dereg
Old man me thinks “$390 million? How are they funding this?! That seems like a massive sum of money to throw down the drain every 20 years.”
Then I did the back of envelope math. Assuming 20% comes from donations, then all you’d need is a $380m fund earning a real 3% to fund the building of the next temple. That’s very doable.
From a financial perspective, there are many ways you could enforce checks to ensure the model is balanced - it just takes time. Data entry can be an issue, but you can automate that too. The deloitte report is saying the health department should benefit from adopting a gigantic erp system but you could get 90% of the benefit by employing a couple people that really know what they’re doing.
You could say that excel should allow those things to happen but the flexibility is precisely what makes it so valuable.
The people writing the reports are consultants. Consultants recommend things that benefit consultants. In their case, a multi year process and tens of millions of dollars trying to install ERP software is more a windfall for the vendors and not the companies.
It took almost a decade but the PA Semi acquisition showed that Apple was able to get out of the shadow of its PowerPC era.
Nvidia will remain a leader in this space for a long time. But things are going to play out wonky and Apple, when determined, are actually pretty good at executing on longer-term roadmaps.
I think the private compute stuff to be really big. Beyond the obvious use the cloud servers for heavy computing type tasks, I suspect it means we're going to get our own private code interpreter (proper scripting on iOS) and this is probably Apple's path to eventually allowing development on iPad OS.
Not only that, Apple is using its own chips for their servers. I don't think the follow on question is whether it's enough or not. The right question to ask is what are they going to do bring things up to snuff with NVDIA on both the developer end and hardware end?
There's such a huge play here and I don't think people get it yet, all because they think that Apple should be in the frontier model game. I think I now understand the headlines of Nadella being worried about Apple's partnership with OpenAI.
They tried the case in New York but it got thrown out for lack of jurisdiction. They did try the case in Germany, but Porsche had fittingly cornered the market for the best and biggest law firms. All of the best law firms refused to take the case because it would mean that they’d be essentially blacklisted by the largest companies in Germany for bringing a case against a German company.
It’s taken a decade, but I now see a pattern.
Assuming these two things are related, if I may editorialize just a tiny bit, I am a little annoyed at how much their rollouts often disrupt service for paying customers. Paid users being impacted by free user rushes really sucks, but is understandable. API developers being impacted by free-user rollouts is unacceptable, and especially sucks for those who have to answer to users of their own.
I suppose this is a wakeup call to migrate to Microsoft's Azure endpoints which, presumably, aren't affected by the current outages. But I'm fully tapped out in terms of yet another service's application and vetting process.
So to connecting it back to the current drama, while I support OpenAI, their employees, and Sam's return, I can understand why folks like Helen would be miffed by management's approach to building. I'm not saying they should slow product development, but would staged rollouts hurt?
Dealing with folks like Ilya isn't necessarily a matter of if, but how much.
I don’t consider anybody beyond forgiveness and if Ilya takes a professional lesson from this and Sam learns to be more mindful of others’ concerns, I consider this a win for all. Starting over in a new entity sounds great but would be years of setback.
I hope they work this out.
[0]: https://exiftool.org
I believe that 1Password has grown significantly in the professional space, and that Okta likely sees this trend as a competitive threat.
If there's anything that Apple's upending of Blackberry taught us, it's that all you need is a one key decision maker in an entire organization to say "wait, why can't I use {product x}?" for that organization to slowly move away from the entrenched enterprise solution. The fact that Okta is joining the consumer space validates 1Password's decision to creep into the enterprise market.
Solutions emerge in my head as I sleep, usually after a day of brute-forcing a problem so much that it spills over into my mind's eye during breaks, which spill over into my dreams, where glowing forms congeal into solutions.
I recently read some comments here about people having vivid dreams of playing Tetris. That's exactly how my dreams feel, but in mine, I see either code, foreign languages, or a spreadsheet. Extending your gym analogy, it's like hitting your PR the day after going all-out on volume training.
OpenAI's developer relations person confirmed it a little whiles back:
> [..] I made the comment elsewhere, but the models are always changing in ChatGPT.
https://twitter.com/OfficialLoganK/status/166447707026357043...
{
"slug": "gpt-4",
"max_tokens": 4095,
"title": "GPT-4",
"description": "Our most capable model, great for tasks that require creativity and advanced reasoning.",
"tags": [
"gpt4"
],
"capabilities": {},
"product_features": {}
}
There are two conclusions I took from scanning through this and trying to reproduce a few of the reported failures.
1. The author is bad at prompting. There are many ways to reduce hallucinations and provoke better thinking paths for the model.
2. The author is using ChatGPT's GPT-4, leading him to conflate "GPT-4" with "ChatGPT". While you can consider this a shared failure with OpenAI, due to OpenAI's poor communication, anybody doing serious work evaluating these models would know that the first thing you need to do is use the API and pin the model version. In the author's case, he should have used gpt-4-0314 or gpt-4-0613. What I suspect he did is that he just used ChatGPT's GPT-4, and likely the default model at that. (Nobody should ever use the Default model. It's their most heavily performance optimized model and performs worse on reasoning tasks than the Plugins model, even on within-context-size tasks.)
There are huge problems with that, because OpenAI has done both a ton of fine tuning and performance optimization continuously on the default ChatGPT model over time that its performance has ranged anywhere from "I'm pretty sure this is gpt-3.5" to "whoa, this is damn good" (the latter being mostly the model at launch, which was probably the same as gpt-4-0314).
If the author has been working seriously at evaluating models, specifying the model is the first thing he'd do. Perhaps he should explain his reasoning.
For instance, a country that accepts more lower-skilled immigrants will see its median income figures grow less than those who accept fewer of those immigrants. Is the country with more immigrants poorer as a result?
The only way that median income would be a valid measure of wealth or quality of life would be if you isolated the cohort of those considered "median" in 2008 and tracked their wealth over time.
..Then I actually used langchain. I was shocked at how poorly it performed compared to my same solutions. Some operations took 10x longer than how I did it, and all the while producing worse results. As tempting as it is to just roll with langchain from day one, I'd highly advise against it. Think deeply about what you're actually trying to accomplish and instead of just injecting langchain in the middle of everything as this messy, amorphous glue code thing .