Tony Rost @raspberryman
Dedicated dad of 2 boys, happily married, and active foster parent. Global AI Practice Director @ Accenture (Logic V&A). ASI optimist. linkedin.com/in/raspberryman Portland, OR, USA Joined April 2009-
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@levie This seems to be describing industrialization. The non-differentiated will just disappear, same as spinning wheel operators, lamp lighters, and stagecoach drivers. OP article is musing on how wheelwrights can stay differentiated in the market.
@quxiaoyin Most are already leaning into LLMs for nearly every possible task - just need to improve the managerial plane and they’ll go just as quick as programming. Once firms bring data science back in house, many SaaS firms will face a renewal collapse.
While we debate USA v China and open model capability gaps, neuromorphic computing continues to mature and will disrupt the dynamics. It’s the hardware, folks, it was always the hardware. patsnap.com/resources/blog…
I suspect there are very few ways a purely feed-forward neural network could develop a valenced state (GWT is a strong candidate!) I also suspect there are many more ways spiking neural networks (SNNs) and similar architectures could. anthropic.com/research/globa…
Models have no moat; their intelligence is merely an ordinary, natural phenomenon in the universe. The big machinery used to bring us this natural resource has a moat, for a very short time.
Two years* until open-weight Mythos class models on smart phones, employee laptops, POS devices, cars and trucks, smart shelves… … and let’s be honest it’ll probably go faster. *estimate source is an musey Reddit post
Fable 5 probably running locally in about two years. That is the projection in this r/LocalLLaMA chart. It tracks how long it takes for cloud-frontier capability to become broadly comparable in laptop-runnable open-weight models. The observed average lag: ~24.8 months.
@quxiaoyin The second we get neuromorphic computing or the like, the disruption will be far grander than mere open/closed transformers. The gigawatt data center sits along side the room-sized computers of the 50s and 60s.
@alexolegimas Our Founding Fathers were in the anti-tyranny business. No matter what we do with that legacy, we need to strive to avoid tyranny.
@alexolegimas If you squint, we are already passed the AGI and RSI milestones in the timeline, and already far into the initial phase of societal superintelligence. From the field I can report than double digit percentages of the economy are being lift and shift to neoclouds right now.
@fchollet Information and energy are just waiting a few years until neuromorphic chips and fusion arrive. Unless you mean cosmically :)
@gabriel1 Only allow them to describe the results 12 months from today.
@leecronin I've seen >200 agentic workflows implemented in the F1000 that had a greater value than any automation technology that came before modern transformers. You might be thinking of a different sample.
@mignano Intelligence can’t be a moat because it is more like atoms or light - it’s just a natural property of the universe. Hard Infrastructure can provide a temporary moat until the singularity arrives.
@emollick System prompt should delegate: deciding which model to use for a subagent; how much verbosity is needed; and how many validator/QA subagents to use
The forward deployed engineers from the labs are aggressively engaged with thousands of businesses, directly converting licensed software token software. The roadmap coverage is exploding. The enterprise market is far more open to token displacement than I think people realize. Massive percentages of platform renewal money will divert to tokens in the next 16 months.
A solders last words to his dad instagram.com/reel/DaWX2_2gQ…
@kimmonismus I will say that the adoption rate across enterprises is higher than people realize, including for labor-shifting workloads. But agree with you on specific model names being less known.
@emollick OP underestimates the very broad adoption of agentic workloads by enterprises small and large. It’s a substantially higher adoption rate than cloud and SaaS were.
I love America. When I was a kid growing up in Idaho, I won a history competition by building an ANSI animation of the Battle of Lexington and Concord. To this day, those who work with me have heard my business analogies of various revolutionary war stories. I wanted to relive that old history competition, and asked AI to generate the image below. The image vibes with my memory extremely well. These gigawatt scale transformer models are absolutely stunning inventions. I know this may be cheesy but it really did charm me.
Vincent Murphy @brainstormvince
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