@herbertroitblat2Introduction to Herbert Roitblat and Reliath AI
I wrote a book about artificial general intelligence called Algorithms are not enough: Creating general artificial intelligence (MIT Press). It lays out a roadmap for AGI. I had started to write another book on how to pursue that roadmap when my now co-founder, Chris LaCour, read a post I did on Substack, The self-curation challenge for the future of AI. We decided to expand that into Reliath AI.
Reliath AI provides a bespoke model for each customer that contains only information identified by that customer as a source of truth. It is not a language model, but uses facts as its atomic level of analysis. It represents each fact as a symbolic proposition and as semantic vector. By the combining the two, we get more power than can be supplied by either one alone. It is a deterministic model, that trains in one pass, so it is very quick to train and very efficient to query. It uses only a tiny amount of energy compared to an LLM.
Rather than including every piece of information that the LLMs can access, its focus on customer-supplied data means that there is no unauthorized data included in the model to block from coming out. Governance is greatly simplified. The symbolic representations can be organized into knowledge graphs without an ontology.
We have applied for patents. We have a few customers and a few applications. Thousands of applications can be built on top of Reliath models. One of our current applications is an AI harness governing AI agents.
Comments2
Running SaasRise, I've seen a lot of SaaS CEOs with a product that could power thousands of uses grow slowly until they picked one buyer with one painful problem and sold only that. For Reliath, the harness that keeps AI agents in check could be that first focus, since a compliance or risk leader immediately gets why answers drawn only from the company's own approved facts matter.
Yes, you're right. I compare it to Antarctic penguins. When they are hungry, they gather at the edge of their ice shelf and jostle one another. There may be Weddell seals below waiting to dine on fresh penguin. Nobody wants to be the first penguin in the water, but as soon as one penguin falls in, they all jump in. Selling novel software is like that. Let one penguin jump in and they all will follow.
Change is stressful for customers so unless they have significant pain, they are reluctant to do anything different.
So, yes, that is the strategy we are following, looking for a nice, preferably large and recognizable, customer who is willing to jump into the water. We have made quite a bit of progress, but it is also very slow.
2 comments
Running SaasRise, I've seen a lot of SaaS CEOs with a product that could power thousands of uses grow slowly until they picked one buyer with one painful problem and sold only that. For Reliath, the harness that keeps AI agents in check could be that first focus, since a compliance or risk leader immediately gets why answers drawn only from the company's own approved facts matter.
Yes, you're right. I compare it to Antarctic penguins. When they are hungry, they gather at the edge of their ice shelf and jostle one another. There may be Weddell seals below waiting to dine on fresh penguin. Nobody wants to be the first penguin in the water, but as soon as one penguin falls in, they all jump in. Selling novel software is like that. Let one penguin jump in and they all will follow.
Change is stressful for customers so unless they have significant pain, they are reluctant to do anything different.
So, yes, that is the strategy we are following, looking for a nice, preferably large and recognizable, customer who is willing to jump into the water. We have made quite a bit of progress, but it is also very slow.