I've been thinking hard about this paradigm shift while thinking about ideas for things to "vibecode"

I started by trying to think about ways of running a vending machine company autonomously using a finite state machine + agents. It turns out most of "automating" a vending machine company doesn't need LLM agents at all, and simply buying machines with reliable telemetry + a database + automated inventory could get you much further than replacing every or even some components with an LLM. The LLM could replace the person on the phone texting the laborers who refill and service the machines, perhaps autonomously order refills (but hey so can a cronjob).

The troubling thought I had is that AI does not displace the technicians, or the vending machines. It replaces the manager. The human manager is the component that is unnecessary. The entire global economy can eventually reflect this reality where most of the wealth is technically owned by humans but where the majority of financial transactions and decision making will be done by machines (at a level not yet seen)

Macroeconomic metrics will go up along with wealth and standard of living, but for actual flesh and blood humans, much of this will be irrelevant.

Fun fact, he almost got the worldwide console rights to Tetris back in the 80s, and tried going to Soviet officials to get those rights. To the point he's the antagonist of a recent "Tetris" movie that came out.

VideoGen models have to have decoder output heads that reproduce pixel level frames. The loss function involes producing plausible image frames that requires a lot of detailed reconstruction.

I assume that when you get out of bed in the morning, the first thing you dont do is paint 1000 1080p pictures of what your breakfast looks like.

LeCunns models predict purely in representation space and output no pixel scale detailed frames. Instead you train a model to generate a dower dimension representation of the same thing from different views, penalizing if the representation is different ehen looking at the same thing

Wang fits the profile of a possible successor ceo for meta. Young, hit it big early, hit the ai book early straight out of college. Obviously not woke (just look at his public statements).

Unfotunately the dude knows very little about ai or ml research. He's just another wealthy grifter.

At this point decision making at Meta is based on Zuckerberg's vibes, and i suspect the emperor has no clothes.

That's such a terrible take.

For a hot minute Meta had a top 3 LLM and open sourced the whole thing, even with LeCunn's reservations around the technology.

At the same time Meta spat out huge breakthroughs in:

- 3d model generation

- Self-supervised label-free training (DINO). Remember Alexandr Wang built a multibillion dollar company just around having people in third world countries label data, so this is a huge breakthrough.

- A whole new class of world modeling techniques (JEPAs)

- SAM (Segment anything)