When you have a real edge in the industry you do have a real responsibility in society
"When I was pursuing the PhD on learning-adaptive machines I was an experienced economist already hence, I could see beyond the hype of A.I. up to its risky implications. The techie world was all about machine maximization back then so I understood I had a responsibility to try to align both worlds from within."
Sergio Álvarez-Teleña, Co-Founder
Sergio, our co-founder, was keen from start on the implications of A.I. on human lives and the world in which we live.
He often uses the term ethical impact when it comes to the usage of A.I. for business disruption. By aligning companies and society's interests the former can find robust sweet spots as opposed to punctual sources of revenues - robust to regulation, to law, to reputational risk, etc.
In nowadays fast changing world, finding those sweet spots required mastering a myriad of complex fields. These, well mastered at SW, span across Microeconomics, Macroeconomics, Labor Economics, Game Theory, Machine Learning, Learning-Adaptive Machines, UX Optimization, Decentralized Economics... up to the avatars in the Metaverse. Hence, our sense of responsibility.
As a result, our co-founders are often asked by supranational agencies to help evolve the application of A.I. on the right path.
GPAI (OECD), UNESCO, IDB... are examples of places where they are leading or reinforcing projects around A.I. Regulation, Algorithms Audit, A.I. Commercialization, A.I. Ethics...
However, we are proud to say that we have also helped a number of local organizations, globally - from a family office in Italy fighting for girls' mental health to Enrique V. Iglesia's foundation at Uruguay, to help elder people keep thriving.
One dimension of our platform is the continuation of Augmented Machines. This field, where Sergio is pioneer, directly assumes that the machine takes over a role - not the human. That's the error we are most afraid of when it comes to Transformation: removing the human role from the equation. Why? From a mathematical perspective - and taking into account both that machines are not intelligent yet and experts are not easy to find - there is low probability for a so-called corner solution. So, we keep innovating on the way companies approach new tasks so that the experts are included as they prove the machine that it performs better with them than without them.
Sergio took that approach on his PhD Thesis - he proved an algo trading machine (a very special one that was the core of a highly regarded award to the Best Trading Platform in Europe) that its calibration was better with his input (without the use of any code) than without it. It was called Avatar Calibration and it was the first use case of a methodology to let your avatar have an autonomous life as close to your profile as possible.
And that was only the beginning. After that, we created SW TipTop ®, a bot augmented by experts' analyses for investing - with 38% and 84% performance on its two different use cases. Later we created a new on-platform protocol, SW Alpha Dynamics ®, to decentralize the investment committee of the asset managers - a combination of a machine and the views of all employees within the asset manager. And a long etc.
At this point you may be already arriving to the conclusion that our mission is our driver in SW - no matter how long it takes the overall industry to adopt our advances we keep improving them and generating use cases for them to onboard as soon as possible.
This was the reason why we created a Virtual Reality - a very especial one that won the award to the Best Innovation in Simulation at CogX - that could help Compliance and external auditors validate the impact of trading algorithms from banks and hedge funds.
We selected this use case as trading algorithms do account for some of the largest IP protection on Earth. The key of this successful example is that our whole audit process did not need to disclose a single line of code. Moreover, it was non-coder friendly as Compliance could define the whole virtual ecosystem that tests the behavior of the algorithms all by themselves - and even use it as a training sandbox.
Part of the industry was expecting us to enter the world of blockchains. But we didn't for a reason: they are not green. All our technology uses as little power (whether human or machine) as possible by design. This has a lot of subtle implications with regards to the way we can run the company but let's highlight two obvious ones in the industry and society.
First, the lower the power required (the more challenging the software design yet) the lower the carbon footprint. So yes, we deliver green algorithms by design. And second, the cheaper it is. By being cheap it is inclusive by design in a way often still disregarded: smaller companies and average individuals can benefit from our algorithmic services. Else, it would be more difficult for them to thrive in a digital world.
So, how about blockchain again? Well, it is time for SW to step up and generate use cases along Federated Algorithms. Those can leverage the Layer 2 of any blockchain rail and remove unnecessary duplicities in calculations around DLTs. That greener and more inclusive sweet spot shall allow to evolve the blockchain ecosystem in a more robust way - just as explained above around A.I.. And that's just the beginning - stable coins, international trade... can all be improved through more refined methodologies that pure L1 smart contracts.
This is only the beginning of a massive change that will take decades to settle. The tip of the iceberg. And we do not settle for just waiting and seeing since, as said above, we have a real edge in the industry that translates into a real responsibility hence, above efforts and all those yet to come.
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