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.
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.
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.
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.
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.
The idea that cutting research will make a dent in the budget is a fantasy. NSF has a budget of 10 billion. Stop rationalizing gutting crucial programs because of “the deficit” Medicare, social security and the military are the main costs in the US budget. Sure universities are bloated, tackle that problem separately then.
I used this to onboard to the PyTorch team a few years ago. It’s useful for understanding the key concepts of the framework. Torch.compile isn’t covered but the rest of it is still pretty relevant.
One of my friends stated this phenomenon very well “it’s a lever they can pull so they do it”. Once you’ve tied your career to a specific technology internally, there’s really only one option: keep pushing it regardless of any alternatives because your career depends on it. So that’s what they do.
Like idk how long I need to hear about all the great things in tech he’s done when I see his handiwork in an actual tech company over at X. Maybe he was a grifter all along?
This is chesterson’s fence playing out in real life with the major superpower of the world and it has real consequences for people. It should not be the insane fiasco that’s happening right now with an unelected foreign citizen admitting in a cabinet meeting that they accidentally stopped Ebola vaccine financing. If you seriously think this is going to turn out well after we saw trump’s first term I just don’t have anything to help you.the funniest shit is that all of this upheaval is literally < 1% of the actual budget and it’s going to be touted as billions in savings by musk the grifter in chief. I don’t need time to see that this is a dumpster fire.
You don’t need to be deep in designing NNs and the theory behind them, but I would say you should be able to take some linear algebra equations and be able to map them to the GPU arch. This does require some knowledge of the math being used. Luckily it’s mostly high-school/college level math. Starting with the CUDA and tritonlang docs are a good starting point for an introduction. They’ll teach you about common optimizations like tiling, thread swizzling and maximizing cache utilization.
Like sure I’m not familiar with the value of these programs, but you get that these programs are literal pennies compared to the government’s budget right? It’s not even worth talking about these. DOGE cuts aren’t going to add up to shit and you bet we’re going to hear “mission accomplished” in six months, meanwhile Russia and China and are going to grab global influence in the absence of USAID and we won’t experience the repercussions for years after these clowns have left office.
I think they could start with not destroying hospitals and schools and doing better than “at least 1/3 of the 40k people killed were militants.” Israel , the most moral army in the world /s, thinks that two citizens killed for every militant killed is an acceptable ratio, it’s not.
I’m glad for this, bus companies have been fighting train development for decades to prop up their garbage service. Hopefully if they get broken up and sold for parts we can have sensible public transit in this country which doesn’t rely on roads and sitting in traffic.
Agreed, when a company rises to prominence so fast, I feel like you can end up with inexperienced people really high up in management. High risk high reward for them. The board was also like this - a lot of inexperienced random people leading a super consequential company resulting in the shenanigans we saw and now most of them are gone. Not saying inexperienced people are inherently bad, but they either grow into the role or don’t. Mira is probably very smart, but I don’t think you can go build a team around her like Ilya or other big name researchers. I’m happy for her with riding one of wildest rocket ships in the past 5 years at least but I don’t expect to hear much about her from now on.
I had to retake a driver’s test recently and I’ve never heard of checking your mirrors before a yellow. What’s “a vehicle unlikely to stop” even mean? Like I can ascertain that in a second? The driver behind you is supposed to be traveling a minimum safe distance behind you for their reaction time. If they aren’t it’s 100% their problem.
> I don't agree because it creates this dilemma for creators: you need to put your work out there to get traction, but if you put your work out there and anything public is fair game, then it will be sampled by a computer and instantly recreated at scale. This might even happen without the operator knowing whose work is being ripped off.
This is no different than the current day, copying already happens (as your friends have seen) AI makes it a little easier but the same legal frameworks cover this - I don’t see why AI stealing is any different than a person doing the same thing. The ability to copy with zero cost was incredibly disruptive and incredibly beneficial to society. Settled case law will catch up and hopefully arrive at the same conclusion it has for human copyright infringement (is it close enough to warrant a case)
Yes it is absurd to rewrite your entire software stack when 99% of scenarios have the same requirements: CPU, I/O, drivers. You know how many bugs you have with one stack? Multiply by 2x for each of your custom OSes. I’ve seen the fragmentation in edge devices and no thanks, I don’t want more “secure” “proprietary” software.