The mirage of AI Cryptos: a gap between hope and execution
AI has been present everywhere, constantly, since the release of OpenAI. In the media, science, chatbots, automated responses on our screens, etc. and hence also in cryptocurrency. Do you possess TAO, RNDR, or FET? This post is intended just for you.
These tokens, which make the bold claim that blockchain technology and artificial intelligence will revolutionise a number of industries, are ultimately little more than marketing gimmicks and empty promises for companies that will never really use the "AI."
The enthusiasm surrounding NVIDIA's stock market success undoubtedly contributed to the euphoria surrounding AI cryptos, which are tokens associated with artificial intelligence-based enterprises. Or, unless we take a closer look, that is what we believe.
Bullrun has the power to elevate anything, and these tokens soar merely by virtue of a hazy connection to artificial intelligence, even in the absence of any tangible use:
However, a number of problems with these three tokens surface under the cover of speculation:
False advertising that is obviously at odds with the whitepaper
A tenuous connection, if not a complete one, with AI
A cursory examination of the blockchain, limited to the Render token (RNDR)
The Render Network presents itself as a participant in blockchain technologies related to artificial intelligence. Nevertheless, Octane Render, a platform that leverages your GPU for more realistic video rendering, is the foundation of its primary activity. The idea is this: instead of having to purchase the necessary hardware, you may rent someone on the platform their graphics processing power. AI has nothing to do with it.
Even worse, every step of the platform's operation happens off-chain. The RNDR coin, which is used to rent GPUs, is the only link to the blockchain. There would have been no discernible difference if they had used euros, SHIB, or BabyDogePepe22.
The Fetch.ai (FET)
Although Fetch.ai's name implies inherent AI capacity, the app lacks any true artificial intelligence features. Its whitepaper and its official website, which discuss artificial intelligence extensively, are unrelated: Making API calls for "Virtual Agents" is the main function of fetch.ai. "Virtual Agents" are essentially simple chatbots that have pre-programmed responses, akin to an answering machine that says, "Type 1 to listen to your messages."
It is possible for fetch virtual agents to obtain data off-chain and conduct centralised API queries. The network's inability to confirm that external API requests are correct is the main issue, though. Accurate data cannot be obtained off-chain, and this also applies to fetch.
Although Fetch.ai appears to offer sophisticated artificial intelligence capabilities, its actual use is restricted to the development of basic chatbots that may respond to preset questions without any quality control checks on the data they supply. They might bounce back.
BitTensor (TAO)
The most AI-related project is undoubtedly BitTensor. Well, almost: the website's "About" section states four times that "Understanding BitTensor is difficult, for the same reason that it is powerful," with cryptic explanations that are, to put it mildly, confusing:
BitTensor is powerful, which also makes it tough to understand. In fact, much of BitTensor's processing capability lies beneath the markets, abstracted rather than explicitly defined. For instance, BitTensor uses machine learning models to generate intelligence goods; for storage products, BitTensor uses physical storage. However, it doesn't go into detail on how these resources are made. Rather, BitTensor only establishes the market that will compensate these goods for being made accessible to the network.
Thankfully, its technical documentation provides a far better explanation of what it performs. It serves as a subnet and miner marketplace. There are validators who assign scores to each response and miners who produce responses for each subnet. Based on their ratings, miners are subsequently compensated in TAO.
And while some refer to BitTensor as a platform for using machine learning to create dApps, a closer look reveals that the website makes no explicit promises or descriptions of this potential.
The issue is that machine learning necessitates a regulated setting where engineers manage miners and validators. Engineers have no control over miners on BitTensor. Hence, miners can easily depart and pilfer any advancement accomplished.
It seems as though OpenAI pays users to create AI models and invests time in training, validating, and other processes, allowing these manufacturers to retain the data and use it anyway they like.
In summary, you would have realised that these initiatives are particularly noteworthy because they prominently show the terms "blockchain" and "AI" on their website. This article's main goal was to expose the often-meaningless but potentially very promising hidden meanings behind "keyword" efforts. One last piece of advise, in the hopes that all this technical language hasn't left you too sleepy: the AI crypto bubble will eventually bust.