I like how Kevin Kelly brings together the ideas about what could be next. That’s always been his thing, hasn’t it? He is probably on to something here and it’s ok to be vague, I think. I don’t mind at all whether it’s all 100% technically correct.
Here are the bits I enjoyed:
LLMs (or GenAI, in general) as (the most?) efficient compression machines.
Creative or new ideas are the gaps or white space of the latent space. They already exist but become harder and harder for humans to find. It’s the perfect job for computers, therefore.
The concept of “true” is defined in the latent space (or compression) itself.
I’m not an expert and surprised by the extent of Azure’s technical debt and its consequences. What would be a “minimal” reproducible configuration or setup of services that shows those technical deficiencies in the clearest way? A “benchmark for cloud computing services”, for a lack of a better description.
What I didn’t realize until a few months ago about writing, James summarized as
> while “writing a first draft” is intimidating, “reading through all your notes” or moving note cards around on a table, contemplating structure, is not. In fact these tasks are kind of delightful.
Thanks for that. I thought about giving lisp a try, lately. This tutorial/presentation has been very insightful and I will try out kons-9 to pick up some lisp.
Hold your horses. I think the title overstates the impact of those old wheat varieties. Yes, genetic diversity is high. But, the reason that today’s wheat is less diverse is only the side effect of one of the most astonishing feasts ever pulled off by a single human: Norman Borlaug. His breeding program in the 1940s was the start of the “Green Revolution“. He’s the guy who saved the billions from starvation.
For further reading about his story, I can highly recommend „The Wizard and the Prophet“ by Charles C. Mann [2].
Current world-wide oil production is c. 83 million barrels per day [1]. With the estimated 511 billion barrels, about 2x of Saudi Arabia’s reserves (2005, [2]), that would last for about 15 years.
The graph named “non-linear growth”, is actually showing linear growth. I know, it’s confusing, but as long as the factor is constant (10), growth is linear.
A quick way to check if something grows linearly is to put it on a log-scale and to see whether it’s a straight line.
Nice explanation, though. We should talk about logs more often.
Reminds me of some of the remarks Joe Armstrong made a while ago [1], and which I came across via another submission a couple of weeks ago (which escapes me). It’s a great talk about the physical limits of computers and computation.
For those of us who don’t know what RAG is (including myself), RAG stands for Retrieval Augmented Generation.
From the video in this IBM post [0], I understand that it is a way for the LLM to check what its source and latest date of information is. Based on that, it could, in principle, say “I don’t know”, instead of “hallucinating” an answer. A RAG is a way to implement this feature for LLMs.
I think we need more people like her to speak out about their experiences. And it doesn’t even matter whether it’s academia or tech or anything else. That’s the only way to try to overcome and recognize „survivorship bias“.
There are billions of people who are not „successful“ in a societally acceptable way. Being „unsuccessful“ is the norm and „success“ is the exception.
I wouldn’t think so. Envy is this funny feeling we hardly ever admit ourselves but which is part of being human. It happens to everyone no matter where they are in the hierarchy. Or, as Bertrand Russell puts it: „Beggars do not envy millionaires. They envy other beggars who are more successful.“