islewis

The article also claims they had 36h to prep the attack, I assume this was the 36h prior to Thursday- if so unlikely to be related.

congrats, this is a very exciting release.

I cannot speak to the other accents, but my experience has been that American south accents are really poorly represented in mainstream Speach-To-Text models. If your STT model is pointed at end users, this can cause quite a quality drift when looking at eval vs prod performance depending on who your user base is.

I am not sure what terms you have collected the speach data on, but I am sure there are lots of people working with voice models that would be very interested in this as an eval set.

no

> The Ariel variant of GB200 NVL72 pairs each NVIDIA Blackwell GPU with an NVIDIA Grace CPU and 2x NVIDIA ConnectX-7 400G NICs at a 1:1 CPU-to-GPU ratio, letting us deploy 800G of I/O per GPU earlier than the rest of the industry

If the 1:1 ratio was purely for I/O (big assumption, very likely wrong), I am curious why they did not just go with ConnectX-8? Other hyperscalers have been shipping NVL72 clusters with ConnectX-8 on roughly the same timeline, and it offers the same 800Gb/s of throughput.

Managing a custom Ariel variant (which seems to be a Meta-only build) is not insignificant complexity, I wonder if they had another need for that 2x CPU-GPU ratio in their workloads relative to the stock GB200s.

EDIT: I looked, the gb200s NVL72s never have shipped with CX-8s, I made this up. This decision could have totally been due to compute availability and timing

It is hard to take the "Public Benefit" narrative from Ant seriously. If developing technology in the name of public benefit was truly the mission, taking the company public would have been immediately shot down- you cannot trick yourself into believing that any of these mission values will be allowed to operate under public shareholders for very long, especially due to the massive dilution Ant has seen in the last few years.

Given OpenAI already did its mask-off moment with their un-nonprofiting, which did not appear to damage them much after the media cycle blew over, I am a bit surprised Anthropic is deciding to continue with this lip service.

> and paid off the shareholders

does anyone know if the employees who didnt get poached got their equity paid out?

> I don't think the challenge with speech to text was size of the binary

The usecase for small models like this is making on-device STT/TTS more accessable. This is important if your usecase is sensitive to either privacy or latency, but this comes at the cost of quality.

My experience has been that these small TTS models are unexpectedly good if your audio is in distribution (western accents, higher quality audio, common vocabulary), but pretty quickly degrade as you move outside of that. They often dont support more complex features such as diarization, multilingual, or realtime streaming either.

You give two critiques relating to the exact numbers the author has choose (equity package at join, valuation at exit), neither of which is really related to the authors hypothesis that people misvalue EV from equity.

You can slide these numbers around however you want and the point still stands, even if you disagree with it for other reasons

Pretty clearly slop, with some of the scandals make no sense. Take Ripplings "scandal":

> Parker Conrad's redemption arc after Zenefits hit a plot twist when Rippling sued competitor Deel for planting an undercover spy inside Rippling who was paid €5,000/month by Deel's CEO to steal trade secrets . The DOJ opened a criminal investigation. Deel allegedly ran the same playbook at crypto HR startup Toku. YC uses Rippling for their own HR — awkward.

I am curious what the motivation for creating this was

Note that this is from 10 months ago

> Figma is targeted towards designers who create thoughtful design systems and cohesive UIs and who don't code, while this is targeted towards vibe coders who can't design. Two different circles that intersect to some level.

this overlap has been widening incredibly quickly. lots of designers are now writing code with the help of cursor, claude code, etc.

even if you believe "real designers" wont ever use this product, it's not hard to see how a low barrier-of-entry tool could affect Figams bottom line. slowing down Figma's adoption from the new wave of entry-level designers who dont already have muscle memory would not at all surprise me at all.

The quality with the 1M window has been very poor for me, specifically for coding tasks. It constantly forgets stuff that has happened in the existing conversation. n=1, ymmv

> It's powerful but dangerous, and is intended for developers who understand how to safely configure and test connectors.

So... practically no one? My experience has been that almost everyone testing these cutting edge AI tools as they come out are more interested in new tool shinyness than safety or security.

This appears to be a psuedo-acquisition, but with a strange format to appease regulators.

Will this still be an exit event for employees or do they get screwed here?

> The cold-start training procedure begins by prompting DeepSeek-V3 to decompose complex problems into a series of subgoals

It feels pretty intuitive to me that the ability for an LLM to break a complex problem down into smaller, more easily solvable pieces will unlock the next level of complexity.

This pattern feels like a technique often taught to junior engineers- how to break up a multi-week project into bitesized tasks. This model is obviously math focused, but I see no reason why this wouldn't be incredibly powerful for code based problem solving.