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granitepail

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A great deal of their research has been focused on zigging where others zag. Their paper "Continuous Thought Machines" (https://arxiv.org/abs/2505.05522, presented at NeurIPS) was posed specifically under the framing of there needing to be more fundamental research beyond squeezing as much as we can out of relatively vanilla transformer stacks. It is very biologically inspired and unique.

Now that models are getting stronger at agentic work, it is very natural that many labs are chasing some form of auto-research.

"Just" Kimi K2.5 with RL—people really misunderstand how difficult it is to achieve these reults with RL. Cursor's research team is highly respected within the industry, and what they've done is quite impressive.

Before people go jumping to conclusions about model theft, it's worth considering the possibility that they did reach an agreement with Moonshot which their researchers were not aware of. That would certainly explain the deleted tweets. Until Moonshot makes an official statement, I'm not particularly concerned.

To me, it’s very obvious that the problem is social media. To social media, AI slop is peak efficiency. The affordances and incentives of the network encourage its creation. I don’t care for the media slop, but eg television media has more or less been producing crap like this for a while.

I don’t think LLMs and video/image models are a negative at all. And it’s shocking to me that more people don’t share this viewpoint.

In my case, I’m paying for inference on the original models from e.g. Fireworks. So it’s not a quantization problem. The Qwen3 I was using was the new 458B (i think that’s the size?) model that was their top performer for code.

I agree with other comments that there are productive uses for them. Just not on the scale of o4-mini/o3/claude 4 sonnet/opus.

So imo open weights larger models from big US labs is a big deal! Glad to see it. Gemma models, for example, are great for their size. They’re just quite small.

While the benchmarks all say open source models Kimi and Qwen outpace proprietary models like GPT 4.1, GPT 4o, or even o3, my (and just about everyone I know's) boots on the ground experience suggests they're not even close. This is for tool calling agentic tasks, like coding, but also in other contexts (research, glue between services, etc). I feel like it's worth putting that out there--it's pretty clear there's a lot of benchmark hacking happening. I'm not really convinced it's purposeful/deceitful, but it's definitely happening. Qwen3 Coder, for example, is basically incompetent for any real coding tasks and frequently gets caught in death spirals of bad tool calls. I try all the OSS models regularly, because I'm really excited for them to get better. Right now Kimi K2 is the most usable one, and I'd rate it at a few ticks worse than GPT 4.1.

From the individual article summaries:

"The Editor-in-Chief and the publisher have retracted this article. The article was submitted to be part of a guest-edited issue. An investigation by the publisher found a number of articles, including this one, with a number of concerns, including but not limited to compromised editorial handling and peer review process, inappropriate or irrelevant references or not being in scope of the journal or guest-edited issue. Based on the investigation’s findings the Editor-in-Chief therefore no longer has confidence in the results and conclusions of this article."

More, I think, preying on the public's interest in UFOs to justify another massive military budget. All of the wild PR around UFOs with absolutely nothing of substance to back it seems to be a very effective PR campaign.

I haven't updated my LinkedIn in around five years. Definitely not a requirement. I do keep an up-to-date CV and just pass that along. Could always try putting n/a in the field and writing a note, or finding a hiring manager or someone in HR to mail directly.

From the hiring side--I've done quite a bit--I never thought twice about whether someone had a LinkedIn or CV. I do think it's lazy not to provide anything on one's background, though. It helps me guide the conversation towards a candidate's strengths.

Exactly. A cryptocurrency is driven by speculation. A treasury system helps manage flows of capital in and out of a business. Said company pays to use the proprietary system. Sure, they're both backed by a ledger, but Adjoint isn't turning profit by encouraging or even allowing people to speculate on the future value of their platform. They're selling a service.

I played a lot of M:tG at various times in my life, and games like Magic teach you a lot about these concepts. I would have never thought about it has I not had that experience! No shame in learning about the meta game!

agreed. living in NYC, i’ve seen how extensive the problem is. we have lots of housing being built over a much broader area than san francisco and yet we still have the same problem. the number of people moving in to the city and getting high paying jobs (i’m a part of this problem) is so great that basically anyone else is pushed out. our affordable housing program has the right idea, but is so limited in its scope as to hardly make a dent. developers keep making luxury buildings with minimal affordable units and flipping them for big money. we need more regulation, more affordable housing.

Gitfs 11 years ago

interesting to see this! the first thing that came to mind was irmin, from the good folks at MirageOS. unikernels provide an interesting opportunity to rethink block storage, as you're no longer bound the rest of your operating system.

curious to see how gitfs and irmin develop.

https://github.com/mirage/irmin

I have no idea why you're getting so much pushback. Products like those offered by Bloomberg ingest and distribute massive amounts of data in real time, as well. The comparison is completely suitable.

While their products for investment managers are mostly run off of persistent databases, the trader terminals rely on a high-volume, nebulous fan out. For many traders, a five second latency is unacceptable.

Incredibly interesting talk and a good write up. Twitter continues to impress! I was surprised to see Redis playing such a critical role, too.

Yeah! Exactly! Sorry if it was unclear, but what I meant was that I saw the latest wave of DBs (Rethink + Riak) as finally letting the administration & scalability side catch up to the programmer approachability side. Anyone with significant experience knows sharding MongoDB can be a massive pain. Sharding Cassandra is easier, but it certainly lacks the juicy programmer interfaces provided by more modern solutions. I'm very excited about the work you guys are doing.

I saw the article as more of a reaction to all of the technical (and often times inane) blog posts about why company x uses technology y.

The main points I took away from the article were:

- They did their homework, and - They knew that, even though it is not the most widely known technology stack, they were seeking the kind of engineer who would not only be able to pick it up, but understand their rational for choosing it

And it seems as though they've been successful! As engineers, most of us are interested in the many interesting technologies available to us, so much so that, when examining a company like Basho, many of us ask "Why Erlang?" before we ask "What are you making and why?"

Without putting words in their mouth, it is my impression that Basho sought to create an incredibly powerful and easily scalable database. They chose Erlang because it was, in their opinion, the tool for the job. As I see it, 10gen got the ball rolling towards approachable scaling/development and now Basho and the team behind RethinkDB are trying to improve by creating systems free of MongoDB's many limitations.

You're generally spot on, but I figured I'd clarify a bit of terminology since it can be so confusing in our field. Generally, TCP is referred to as a "stream" based protocol because it guarantees, amongst other things, that all packets will arrive in the order in which they were sent, as you've mentioned.

UDP _is_ great for "streaming" data, meaning data sent piecewise over a continuous connection (or, at least, emulated connection) because packet loss / reordering is an acceptable loss, since a minor blip is less destructive than pausing the video. In this type of setting, packets that arrive out of order (i.e. a packet that was sent earlier arrives after a packet sent after it has been received) are thrown out and the process keeps on chugging.

Having worked on a sizable AngularJS project for a good while, now, I can't begin to imagine where you're coming from. The strength of Angular, in my opinion, is that I write ~1/10th the code I'd write using jQuery & Underscore. Event handling, display logic, data binding, directives, resource factories – all of these and more mean I can focus on my business logic as opposed to re-binding events when I update the DOM and the dozens of other trivial bits I have to care about when using jQuery (or Backbone, really).

Obviously jQuery/Backbone setups have their place, but to claim that AngularJS makes you less effective is absurd.

it's not funny and that was not censorship. it was an expression of collective disappointment at a user's attempt to marginalize the CEO of a large and influential tech company made purely on the grounds of her being a woman.

it's an interesting move for yahoo! and i'm curious as to see how their revitalization campaign plays out.

It's also worth noting that while blunt objects such as hammers and baseball bats find uses in construction and non-violent sports, guns do not necessarily share such innocent use cases. Sport shooting is the major exemption (I'm quite a fan, myself) but at the end of the day guns are designed to put holes (some messier than others) in objects very far away. When a gun is pointed at a living organism and the trigger is pulled, its chances of survival plummet.