Eduardo Ordax’s Post

I've been following your posts, and I always enjoy them. The limiting factor when push comes to shove is energy. And yes, general AI is the current race of the best model, forgetting that the hyper-exponential advancements are only as relevant as their adoption. Right now, there is a significant dissonance between the good old problem/solution fit (systems that address actual pain points based on GANNs GAIs) and how it's converted, presented, and communicated so the average Joe feels comfortable. Until then, it's like the analogy of the tree that falls in the woods, but no one (or the 4.5%) was there to hear it. Keep posting. You made a great post that outlines genAI use cases per vertical/industry. I still often refer to it to identify where the most exciting BUMPS (big, underserved, meaningful problems to be solved at scale). And one must not forget: people don't want AI—just solutions to problems.

How do you see SLMs evolving and creating their own space

Without a doubt, the ones who are selling the shovels in this Gold Rush are companies like Nvidia. From a macro perspective, the changing geo-political situation also becomes apparent. While once, the highest-valued product was oil, and hence, it monopolized. Very soon, it becomes nickel tantalum neodymium, dysprosium and other rare earth minerals (that can't be just whopped up with alphafold3, for example) and that monopoly is owned by a different player altogether—locations of the modern silk trade route. Something else: Blockchain, for example, is a technology. It's only when it's paired with an existing or new business model that it becomes of value. In the same way, AI will see more of this. Its true potential is in synergic integration with entirely unrelated areas. With that in mind. We are talking about winning bets. One could make the case that ALPH could turn into a winner. P/E Value, compared to lowest of S&P500 ATM. Severely undervalued. Perhaps, for correct reasons. Yet, ALPH's portfolio of moonshots (in longevity, genetics, robotics, mass-compute, material science) can switch things up. That said, we as a startup focusing on exactly what you mentioned, would rather talk to AWS to work together. 🫡

The projected growth of the Global LLM Market presents a significant opportunity for AI innovation, with analysts forecasting remarkable expansion to $140.8 billion by 2033. NVIDIA and Jensen Huang's substantial revenue surge underscores the critical role of compute power in driving advancements in LLM technology. However, to fully capitalize on this market potential, a shift towards smaller, specialized models tailored to specific customer needs is essential. This approach, championed by leaders like Mark Zuckerberg and Yann LeCun, ensures continuous improvement and relevance in an evolving landscape. How do you envision the future of LLMs shaping the broader AI ecosystem and transforming industries?

There is no race here. The race will be in predictive AI. Based on the above this llm isn’t a profitable business or the analyst haven’t figured out the killer app. Also nvidia money is …🤫