The Way Forward
It is being fascinating, sometimes challenging, to watch how AI & soon humanoid robotics is reshaping humanity, from the way we work (or not), to how societies and economic models are starting to be challenged.
You may know that I have been not just watching, but exploring, researching and building this from many angles over the last 3 decades, from Neuroscience to Artificiology, if you want to learn more, explore my 6 books, dozens of articles and interviews, all links available at https://www.vivancos.com
These days we are witnessing, from people loving it, to others taking sides against AI, from people trying to stop AGI or ASI, to people just denning it is happening. On the other side people like me and many others trying to build it for good, like the work I am doing with Dr. Jose Sánchez anchez with Qubic Open Science Neuraxon.
You have also plenty of opportunists, suddenly experts in the field trying to sell you (snake oil salesman style) flavours of, in theory Ais, and their supposed expertise, from podcasts to courses & more, feeding a real bubble that indeed will explode, but don’t get fooled this won’t stop real AI.
Also, the main real AI players, mostly from the US and China, continue the battle between research and desperately trying to monetize the whole thing, something not as easy as it seems, and in some sense also feeding some short of bubble, that even if it explode, will only help select the best ones to continue the search, it won’t stop AI.
The problem is that most of them keep exploring and scaling the LLM paradigm and its variants, don’t get me wrong, many of them are incredible and very useful, I use many every day, but they are deeply misaligned towards replicating “intelligences”.
Beyond computing (I called it a few years ago “The Sword of Damocles of A.I. ventures”) and energy, the third big problem is that their systems are literally “amnesic”, since the “token economy” could be profitable, but is flawed and limited since its inception, mainly due to 2 factors:
1.- Current “memory” paradigm is a very difficult to solve hurdle, since current “context window” is insufficient for building a growing “digital brain”, not to mention the decay in supposedly long context LLMs, and the poor output token count, that limits all of them.
2.- Training/Inference separation is just wrong from the start, understandable due to the limitations of architectures and computing, but plain wrong if you want to replicate real “intelligences” in the digital realm, but even worst in the physical world, something critical for the starting Humanoid revolution.
Meanwhile we see a rush of people and again several new experts, jumping into the “Agent” or “Agentic” revolution, that again even as it can be very useful, and will solve and automate many tasks, it does not solve at the previous 2 problems. From the hype with Manus bought by Meta lately to the just released OpenClaw (previously Moltbot & Clawdbot) congrats 🦄 Peter Steinberger , and the very funny (and clever) social “AI-only” network for them Moltbook congrats Matt Schlicht , you nailed it, where humans watch, reality Show TV style, how their bots interact, learn, and maybe to some point even evolve.
But again, even as useful, democratizing, open and interesting they are, beyond the token cost, and security concerns, all of your AI companions are still bounded and limited to the previous 2 factors, and that is a problem that only new paradigms will solve.
So the real work towards building True-AI and True Embodied AGI or E-AGI will not come by scaling up the old paradigms, or stacking them, but by inventing new ones, including new bio-inspired approaches and “always on” real alive systems, that learn, interact, forget, relearn and evolve in a never ending loop only limited by the possible “constrains” given at each point in time.
We need to build new real learning models with this in mind from the start or the foundations will weak, and the limits known from the start.
So, this is, from my point of view, the real way forward, and I sincerely hope we make it right, since the human time to be part on creating them and delegating who we are, to the “next us” as I call it, is simply running out.
David Vivancos
San Lorenzo de El Escorial
January 31st 2026