finally found time to make a new video! https://t.co/uuRpjRGd5g this time i'm sharing a slightly more advanced agentic engineering session, focused on high throughput multi-tasking hope you find helpful!
Strong liability enforcement could be helpful in the AI debate. If your agent swarm goes rogue, you’re liable. If your weakly protected model gets jailbroken, you’re liable. If you serve a weakly protected OSS model, you’re liable.
I think the way that you'd measure conjecture generating ability is going to be more subjective on like that tone shift where um it'll be mathematicians saying they're not just using it to like solve their problems, but as they step back and decide what their research field should even be that a conversation with such and such model like was genuinely helpful for that.
a more relevant metric in the long term is the cost, not the efficiency, of food production methods at sustainable levels of energetic and material throughput.
Even for back end, it can be a problem because if you have a request incoming right when it checks all of your objects like you have some sort of latency spike where you it takes much longer to to reply. So that's one of the reasons it can be helpful in in back end as well.
They could release claw slow mode and have an increase in tokens per dollar by a significant amount. Um they could probably like reduce the price of Opus 46 by you know 4x 5x and reduce the speed by another by maybe just like 2x like the curve on inference throughput versus speed is there already just on hm um and yet they don't um because no one actually wants to use a slow model
Number three, I think it would be really materially helpful if the power of the most powerful super intelligence was somehow capped because it would address a lot of these concerns.
the improvement software improvements of really throughput in terms of tokens per dollar per watt that we're able to get uh you know quarter over quarter year over year is massive uh right so it's 5x 10x maybe 40x in some of these cases
One interesting point is that, in China, you ask the companies to innovate first, and then you regulate after, right? So, that has led to things like P2P platforms. It’s led to lots of kind of financial innovations, some of which has actually been very helpful and good, some of which had been disastrous, but the intention to regulate after the fact is to really not slow down or hinder the innovation. This is a very different approach from Europe. You regulate first, and then companies have to work around that.
Opaque, inert and obstructive elements might occupy the same place as full-screen command line interfaces — a powerful niche UI that was a marker in history, passed on by the windowed environment of the multi-tasking, graphical user interface revolution.
Josh Hardman at Psychedelic Alpha provided a detailed live account of the advisory committee meeting, which I found very helpful in developing a more granular sense of how the meeting unfolded without having to watch it myself.
Mestre and Docktor tackle this challenge by reviewing the large body of literature on learning physics. I plan on writing a full review of their book, which I found to be a helpful summary.
For example, large language models can generate outputs that are untruthful, toxic, or simply not helpful to the user. In other words, these models are not aligned with their users.
I wouldn’t say that this is the most compelling book I’ve ever read in terms of the prose style or storytelling, but it does provide a very helpful, almost quantitative overview of all the potential threats looming out there
This is the book that started the Lean Startup movement. While it is not an easy read, it is packed full of good information and helpful charts and guides.
If your company is struggling because your initial idea isn't working, this is the book to read. It provides a great blueprint for thinking through pivots for your business. As oneforty was considering pivots in Fall 2010, this book proved very helpful.
Hamming was a practitioner, spending much of his career in Bell Labs, so unlike many books on probability, this stays grounded in the kind of intuitions that come up a lot in solving practical problems. It has countless helpful puzzles and problem-solving tricks which are organized in such a way as to give a sense of the deeper theory underlying probability and statistics.
As the title suggests, this offers a highly pictorial introduction to complex analysis. I would not use this as the only text to learn about complex analysis, but Needham does a marvelous job of conveying the beauty of the subject, with numerous helpful intuitions for otherwise famously tricky ideas.
Another text with a titular promise to focus on pictures, this one tackles a subject which is more commonly taught purely symbolically. One of the most important things for any student learning about groups to understand is just how many different ways there are to think about a group, and how different views might be helpful in different contexts. Again, I wouldn't use this as the only book to understand the topic, but it offers a refreshingly different perspective on the topic from most others out there to help arm your arsenal of intuitions.
I use Scrivener to draft my novels. Since these novels regularly go over 300 thousand words and take multiple years to write, Scrivener's organization capabilities have been really helpful. It also syncs seamlessly between all my devices.
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