Artificial intelligence has unleashed a torrent of cheating on campus and created chaos in the job application process, as both students and employers use large language models: the former, to write hundreds of AI-assisted applications; the latter, to screen those AI-written applications with AI-written filters, thus removing from the process of finding a first job those procedural frictions sometimes known as "people."
It looks to me like OpenAI’s sandbox for this agent suffered from the (quite naïve) assumption that GET requests cannot be used to update data. That’s certainly how the web is supposed to work, but clearly there are applications that don’t hold to that contract.
everybody on your team who is making architectural decisions, those people must know performance and they must make decisions that will allow the other people downstream of them to use an architecture which can be optimized later. If you don't do that, you're just rolling the dice.
One of the things I found most exciting in the last couple of years was seeing as model qualities gotten better and and harnesses and tools have gotten better, how many people um that were directors or VPs or SVPs or any of these levels were actually rolling up their sleeves and trying things out.
open models are still incredibly useful, but fill a long-tail ecosystem relative to the closed counterparts that have monopoly ownership stakes in the most valuable areas like knowledge work collaboration, drug discovery, SWE, etc.
And in all of these applications, the customer is making a decision based off of the recommendation of the AI model more or less. Uh, and this means that if the customer is ultimately like kind of making the decision, this means that if the system makes a mistake, um, that's okay because usually the person can kind of recognize that or or decide what to do even despite that mistake.
Then you had code review which gave you another level of feedback. You could roll out internally more frequently. And everybody was using Facebook for all kinds of stuff, personal and internal business stuff. So whatever feature you developed, people would start using it immediately. So you get another round of feedback. Then we had this phased roll out process where you'd start rolling your stuff out. If there was a problem, the blast radius would be limited to a a few million people.
In truth, rather rapid electrification projects, without decade-by-decade continuity, exist outside the UK and are often quite reasonable in their costs, as in Denmark, Israel, and especially India.
local-first software, which is this idea that we want to take away a bit of the power from cloud operators and give it back to end users. So, end users should be more in control of their own data and less dependent on cloud services for providing the applications and the data that that the users need.
Our market reach is far greater than any any TPU can any ASA can possibly have. And so if you look at our position, uh we're the only company that that accelerates applications of all kinds.
Furthermore, I believe it’s very unlikely that space-based manufacturing or mining could be lucrative enough to fund the venture.
Their words now
Today, exploding demand for power-intensive AI applications provides enough of an upside to justify producing components in space, providing the economic engine necessary to justify and fund the trillions of dollars necessary to build and sustain space factories.
When applications can generate capabilities on demand, the definition of "what this product does" becomes more fluid. Features aren't just what shipped in the last release, they're also what users will ask for in the next session.
we will build our own applications scaffolding which will be model forward right it won't be a wrapper on a model but the model will be wrapped into uh the application
It's also worth noting that chat isn't the only way to integrate AI in software products and increasingly agent-based applications outperform chat-only solutions. So expect things to keep changing.
Yet the production methods still can’t make them below $10 per gram, so they’re still not cheap enough for some “obvious” applications like preventing kids getting malaria in a rainy season.
I moved from Alacritty to Ghostty, which has been absolutely excellent. It’s wicked fast, it has my favourite colour scheme built in, and I just love the way @mitchellh has set the project up for success in the long term. It also fits in nicely with my minimally configured applications, with excellent defaults out of the box.
The Social Network is substantially made up, more a source for vibes rather than a source for facts. Even the vibes fail to cohere with reality. And yet it convinced many proto-founders to put in YC applications.
If the future is like the past, this implies that debt rollovers—that is, the issuance of debt without a subsequent increase in taxes—may well be feasible. Put bluntly, public debt may have no fiscal cost.
Their words now
Across advanced economies, the celebrated ( r - g ), i.e., the difference between the interest rate and the growth rate, appears to have durably changed sign or, at a minimum, to have gone from a substantially negative number to a number closer to zero.
computers are fast enough that high-traffic apps can be served with simple architectures, which can generally be created more cheaply and easily than complex architectures
Despite these advances, contemporary physical and evolutionary-history-based approaches produce predictions that are far short of experimental accuracy in the majority of cases in which a close homologue has not been solved experimentally and this has limited their utility for many biological applications.
Other applications I use frequently: 1Password, Slack, PureVPN, Photoshop, LICEcap (for creating screencaps to be shared with teammates or added to GitHub PRs, particularly for UI changes).
Other applications I use frequently: 1Password, Slack, PureVPN, Photoshop, LICEcap (for creating screencaps to be shared with teammates or added to GitHub PRs, particularly for UI changes).
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