Maybe I’m getting old but I couldn’t tell if this was a joke or not. I think they should explain a little more like what these products actually do?
Readit Newsmlazos commented on The next generations of Bubble Tea, Lip Gloss, and Bubbles are available now charm.land/blog/v2/... · Posted by u/atkrad
>But all they are doing is updating a financial instrument that suggests an increased likelihood, and getting massive bank for not providing the information that would make everyone else bet the same way.
That's the incorrect way of thinking about this, at least according to how US insider trading laws work. If a hedge fund has reason to believe oil prices will spike due to some secret info (eg. they paid some intern to camp out at US airbases and spot outgoing flights), and then they made massive bank on that trade, that's not insider trading. It's not a crime to hoard material nonpublic information and trade on it (ie. "updating a financial instrument ... and getting massive bank for not providing the information that would make everyone else bet the same way"). Now, if they paid off some guy inside the base, that might be breaking a bunch of laws around national security, but still not insider trading.
That’s 100% insider trading. If you use material non-public (including confidential) information to perform the trade it’s illegal. Paying someone to provide confidential info is still insider trading. Paying someone to observe planes (public information) is not insider trading. Researching using publicly available information (even though you don’t share your research) is not insider trading. The key point is the channel from which you receive the information.
mlazos commented on Nvidia to buy assets from Groq for $20B cash cnbc.com/2025/12/24/nvidi... · Posted by u/nickrubin
This is the absolute biggest grift of the century by the groq team. They never shared actual TCO, and I remember a Seminalaysis article about the power consumption being actually insane - this makes sense because they scale the number of chips to fit a single model when they have no dram. They have good inference latency but there was no way the economics were going to work out. Meanwhile Nvidia with every advantage in the world decides they’re worth 20B? It actually doesn’t make sense at all. The only scenarios the groq system would be worth it is in the exact throughput-optimized scenarios Nvidia already thrives in.
If the neo-nazis celebrate it as a Nazi salute, I don’t think it really matters what others think. In addition to that, seeing it with my own eyes is all the confirmation I need.
On his intelligence SpaceX and Tesla were/are revolutionary companies, but seeing him buy twitter and then send the DOGE five things email makes me feel like maybe it was more of a right place right time sort of thing and not management prowess. I’ll give him credit for hiring the right people which is a skill but other than that his blunders are just too difficult to ignore.
We do need to start talking about the failure of capitalism. I'm not naive enough to think that we should turn to communism, but it's clear how we're taught capitalism is suppose to work and how it plays out in reality are two different things.
Ideally capitalism would yield better product or services, for a lower price. That's no longer happening. We're getting shittier products and we're paying more. But somehow we convince ourselves that it's still good, because the stock market is going up, corporate profits are going up.
If there was ever any doubt that the hype is the product, then please explain the Tesla stock, 100% hype driven, there is zero correlation between the stock price and how the company is actually doing.
It’s because capitalism assumes a free market with competition. If you allow monopolies to thrive, you will not get those benefits. It’s just that some of these types of markets have different dynamics due to their structure. E.g. natural monopolies where the barrier to entry is huge up front costs. Interestingly the AI startup ecosystem is raising enough money to surpass the barrier of needing a ton of data to train AI.
mlazos commented on ChatGPT agent: bridging research and action openai.com/index/introduc... · Posted by u/Topfi
> It feels kind of odd that almost no one is talking about self-driving now, compared to how hot of a topic it used to be
Probably because it's just here now? More people take Waymo than Lyft each day in SF.
Yeah where they have every inch of SF mapped, and then still have human interventions. We were promised no more human drivers like 5-7 years ago at this point.
mlazos commented on FP8 is ~100 tflops faster when the kernel name has "cutlass" in it twitter.com/cis_female/st... · Posted by u/limoce
Good idea. Random selection is interesting but I don't know if it can work today. A solutions for the issue you mentioned "Nobody knows anything about any of the candidates" is a system that allows people to vote only for people they know personally, and use some algorithm (maybe something like the PageRank algorithm that Google used) that rates each citizen according to the votes they get but also the votes are valued according to the rating of each citizen. That way the rating flows to the people who are really trusted by the people and not the best funded career politicians. Just an idea. maybe there are problems with that too if it can be gamed but it's worth trying.
It just seems like the rating is a vote. You’d end up with the same problems.
> everyone believes it’s a winner takes all game
Why would anyone think that, and why do you think everyone thinks that?
Everyone always thinks this at least in big tech I’ve never heard a PM or exec say a market is not winner take all. It’s some weird corpo grift lang that nothing is worth doing unless its winner take all.
I’m amazed this is even viewed as a “hot take” tbh most of what he said here is pretty high level of abstraction and standard practice for custom hardware. In essence I feel like he’s saying nothing really controversial other than publicly calling out TT for too many abstraction layers (and tbh it’s just in a readme). This is completely fine, he’s a user and this is his experience.
I’m a dev working on torch.compile at meta (previously I worked on ML focused FPGAs) and the approach I would use is build a static graph compiler, use torch.compile (and probably JAX) as graph extraction front-ends and call it a day. I feel like hardware companies don’t know how to handle the flexibility of PyTorch and as a result develop their own APIs which is mistake #1 and virtually makes it impossible to get any market penetration once you head down that path because nobody will ever ever rewrite their models for your hardware when they don’t even know what perf they will get, the risk is just too high. As a result, hardware companies offer inference APIs which hide all of this behind a REST API to basically paper over the lack of generality of the software/hardware interface. This is convenient because then nobody actually knows the perf/$ and they can burn VC money for as long as they want. Whether this is a viable business model or not, we will have to wait until they go public to actually see what their true inference costs are.
To sum it up, start from PyTorch and work your way down to your hardware, this is the only general way if you want to actually sell chips and not just constantly port the model of the day to your hardware.