Over the past few months we have produced a number of demos of our mobility solutions, so we wanted to share with you all a brief update of the progress over the summer, and what’s next for us.
At Fetch.ai, we are broadly grouped into research, the core ledger and economics team, and applications. Our applications teams are focused on mobility, financial, and collective learning, and each of these are working on a product roadmap to bring the Fetch.ai vision to life.
This blog is a summary of the mobility product activity within our Applications team.
Why mobility?
Mobility is a key vertical to target for Fetch.ai technology as it sits right in the heart of our sweet spot; highly complex interactions among multiple participants, where there is currently not a good co-ordination mechanism, and where a multi-agent system could unlock huge value, and create markets that do not currently exist.
There are billions of devices, processes and pipelines around the world that are desperate for automation and communication. Most blockchains aren’t built to handle such a large number of transactions, and none enable their clients to learn from the data generated and exchanged.
Fetch.ai is a platform built to bring value to data, by connecting devices and facilitating the creation of new markets based on what they learn from each other. It is the platform where truly autonomous decisions can be made.
Development areas to date
Trains
You may be aware that we have been engaging in a number of industry associations for some time, including Mobi, The Convergence Alliance, Blockchain for EU, Warwick Business School, Cambridge University, and notably for our Mobility activities: the Rail Industry Association (UK)’s special technology interest group.
From this it has given us the insight to create some of our recent initiatives on optimising Rail infrastructure in the UK:
Taxis
The “delivery” of people, and by extension other physical objects via couriers, is a great example, as it is so familiar to people, but also accounts for such a huge amount of economic activity. Statista estimates a market size of $366bn by 2024 for ride hailing and taxis alone, online food delivery will soon be a $200bn market, and the global logistics market was $9.6 trillion in 2018 according to Armstrong and Associates.
Uber and co have created platforms to enable a “sharing economy” but we believe this is only the first step. Why should intermediaries sit in between counterparties in mobility transactions, when a software based system with a minimally extractive protocol will improve utility for all participants?
That is what we are building with our multi-agent based approach to mobility. We pioneered decentralised delivery of people with the taxi network demonstration, and now that has grown into delivering people, packages and pizzas: and the prototype system is up and running now 24/7.
Parking
A good example of how multi-agent systems can impact at the small level, as much as the large, is in parking solutions.
A huge part of traffic in cities is looking for a parking space.
With agents representing congestion and pollution zones, as well as traffic junctions and more, it’s possible to optimise everyone’s journey alongside air quality and more: it’s good for the environment, our stress levels and it adapts in real-time to changing circumstances.
Our aim is that by bringing all the component parts of a mobility system together, including all those elements that are currently ‘inert’ cities will be much more efficient, pleasant places to visit.
Autonomous driving
Another example of how agent based solutions can create value that doesn’t currently exist in today’s economy is via our recent collaboration with T-Systems.
The “Signs” project looks at how a reactive and responsive environment can enable higher level autonomous driving using today’s technology, by bringing the environment to life with agent-based representatives of aspects of the physical world, that can then communicate with vehicles.
For more info on the challenges of higher level autonomy, check out Toby’s recent blog on “The Courcehevel Test”.
Building towards a universal ‘mobility’ platform product
The goal is that all these elements will converge around a ‘Decentralized Delivery Network’ or DDN, that provides an extensible library of tools and services that anyone can plug into to create agents and transact across the Fetch.ai network.
We’ve been running our DDN constantly now for a while, and now it runs 24/7 simulating passengers, parcels and vehicles.
We’re ramping this up to far, far bigger numbers in the coming days and weeks, and we‘re preparing an update video and blog post really soon.
Our summer mobility presentation
This approach was summarised well by Toby and Josh in our recent mobility presentation over the summer. You can watch the playback here:
What is live today?
So what is happening on the Fetch.ai network today? Right now we have the following agents working:
- 170,099 agents on the network
- executing 109,451 search queries
- with a peak rate of 15,615 interactions per minute
You can all interact with the soef yourself, of course, with your own agents and contact/trade/view what’s going on with your own agents.
Go to docs.fetch.ai to discover more, or join our Developer Slack channel.
Current development activities
The focus of all these activities is building up to the integration of a mobility focused product suite and tool-set that will be going live into our v2 main net, which is slated for launch in the next few months.
We’re also porting it all across to Agentland, which is the testnet for our upcoming main net v2.0, supporting fast, low-cost transactions that these agents need in order to work.
In the Fetch.ai world, Autonomous Economic Agents do the work on your behalf, operating on your preferences and learning as they go, adjusting in real-time to any unforeseen consequences.
An openly accessible, real-time infrastructure for sharing insights about the state of the transportation would create wealth, increase productivity and drive economic growth by allowing the sale and use of knowledge about the demand for, and supply of, mobility.
Here’s a short overview of some of the in-development screens:
Starting small with a couple of drivers and routes.
Getting bigger: showing multiple destinations, passengers and drivers all going around their business
More complex routing as the jobs start to spread out.
Simple Open Economic Framework (SOEF)
And a sneaky peek into an admin output from the SOEF showing a couple of the agents doing their thing.
And what’s important about this demo is that any of the agents can be taken over, i.e., “inhabited”, by real humans: and we’re very, very close to doing that, and running a live demo of the whole thing.
It’s a fantastic example of a key use-case, and shows huge utility value in the FET token now and in the future.
And for those of you who have not already seen it, check out our co-founder and COO Toby’s recent blog post on our vision for decentralized mobility services:
