288 - Strategic Advisors

As my team nears our next milestone, the real-time and scalable ICOM-based systems, along with 3 years of other feature integrations and major upgrades, the time to appoint a fresh Advisory Board is also approaching.

I’ve encouraged my team to consider people they’d like to nominate for our new Advisory Board and brainstormed on this topic with other colleagues, but I’d also like to offer this opportunity for collective intelligence to my network here on LinkedIn.

We’re looking for Advisory Board members who can:

• Contribute sound advice to approaching a myriad of promising verticals for deploying systems that deliver human-like, human-level, highly efficient, easily scalable, and recursively self-improving performance across arbitrary domains and complexity.

• Be responsible and ethical, working together to produce collective intelligence.

• Help make the world a better place each step of the way, bridging the divide between vision and reality by building that path from one to the other.

Note: We won’t be accepting any self-nominations.

I have lined up a list of people who’ve weathered the AI hype very well, candidates who I’ll likely be asking and giving demonstrations of our systems to in the coming weeks. Three of these people have already taken the step of connecting with me on LinkedIn of their own accord, Grady Booch, Bojan Tunguz, and Paul Burchard, with other noteworthy nominated names including Mary Lou Jepsen, Cassie Kozyrkov, Matthew Mayo, Richard Self, and Brian Behlendorf.

I’d also nominate Jaron Lanier if I could find a carrier pigeon able to reach him, as his name came up both in my own thoughts and was independently suggested by another.

As we deploy and begin testing and releasing new results of the first minimally complete 8th generation ICOM-based systems, looking to benchmarks including SWE-bench, SimpleBench, and more, things are likely to begin moving rather quickly. I’m also taking suggestions on benchmarks to target, specifically focusing on those where other models and systems score below 50%.

If OpenAI’s latest joke confirms anything, it is that we’re still far ahead of everyone else, even when the other parties burn billions on naïve attempts to compete. Our work was slowed down by all of the industry’s funding being redirected into dead-end technology these past 2 years, but we’ve continued to make progress, while they’ve continued to fester.

Who would you trust to give sound advice on this matter? How would they shape 2025?