I'd be curious to learn more about how/why executives come to sign their names to this kind of writing. Maybe it feels like a natural iteration of the pre-existing experience of signing one's name to an assistant's manuscript, or a press release from staff in Comms? I don't know execs who do this kind of thing, so would be grateful for any observations others might be able to share (anonymously or otherwise).
Aside: I think it would be very good for the culture if HN automatically ran Pangram on any text-centric articles. Even perhaps just those which hit the front page? I have my own browser plugin, of course, but judging by comments here, at least some seem not to notice?
At risk of greatly oversimplifying American politics, it's truly impressive how good Democrats are at shooting themselves in the foot. That's why I personally believe Sanders and Mamdani have found so much success with the working class; they keep themselves separate from the Culture War slugfest that mainline Democrats either voluntarily engage in or let Republicans drag them into. IMO the vast majority of those "cu…
It’s very difficult to be for the people and also get hundreds of millions of dollars from wealthy donors. That is the democratic party’s plight.
I'm not sure I understand what part of my post this is in reference to. I agree that the democratic party gets a _lot_ of money. Are you contrasting to something in my post, or agreeing?
Appreciate clarification, I could also just be dumb today
Perfected multi-touch touchscreen Before that we had touchscreen but they sucked. --- 2002: FingerWorks makes advances in multi-touch technology 2005: Apple acquires FingerWorks and its patents 2007: iPhone launches
I really don't think multitouch is what made or broke the original iPhone.
Speculation: open models is what will kill Anthropic and OpenAI. Hyperscalers can run the models without a licensing fee. Apple can make them smaller and put them on the device. The frontier models are an edge and a liability. They're astronomically expensive to train. Without them, their models will fade into obscurity. Their marketing depends on people believing the models are meaningfully different, as people have…
Are frontier models actually astronomically expensive to train? GLM 5.2 was trained on ~30T tokens, so ~10^25 FLOPs. Say you get B300's for $5/h (pretty high), and you get 50% MFU; that's ~$15M. Of course there's also a bunch of risk that the training itself goes badly, post-training, etc. But still, compared to the inference spend after, it's not that crazy.
One big difference is that the US doesn't have much public record of using state espionage resources to steal industrial secrets to give domestic industry a leg up in the market, whereas CCP very much does. And while I use and love the open weight models, it seems likely to be pretty hard to prove conclusively that they have no reinforcement-learning-trained proclivity towards curling specific URLs if the topic happe…
I don’t think US companies could ever fully trust models sponsored by foreign adversaries. How would you ever verify they are safe? Provenance of training set is going to be critical. It’s largely ignored now, but the first time a malicious exfiltration occurs it will go off as if a bomb was detonated.
Only way would be an actual open source model: code + training data
Yes, the problem with comparing open models to open source is that open source requires humans to volunteer their time. Open models requires humans to volunteer their money. These two types of contributions have very different behavioral profiles, and it doesn't obviously follow that the historical success of getting people to collaborate socially on building software for fun and for the benefit of the community will…
The biggest hurdle is whether humans volunteer their expertise. Not time or money. We need top talent to make the open models. Sponsorship is plentiful. Open source volunteers are less critical with LLM doing the grunt work. Its about talent contributing to the open
This is not my experience working in the field the last 8 years. There is not a dearth of talented researchers, engineers, etc. who are willing to contribute to open models. Just look at the ecosystem generally, from academia to industry. So much research still happens in the open, and the open source community in ML is still massive and energetic.
Training a new frontier model just costs a lot of money and there are very few companies for whom it makes sense to do so, and even fewer orgs who are just going to gift those kinds of resources to an open source initiative.
Apple and Google (via smartphones) are in literally everyone's pocket. Running KIMI on a phone is not possible today and I agree with you that it will "probably be years before..." it is. But how many years do you guess? I personally do not think it will take even 10 years for the situation to be commonplace.
> I personally do not think it will take even 10 years for the situation to be commonplace. Do you personally remember how far smartphones progressed in the past 10 years? It's not as long a time as you think it is, the limits of what a smartphone GPU is capable of did not substantially change in that time. Nor did the amount of onboard RAM that we include in the package. This is true even for Nvidia's ARM SOCs, fran…
Only if you narrowly define AI as talking with a chatbot. Today, on an iPhone, there are a number of features that only work due to some sort of a model running locally. OCR and intelligent object selection in a photos, and summarization of texts are local models running on the iPhone hardware, they're just not a chatbot. Yes, there's also cloud backing various features, but the idea of running models locally isn't foreign to Apple. On Google's side, the Pixel 10 Pro is powerful enough to run quantized local chatbot models locally today. Local translate is a model, and has been for a while. Both corporations are going to sell whatever customers are willing to pay for, in money or via ads, and if local models get good enough that customers actually are willing to pay for it, I have no doubt that it's Apple and Google will go that direction. It's Google that's releasing Gemma models for download, and they're a big enough organization that the left hand doesn't know what the right hand is doing, so the one conspiracy theory that they'll never do local models because they only want to profit off hosted models is too simplistic.
Speculation: open models is what will kill Anthropic and OpenAI. Hyperscalers can run the models without a licensing fee. Apple can make them smaller and put them on the device. The frontier models are an edge and a liability. They're astronomically expensive to train. Without them, their models will fade into obscurity. Their marketing depends on people believing the models are meaningfully different, as people have…
I hope so, but I am not holding my breath. OpenAI and Anthropic have too much money riding on them. I'll be surprised if they die.
I think (and have heard) the Chinese govt is also interested in trying to embarrass the US as well by showing off their capabilities (so there's a political angle, too)
All countries see AI as a geopolitical concern. An open source strategy is smart. It’s effective and also builds good will / soft power. Many see Chinese AI companies as the good guys and root for them. I’m pro open source and also celebrate but still aware this is most likely just the means to an end. I used to work at Mozilla. I think we are missing a player in the market with a more principled open source approach…
And who might that be, I wonder? The company that seems more worried about executive bonuses than to adhere to its mission, for at least a decade now? Perhaps a certain one whose name starts with M and ends with ozilla?
The prose is, of course, LLM-generated. https://www.pangram.com/history/29a71663-e6b2-4db6-87bd-b943... I'd be curious to learn more about how/why executives come to sign their names to this kind of writing. Maybe it feels like a natural iteration of the pre-existing experience of signing one's name to an assistant's manuscript, or a press release from staff in Comms? I don't know execs who do this kind of thing, so…
I agree that it would help the site a lot but Pangram is notoriously inaccurate.