The intersection of investors who understand what it takes to build a game engine and also the capabilities and plausible future capabilities of Google’s model is practically zero.
The tail of the distribution justifies the entire distribution. I agree that a large percentage of PhD research is inconsequential, but a small percentage is massively consequential. It’s ok to whiff on a thousand STEM PhDs if you pick up one Andrej Karpathy (for example).
The number of people capable of identifying potentially consequential research is smaller than the number of people performing consequential research. And they’re all busy with their own projects.
Maybe this is true for academic institutions granting the PhDs (although even this I am skeptical of, training a PhD costs a lot in terms of time, money, and human effort). But that doesn't mean it implies that the federal government needs to employ a thousand STEM PhDs just to get someone like Karpathy - indeed, Andrej Karpathy does not work for the federal government! He made his name working in the private sector!
Maybe, let's see if AI overall is a net positive or net negative to the US overall. If AI turns out to be a net negative (which seems likely) maybe we don't want this type of AI research being funded by taxpayers.
Like $40k bonuses for ICE agents. Incidentally, $40k is about the stipend for a typical PhD student. I'll take a smart student doing nothing but eating food and digesting theorems over the absolute chaos that is being funded by our tax dollars.
There’s more to AI than foundation models. I think you are going to see meaningful progress on chore automation over the next decade through a combination of algorithmic and mechanical improvements, and it will measurably improve our lives. Recently got a Matic robot (awesome btw), and I no longer feel the need to vacuum my floors. It’s not life changing, but it’s an appreciable convenience upgrade. The capabilities feel like a peek into the future.
The customer service is better. Rates are generally way better. The downside is generally their phone apps and their fraud departments. I had a lovely credit union but their CC was basically unusable because they hired some crummy and over aggressive fraud detection third party that would lock down my card any time there was a strong breeze.
Their tool code use makes a lot of sense, but I don’t really get their tool search approach.
We originally had RAG as a form of search to discover potentially relevant information for the context. Then with MCP we moved away from that and instead dumped all the tool descriptions into the context and let the LLM decide, and it turned out this was way better and more accurate.
Now it seems like the basic MCP approach leads to the LLM context running out of memory due to being flooded with too many tool descriptions. And so now we are back to calling search (not RAG but something else) to determine what’s potentially relevant.
Seems like we traded scalability for accuracy, then accuracy for scalability… but I guess maybe we’ve come out on top because whatever they are using for tool search is better than RAG?
I’d have to guess that new startup founders are building leaner teams leading to slower burn rates and longer run ways. That has value. I think share skepticism is warranted is whether or not old behemoths can retrofit AI efficiency gains into their existing organizational structures.
Anyone know what the deal is with connectors? I don’t see them in the app and they made it sound like Google Calendar would be made broadly available as a connector.
Being fully leveraged is great for capitalism and horrible for your mental health and general well being. Ever live under crushing debt? It’s awful. Step back for a minute and look at the big picture. People are taking on debt to eat lunch. That’s insane. The author acts like it’s zero sum and if BNPL isn’t the one offering the short term loan someone else will at worse terms. That’s just not true and hand waves over the fact that people who are uneducated are unwittingly being coaxed into making bad decisions with glittery UX and one click checkout.
