Fetch.ai are a UK based company that seeks to harness the power of artificial intelligence, machine learning, the Internet of things and blockchain technology. I know what you are thinking, aren’t we all…
In all seriousness, there are a lot of buzzwords there and a lot of topical words that can often amount to companies using them to gain traction.
But, hopefully, after reading this article you will realise what they actually mean and that Fetch.ai may actually have found a harmonious way of implementing them for the greater good.
In our ever-increasing digital world, things can sometimes feel like technology is consistently working against us. The Cambridge Analytica scandal shocked everyone and if it didn’t it should.
This combined with the largest tech companies in the world consistently monitoring our every move all the while using that data to create a bigger and bigger technology gap by feeding their AI machines information, the smaller tech companies could only dream of.
We seem happy to blissfully give away our every move, mood, location, occasion political standpoint and personal preferences and not get anything back apart from targeted ads…
Seems a little unfair to me…
So what if there was a way for all that data and self-identifying preference information could be used to make technology great again?
Fetch.ai seeks to use that data, in a trustless, transparent and decentralised way, feeding the information back to what they like to call agents.
Everything around us has some level of intelligence. Yes, even your partner… But if you have ever used a Google Home, Alexa, Hive heating system or digital blinds, you have used the internet of things technology (IoT).
Lots of devices in the wild (streets of the world) also have some form of smart connectivity or even in their most basic form a sensor.
Fetch.ai is seeking to connect these devices in a secure and decentralised way and ensure this connectivity is intelligent.
A basic example is the train network. Trains, tracks and signals are already equipped with sensors and passengers are equipped with smartphones.
These can be used in a way to exchange information in a very effective and efficient way, all the while being secure and decentralised.
The Fetch agents are highly intelligent little things that are great at machine learning and artificial intelligence.
You can set preferences based on your train journey and your habits and as you begin to use the agent in everyday life it will pick up and learn from your habits.
This way, if you encounter another agent or device using this technology, the whole experience is tailored just the way you like it.
Let me explain with an example…
If a train is to be delayed and you are running late, if you had known in advance that you could have hopped on at another destination and got around the delay, Fetch AI could suggest this to you.
Now that might not be world-changing, although it is useful, Fetch.ai could, in theory, understand that you aren’t in a rush and you are the type of person who prefers to travel in comfort.
An agent would understand this and notify you when would be best to leave for the next train that has a spare seat in a quiet carriage or at a discounted rate in 1st class.
It is a completely tailored experience for each user, which is built around the Fetch agent understanding and learning your likes and dislikes through machine learning and AI, all the while protecting your data and not funnelling it off to the highest bidder.
So what are the Fetch.ai Agents?
They are referred to as Autonomous Economic Agents or AEAs
So what does that mean?
Autonomous – acts of their own accord.
Economic – Behaviour and interactions between individuals and businesses.
Agent – Perceives its environment through sensors and can act on the environment with effectors.
AEAs in a basic form could initiate actions like:
When x is low buy
When y is high sell
If this happens then do that basically.
An AEA could, as an example, be deployed to search for cheap concert tickets. It understands how to negotiate and how to search for sellers.
If it encounters another AEA that has been deployed to sell the tickets at an auction, the buying AEA can learn from the selling AEA how auction skills work. Then it could act on that accordingly to secure the tickets at the best price. Fascinating.
Act on your needs and requirements whilst you can sit back relax and not have to lift a finger.
Electric vehicle (EV) companies could implement the Fetch.ai framework into their EVs as a way to communicate with other cars on the road for traffic updates, charging stations to assess for queues and also assess for the most favourable charging station based on driver preferences.
If you were in a hurry and wanted the fastest route home on a long trip which would require at least one charge of your EV, you could set the AEA to understand the hurry and constantly monitor the charging stations which have the quickest charging output, cheapest cost per charge and with the smallest queues.
I understand Tesla implement a couple of bits similar to this in their cars, but if any other car manufacturer going forward wanted to implement such technology into their cars frameworks Fetch.ai could facilitate this all in a decentralised and secure way, without the need for expensive and slow development in a fast-moving industry.
So where do the FET tokens come in?
To understand the FET token you need to understand how it is structured on the Fetch.ai blockchain.
Here, we go… Fetch.ai has produced its own blockchain taking a lot of fundamentals from the Cosmos blockchain. This is a quick and effective way to produce a blockchain but to also be able to change a few things slightly.
Remember the blockchain is a record. A decentralized ledger. So, a record of all FET transactions, spread out across lots of different computers (nodes) all keeping a track of what is going on and making it permanent on the Fetch blockchain.
To confuse you a little more, the Fetch.ai blockchain also has a bridge to the Ethereum blockchain, which allows for the crossing of the FET token from Fetch to Ethereum. This is great for traders, users and the overall liquidity of the FET token.
The blockchain in this example is the trunk of the tree it moves in one direction constantly growing and keeping track of all the transactions, from the ground up.
The AEAs we spoke about above, act on the next layer which is called a directed acyclical graph (DAG). Think of this DAG (I can hear your Brad Pitt impression through the computer), as the branches, smaller branches leaves and budding flowers.
The difference between a DAG and a blockchain in the most simple terms is that to confirm a transaction on a DAG, you only need to verify the previous two transactions to ensure everything is good and proper.
Because of this, the speed and scalability of DAGs are immense. You can on one shard (branch) achieve up to around 30,000 transactions per second. Big trees have a lot of branches…
The way the Fetch.ai ecosystem work is structured allows a legitimate decentralised blockchain layer that is robust and extremely secure, whilst the heavy lifting of the AEAs is carried out on a DAG for scalability and speed. It is genius if you ask me.
So, back to the FET token.
There are a lot of uses for the FET token including –
Staking – Holders and users can stake their FET tokens, meaning they can deposit their tokens into the network to help validate all the transactions on the Fetch.ai blockchain. In return, stakers get rewarded in the transaction fees.
If a company builds an autonomous agent and would like to deploy it on the FET network, to do so they would need to transact using FET. Both the building and deploying would require FET.
Someone looking to learn from existing agents as in the auction example would have to do so by paying the already experience AEA in FET.
Apps that integrate with Fetch.ai such as the decentralised delivery agent below will transact in FET.
The actual tokenomics of FET are as follows:
Circulating supply – 746,113,681
Total Supply – 1,151,441,226
Percentage – 65%
Given the network effect of Fetch.ai, the remaining supply will be quickly swallowed up as builders and AEAs are released on to the imminent mainnet launch.
Currently sat at $530,000,000 market cap even at a fully diluted market cap of $819,000,000, FET to me is still undervalued.
This link will give you discounted trading fees and also help support our website. We appreciate any contribution. Back to the article…
Partnerships and funding
The list of partnerships and use cases FET has already produced is also very encouraging. Cambridge and Oxford University, Network rail in the UK, Bosch and T-Labs the R&D sector of T-Mobile.
The initial seed round ($15 million) of funding was provided by Outlier Ventures. A team of investors who also backed Chainlink, Ocean and Brave to name a few. I bet they aren’t short of a few quid now…
Mainnet launch –
The mainnet is the Fetch.ai blockchain going live and allowing business to start. All the processes above have been carried out on the mainnet v1.0, At the end of March 2021, Fetch.ai will be releasing their v2.0.
It wouldn’t surprise me if a whole list of big-name players begging to utilise the platform and create AEAs and more. There are some rumours are surrounding IBM but until this is confirmed take it as hearsay.
As Fetch.ai was released on the Binance launchpad as an Initial exchange offering (IEO) it is amongst great company. ONE, THETA, BTT, MATIC and others are all flying and a lot of them have reached above $1 billion market cap.
Fetch.ai with the launch of mainnet2.0 in my opinion is set for a great 2021.
This is not investment or financial advice and this article is for educational and entertainment purposes only. For full transparency I own FET.
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