Solving information failure

We believe that most bad things in the world are the product of some form of information failure; from economic collapse and the outbreaks of war and disease, to choosing the right life partner or university degree.

We’re on a mission to help everybody make the right decisions and overcome information failure once and for all.

Brilliant innovators have sought to organize the world’s information, but the next step on this journey is to make information understandable, usable, and accessible to everybody.

Overcoming bounded rationality

While high-tech, well-funded organizations like hedge-funds are able to process vast swathes of the world’s information efficiently for minute gains and millisecond edges in economic trades, the vast majority of businesses and individuals have no systematic way of parsing the wealth of signals contained in the world around them.

AI and simulation have the power to unlock a better world: advancing our understanding and appreciation of the environments around us, and helping us understand information that is being collected and generated at a pace like never before. They can alert us to possibilities never considered, highlight hidden relationships between the agents within them, and force us to make explicit our assumptions about how the world works.

Not only are simulations useful cognitive tools for humans, but they have the potential to be rich, machine-readable representations of real world problems as well.

At HASH, we see simulation as the universal interface for both humans and AI -- and in our view the best bet we have for growing connective tissue between human and machine learning.

We hope to enable better human and automated decision-making: bringing about the rational resolution of conflicts of all kinds -- social as well as financial -- reducing and eliminating suffering of all kinds, as well as market failures, and supporting people to achieve happier, healthier lives. We don’t want to wait for this.

An open platform for modeling

Good simulation models are today expensive to build, and costly to run as well as maintain. Software for agent-based modeling has been stuck in the 90s, and the resulting models are grossly over-complicated or questionably opaque.

We believe the solution to better modeling lies in allowing individual high-quality, high-fidelity models to be built, which can be mapped to common data structures that describe the agents and events within simulations. This allows for individual models to be combined into more trustworthy, high-fidelity models of domains or problems.

However, to build realistic agent-based simulation models, we need realtime "collective awareness" of what's going on in the world. Our first product, the open-source, self-building HASH database helps bring this to life, supporting the AI-powered retrieval of information from across the internet, and the two-way sync of data across systems, mapped into a semantically meaningful form.

Our ultimate vision for HASH is much broader, akin to a "computational Wikipedia" of sorts: an open ecosystem of interconnected knowledge graphs where individual world models can be captured, best-in-class representations can be maintained by domain-experts, and anybody can utilize and combine information that is made public.

To eliminate information failure, we need to build tools that have never been created before to solve problems that can’t be solved today. We need to give people superpowers, and that’s what we’re on a mission to do.

If you want to join us on our mission, you can help by publishing entities and types to HASH, by using our simulation tools, or by working with us.

And finally, if you’re a decision-maker interested in learning how HASH or simulation can be applied to help your organization, contact us.