored the seed phrase accurately. By simply selecting the words in the correct order, our seed phrase is verified, and the [Confirm] button becomes selectable.
Once selected, the final confirmation page indicates that our wallet setup is now complete. Here we select [All Done] and our wallet is ready.
When looking to receive funds (cryptocurrency or NFTs), the public address can easily be copied from the top of the browser extension wallet.
Right now, the biggest thing in emerging tech is AI chat protocols. While most of the buzz centers around the latest version of ChatGPT (available for free and public use at https://chat.openai.com/), high layoff rates across the tech industry led many to wonder if AI is already replacing mainstream jobs (https://fortune.com/2023/01/20/big-tech-microsoft-alphabet-touting-ai-artificial-intelligence-amid-mass-layoffs/).
As professionals and journeymen of a different school of emerging tech (blockchain and cryptocurrency), we have seen an inflow of capital in the past couple of months specifically targeting AI-branded protocols. But are these protocols truly iterating on a continuous concept called “Artificial Intelligence” or simply a recycling of old terminology, but with fundamentally different utility and purpose?
Our social understanding of what Artificial Intelligence (AI) is, and what it will become, is constantly changing and evolving. 16 years ago, the Euphoria game engine was developed as the primary game engine for the George Lucas approved (but no longer canonical) Star Wars game (https://screenrant.com/star-wars-force-unleashed-rebel-canon-legends-starkiller/), The Force Unleased. While no real learning algorithms or functions (things we now commonly associate with AI) were implemented into the engine, the advancements of the tech were widely toted as the pinnacle of AI advancement for the time period, as we can see in this video demonstration from that year (https://youtu.be/6o6YVLmOs74). In the footage, we can see the AI Stormtrooper trying to avoid a fatal fall by grabbing onto an object. The experience became even more immersive when the stormtrooper began hanging onto each other, to a human appearing to mimic the behavior of cooperation, or in the most extreme cases, even self-sacrifice. Here we saw the early personification of AI and used it to justify a technological breakthrough.
Similarly, I recall reading an article in Time magazine during the early 2000s that explained the state of AI in warehouse management at the time (“AI” has been used for this purpose in unmanned warehouses for decades already, and without the need to mimic human behavior in the process, machines, when left to themselves, create their own efficient methods which may or may not appear useful to human observers but persist as they improve upon the objective. This means that if an AI-powered warehouse can find an object in 10 mins, that would take a human 20 mins to find in the same space, it does not matter if the warehouse can be efficiently parsed by a human or not, because the purpose of the warehouse is to remove human action anyway.
So how does this scenario relate to the AI that is changing the way we work and live? Well at face value, it doesn’t. In the case of the game The Force Unleashed, AI is a term being used to implement the mimicking of human behavior with respect to body movements and self-preservation. The feelings evoked by seeing this act played out in real-time, and without direct prompting from the user, gave the viewing human feelings that the AI is autonomous (even though it is not).
Today we are again reinventing what AI is. In the case of ChatGPT we aren’t using “AI” in order to maximize real-world space efficiency or access to items within a physical space. We are also not using “AI” to mimic human movements. Instead, we are using AI to mimic human responses to verbal prompts.
This shift in purpose finally does beg the question, is the progress and development of “AI” in fact iterative in the long term? Based on the evidence provided here, we can easily say NO. In fact, the focus of “AI” did not shift to “deep learning” as the core driver until post-2010 (per the Wikipedia timeline here: https://en.wikipedia.org/wiki/Timeline_of_machine_learning).
While the ideas behind each stage of AI development certainly share similar concepts, the application of the technology seems to be constantly shifting and evolving. This raises a very serious question regarding the validity of AI-themed altcoins in cryptocurrency and Web3.
Through the lens of modern AI writer assistants and image creators, the improvement in functions of AI, when compared to only a little more than a decade ago, can hardly be understated. ChatGPT (and similar applications) is proving to be very useful! But what about the limits of current AI? Well, it appears that even in its current form, AI still has some very practical limitations, especially when it comes to discrete mathematics.
This is disappointing when we consider (as Web3 developer DCbuild3r did in a recent Twitter post https://twitter.com/DCbuild3r/status/1636336407647068161?s=20) that the computational shortcomings in this area, do extend to areas of finite mathematics, limiting the usefulness of AI when applied to adjacent fields of emerging technology.
A final concern relates to the possible exclusion of minority opinions by AI. Though this is not a new concern, it is an important one, when we consider that widely held scientific positions have been reversed in the past.
In the end, The usefulness of AI is predicated on the basis of the social consensus providing the correct point of view (in most cases), the AI will not on its own defy overwhelming data that supports a specific conclusion, where humans often due this categorically and intentionally (in order to avoid groupthink or to benefit a disadvantaged group intentionally). While AI may be able to mimic this, If the issue is a direct product of backpropagation (the method used to produce the gradient data needed for the foundation of the AI https://brilliant.org/wiki/backpropagation/), it may be impossible to overcome without a new method entirely.
Well one thing is for sure, the AI narrative is alive, and where there is a narrative we are likely to see a market pump.
Still if we consider what we know about AI and the history behind it, is it really a Web3 narrative, or something else?
“AI Protocols” is not a category tracked by CoinGecko.com (https://www.coingecko.com/en/categories, a method of viewing all coins matching a specific narrative or theme). Google searches for “Top AI coins” yield a wide range of results including many articles from more than 2 years ago, indicating they may play a zero role in the current hype, that has emerged in only the past few months.
Active and recent “AI” themed tokens and protocols do exist as well. Bollow is a breakdown of some of the most popular and/or newest players:
Launched in 2021, Fetch.ai is not a brand-new protocol. However the protocol asset FET saw major price appreciation early this year as the AI narrative was gaining traction. The protocol hosts AI applications already, and FET is used to pay for services on-chain. Unfortunately, a public demo if available is far less easy to access than options in Web2 such as ChatGPT
Singularity next is another AI provider protocol, allowing pay-per-use AI services to be offered and leased on-chain. The protocol along with Fetch.ai is now in the top 100, again the ecosystem is targeted at AI developers and production users ready to pay for service, no public offering was found in our research.
ChainGPT, https://www.coingecko.com/en/coins/chaingpt (unlaunched?)
ChainGPT unlike our first two examples is quite new. In fact, it appears that the token has not yet launched at all. Visiting the official website does display a “Try ChainGPT Prototype” button, which links to a working demo. However, without deep research, it is difficult to determine in what way the demo relates to the final product. While there is a demo, it appears from the other marketing on the page that they are targeting the same user base as Fetch.ai and SingularityNET.
Saving the best (or worst) for last CryptoGPT boasts a website that starts off with the words “…revolution…billions of users.” Then lists big-name partners: PancakeSwap, Uniswap, Gate.io, etc. Has NFTs. Is somehow related to gaming… And then I stopped reading, but let’s assume that the project is 100% legitimate (I know it screams SCAM! but let’s pretend we don’t all have Crypto-zoo PTSD), none of the base products have all that much to do with the recent AI advancements and have even less to do with the history of AI. So perhaps there is some AI on the backend powering all of it, and it makes sense enough to be a decent product. They still have the issue of trying to fight an uphill battle on multiple fronts within the blockchain industry. Web3 gaming has not yet grown to rival mainstream gaming, and it may take a while for this to happen. NFT markets are crumbling and some are outright failing, so launching more NFTs seems like risky business too. Finally, the tech is a bit confusing, we were not able to figure out why collecting data into an NFT makes the NFT valuable to hold. Clearly, the designers are very creative, but should the ecosystem users need to be equally creative to understand it? (it is clear that they want to displace the AWS and Google controlled data marketplaces, but I don’t understand how CryptoGPT plans to position themselves to actually do this).
What it is unfortunate, despite the effective branding of these projects, the expected functions are simply not at the same level (or same accessibility) as their Web2 counterparts. Today there is no compelling reason to use Web3 in order to access AI, and the route to this does not seem clear (one possible angle is price, but even this could be a losing battle long term, this is because “as a database” blockchains are woefully inefficient when compared to their centralized counterparts).
In the end, it is without question that the most recent version of popular AI protocols are breaking new ground in a significant way, as they seem to overnight be replacing many technical writing positions or other areas of published content staffing.
However, we must consider what we threw out in the process. The 2008 AI breakthroughs sought to humanize a non-human thing, by making it appear to act based on common human emotions and responses. The feelings of humanity evoked by the AI in the player were basically a mental phenomenon taking place within the mind of the user (the AI was not designed to do this, only to mimic grabbing an object to keep from falling). The AI objects, though appearing to be “alive”, lack the programming to perform even the simplest prompt completion (what many call AI conversation), much less would they be able to explain their actions.
In the case of ChatGPT (and other AI chat protocols), we are faced with a wholly different outcome. Rather than an AI with becomes more real in the mind of the user as they experience it, we have a product that becomes less real the more it’s tested (sometimes it even gives up and tells you its an AI and won’t respond in a useful way https://www.inman.com/2023/03/15/do-i-need-to-disclose-even-more-queries-chatgpt-cant-answer/). Finally leading to major frustration as the protocol fails to properly complete even simple math equations (https://ai.stackexchange.com/questions/38220/why-is-chatgpt-bad-at-math).
While much remains to be seen within the field of artificial intelligence, it is disappointing to discover so much fracturing (or lack of contingent interaction). Should the trend of reinventing the base principles continue, it may become even more difficult to map the future of the industry, and even more difficult to apply a specific standard for use within other fields.
What AI has shown to do consistently over time, is take the combination of things that we feed it and then spit back to us something we didn’t expect. This didn’t start with ChatGPT, rather it started the first time that
Lastly, we are left asking the question: Are the showcase, most accessible, and mainstream AI protocols still dreadfully behind the times when it comes to functional computation? And, then how is the current version of Chat capable AI iterations any different from a promising-looking Web3 project with a stellar timeline, and awesome events on the horizon; but then fails to deliver on any of it? An event that in crypto we are all too familiar with.
We all need to make our own decision on where to place our bets when it comes to AI. Confirmation of a breakout in AI capabilities (by a Web3-powered protocol) could end up looking very different from what we think too, giving even more for the strategic Web3 user to consider. When they actually appear on the scene that is.