calebkaiser

4 ms·

1.
by calebkaiser 6d ago
Yeah I'm actually less hesitant to try out Google open source projects than I am new Google products. I have no idea if this is accurate or just my impression, but I feel like I've been burned by the "killed by Google" m
2.
by calebkaiser 6d ago
I think this is basically the motivation behind MCP servers, so you're in good company. But I've spoken with many people at companies who've decided to add an in-UI agent to their apps, and I don't think this trend will
3.
by calebkaiser 7d ago
Jev seems pretty cool! I just got access and have only gotten to do minimal experiments, but I love this general area of research and it fills a very real need. I agree with you. I think the OPs pushback is emblematic of a larger reaction I
4.
by calebkaiser 7d ago
This is also a really common thing in ML specifically. We joke about getting Schmidthuber'd, which is when Jurgen Schmidthuber (sometimes correctly) announces that he or one of his colleagues actually proposed your thing 37 years ago i
5.
by calebkaiser 7d ago
I understand the distinction you're drawing, but in my experience, it gets a lot blurrier as a project evolves. Caveat that I use LLMs all day and have for quite some time, so I'm coming from a positive perspective. The danger for
6.
by calebkaiser 7d ago
I think about this a lot. I started my teenage-to-young-adult life in the literary world as a poet who loved programming, and made a living as a ghostwriter. At some point, I fell in love with mathematics and wound up in ML in research&#x2F
7.
by calebkaiser 15d ago
Which hyperscalers are doing that? I've heard of one startup trying this, XFRA, currently in early pilot phases. But I'd be pretty surprised to hear that AWS or Google are paying people to host GPU clusters in their home.
8.
by calebkaiser 16d ago
Yeah, in essence. This is actually a pretty cool part of working in Lean. It's a somewhat normal convention to write something in a human readable way and then write a second optimized implementation with some kindness of correctness t
9.
by calebkaiser 16d ago
I'd wager that the vast majority of the ML research community, especially anyone interested in "AGI", is familiar with Hofstader's work. And I don't think anyone working on contemporary language models would argue t
10.
by calebkaiser 21d ago
Love seeing projects like this. The performance benchmarks are nice to see. Have you done any benchmarks against approaches like OpenAI's Symphony for things like token usage or task completion?
11.
by calebkaiser 22d ago
There will be companies doing this. I'm saying the labs are well positioned to be those companies, as they effectively are those companies right now. The same dynamics that define the public cloud ecosystem are at play here. What AWS s
12.
by calebkaiser 22d ago
I support and use open models as much as possible, but I'm not totally convinced that OAI or Anthropic have no moat, even as open models catch up to the frontier. Serving and inference are still hard problems when you're talking a
13.
by calebkaiser 25d ago
I haven't read this in depth yet, though I plan to. If this general line of research is interesting to you, I'd recommend checking out some of the lines of research it touches upon--they're really rich and fascinating, and so
14.
by calebkaiser 25d ago
It gets extremely blurry, because people commonly refer to any model that uses a component associated with the Transformer architecture as a Transformer (i.e. using some kind of QKV-esque attention mechanism). I think it's easier to th
15.
by calebkaiser 1mo ago
I think maybe just click around Huggingface's site a bit? They don't run a compute-intensive business on low monthly plans. You're describing frontier labs that sell access to their enormous models with subsidized subscriptio
16.
by calebkaiser 1mo ago
I just feel like you're saying things based on a general vibe about "AI companies" but didn't pause to look up the particular company being discussed. Huggingface reached profitability 2 years ago. They've reportedl
17.
by calebkaiser 1mo ago
I'm curious why?
18.
by calebkaiser 1mo ago
It's not too dissimilar from GitHub, but geared towards ML. They have a 9/mo pro plan for individual users for upgraded storage/usage, and an enterprise version of Hub that larger orgs can pay for. I think the enterprise has
19.
by calebkaiser 1mo ago
Solid point. I'm sure Nvidia went into this deal expecting completely flat growth and no other benefits to their core business. Sorta like how Meta never increased Instagram's revenue from $0 and is still waiting for it to pay off
20.
by calebkaiser 1mo ago
Yeah, great point. Nvidia could potentially be overpaying. Not sure how that equates to Huggingface being "a file download mirror with a couple of side features dangling off".
21.
by calebkaiser 1mo ago
I dunno. You can argue over whether they're overpaying, but it's not like Huggingface is Clinkle. They hit $150 million in ARR this year, they have tons of runway, and according to reports, have just started to even burn the money
22.
by calebkaiser 1mo ago
They hit 150 million in annual recurring revenue this year. Pretty nice dangling side features apparently.
23.
by calebkaiser 1mo ago
What? Both of those companies absolutely serve LLMs, and both of them would love for serving LLMs to be an even bigger part of their business. Not only that, AWS is Anthropic's primary compute partner for training and inference. They l
24.
by calebkaiser 1mo ago
Google rolled out TPUs in 2015. AWS released Inferentia and Trainium chips in 2020. If companies working on ML-specific chips was evidence that large transformer models have fully saturated their potential, the field would have been done ci
25.
by calebkaiser 1mo ago
Sorry--I was unclear. I was specifically responding to the OP's "CEOs these days want to join the AI hype wave" claim. My point was that the "hype wave" OP is referencing is really about deep learning, not what we t
26.
by calebkaiser 1mo ago
1. That's not what progression-free survival means. 2. I don't think AI was mentioned once in this press release. 3. This drug was approved for trial in 2014, so if it had something to do with deep learning, that would actually be
27.
by calebkaiser 1mo ago
I dunno. There is a lot of valid and interesting criticism to write about digital marketing. Lots of people have attempted to study the efficacy of digital advertising, and I'd love to see a deep dive into the "MarTech" ecosy
28.
by calebkaiser 2mo ago
It's a totally reasonable question, and one that everyone asks when they're learning about CUDA. The frustrating answer to your last question is that lots of companies have shipped GPU dev environments that can theoretically be us
29.
by calebkaiser 2mo ago
So OpenAI would be proving to the government that they should be trusted to govern models, by failing to govern their models? Plenty of shady stuff goes on in marketing, and I'm sure that OpenAI is going to opportunistically grab any p
30.
by calebkaiser 2mo ago
I think the commenter is saying that OpenAI committed a false flag operation, not Tailscale. For Tailscale, this may very well be marketing, but it would be strangely self defeating for OpenAI to do something like what is being suggested. S

More ›