ML

p8q8

yes I'm basically building an ML-powered screener that finds the right combination

moar-warpstone

SNOW is not in a good spot. A lot of their top competitors are ahead of them on tech, particularly ML and GenAI. They’re a fine SQL warehouse and that’s it

Successful_Athlete38

I've bought three over the past 3 years from Carvana (2020 X5 ,2014 ML350, and a 2020 Giulia quadrifoglio)..A+ experience honestly.

suddenuser

Mentions AI/ML and it is going down? Lameee

nanotothemoon

https://www.macrumors.com/2024/04/23/apple-developing-its-own-ai-server-processor/ Ah well, I may have jumped the gun a little. This is not an official announcement from Apple, but this is being widely reported. Another thing that is unknown is whether they will farm it out or keep for in house. But as someone who is playing with this tech a lot on a daily basis (writing apps with LLMs and ML), and having an understanding of where the hardware bottleneck is, this would position them very well. Right now my buddy and I are having a daily battle to see what kind of LLMs we can run locally. He’s got a server PC, I have a MacBook. It’s amazing what Apple has done with this silicon. And they already have experience designing NPUs. I expect them to have a lot of success with an AI server chip. Aside from the server chip, I expect the M4 chips for consumers to be heavily geared towards ML computing and AI capabilities. Which probably means more RAM and more NPU cores. Developers are going to like that.

wandering-monster

That's why the new ones are leaning on ML. I recently worked at a place looking into machine vision diagnostics for tissue and blood samples, and they've published some truly impressive stuff along these lines. We're talking detecting gene expression that would normally need IHC staining from an H&E slide, or detection of cancer in nearby tissue (where the tumor wasn't even part of the slide). The work to figure out what exactly it was detecting was ongoing, but the results were pretty damn impressive. I know one is currently undergoing clinical trials as a companion diagnostic for a PD-1 targeting treatment.

Euphoric_Interest_59

bruins ML

thisoneismineallmine

No serious talent in Ai/ML wants to work for Musk; his professional reputation is garbage in the tech industry. Tesla is just a shitty electric car company. 

Mediocre-Ad2227

I'll leave specific use cases to other Replies buried in this thread. And I'll repeat here part of what I wrote elsewhere in this thread. Quantum is beyond digital absolutes, 0 or 1, yes or no - I think digital programming is done best on CPUs. Quantum enables programming of "Maybe", or Fuzzy Logic, based on capabilities for massive parallel processing. In this way, it goes far beyond capabilities of GPU based parallel processing. So it's the use cases currently on GPUs that are likely candidates for a shift to quantum, such as ML for example.

Mediocre-Ad2227

Quantum is far beyond programming absolutes, 0 or 1, yes or no. Quantum enables programming of "Maybe", or Fuzzy Logic. Some ML based on GPU parallel processing also applies this approach. But quantum provides super massive parallel processing far beyond current capabilities. As others have written, benefits of quantum capabilities only apply to certain use cases.

Primary-Gap-220

ML with better marketing

IHadTacosYesterday

And we should honestly expect nothing less. They've been in the AI game at least five years before anyone else. Google Brain (their original, internal AI division) was formed in 2011. They acquired DeepMind in 2014. Microsoft, everybodies AI darling wasn't doing jack shit back then. Also, OpenAI wouldn't even exist without the "Transformer Networks" whitepaper that google ML engineers published in 2017. Google should OWN AI with an iron fist, and anything less is abject failure.

Fattyman2020

Ehh with their new VIA strat they can get more than 10-15% improvement. This is intel we are talking about they do a good job of improving routing and pulling another 20% performance out with their tocks. Tick down a size then improve routing with a tock. AMD’s routing is crap, their saving grace is their ML predictor. Which is why AMD isn’t really surpassing Intel despite having smaller transistors. If you have a smaller transistor but the trace length of the signals is not shorter you can’t get a higher bandwidth.

Coarchitect

I am working in the field of AI. Recently, Apple started publishing a lot more papers regarding their ML research. In particular on device LLMs. I expect a large AI assistant for the iPhone and Mac anytime soon. But probably around June. I am very bullish.

burmaning

You seem to understand the cash flow of the company, but it's important to note that the fundamentals of Cisco and NVDA are entirely different—despite both being in the technology sector, they operate in a much different capacity. NVDA’s applications span in IT, computation (including AI/ML), and telecommunications. The company is in the perfect position for further growth into various computational fields and is entering the CPU market, which would position NVDA as a competitor in yet another industry. Even if NVDA's CPUs don't manage to compete with those from INTC or AMD, the company attracts top-tier talent and researchers, because of its reputation over the past five years. NVDA is known for the quality of its products. As someone with experience in IT, finance, and tech, I can assure you that NVDA are marginally ahead of its competitors. NVDA also has obligations to not only major tech giants but also to higher ed, F500 companies, and IT services; NVDA will continue to expand their computational capacities to meet the growing demands for AI/ML and data traffic; While NVDA may face bullish trends over the next two years due to fiscal constraints, the current market sentiment and NVDA's intrinsic value to all the aforementioned industries make a drop of 80% improbable—unless there are significant product issues, legal battles, or a massive, unpredictable geopolitical event. Furthermore, if such a drop were so apparent, we would likely see higher implied volatility (IV) and premiums for put options. If you were to bet on NVDA's 80% drop, the decay of option value over time (theta) and changes in IV could erode most of your investment before you realize any profit. Cisco and Nvidia are only 9 years apart in terms of company age, and both companies were thriving in pre .com bubble, but in the current context of today's economy, even if the Fed does threaten higher rates, Nivida has too much intrinsic value for it to fall 80%. I hope this helps, many people are bashing your question before addressing what is flawed about it. I hope you continue to study how options work, esp the greeks, and how options are priced, this will help you to become a more profitable trader :)

BullBeater

You are welcome sir. Here’s the post that made me get into the position https://www.reddit.com/r/wallstreetbets/s/i6ML8lx2ul

grasshopper2jump

this is a godsend that everybody is talking about Ira money I happen to have my IRA money in ML and I want to get away from them. I'm not even loving all the positions I have in my sep. any suggestions would be wonderful I'm 64 years old and I'm reassessing a lot of my money and I really feel I learned so much from blogs and just taking the time my advice to anybody is do it early. Don't leave it up to someone else to manage your money thank you to all of youthat are helping to educate us. I hope I can give it back.

grasshopper2jump

can you explain this to me? I would like to move my IRA money Frim ML what do they match

grasshopper2jump

i'm curious as I'm reading members talk about having ‘a match ‘ when they move retirement money. I want to move my sep from ML and would like some advice.

Mean-Coffee-433

This is a Hail Mary. No way this is a good idea to use in any serious ML or AI development

Frogeyedpeas

I've worked for ML tech at a bank. They're against it because it causes capital expenditure. You can't NOT have a trading desk awake when trading is occurring. At least double the salaries have to be paid, volatility will be high, and the bank's main business is trying to reduce risk wherever possible. Also having a single head of \_\_\_ doesn't make sense now if absolutely critical decisions (that happen once every few years ex: 2008, covid etc...) are just as likely to happen middle of the night as middle of day. You are mistaking "inertia" for intelligence. The Hedge funds, Prop shops, and Banks are content with how things are and hence do not want change. It's not that the change is bad. In fact, I would expect the good funds to profit MORE because of this. Still they oppose it because no one wants to work more/spend more in the short term even if they are better off in the long term for it.

WorkingYou2280

I do think Tesla will solve self driving but I think it's going to be as part of overall advances in ML and AI. By the time Tesla solves autonomy it will be because the whole industry has solved it. it doesn't appear to me that Tesla has had anything particularly special or revolutionary in this space. If you've followed it reasonably closely Tesla has had one failed approach after another. I think recently they gave up on updating older hardware. Transformers may be the missing piece here. I'd guess a lot of companies are now training self driving models using transformer tech and maybe that's finally the thing that makes this robust enough to be generally useful. Other companies have more advanced offerings that are level 3 or geofenced conditional level 4. Tesla is really only notable in the space for being willing to yolo level 2 across so many different driving conditions.

qroshan

dumb comment. Google doesn't have to give money to NVidia because they make their own chips. There is also this https://chat.lmsys.org/?leaderboard While idiots who don't anything about LLMs, ML are shitting on Google, they are quietly innovating and slowly crushing it

TheMcRobinson97

Timberwolves ML tonight

Hairy_Advice6669

Yes, because technology drives productivity which drives growth. To all those giving regression to the mean arguments or short term issues with the tech industry, they don't quite understand how transformational AI and ML have been. And any company that has the best models is going to have the tools to build the next best models and that is just going to compound. There is almost no parallel to technology that keeps improving itself and does so at an exponential rate. So yes, this is unprecedented.  And any company that ultimately comes up with AGI will basically rule the world. From my own experience LLM tools have increased developer productivity massively this year. And we are just scratching the surface, so the next few years are indeed going to be transformational. And I am a strong believer in what Ray Kurzweil thinks about this. https://www.ted.com/talks/ray_kurzweil_the_accelerating_power_of_technology/transcript One caveat though is that I am as clueless as anyone else when coming to stock picking for technology.  But any tech index fund should give you sufficient exposure to realize these exponential gains.

Bimperl

I don't think you're proving what you think you are. Almost all of the inventions that you mention are more than a decade old and some are really close to 20 years old. AWS, Alexa (almost), Kindle, Prime, iPhone, iPad, Facebook's social media platforms, Google Maps, Youtube etc. That's not exactly showing "new" innovation. Most of the new stuff that you mention is just ML or AR/VR.

achentuate

No you cannot? In the last 20 years, Amazon went from selling books to literally everything, within a couple of days, launched the worlds most successful subscription in prime, invented AWS and took control of the internets data, invented other products like Alexa, drone based deliveries, kindles, very successful ML training chips etc. Apple invented the iPhone, iPad and the new highly successful Mac generation. Visión pro may be huge as well. Meta built the most successful social media product and advertising algorithms to monetize them. Most recently they have fantastic gen AI models with llama competing head to head and doing well against GPT. They also pushed boundaries in VR tech though it is too early to say if they’ll win this race. Google invented Maps and expanded to video content with YouTube. They also were the original inventors of the underlying “AI” algorithms that everyone is hooked onto now. They have big plays in self driving and other computer vision tech as well. I’d say Google is the second weakest inventor of big tech. Apple, Amazon and Meta are honestly clear in terms of attracting top talent, and inventing successful products in house VS buying

YouMissedNVDA

And META is probably the smartest firm with respect to AI possibilities right now, so their perspective carries a lot of weight. Even Yann, who is a big critic on LLM continuing potential, is still gung-ho on ML techniques continuing to scale in general. Which I believe to be fundamentally correct. Complexity science kind of prescribes these techniques, and most untapped value is gated behind complexity problems. ML continues to prove to be the only scalable method to map and use regions of complexity, and that's very exciting for the supplier of the best ML tools, NVDA.

AP9384629344432

On the other hand, META consistently shows an ability to generate a high ROIC (20s-30s). Oil companies will never match that on a consistent basis. So you have a company that has a track record of generating stellar FCF, and the question is if this particular capex will be a waste. I mean AI or ML or whatever you call it clearly played a huge role in Facebook's success with ads. From the beginning they have been hiring tons of ML/AI researchers and investing heavily into relevant software. I'm just skeptical that LLMs specifically will be an extremely high ROI investment. But higher than the risk free rate is a really low bar imo...

nukem996

Meta recently announced their own AI/ML hardware. MSFT did as well. Big tech is transitioning off NVDA for custom hardware. I expect lower sales going forward.

_hiddenscout

Well a big part of METAs bull run was from the idea of the year of efficiency. That’s part of the reason why the stock sold off so much, was the increase capex spend to the metaverse.  To the point though, with all the investment in AI, what will be the ROI. All that capex shouldn’t be required if ML was already working. 

_hiddenscout

Sure, but how much is that from existing infrastructure form their ML stuff in the past. Facebook has been doing this since like 2020: [https://www.adweek.com/performance-marketing/facebook-brings-machine-learning-into-the-dynamic-ads-creation-process/](https://www.adweek.com/performance-marketing/facebook-brings-machine-learning-into-the-dynamic-ads-creation-process/) [https://www.spiceworks.com/marketing/advertising/articles/instagram-and-facebook-ads-automation-how-ai-and-machine-learning-will-power-your-campaigns/](https://www.spiceworks.com/marketing/advertising/articles/instagram-and-facebook-ads-automation-how-ai-and-machine-learning-will-power-your-campaigns/) So in theory, their ML's have been doing this years.

_hiddenscout

I mean as an investor the question still becomes what the roadmap? Why so much? What is the ROI of the investment? Also would be curious to know how much of this is actually new versus what is being used from their earlier stuff with ML and what not.

_hiddenscout

Well it's been over a year and we haven't seen any revenue or EPS growth from it. I don't really think there has been any substantial growth from any company at this point. Becomes a question of how valuable "AI" is in terms of that investment. Before ChatGPT brought a lot of hype into the idea of "AI", companies were doing a ton with ML already. It's not really a bad thing, but still, what is the road map? Why are they investing so much to do what? Also with META, zuck owns the company with his class B shares. He has 10-1 voting with them. So if any point you aren't happy, it doesn't matter, Zuck will do what he does. Part of what tanked the stocked was when they went heavy into the metaverse, with a ton of capex spending.

elgrandorado

You're right. Something tells me that the answer right now is no. I always assumed this huge LLM/AI/ML/datacenter boom was being sought after with the intention of massive cost cutting through automation. That doesn't seem to be happening.

Talic

AI/ML cockblocked-chain their mojo.

semitope

I've actually had an insurance where it was better. Google was giving me more crap. Usually Google is better but I can see them shifting towards sucking. Especially if Ms can get search results processed by ML models to some useful degree first.

Spara-Extreme

Yes but Tsla was stupidly valued to begin with - all of its insane market cap was based on the premise that it had a technical moat around batteries, charging, and ai. Turns out it can’t even compete on cars anymore and it’s ai got thrashed by Mercedes of all companies (which doesn’t even use ML). Tesla is the pimple that isn’t anywhere near done bursting.

natures3

Yeah Neural networks for unsupervised learning I guess. I think it was good move for FSD v12 and beyond to let the new ML framework learn real time on edge cases than to manually code edge cases with C++. Flywheel for ML.

thisoneismineallmine

ML was a thing years ago. DeepMind was acquired by Google in 2014... So nobody "copied", they simply accelerated their release dates. 

Maximum_Reputation96

Vegas Golden Knights ML since my old coach plays for them

Pirwzy

It looks like the data ML shows 401(k) account holders doesn't include the current month. It only shows details of the last previous month and the quarter ending in that month. Being three weeks into April right now there are three weeks of data not being shown to me, and most of the funds I've allocated into have had big drops just in April.

Pirwzy

[This](https://imgur.com/a/ntGALip) is everything that ML shows me.

thunder_jaxx

That seems very reductionistic. Have you ever tried using Full self driving before? Have you ever sat in a fully self driven car ? I understand people’s skepticism but the current tech is leaps ahead of the competition given what it can do. Additionally this is not an e-commerce site that any person on the road can copy it by just being clever. Machine learning is not child’s play. The work / setup Tesla has for its ML is decades ahead of the competition. Even if someone manages to copy it, they still don’t have the data advantage that Tesla lives with. On accidents: Yes there will be accidents, it is just not possible to launch something like this without accidents. other auto manufacturers don’t even have the same level of capabilities ( try making the car drive itself on the streets of SF) and I can gaurentee you when they reach the level Tesla is at, then they will have even more accidents. Additionally accidents are not growing at an alarming rate. If accidents are a reason for Tesla being a bad company then people should never board a Boeing plane since they have had way more casualties than Tesla cars.

ekdaemon

Is the info at ML with an "as of" date of a month ago? A recent drop could cause what you're looking at.

greytoc

Looks like about 7.59% ytd to me - [https://www.troweprice.com/personal-investing/tools/fund-research/TRBCX](https://www.troweprice.com/personal-investing/tools/fund-research/TRBCX) Perhaps you can call ML and have them explain what you are seeing. You may be looking at the effects of dollar cost average contributions - which is why dca is often recommended.

Pirwzy

My employer goes through Merrill Lynch for my 401(k). The information I get about funds from ML looks incorrect and I'm not sure how I'm supposed to make informed decisions on fund allocation when I'm not getting accurate information about the performance of the various funds, or if I'm even reading the information right. For example, the T ROWE PRICE BLUE CHIP GROWTH FUND (TRBCX) according to what ML is telling me, has a total return for the last month of 2.11% and year-to-date of 14.05%. However, when I look up the fund and check MarketWatch, the chart is clearly showing that the fund is negative for the month at -6.09% and a year-to-date of just 7.59%. Are they even the same metrics and which am I to believe?

Educational-Air-685

I have been using the ML web app for such. This is a 2 step process. First step is to get your buy order executed, typically market or limit price. Let’s assume you placed an order at $1 premium, so total expense is $100 + fees. Second immediate step is to put “SELL to Close” stop or stop limit order. Let’s say you want the initial SL to be at 25%, you put a stop price of 0.75, order cost would bd $75. I suggest to put this as GTC. Once the trade starts going in your favor, say the premium is gone up 25% ($125), you can edit the 2nd (Sell) order up, say to $1 ($100). You have to manually trail your profits, they don’t have automated way to setup percentage based orders. The challenge I have is with spreads, will create a new thread for suggestions or alternate / substitute approaches.

nanotothemoon

Have you heard of AI? “AI” is a predictive machine learning model that predicts the next word (in the subset of ML that is language processing). It requires a lot of hardware resources to run and train/build/test these, and in general ML and Deep Learning type computing is exploding in popularity. Right now, everyone is racing to get the hardware to power this stuff, but none of the hardware out there was specifically designed for this. Nvidia has a dominant lead on the hardware design and they can’t keep up with demand for production. But GPUs were designed to process graphics. In fact, ML/LLM computations are handled better on the CPU, but those are not specifically designed to leverage neural computing either. That’s what Neural Processing Units (NPUs) are for. And it just so happens that the new M chips have a 16 core NPU directly embedded with the RAM (which happens to be another major constraint for loading LLMs). Initially, it was unclear what these NPUs were going to be used for. Google also has its tensor neural chip (though it’s currently hampered by being on the backs of Samsung). And these companies put this stuff in place back in 2018-2019 to handle some niche ML closed projects like Google Lens, Translate, Face Unlock, Siri, Speech dictation, etc etc. But everything has changed now in the last year in regards to the demand for ML computing. Apple just announced the new M4 chip will have more cores in their NPU (the first ever increase of cores on the NPU) along with new “AI enhancements”. Nvidia is also rumored to be releasing an AI specific chip in 2025 (either some kind of NPU or possibly even an LPU like Grok’s commercial chip design which stands for Language Processing unit being designed for an even more specific ML computation). I’m not saying Nvidia and Apple are in the same boat. Nvidia is a leading company in this field for many other reasons. However, the way I see it, Apple has sort of accidentally lucked into a big heard start with their chip design. At least in the B2C arena. Because all they need to do is open up more access to those embedded NPUs for everyone to leverage their models on and many developers can get a lot of work done with simply their MacBooks instead of having to build a server with an expensive Nvdia GPU that wasn’t even designed to do neural processing. But currently MacBooks aren’t quite enough to do big big models. So here now we have an exploding demand and a clear path for Apple to meet that demand, and it sounds like that’s exactly what they plan on doing based on recent announcements. Nvidia has a similar setup. Google? Idk. They’ve been in the ML game a while now so software wise they are ahead (although their LLMs are not inspiring anyone lately). Hardware wise they are very behind, despite having experience with their Tensor chip design. Idk, maybe they will take advantage with all of the data they have? Their path is less clear to me.

nanotothemoon

They are ahead on hardware for ML. Can’t speak to 20 years, but the next 5? Yes

nanotothemoon

NPUs. I view Apple aligning with Nvidia for keeping ahead of the curve for hardware that can train LLMs and all ML tasks moving forward. If you think Nvidia is good long term, so is Apple imo

thunder_jaxx

Maybe I am baised here. But the only reason I like my tesla is because of FSD. I have the car drive me everywhere. in-city roads/ on free ways, you name it. And it is pretty impressive what it can do in city traffic. Maybe other cars can do the same but I haven't seen any other can in the same pricepoint that gave me such a feature. The technology is also not as trivial to build as most speculate. Huge leap between even current self driving and lane-centered-assist. For Ford to catch up to Tesla(in FSD), they will need to build out an entire Self driving ML/Software infra structure that only has value when most cars are integrated with it (which they wont be until a few years even after they launch it).

nandeep007

You can't used fsd in India, nobody follows rules. ML would get confused what to do and just ram into cars lol

chilpanduk

Traditional ML is closer to statistical learning, not GenAI. Sure, it’s nowhere close to AGI but it’s not some variation of statistics either.

btoned

This. It's no different than betting the ML on a perceived blowout. If the team in question turns around, those +1200 odds can turn -100 in a heartbeat. 10x gains if you time it right. In OPs case he did this overnight which is akin to flipping a coin.

2beatenup

These jokers came to me with the same 1% fees on total assets. I told them I’ll give you 10% on gross profits. Do you have the balls to take this offer if you think you are really that good? They could not say a word. I have ML, Fidelity, Sofi and multiple accounts. I do a good 20-27%. How? I educated myself and I very actively manage my own funds. I am in control and it’s fun. They still send me new guys to talk to… my response is the same 10% and beat the market more than I can then we will talk. And I am not even a financial or market person. Just a Joe blow in a 9-5 corporate job. Most IMPORTANTLY: Do I do mistakes and lose money. YES but that is within my scale of risk management and I still beat the market. Long story short. Educate yourself and manage your own money. 1% my arse…

Maximum_Reputation96

76ers ML

chimmychimchum

Nvidia have been working in the quantum space for a long time. They have sown seeds there with cuquantum the same way they sowed seeds with cuda for ML/AI. Nvidia will be at the forefront of the quantum wave as they are the forefront of the ai wave.

TQuake

Man I don’t doubt that NVIDIA has a huge lead on the competition, but no one, not even he, can accurately predict if/when others will catch up. He simply doesn’t have enough knowledge of the competition’s internal research, or how AI tasks may evolve. I agree it’s unlikely anyone beats or catches up to NVIDIA anytime soon, but that doesn’t mean no one could develop a compelling alternative. If a company with a huge need for GPUs could develop their own chips in house and get them at cost, even if they’re worse than NVIDIA’s offerings. It could be compelling enough from a cost perspective to disrupt NVIDIA’s business. Obviously not many companies are anywhere close to being able to do that, I think Google is the best positioned, maybe Apple too since they have a lot of chip design experience, but they seem to lack the motivation with their ML/AI services seemingly being much smaller.

script_sibi

This regard works in ML, doubt he’s competent enough on the hardware side for this claim to have any weight.

Shronx_

Sure, go believe that. Then, next year, IBM or some other company drops a quantum technology that accelerates ML training and inference by orders of magnitude and NVIDIA is going to fall like a stone, transferring it's market cap to the next star on the rising.

CriticallyThougt

Watching you regards talk about something you don’t know is fun. AMD will continue to eat INTELs lunch but NVIDIA’s moat mostly lies in its CUDA software, which is the industry’s gold standard for AI/ML training Theoretically AMD could make chips that are both faster and cheaper than NVIDIA and it wouldn’t matter much unless they also deliver on the program side. CUDA is a walled garden, a golden walled garden that is highly optimized to fuck.

Immediate-Product167

He's a great ML researcher but he has no advantage in hardware.

UsefulReplacement

Don't you think that if Apple was capable of fixing Siri, in terms of both AI know-how and in-house NLP and ML talent, they would've done it by now? Even before GenAI, their assistant was at least 10x worse than Google Assistant. They also moved the compute to on-device, which will prevent them from running any of the large / advanced GenAI models. Apple's core competency is human interfaces and the integration of software and hardware. AI has nothing to do with that. They have a lot of cash and a bunch of software engineers, but, you know, so do a lot of tech companies. So even if they go "all in on AI", what makes you think they'll be able to pull it off and won't be another Apple Car-like project? Also, who in upper management has any deep knowledge in AI? Seems nobody, as they learned about GenAI about the same time as the general public.

mortgagepants

glad to see another money stuff reader. (unless you are ML himself, in which case, everything is securities fraud!)

The-Kingsman

That's incorrect. They're an AI/ML company, they just don't have any good AI/ML platforms yet.

SwellsInMoisture

Amazing and thanks for the offer! I recently took some ML/AI courses and it's hard not to see EVERYTHING as an MLE problem now!

moosebearbeer

It will be nvidia. The market has yet to appropriately price in the cost of video-based generative AI. Video takes orders of magnitude more compute resources than text-based LMs, at the minimum let's say 10x more compute resources. The results from Sora look very promising, far better than was expected. And when it was released on Feb 15th, nvidia stock didn't react at all. I believe nvidia will reach 10 trillion by 2026, as more video-based ML models are experiment with.

DD_equals_doodoo

Are you intentionally missing the point? Someone claimed that CUDA is a moat for NVIDIA. You can run it on an AMD. Even then, there's other options that are essentially equivalent and/or growing. It's nonsensical to argue that CUDA is a moat for NVIDIA. It isn't. Don't get me wrong, I use NVIDIA for ML/AI, but there are other options to CUDA and will be more in the future also.

SwellsInMoisture

Ticker Symbol: JPM P/E: 11.27 P/E Rank: 83.53 P/S: 3.08 P/S Rank: 38.18 P/B: 1.77 P/B Rank: 59.49 P/FCF: 40.46 P/FCF Rank: 43.29 SHYield: 4.31% SHYield Rank: 74.24 EV/EBITDA: 10000.00 EV/EBITDA Rank: 16.44 Overall Score: 315.18 6 month price momentum: 25.07% Ticker Symbol: META P/E: 34.36 P/E Rank: 50.42 P/S: 9.67 P/S Rank: 15.39 P/B: 8.56 P/B Rank: 16.07 P/FCF: 29.76 P/FCF Rank: 48.84 SHYield: 1.83% SHYield Rank: 55.87 EV/EBITDA: 20.81 EV/EBITDA Rank: 46.82 Overall Score: 233.41 6 month price momentum: 56.15% Ticker Symbol: VRTX P/E: 28.55 P/E Rank: 55.11 P/S: 10.41 P/S Rank: 14.65 P/B: 5.81 P/B Rank: 22.43 P/FCF: 30.70 P/FCF Rank: 48.00 SHYield: 0.29% SHYield Rank: 41.75 EV/EBITDA: 20.55 EV/EBITDA Rank: 47.21 Overall Score: 229.15 6 month price momentum: 8.57% Ticker Symbol: GOOGL P/E: 27.17 P/E Rank: 56.83 P/S: 6.38 P/S Rank: 20.90 P/B: 6.94 P/B Rank: 19.32 P/FCF: 28.22 P/FCF Rank: 50.21 SHYield: 3.04% SHYield Rank: 65.25 EV/EBITDA: 18.77 EV/EBITDA Rank: 49.93 Overall Score: 262.45 6 month price momentum: 12.22% Ticker Symbol: PFE P/E: 71.95 P/E Rank: 39.96 P/S: 2.50 P/S Rank: 44.58 P/B: 1.64 P/B Rank: 62.43 P/FCF: 30.47 P/FCF Rank: 48.25 SHYield: 6.57% SHYield Rank: 86.33 EV/EBITDA: 18.14 EV/EBITDA Rank: 50.99 Overall Score: 332.55 6 month price momentum: -21.90% Ticker Symbol: PYPL P/E: 16.79 P/E Rank: 71.90 P/S: 2.29 P/S Rank: 47.42 P/B: 3.29 P/B Rank: 36.66 P/FCF: 16.11 P/FCF Rank: 65.00 SHYield: 6.69% SHYield Rank: 86.87 EV/EBITDA: 12.31 EV/EBITDA Rank: 66.68 Overall Score: 374.52 6 month price momentum: 11.23% Ticker Symbol: TSN P/E: 10000.00 P/E Rank: 17.15 P/S: 0.38 P/S Rank: 92.82 P/B: 1.11 P/B Rank: 79.22 P/FCF: 34.45 P/FCF Rank: 45.58 SHYield: 3.56% SHYield Rank: 69.14 EV/EBITDA: 13.90 EV/EBITDA Rank: 61.90 Overall Score: 365.81 6 month price momentum: 19.85% Ticker Symbol: QCOM P/E: 24.82 P/E Rank: 59.68 P/S: 5.27 P/S Rank: 24.17 P/B: 8.31 P/B Rank: 16.58 P/FCF: 19.33 P/FCF Rank: 60.00 SHYield: 3.01% SHYield Rank: 64.83 EV/EBITDA: 17.93 EV/EBITDA Rank: 51.30 Overall Score: 276.55 6 month price momentum: 54.15% I don't have a GitHub directory, but it's not a bad idea to create one! I've got a couple different ML-based financial modelling projects I've been tinkering on, but they're definitely not ready for sharing.

big-rob512

Yea, it's a combination of hardware and software, gaming cards are easier to explain but AMDs cards just in regards to brute force are technically faster they have better rasterization performance. But over all Nvidias cards are better because they include tensor cores for ML algorithms, and Raytracing cores, on top of Cuda cores so they can do things that aren't even possible with AMD like give you a path traced scene at a playable frame rate because it takes advantage of the entire set of hardware. Nvidia will probably always have the best total package whether its for gaming, or AI.

FruitnVeggie

**Matt Laslo**: “Have you heard anything about DEA and the administration moving?” **Cory Booker:** “I have heard a lot about it.” **ML**: “I've heard rumors that it might be April 15th — have you heard that?” **CB:** “I do not want to comment on that.” *Booker laughs as he hops onto elevator with his aide.* **ML**: “Ooooh — I'm warm?” **CB:** “Yes...” [https://www.askapol.com/p/cory-booker-on-dea-rescheduling-marijuana](https://www.askapol.com/p/cory-booker-on-dea-rescheduling-marijuana) I'm hopeful but the vast majority of rumors turn out to be duds so be prepared for nothing to happen.

roloplex

There aren't the GOP votes to pass SAFE. been asking for years. NAME THE 10+ GOP senators that are voting yes on SAFE. You should also know better that the Senate ML and a governership are completely different positions. And Desantis? who is actively working against the cannabis industry? really?

take_five

https://www.reuters.com/article/us-usa-trump-fed/trump-calls-loco-federal-reserve-too-aggressive-idUSKCN1ML1TA/

CucumberPopcorn

A lot of companies are using "AI" and "ML" to attract investors. A lot of these companies aren't meaningfully using AI or ML in any way that would add anything to their business. If you want to do better than sports betting, don't gamble on individual companies without a deeper knowledge of the company. Even then, investing more broadly in a fund (ETF) that holds pieces of many companies that may benefit significantly from AI would be a safer bet. But at the end of the day, especially given that you say you don't understand the stock market well, doing some self-learning on fundamentals would help you to get a better sense of general investment strategies.

YouMissedNVDA

Yup - that is the "gamble", but considering the ChatGPT moment was not driven by a fundamental action of them, but an exceptional result from their regular business, I see blue skies ahead. Blackwell will be the first hardware release that at least knew the scale of demand ahead of time. Hopper got smothered with demand part way through a regular cycle. We literally have not even seen the first hardware iteration amidst this next-gen ML revolution. Imagine where we might be in 5 iterations? And sure, competition is coming. Competition was always there, and coming. Fact is, NVDA stands head and shoulders above their peers, always has, and there is no real indication or justification for that to suddenly change. If anything, the available resources for them to throw at the problem has never been greater. And on saturation - the market for compute is not like most. "There is incredible opportunity in markets where solutions are never good enough", paraphrased from Jensen. Think about it: compute costs are incredibly deflationary, on the order of 100x cheaper over 10 years. In consumer markets, that kind of deflation would cause a reckoning - who would buy today if they can just hold on to their phone/computer for another year and get the same thing for so much less? This is why the Fed abhors deflation - it freezes economies. But in compute markets, no one cares if next gen will be less for more, because there is demand/opportunity/productivity on the table NOW, as well as tomorrow. And as we see - compute at scale gates unfathomable possibilities. The world will never have enough compute. Never has, never will. And the platform that nvidia offers facilitates the widest breadth of customers for compute in the world, from robotics to genomics, and so much more. This is a moment decades in the making, and it is just the start.

putreaper

AI is overdone. Super Bowl ads. LLM’s and ML. AWS and TSLA are developing their own GPUs. Current GPU architecture is advanced beyond the processing needs of LLM and ML applications. NaCl batteries to store solar energy is the next boom.

Advanced-Speaker-729

cocoa futures are overheated more than the surface of Venus. There is no cataclysmic yield event. The drop is predicted to be 10% at maximum. So the 450% price increase is hugely overblown. Also an AI ML software has been developed to recognise hidden cocoa plantations that aren't recorded in efforts to disguise deforestation. They estimate that second biggest producer, Ghana are understating their cocoa plantation figures by 43%.... That is massive. There is not a supply issue at all. Simply a cornering aided by bottlenecking.

pascalsAger

H100 is 4 years old now? That must mean NVDA already has another AI Accelerator in the market. Oh wait, no. Blackwell is still being sampled. H100 is NVDA most advanced AI chip in production and also the one they use for their ML perf benchmark LAST MONTH. 500+ upvotes for a demonstrably false comment:

IHadTacosYesterday

Also, idiot CNBC analysts that have no idea that ChatGPT4 wouldn't even exist if for not a whitepaper on "Transformer Networks" that was published by Google ML engineers in 2017. All they could talk about was how Google had to play catchup to everybody else, when Google was actually leading the field

That-Intern-7452

Intel builds chips? Last I checked, they build electric heaters that sometimes compute a bit on the side. AI chip? More like a heater that tries to run an ML model

Fikkafikation

Yup, that's very true. I was so impressed by their digital currency revolution since covid and demonetization. So well integrated from the smallest of the sellers to the biggest corporate. I mean challenging VISA & Mastercard becoz they charge exorbitant fee due to which small businesses suffer and creating your own is a massive feat for the betterment. I don't recommend AD, ML/AI is riddled with false positives atm. Of course 25yrs down the line - who knows.

butts-kapinsky

I am a physicist. From time to time, I dabble with ML. Both for work and for personal projects. Amazon was lying about their product. It's not that hard to understand.

Fikkafikation

That's not how it works. My example was not related to Tesla, it was a generic issue with ML/AI about false positives. Irrespective of your training data they currently exist at high enough levels which cannot be deemed safe wrt to autonomously driving a car.

Fikkafikation

I'll just say, I work in the ML/AI field too and the amount of false positives it gives is ridiculously high. For image generation where you might end up with some anomalies is acceptable. When dealing with people's lives - it's not. A beta testing software is not for mainstream prime time. Period.

xRICHxPIANAx

Iowa ML?

LivingDracula

Forecast volatility with ML, generate strikes with ML for P, R1-4, S1-4, plug those into a modified Black-Scholes to generate probabilities of assignment/expiration. Downvote me for being having a wrinkled brain...

Moterboat76

AI/ML All Indian Manual Labor

forrestthewoods

AMD CPUs thoroughly defanged Intel. Their gaming GPUs are ok but not spectacular. Nvidia drivers have an outrageous amount of “per application” support – but that’s not relevant to ML server workloads. The world is *desperate* for an Nvidia competitor.  NVDA margins are what, like 70%? That’s bonkers. It’s not a matter of “if” AMD produces a decent AI competitor but “when”. However that when is likely 4 or 5 years away. NVDA has a safe lead now and with the upcoming Blackwell. So *maybe* after that. AMD is a buy and HODL stock. Not for regarded FDs.

New-Set-3059

I downloaded the activity into excel to show trades for easy to read, otherwise as they fill different transactions which makes very hard to read from a direct screenshot from ML app.

eht_amgine_enihcam

The problem is, you're regarded and you don't understand how AI works. The hype behind AI is the genius idea that if you can get a computer to do all of the work for you, it's free and you'll make a ton of money. Many CEO's have had this idea, but get tripped up with the pesky step of how to get the computer to do all the work for you. ML is good at maximising around an objective function by taking nonlinear relationships between a feature vector (pattern recognition and duplication). Much of the hype is generated by LLM's such as chatGPT. These learn by tokenising language, and then predicting what the most likely next token is based on the previous ones. This will by design only create generic stories. A suitable function to maximise around (audience reviews etc) may be found but I think LLM's are limited by design. AI is a ways off from creating "good" stories that you'd actually want to watch. I think AI will come to around 80% of a film you want to watch and then hit roadblocks, similar to what self driving cars are having. Things like Sora are very impressive, but they will likely be a supplementary tool. Images can be generated but there has to be advances to connect these into a cohesive story. Very plot light films and porn are likely exceptions.

BlurredSight

This is a big reason why later models of Teslas can't park for shit, the older 2015-16 models had no issues parallel parking because it was built upon sensor information. The later editions went for a more camera/ML based design leading to it needing human intervention. Yiannimize did this test and Tesla was the worst of all 6-7 cars he tested for parking, the others were BMW, Mercedes, and Audi

gamarrex21

Right now that problem is the only one I can think of. Interior facing cameras solve a lot of problems, especially for manned taxis. Alas, you’ve got a point. People tend to be malicious when nobody is around to immediately punish them. At the same time, I can also see Tesla offering all hours cleaning service at Tesla stores (not technically dealerships?) and other verified partners. Someone pukes, ML camera system detects abnormality, sends owner a push notification with snapshots of what it sees, owner can choose to send it home or to the nearest cleaning center for a $ fee. Owner submits complaint ticket about rider with video for review, Tesla judges the rider responsible for a $$ cleaning fee. I’m just getting carried away now

Purple_Tangelo_399

this is the dumbest shit ever. electric cars are going to revolutionize transport? the highway system is fucked in the ass and is never going to be truly rehabilitated. it doesnt matter how smart the car is if it cant mother fucking fly and flying cars are actually only a wave or two of ML models after self-driving. its a hardware and regulation problem and those get solved real fast once there is money to be made

nero626

Nvidias advantage is definitely partially in hardware, the reason however is not as simple as "no one else is offering competitive hardware", but rather the network effect created by the immense popularity of PyTorch in the ML community and its reliance on over ~2200 unique operators that tensor and CUDA cores natively support, and that number is constantly growing, everyone else is just playing catch up, if they find the incentive to focus on it that is. the talent level required to train a massive model with high FLOPS utilization on a GPU grows increasingly higher because of all the tricks needed to extract maximum performance. the only way to break the vicious cycle is for the software that runs models on Nvidia GPUs to transfer seamlessly to other hardware with as little effort as possible. as model architectures stabilize and abstractions from PyTorch 2.0, OpenAI Triton, and MLOps firms such as MosaicML become the default, the architecture and economics of the chip solution starts to become the biggest driver of the purchase rather than the ease of use afforded to it by Nvidia’s superior software

butts-kapinsky

I'm a physicist who dabbles around with ML from time to time. Maybe hold off on disparaging the way I think until you get to know me a bit better. Amazon did not take a risk. They ran a scam. They were touting advanced AI when all along the product was just outsourced labour. 

butts-kapinsky

>  Reviewing and correcting data is still ML training regardless if it's 1% or 90% Technically correct. The required human overview would still be utilized for training purposes. But the primary reason behind reviewing 70% of purchases wouldn't be for annotation. It's quality control.

MarxKnewBest

This is stupid. I’m not saying Amazon can’t get up to shady stuff but they’re clearly talking about some sort of ML model training or audit work and trying to make it seem like it’s a man-behind-the-ATM thing. Ignorant and lazy journalist.

ogaat

It was a Hail Mary by Jensen Huang around 2015, I think. Nvidia was lagging in the market and he decided to put all the company's eggs in the software for GPU computing market. Luckily for him, the scientific community, the crypto community and then the ML communities developed Python libraries for number crunching using GPUs because those acted as coprocessors and did not bog the CPU down. Nvidia paid attention to their needs and went out of their way to serve those markets while others were focused on the much bigger gaming markets. Then OpenAI happened and rest is history.

ogaat

Nvidia's advantage is not in the hardware. It is in their proprietary CUDA software which is the gold standard for running AI/ML code only on Nvidia GPUs and has a near monopoly for that field. No one else has a similar moat.