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| Fetch.ai 
| #FET
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| FET Price: | $0.56 | | Volume: | $0.1 B | | All Time High: | $1.18 | | Market Cap: | $0.5 B |
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| Circulating Supply: | 971,500,984 |
| Exchanges: | 38
| | Total Supply: | 1,152,997,575 |
| Markets: | 58
| | Max Supply: | — |
| Pairs: | 32
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The price of #FET today is $0.56 USD.
The lowest FET price for this period was $0, the highest was $0.556, and the exact current price of one FET crypto coin is $0.55629.
The all-time high FET coin price was $1.18.
Use our custom price calculator to see the hypothetical price of FET with market cap of BTC or other crypto coins. |
The code for Fetch.ai is #FET.
Fetch.ai is 4.7 years old. |
The current market capitalization for Fetch.ai is $540,435,168.
Fetch.ai is ranked #84, by market cap (and other factors). |
There is a very large volume of trading today on #FET.
Today's 24-hour trading volume across all exchanges for Fetch.ai is $114,257,905. |
| The circulating supply of FET is 971,500,984 coins, which is 84% of the total coin supply. |
Few-Shot Learning: Helping AI Learn from Little
Few-shot learning is emerging as a captivating and challenging domain In the fast-evolving realm of artificial intelligence. This concept is focused on teaching AI to make accurate classifications or predictions from a very limited dataset, which heralds a significant shift from traditional machine learning methods. Imagine teaching a computer to differentiate between two unfamiliar animals, such as Armadillos and Pangolins, using only a handful of images. This is the essence of few-shot learning — a task simple for humans but notably complex for computers! — The Game of Few-Shot Learning - To understand few-shot learning, consider a scenario where you’re shown four images: two contain Armadillos and two contain Pangolins. Without prior knowledge of these animals, it’s possible to spot differences by observing their ears or scale sizes. Now, if you are presented with a new image (the ‘query’), you could likely identify whether it depicts an Armadillo or a Pangolin. Humans excel at this kind of task, learning from very few examples. However, the challenge is to enable computers to do the same with limited data. In traditional machine learning, vast amounts of data are required, particularly in deep neural network training. But in few-shot learning the objective is to make accurate predictions from a sparse dataset. This approach fundamentally differs from standard supervised learning. Instead of training a... 
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The Paperclip Maximizer Fallacy
Welcome to the future. AI is everywhere: controlling our cars, managing our homes, and more. Yet, even with such progress, we still face tough questions about AI ethics. One thought experiment that has gained notoriety in discussions about ethics is the Paperclip Maximizer, first posed by philosopher Nick Bostrom. It has quickly grown into a cautionary tale that embodies both the promises and dangers of AI, echoing from academic symposiums to Silicon Valley tech labs. Why should we care about a hypothetical AI whose only goal is to manufacture paperclips? — Understanding the Paperclip Maximizer - Imagine a superintelligent AI system programmed with a seemingly simple objective: to maximize the production of paperclips. The AI is so efficient that it begins transforming all available materials into paperclips. Sounds good so far! But then comes the twist: the AI is so obsessed with its objective that it starts converting everything into paperclips: houses, cars, and even humans. Eventually, the entire planet becomes a haven of paperclips. While it may be a compelling narrative for late-night philosophizing or an episode of Black Mirror, how grounded is it in scientific or logical feasibility? The heart of the issue is that AI, in its relentless pursuit of a programmed objective, might disregard any unintended but catastrophic consequences. It’s not that the AI has malevolent intentions, it’s that it doesn’t have in...
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What Really Caused the AI Boom
The path to artificial intelligence is one for the history books. A labyrinth of innovations has collectively breathed life into the AI we know today. While the intricate dance between hardware, algorithms, and data has been ongoing for years, the rhythm has recently intensified, propelling AI into the limelight. But what were the factors that led to it? — The Era of Gigantic Neural Networks - Let’s rewind a bit. Neural networks before 2012 were like quaint little villages — small and manageable, sporting just a few thousand neurons. The post-2012 era, however, saw them grow into bustling metropolises: large, deep, and complex. This growth in size and depth wasn’t merely for show. Larger models demonstrated improved performance across a multitude of tasks, hinting at the potential of scaling towards Artificial General Intelligence (AGI) and possibly — even Superintelligent AI. — GPUs: Gaming Chips Turn AI Powerhouses - Interestingly, the video game industry can claim credit for the growth of AI. Graphic Processing Units (GPUs), initially developed to satisfy gamers’ demands for better graphics, soon became AI researchers’ workhorses. While the architectural skeleton of GPUs remained relatively consistent, the scale, speed, and efficiency ballooned. Modern GPUs, like the V100, can churn out computations at a staggering rate, rivaling the supercomputers from just a decade ago. When companies u...
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From Attention Economy to Intention Economy
Have you ever experienced information overload? For the last few decades, our digital interactions have been heavily influenced by the concept of the Attention Economy, where companies essentially compete to grab our focus amidst the online noise. However, a new paradigm is emerging: the Intention Economy. In this emerging model, our interactions may well be shaped by the need to understand and cater to our actual intentions or needs. AI, especially in the form of AI agents, is playing a pivotal role as the main driver for this transformative shift. — Understanding the Attention Economy - At the dawn of the 21st century, the popularization of the Internet and digital media platforms led to a surge in content creation. It quickly became apparent that human attention was the primary currency and in the 1970’s the term ‘Attention Economy’ was coined by political scientist Herbert Alexander Simon to represent this new marketplace. However, this attention-centric model has its pitfalls. With data creation becoming faster than ever, the focus shifted from the quality of content to mere quantity. Recent data supports the claim that a significant portion of global content was generated in just the last two years! As a result, consumers often find themselves inundated with vast amounts of irrelevant, low-quality information. making it challenging to discern quality information from the noise. — Transition to the Inte...
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Unpacking Bimodal Neural Networks
AI is a space where patterns and rhythms that imitate human cognition keep emerging. Enter the domain of Bimodal Neural Networks, where AI doesn’t just see or hear — it does both simultaneously, merging these senses to offer a richer understanding of the world. You can think about it like this: It is now possible to train AI to appreciate an orchestra, both the visual spectacle of the performance and the auditory magic of the music. — Dual Channels, Harmonized Understanding - People naturally take in info from many senses, always mixing different signals to get a full picture. In the same way, Bimodal Neural Networks use two kinds of info — usually pictures and sounds — and work with them together. This isn’t just about doing two things, it’s about getting a mixed view, kind of like how seeing and hearing help us understand what’s happening on a busy road. — Why Bimodal? - Single modality networks focusing on either vision or sound have made remarkable strides in recent years. Image recognition algorithms can discern objects in a cluttered photo, while voice recognition systems transcribe or respond to our spoken words with increasing accuracy. But real life isn’t just about looking or listening. A video of a music show, for example, isn’t complete if a tool only sees the players or hears the songs. Bimodal networks capture the richness of such experiences, offering a 360-degree pers...
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Decoding AI Consciousness: A Dive into the Mind of the Machine
In the ever-evolving world of tech, a big question stands out for many: Can we make AI feel like us? This question isn’t about whether AI can beat a human in a game of chess or write a story. It is about whether it could someday experience the world as living beings do. As AI evolves and becomes more intricate, the debate about its consciousness has gained momentum. While AI might convincingly mimic human conversation, could it ever truly feel? — The Challenge of Consciousness in AI - For us, being aware means understanding what’s happening around us and knowing who we are. But for machines, this idea isn’t as straightforward. A groundbreaking paper from NYU shines a light on this very topic, suggesting a structured approach to evaluate AI’s potential consciousness. There are two major takeaways from this report: Scientific Applicability to AI: Contrary to some opinions, consciousness isn’t just a nebulous concept. It can be scientifically studied. More importantly, findings from such research could be relevant when assessing AI consciousness., The Theory-Heavy Approach: While it’s tempting to judge consciousness based on behavior, it might be misleading for AI. Machines can mimic behavior without truly understanding or feeling it. So, researchers advocate a deeper approach, examining whether AI systems exhibit functions that scientific theories link to consciousness., — Indicators of Potential Con...
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Emotion Simulation in AI: A New Frontier in Human-Machine Synergy
Technology is often mischaracterized as cold and impersonal. Yet there is a growing trend in AI that could be a game-changer for AI’s image: Emotion Simulation. Let’s dive into what this means for both consumers and the tech industry. — Humanizing AI: The Why and the How - The idea of machines mimicking human traits isn’t entirely foreign. So let’s stretch our imagination a bit further: What if AI didn’t just mimic us but could also resonate with our emotions? Imagine a healthcare bot that could detect a patient’s anxiety and respond with empathy or a virtual assistant in your car that could sense your frustration in traffic and play your favorite calming tune. Achieving this level of connection isn’t science fiction — it’s becoming a reality through facial recognition, voice analysis, sentiment analysis, and monitoring physiological signals. By simulating emotions, AI can move beyond mere functionality to provide more personalized and empathetic interactions. — The Real-World Applications - This isn’t just about making our devices more friendly. Emotion simulation in AI has practical applications that could revolutionize industries: Customer Service: AI chatbots can provide more compassionate support transforming the customer experience., Mental Health: Virtual therapists who can assist human professionals in providing continuous care., Entertainment: Video games and virtual reality exper...
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Behind the Curtain: Explainable AI
Artificial Intelligence, once confined to the echelons of high-brow science fiction, now flows beneath the surface of our everyday. From the smartphones in our pockets to the digital assistants that orchestrate our smart homes, the AI age is upon us. Yet, with its extraordinary advancements comes an ever-looming shadow: How do these intricate systems make their decisions? In a bid to lay bare the mysteries of AI, a new vanguard in tech is emerging — Explainable AI (XAI). Simply put, XAI is an approach within AI that aims to make its decision-making processes clear and understandable to humans. Let’s dive into this movement, seeking to understand why clarity in AI is not just an intellectual pursuit but an urgent necessity. — A World Hungry for Transparency - Imagine an AI system designed to screen job applications, which continually sidelines candidates from a particular region. The algorithm may be efficient, but without understanding its decision-making process, it’s impossible to identify inherent biases. This scenario, unfortunately, isn’t a fictional one. At its essence, XAI endeavors to untangle the vast web of computations and decisions within AI models, enabling humans to interpret and understand their rationale. In fields such as medicine, finance, and even the judiciary, where AI is rapidly gaining ground, this clarity can be the difference between life-altering decisions and uninformed choices. Pio...
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Neurosymbolic AI Agents: Where Classical Meets Cutting-Edge
In the rapidly evolving realm of artificial intelligence, there’s a blend of old and new taking center stage: Neurosymbolic AI. For those on the cutting edge of AI innovation, this isn’t just another buzzword. It’s the nexus where classical AI meets modern neural networks, promising a leap in AI capabilities. — Understanding Neurosymbolic AI - To understand the significance of neurosymbolic AI, we need to go back in time. Classical AI, or symbolic AI, was all about predefined rules and symbols. This system used logic and structured knowledge representation to draw conclusions. While it excelled in certain tasks, it was rigid and lacked adaptability. Enter neural networks, the darlings of modern AI. These systems learn from vast amounts of data, allowing them to perform complex tasks like image recognition and language translation with astonishing accuracy. But here’s the catch: they often act as black boxes, with their decision-making processes being somewhat elusive. Neurosymbolic AI seeks to combine the best of both worlds. It fuses symbolic reasoning’s structured, logical nature with the learning capabilities of neural networks. Combining the technology with AI agents can yield amazing results. Agents can learn, reason, and generalize from limited data, while also providing transparent decision-making processes. — Why Neurosymbolic AI Agents Matter - One major advantage of neurosymbolic AI is its abi...
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The Rise of Sparse Learning
In the noise of ever-evolving narratives surrounding the AI landscape one might be forgiven for overlooking the term ‘sparse learning.’ Let’s tune into the concept that’s promising to streamline and redefine AI’s future. — From Dense Complexity to Sparse Efficiency - Picture the bustling streets of New York during peak hours. Every lane is occupied, traffic is dense, and whilst things are moving: everything seems packed and congested. Traditional deep learning models resemble this traffic scenario, with millions, sometimes billions, of parameters. While undeniably powerful these models can become excessively complex, resource-draining, and occasionally redundant. Enter sparse learning, which gets to work optimizing these neural pathways, ensuring a smoother, less congested flow of information. In technical parlance it’s about ensuring that only the most essential connections in a neural network are active and the rest are turned off or ‘sparse.’ — Why the Hype Around Sparse? - sparse learning isn’t just about creating sleek models. It addresses some pressing challenges in AI: Computational Efficiency: Sparse models require fewer resources. Think about the potential energy savings, particularly when scaling operations., Enhanced Generalization: Sparse structures tend to generalize better to unseen data, often improving the model’s adaptability., Model Interpretability: Fewer active parameters ...
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 | Fetch AI Breakout Confirmed: Analysts Reveal Bullish Targets For FET Pri...
Fetch AI (FET) has been riding the bullish artificial intelligence (AI) narrative following Sam Altman being ousted from OpenAI. Its native FET token has seen an impressive move upward since then, maintaining its bullish headwinds at the same time. But even after the altcoin has grown so much, crypto analysts are convinced that the coin is only at its starting level, and will continue to rise.
Analyst Who Called FET Initial Rise Is Back Again
Crypto analyst Tony The Bull, Founder of CoinChartist, was one of the most vocal voices for buying FET when the price fell to $0.09 back in 2022. The coin has since risen more than 5x from this level but even this has not deterred the analyst, who believes that there is more to come.
In a recent analysis, Tony presented the reasoning behind why he is still bullish on the FET price. The analyst had previously expected a retracement. But from the current level, expect the price to increase once more.
The chart shows an initial bounce above the $2.5 mark before a retracement that takes it back down to around $0.55. Then from here, there is another bounce upward to over $4 once more. If this plays out as expected, then the FET price could be looking toward multiple bounces of over 500% from here.
Updated plan pic.twitter.com/pkfhHBQxCC
— Tony 'The Bull' (@tonythebullBTC) November 20, 2023
Fetch AI On Bulls’ Radar
In the same vein as Tony The Bull, another crypto analyst has predicted that the price of FET is headed for more ral...
|  | Is Fetch.ai (FET) On The Cusp Of Another Mega Bull Run To 2021 Highs?
A crypto trader took to X on November 15, predicting that FET, the native currency of Fetch.ai, an AI-centric platform, could be aligning itself for a 'green path,' resuming the uptrend of the past few weeks.
The analyst, @rektcapital, believes the recent price action on the weekly chart points to strength. Moreover, the possibility of FET bulls flowing back and driving prices above the immediate resistance level registered in early November remains elevated at spot rates.
FET Remains Bullish, Up 770% From 2022 Lows
Looking at the candlestick arrangement in the weekly chart, FET buyers have had the upper hand. To quantify, the coin is up 140% from July 2023 lows and may be preparing for even more upsides if prices break above $0.46 recorded in the first week of November. As it is, FET is up by over 770% from December 2022 lows when the coin plunged to as low as $0.0570.
From technical analysis, FET recovered from around $0.17, representing the 78.6% Fibonacci retracement level of the trading range established in the first half of 2023. FET prices may rise, building on the bullish engulfing bars of late October and early November 2023, breaking above $0.46. This expansion, in turn, may create the base for the next leg up to $0.60, marking 2023 highs.
Despite the current rally, whether FET prices will find the momentum to retest 2021 highs of $1.20 is still unclear. Even so, as FET expands, there is a notable change in participation levels, lookin...
|  | New Biden Rule Could Affect AI Cryptocurrencies Like GRT, AGIX, FET (Opi...
The new rules require companies to conduct AI safety tests and share the results with the US government. In addition, they include meeting official standards for safe AI development and clearly labeling AI-generated content. That's worth avoiding a Skynet or Omni Consumer Products fiasco.
White House Issues New Rules for AI
A fact sheet released by the White House briefing room notes:
'AI can bring real benefits to consumers—for example, by making products better, cheaper, and more widely available. But AI also raises the risk of injuring, misleading, or otherwise harming Americans.'
Here's how the government's new regulations for artificial intelligence developers could affect the cryptocurrency industry. But also, here's how cryptocurrencies can help support the government's priorities.
Increased Regulatory Costs for AI Blockchains
The new reporting requirements in Biden's executive order are apt to add costs for AI cryptocurrencies. However they pan out, blockchains that utilize AI will have to take on the additional time and cost burden of staying in compliance.
But that doesn't mean bootstrapped startups will be overburdened. The White House release on the new executive order specifies that it's 'developers of the most powerful AI systems' that must 'share their safety test results and other critical information with the U.S. government.'
Ostensibly, by the time an AI blockchain reaches a critical threshold of capability to fall under this requirement, the project ...
|  | FET Blasts 14% Higher: See The 'Golden' Signal Behind The Surge
As the broader cryptocurrency market breaks out on the back of Bitcoin's big rally, FET is the next altcoin to double-digit gains. The AI cryptocurrency at one point hit 14% higher intraday.
The move could be the start of something special, according to a 'golden' signal in Fetch.ai.
FET Soars 14% As Golden Cross Triggers
FET is up 14% today as cryptocurrencies across the board see significant gains led by Bitcoin (BTC) this week. Even before the big move, the AI coin had opened this weekly trading session forming a golden cross of the 50-week and 200-week moving averages.
A golden cross occurs when a short term moving average crosses above a long-term moving average from below. This is a buy signal in trend-following technical systems and suggests that a new trend is potentially blossoming. A death cross is the opposite sell signal.
While the signal in and of itself is bullish based on the performance of trend-following systems, FET could be showing itself as a crypto market leader by being among the first coins to form such a golden cross. Ethereum (ETH) and Bitcoin are still death crossed, for example.
Even recent market stars Chainlink (LINK) and Solana (SOL) haven't formed a golden cross on the weekly timeframe.
Can Fetch Recapture AI Hype? There's no denying fetch.ai's latest double-digit price surge has brought fresh excitement and validation to the project. The startup's vision of an AI-powered decentralized machine economy clearly resonates with many crypto investo...
|  | Fetch.ai (FET) Price in Top Crypto Gainers Today, Are AI Coins OCEAN, PA...
The Fetch.ai price is among the top crypto gainers today and outperforming the market, one of the few altcoins not to fully retrace their post-Grayscale news pump.
FET Price Predictions
FET was one of the best performers of early 2023, pumping 200% in January and a further 60% in February, as AI crypto projects took the limelight - before meme coin season took over in Q2.
One of the most followed crypto Twitter accounts, @Nebraskangooner, again noted ‘$FET is one of the better-performing altcoins at the moment’ and plans to chart the FET price chart live on stream today.
Another prominent trader and streamer, Cold Blooder Shiller, noticed this week FET had been ‘resilient to low-timeframe selling’ and one of the ‘only charts with a triple high-timeframe bullish divergence.’
@Phoenix_Ash3s added that the FET price action had swept its June lows earlier this month, and if the FET price can print a higher high at $0.25 or above, it may be time to ‘brush the dust off your AI coin list, as they might wake up too.’
Best AI Crypto Coins to Watch
With the FET price about to close an over 10% monthly candle for August, are AI crypto coins making a comeback? Below may be some AI coins for your watchlist, including both new and old AI projects:
Launchpad XYZ
Launchpad XYZ (LPX) is not yet listed on exchanges as it’s still in the presale phase, offering a chance to invest early in a high-potential AI-related crypto project.
We previo...
|  | Bitget Betting Big on AI With $10M Investment in Fetch.ai Ecosystem
On April 27, Bitget announced it has pledged $10 million for the development of the Fetch.ai ecosystem.
Bitget plans to provide a range of services to Fetch.ai, including marketing consultations and strategic directions.
Fetch.ai provides a service automation infrastructure that is powered by an AI agent network. These autonomous agents perform various tasks, including data analysis and complex financial modeling.
The move is the latest to latch on to an AI boom driven by platforms such as ChatGPT.
'BitGet Pledges $10 million to Foster https://t.co/kJ9URVpOul Ecosystem'
Exciting news! A strategic partnership has been struck between https://t.co/kJ9URVpOul and @bitgetglobal with plans to push the #AI ecosystem further
Read more details https://t.co/yYAxgEXjIR pic.twitter.com/TcE7kUUf3B
— Fetch.ai (@Fetch_ai) April 27, 2023
Bitget Spending Big
Bitget Managing Director, Gracy Chen, commented that Fetch.ai already consists of a host of functioning and applicable technological AI solutions before adding:
“That is the main reason we have decided to pledge our support to this promising startup and will continue to do so as we identify others in need of assistance from our dedicated fund.”
Humayun Sheikh, Fetch.ai founder and CEO, said the opportunities for applying blockchain to AI are limitless.
Fetch.ai uses decentralized machine learning algorithms to provide its users with various innovative software solutions.
On April 10, Bitget announced a $100 million ve...
|  | Bosch and Fetch.AI Launch $100M Foundation to Fuel Web3 Adoption
German multinational engineering giant Bosch and Cambridge-based artificial intelligence lab - Fetch.ai - have jointly unveiled a new foundation focused on fueling industrial adoption of software agents, AI, and Web3 technology.
Dubbed - Fetch.ai Foundation - this new initiative will focus on areas such as research and development as well as harnessing the application and adoption of agents, Artificial Intelligence, and Web3 decentralized technologies for real-world use cases to improve the existing network.
The target will also be to assist in the long-term development of Web3-powered solutions and services in sectors across mobility, industrial tech, and consumer products.
In a press release shared with CryptoPotato, Humayun Sheikh, Fetch.ai's Founder and CEO commented,
'Over the next three years, our team will look to inject upwards of $100 million into industrial AI through various grant programs as a way to accelerate growth within our space alongside like-minded businesses and partners. We would also like to encourage other industrial players to join the foundation to steer and influence the development of this AI-powered peer-to-peer tech stack.'
At launch, the foundation's board will be anchored by the Fetch.ai and Bosch teams. Meanwhile, the focus will be on slowly developing strategic participant growth with businesses that seek to develop the infrastructure for a 'decentralized digital economy' driven by AI.
To that extent, Peter Busch, Chairperson of the Fetch....
|  | Fetch.ai Announces DabbaFlow, A File Sharing and Data Management Platfor...
Fetch.ai, the development team building an open-source, machine learning-powered network for smart infrastructure and customizable dApps, has launched DabbaFlow.
In a press release, Fetch.ai said the ready-made and end-to-end encrypted file-sharing system is the first of its kind and would empower businesses and entities to take control of their data privately and securely. Notably, DabbaFlow leverages the benefits of the Fetch.ai blockchain to ensure privacy preservation of all sensitive data transmitted on its rails. All data piped through the product will be auditable and secure, a guarantee vital for maintaining and protecting business reputation.
The solution is borne out of necessity, considering the exponential expansion of data online accelerated by the COVID-19 pandemic of early 2020. With more businesses coming online and uploading data, there is also an increased risk of hacks and unauthorized access by third parties. These breaches can be consequential to victims and businesses, mainly if they are engaged in data-sensitive sectors like healthcare and finance. The resulting loss of business and reputational damage can adversely affect the entity's ability to expand, partner, or even do business.
Accordingly, the demand for a secure file-sharing platform is paramount. Fetch.ai is, therefore, timely providing a solution to cater to businesses desirous of using a superior product in the digital age to shield data against unapproved access while being a conduit for fur...
|  | West Ham United Announces Fetch.ai as their Official Artificial Intellig...
Fetch.ai is West Ham United's exclusive official artificial intelligence partner and the premier league's giant non-exclusive Official Global Partner. Under the deal, Fetch.ai has also been designated as West Ham United Women's football club's non-exclusive official partner. Through this partnership, Fetch.ai and West Ham United will leverage and promote the impact of artificial intelligence in enhancing businesses and daily lives.
Fetch.ai Brand to be Displayed in West Ham United LEDs
Subsequently, West Ham United will promote the Fetch.ai brand and its products in their mega London Stadium on their LED perimeter advertising boards and displays, marketing Fetch.ai's smart parking concept, upcoming social media platform, and future smart solutions.
West Ham United's London Stadium at the Queen Elizabeth Olympic Park has a capacity of 67,000 fans. It is larger than Tottenham Hotspur's £1 billion stadium. In London, the West Ham United's mega stadium is only second after Wembley and Twickenham stadiums.
Nathan Thompson, the Commercial Director of West Ham United, said he was delighted with the partnership.
'We are delighted to announce our first Official Artificial Intelligence Partner and welcome Fetch.ai to the Club at an exciting time for the business, and the industry. We're looking forward to working with Fetch.ai on their smart parking concept, social media platform, and upcoming projects that will provide smart solutions for fans.'
Using Artificial Intelligence to ...
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