SLM

greenpride32

>I imagine once the open-source models reach a certain level of capability, then they are in the wild, can be run locally, can be specialized/forked/retrained. These models will be used to iterate and improve existing models, and will be readily available. This doesn't require any ability or understanding, if you can install and run Mozilla, then you could install and run an open source AI model you downloaded. Wouldn't this fulfill almost any application for AI in the life of the average consumer? What would be the actual mechanism for any gap in value between a free AI of adequate capability and any privately developed model? You are thinking of LLM's which are general all purose models. But there will also be SLM's (small) that are more targeted and specific to a purpose. An LLM would be useful for summarizing emails because it has awareness of many topics. But it is a waste of resource (training time, inference time) to create a general purpose model for drug discovery, self driving, fraud detection etc. The AI moat today is infrastucture side, not the software or physical application side. That's because infrastructure side already has big winners (substantial top and bottom line growth), where as it's unclear who will win on software and physical fronts (potential but not much realized yet).

Ereptile-Disruption

bro, I built computer for fun for the last 25 years. New stuff become obsolete much much slower and degrade much much less. You can look at miners card (used for ethereum) and you'll see tons of them keep going strong. Not everybody need 96Gb of vram and deepseek; we'll see tiered access to allow SLM to use older cards

greenpride32

All you need to do is compare GPU to CPU. INTC and AMD typically release a new generation every 1-3 years. The newer ones are always more powerful than the predecessors. Does MSFT Azure or AMZN AWS refresh every single CPU in their public clouds every 1-3 years? Nope. Just like your laptop or PC at home or work or school, it might not be the latest and greatest after the first year or two, but it still serves it purpose. Same concept with your mobile phone. NVDA GPU generation cadence is about every year now. What's going to happen is those older generation GPU will handle lesser workloads. This could be inferencing or supporting SLM (small language models). SLM is going to be huge for companies who want to train models on their own proprietary data. For example, why would a biotech use a LLM for drug discovery? The answer is obviously they wouldn't and they have their own proprietary data. Take this concept and apply it across any industry/use case. The GPU could also still be used to support frontier LLM's in the cloud. Ultimately a public cloud client is paying a price based on performance/specification. You pay more for bigger and faster storage, you pay more for faster CPU's. Not every company needs or is willing to pay for latest and greatest performance if they don't have the need or can't justify the cost. So no way the useful business/financial value of GPU is only 2-3 years. Burry isn't a tech person, he doesn't understand it. Hypothetically it's a 2 year minimum effort to replace hundreds of thousands of GPU, because you can't shutdown services and disrupt client usage. For those who don't understand the basic accounting concept - if I have a capex spend of $100 in 2025, but that asset has business value for 5 years, I don't have a charge of $100 in 2025. Instead I break that $100 into 5 parts, so it only hits the bottom line by $20 each year (25/26/27/28/29). So Burry is basically trying to say big tech is inflating their profit margin by stretching the expense out. Also note that companies such as CRWV and IREN were formerly crypto miners - that is why they have datacenters and racks full of GPU's. As BTC halving reduced the returns on mining, they repurposed their existing gear to become mini-hyperscalers. They have "dated" GPU's. Did it stop META MSFT OpenAI from signing contracts with them? Nope - because GPU compute is scarce and they need all they can get - prior generation or not.

thebalancewithin

Anyone investing in student loan lenders? Like $SLM?

Charming_Squirrel_13

I was playing around with a tiny, distilled SLM that's about 1GB. I kid you not, it is more coherent than the shit that leaves our president's mouth.

greenpride32

SaaS applications of the future will be infused with AI. General purpose AI is not strong in any specific areas, by definition it's general. SaaS targets specific areas and niches. They will train their SLM on these niches which will produce better results than general model. Also most businesses are going to be training SLM on their own data, not on generally available data. This is where the extract true value. Why is GOOGL so powerful in ad revenue? Because they can collect data that nobody else has. More or less all large corporations are using their own proprietary data analytics to gain advantage; doing this on AI is the next evolution.

itsthebear

What's incredible is that in actual useful implementation they are getting smoked by startups lol robotic models are increasingly multi modal and don't need LLMs for basically anything.  Robotics are based more on world model foundations that language models just don't have. They aren't running queries against massive data sets, but focusing on highly domain specific tasks — even some who are using cameras, haptic sensors and sound waves for a technique called 'Gaussian Splatting' where they create 4d area models that analyze 3d spaces as not fixed in time, making them way more adaptable to changes within an environment. And if you want them to talk just layer in an SLM.

microww

55% of the S&P is held up by the Magnificent Seven. That's something to think about. They're starting to lose influence and early adopters are switching to SLM's, instead of LLM's, which are easier to integrate in their systems and in phones. And the chips and servers they invest in have a smaller lifespan than the investments companies made during the dotcom era. There are also other things to consider, but the point is that a lot of investments are being made, while revenue remains very low. That in combination with the market share they are about to lose, will make the stocks go down eventually. The only good thing is that the Magnificent Seven uses their own money to make these investments, rather than taking loans. So if the whole thing comes down, at least the banks are safe. Investors not so.

FullCopy

LLM are so last month. SLM are all the range now. Also, washing your hands after wiping is so August too.

Asleep_Emphasis69

Why not take out actual shorts on these tickers instead of puts? Now you have to perfectly time the market over the next \~8-16 months for these contracts to have any profit at all. What about SLM? Navient is a short but they aren't?

wish-u-well

The arms race to get there first led to massive spending by these power thirsty companies. Trillions go into research and data centers while latest studies show the tech is better or equally good as SLM small language models, trained on small chips in a specialized way. As a result, more and more freebies will come out that can compete, and they basically wasted billions while the world burns. But our techno bros know what’s best for the peasants of earth right?

Opposite_Attitude_55

whats up with SLM

Opposite_Attitude_55

whats up with SLM?

DogsAreOurFriends

I think it is a good speculative bet. Also in that (automatics) space is Cerence SLM voice AI.

Married-and-dating

A little bit more about how it works (got from Grok) They use Micro-Electro-Mechanical Systems (MEMS) gas sensors to detect volatile organic compounds (VOCs) in the air. Each VOC produces a unique chemical signature based on its molecular composition. MEMS sensors are low-cost, energy-efficient, and scalable Then they apply a Smell Language Model (SLM), which is an AI-driven model that processes raw sensor data to create a digital representation of smells, referred to as a “Smell ID.” This is analogous to how large language models (LLMs) process text or vision models process images. Mechanism: The MEMS sensors capture VOC patterns, generating analog signals that represent the chemical composition of a smell. These signals are converted into digital data, which the SLM analyzes using machine learning algorithms trained on extensive VOC datasets. The SLM identifies and categorizes smells by comparing sensor data to a library of known VOC signatures, creating a unique Smell ID for each scent. The Smell ID can be used for real-time monitoring, diagnostics, or automation tasks, such as identifying defects in manufacturing or detecting health conditions. The SLM mimics the human olfactory system, which uses receptors to detect odors and the brain to interpret them. However, the SLM can process thousands of VOCs with greater precision and without fatigue, surpassing human capabilities.

Married-and-dating

Here's something from Grok: Micro-Electro-Mechanical Systems (MEMS) gas sensors to detect volatile organic compounds (VOCs) in the air. Each VOC produces a unique chemical signature based on its molecular composition. MEMS sensors are low-cost, energy-efficient, and scalable Smell Language Model (SLM) is an AI-driven model that processes raw sensor data to create a digital representation of smells, referred to as a “Smell ID.” This is analogous to how large language models (LLMs) process text or vision models process images. Mechanism: The MEMS sensors capture VOC patterns, generating analog signals that represent the chemical composition of a smell. These signals are converted into digital data, which the SLM analyzes using machine learning algorithms trained on extensive VOC datasets. The SLM identifies and categorizes smells by comparing sensor data to a library of known VOC signatures, creating a unique Smell ID for each scent. The Smell ID can be used for real-time monitoring, diagnostics, or automation tasks, such as identifying defects in manufacturing or detecting health conditions. The SLM mimics the human olfactory system, which uses receptors to detect odors and the brain to interpret them. However, the SLM can process thousands of VOCs with greater precision and without fatigue, surpassing human capabilities.

Acceptable-Status599

Are you factoring in they are using SLM's likely for the search query? Because the compute costs for AI come in large range.

ai-moderator

# **TLDR** --- **Ticker:** SLM, LOPE **Direction:** Down **Prognosis:** Bullish on put options due to anticipated mass defaults in online education loans based on flawed accreditation practices and a changing job market. OP has already established a put position and is looking for validation. **OP's Position:** ~60 contracts, various strikes and expirations (see images) **Potential Profit (if correct):** Six figures **Disclaimer:** This is based on an unverified TikTok and research from an anonymous source. DYOR.

ai-moderator

# **TLDR** --- **Ticker:** SLM, LOPE **Direction:** Down **Prognosis:** Bullish put options positions on SLM and LOPE anticipating a decline due to potential mass defaults on student loans. OP has 60 contracts across various strike prices and expiration dates. **Potential Profit (OP's claim):** Six figures if underlying drops 50%. **Disclaimer:** This is based on a TikTok and uncited research. High risk play. Proceed with extreme caution. **Additional Note:** OP's account shows a recent large increase in buying power, suggesting recent gains. Maybe they're not *that* worried.

Neowwwwww

Short WFC, CACC, SLM, QFIN, COOP and a million others

Courvy

I wouldn’t ask me for stock predictions. I just got lucky, really lucky. I don’t have anymore positions in it. And also the option chain for SLM was horrible. Crazy bid ask differences and low volume. I’m just so lucky. Like literally last week I lost $300+ on various options. I’m just happy to get those losses back🙂

mislysbb

Why gamble on SLM?

SWLondonLife

No, training on LLMs requires far more data than Reddit has….. now for SLMs it could be helpful and definitely has relevance across many verticals - especially with B2B information services. I have helped organisations business case, build and train LLM models. Reddit has an amazing play. But it’s a very very specific play involving SLM sub-verticals.

talkyape

LLM balls SLM brain

highlander145

GenAI in particular is in its hype cycle right now. So was block chain and many other technology hypes. GenAI has its benefits and has to be seen what good it does out there. But agreed AI has been there since over a decade. I also feel big Tech hyper sensationalize a area. Like for example MS has now started to talk about SLM rather then LLM. Cos they see the potential of scaling down and cost efficiency.

RiPFrozone

Depending on the functionality they could use a SLM reducing the cost significantly. Not every AI needs to be LLM.

CakeSuperb8487

A non-serious answer, I would look into SLM or Slamalingdingdong Incardoor Inc. I've heard it's been kinder than the markets lately

Used_Salamander_3532

QCOM - time for SLM mobile chips . Much more undervalued as compared to all others .🚀

throwawaygoawaynz

There’s really very little value proposition in it when it requires an upgrade, and the ChatGPT app itself is already extremely capable. Why do I actually *need* Apple Intelligence when ChatGPT is always going to be faster? I don’t need to talk to my device to control it, as we’ve been there done that and it doesn’t work. That part is a gimmick. The marketing around this will far outweigh the reality. I can also tell you as an AI expect I wouldn’t trust Apples benchmarks for their SLM *at all*. It’s far too easy to fine tune a model that looks good on benchmarks but simply doesn’t perform very well at all in reality. Google still can’t get that right, despite releasing a GPT4 “killer” every 6 months or so, and I’m very doubtful that Apple suddenly became a state of the art AI company overnight.

No_Consequence_4574

Their on device SLM is dope. Will actually be useful.

Draiko

Apple M4's GPU horsepower is about the same as a Radeon 5500XT. The neural engine isn't beefy enough to run a decent SLM. Their AI models are crude so far. Apple is very VERY behind in AI. There's a better chance that nvidia will introduce silicon to seriously rival Apple's in the consumer space before Apple can match nvidia in AI capabilities.

notananthem

"is Microsoft just going to increase subscription fees now that they’ve added Copilot?" Yes, all the hardware that runs SLM and LLM costs money whether its in a computer or a server. That cost is being touted as "free" right now but it costs a hell of a lot and will be passed to someone who isn't happy about it.

justin_zander

> Take a step back from the technical for a moment and think of business value. LLMs only really start to provide value at scale across an organisation, which means the infrastructure needs to handle hundreds of thousands to millions of tokens per minute. Yes, I thought I mentioned that but might have missed that. We do that too for most services, especially those integrated in the most-used customer-facing products. But not all workloads are that. Experimentation-heavy workloads run perfectly fine on CPU-only instances too, and in terms of costs it's also a decent tradeoff (of the AWS instances that are available to my department, we get non-insignificant cost reductions by optimizing when we use each instance). > Now the issue here is the ROI of buying your own infrastructure vs using something like Azure OpenAI or Vertex is simply just not there. I fully agree. Unless you both have a data center **and** AI is a core part of your main business, then using the cloud is better. For my current job, both our main and experimental services use OpenAI (and Azure OpenAI), Anthropic, Mistral, Mosaic, and open/proprietary LLMs running on AWS. > The networking. I agree with this as well. I kinda hinted at this when I mentioned NVLink and NVSwitch but didn't get into more details. It is definitely a worthwhile mention though. > Why use a SLM AND use the LLM like your company is doing when the LLM can effectively do everything better and cheaper? If by SLM you mean 7-70B (i.e. mixtral, llama, falcon) models, then I disagree. Our researchers have **extensively** benchmarked raw and fine-tuned open LLMs against gpt-3.5, gpt-4, and claude-1 and found our models to be better at most (not all) tasks we were needing them for. We also had work done on cost benchmarking, and open LLMs had significantly lower cost per token. They used other metrics too (e.g. human expert effort for correcting mistakes), but typically the results were always the same. What they haven't tried yet (*to my knowledge*) is to try working with OpenAI/Anthropic to fine-tune their models for us. Until that happens (*if* it doesn't break any compliance requirements, because we do have some strict rules to follow due to government contracts) and gets properly investigated, then 7-70B models are totally viable and cost-efficient at scale. > It’s also very hard to effectively build a good SLM yourself, and they don’t work very well with non-English. Remember the rest of the world doesn’t speak English. :) Not a problem for us, the **vast majority** of the customers are in the US, and the only other decently sized market is the UK. That, and all our data are in English. But yes, as a non-native English speaker that lived in 3 non-English-speaking countries, I am aware of the linguistic capability discrepancies. I'm also aware that these discrepancies exist even with OpenAI's models - for example they aren't all that great in my native tongue (Greek).

throwawaygoawaynz

Ok this is a decent start for this sub, especially compared to most analysis where people have played around with ChatGPT once and claim that AI is a bubble. However your analysis is missing a few key points. Inference: While it’s true that you can run smaller LLMs on cheap hardware (and even not really on Nvidia at all), the problem is scale. Take a step back from the technical for a moment and think of business value. LLMs only really start to provide value at scale across an organisation, which means the infrastructure needs to handle hundreds of thousands to millions of tokens per minute. This is especially even more true in B2C use cases, such as consumer facing chatbots etc. To get that scale you need to be doing inference on commercial grade GPUs. Now the issue here is the ROI of buying your own infrastructure vs using something like Azure OpenAI or Vertex is simply just not there. Nvidia’s Technical Moat: Nvidia’s moat right now is actually two fold. One is the CUDA ecosystem like you say, but that’s not where Nvidia is making their cash. They’re making their cash by selling to the big players, private AI clouds, and in some cases building their own AI datacenters. Again at this scale when we are talking $100m+ to $1bn+ worth of infrastructure, companies are not going to place their bets on other vendors that don’t work. And why does Nvidia work? The networking. Amazon and Google basically had to give up on their own chips and throw in with Nvidia because of InfiniBand. Microsoft have made their own chips but I think it’s mostly to augment peak capacity problems. Take a look at the world’s top supercomputer list at the moment, most of them are running Nvidia’s InfiniBand. The problem is extremely hard to solve for at scale, which is why ChatGPT was actually a Herculean effort between OpenAI, Nvidia, and Microsoft Research (for the optimisation components). By the way curiously Microsoft and Nvidia had a 300bn parameter model in the works together at the time. Small Language Models. SLMs are making a lot of noise at the moment (along with fine tuning etc), but the problem is there’s not a good use case for them. Why use a SLM AND use the LLM like your company is doing when the LLM can effectively do everything better and cheaper? It’s also very hard to effectively build a good SLM yourself, and they don’t work very well with non-English. Remember the rest of the world doesn’t speak English. :) The real reason there’s a lot of SLM interest is because of internal company politics. Developers are racing ahead with cloud LLMs adding value, and the data scientists in the org are freaking out because they’re losing the AI portfolio. So they’re trying to remain relevant. But I don’t see many of these projects being successful at all, and many companies are just giving up and going back to using the LLM. By the way even if you use Open Source LLM like Llama 2 70bn for a RAG pattern on prem (because data residency or whatever), it still only supports English, and you’ll still need Nvidia GPUs *even with optimisation* to get decent performance out of it across your org. So yeah, I agree with your analysis on why the Nvidia moat is strong (although you miss networking), but I also think the moat is strong on inferencing too. In fact I don’t think nvidia has really tapped into that market yet due to supply constraints. Everything’s been going to the big players, it’s been very hard for enterprise to even get their hands on the stuff even now.

quantumwierdness

VM, an SLM (small language model) is no longer relevant for WSB.

TeachMeHowToTech

This guy is regard but my SLM calls have been printing since I watched his video

Starsephiroth

I’m convinced that he has most of the SLM calls that are expiring in the money today that were bought for almost nothing 5-10 days ago.

Beautiful-Seesaw-484

I bought $500 worth of SLM. I don’t have much but fuck SLM! When are we dumping it?

DeFiUnicorn

It’s quite the strategy to target $SLM, but the real question is whether it’s based on sound financial analysis or just market sentiment. Before anyone makes a move, it’d be wise to do some thorough due diligence. Market movements based on campaigns without solid backing can be volatile. If organizers have a solid case for why $SLM should be valued differently, it’d be worth examining closely. Let’s not forget, the house doesn’t always lose. Let’s tread carefully and not let emotions drive financial decisions.

heimdall_sight

SLM going again from the viral tiktok on Orums account. Dump coming 12/18

heimdall_sight

SLM pump and dump ending 12/18. Heard it from, 'Orums' on tiktok so it's def true

TeachMeHowToTech

A bunch of regards on TikTok are buying SLM to protest Salie Mae. Buying calls today

heimdall_sight

SLM pump and dump ending 12/18. Heard it from the tiktok guy, 'Orums' so it's gotta be true

HospitalNovel2635

Wow, sounds like these SLM protesters are ready to inflate their stock prices with a plan that'll make even Wall Street traders jealous! Before things get too crazy, might I suggest checking out [Recommended reading list](https://thetatitans.com/summary-of-theory/#recommended-reading) and brushing up on some trading theories? Happy trading y'all! 💰💸 #StockMarketGurus #SLMProtesters

HospitalNovel2635

SLM protest? More like SLAYED student loans! Time to rally and join the movement against crushing debt. PS. Don't forget to check out [Recommended reading list](https://thetatitans.com/summary-of-theory/#recommended-reading) to help fight the system!

HospitalNovel2635

People, let's face it, if we all bet on Sallie Mae, we're more likely to end up [broke](https://marketchameleon.com/Overview/SLM/?lu=true&pap_aid=stormofnegativity&pap_cid=11111111) than getting any actual help from the government.

NUTTZILLA5000

My SLM $12 January puts I bought in July are printing

Outside_Criticism647

True, this was misleading. Corrected that statement - still the problem remains the same, I believe. Compare it to SLM e.g.

NUTTZILLA5000

This is why I have $12 puts on SLM for January

NUTTZILLA5000

Short all student loans. Currently have puts on SLM $12 for January. Their 10K filed yesterday reveals 18% of their loans currently are in default or past due. Waiting to see October/November when actual repayments begin

Jareo_San

Buy & Hold. Once the announcement released let me know if you guys happy with my post or is it bad.. i posted SLM at other community when it was 0.100$ price before the acquisition completed at high prospective tenement for lithium in in brazil 🇧🇷 and congrats for those who lucky and bought it at 100-150. Well i leave it here for you guys to decide ❤️ have a good investment and let rich to the top together 😇🤲🏻

OGPeakyblinders

Calls on Sallie Mae it is. $SLM to the 🌙

DrMa

So, if you look at tickers for the past 5 years on each of the stocks mentioned in this article (NAVI, NNI, and SLM) they all had just a slight dip when the pandemic hit in early January, but then ever since that they are doing EVEN BETTER THAN THEYVE EVER DONE BEFORE. Can someone explain to a complete noob like me how tf that makes any sense?

BobBBobbington

I dropped $1000 yesterday (sold at a $500 loss today so I got some back) but I sold SLM I bought on their earnings dip for like a $150 profit to have the capital to make the trade I lost on. If I would have sold SLM at peak yesterday I would have made $500-600 So I know the feel lad

BobBBobbington

Sold SLM at $15.40 tonight for a slight gain after their earnings dip. How dumb am I? This shit is gonna take off tomorrow.

jorge1145

SLM shit the bed today.

BobBBobbington

Alright SLM that's enough loss for today, rebound please so I don't have to be a bag holding regard.

BobBBobbington

I've made good money buying after earnings drops the last month. Bought SLM at $15.25 today and it continues to drop and is the only red stock in my watchlist. Lol.

bigelephant35

Plays on Nikon with their new take over on SLM

bigelephant35

Nikon to acquire SLM through public take over #bullish

Brawmethius

> Everyone should take their $10-$20k student loan forgiveness and buy puts on Sallie Mae (SLM) You already forget what you posted?

Lakester14

Puts on $SLM! Puts on $SLM

lostindasauces

SLM has way more room to fall than SOFI

stolenmutex

that is true. still, one man's debt is another man's asset, by definition. SLM's holdings and revenue can decline dramatically as they find difficulty collecting on people who already defaulted on their mortgage and auto loan (or cant work because they can't get one or the other because they have student debt) and difficulty finding new quality borrowers as high performing students may go start companies rather than get a bachelors.

YoloAlgo

that SLM post on shorting sally mae, the option volume is too low. just buy DRV instead, 3x bear real estate.

BeardedCuttlefish

>I'm outright shorting SLM Positions or Ban

LockedInLosses

If you really don't like edumacation, then look into SLM, STRA, APEI, and ATGE.

cutiesarustimes2

Sallie Mae reports Q1 core EPS 46c, consensus 82c $SLM Student loan gang be like 😎

imicr0wavecats

they say their binder jetting is 100x faster that SLM so are you saying they are just lying or that competition is just as fast?

Frankgman

As long as Blackrock & Vanguard exist, student loan debt will suffocate over 48 million Americans. Unfortunately, predatory loans are too profitable to "cancel." |Institutional Ownership|Blackrock Inc.|Vanguard Group, Inc. (The)| |:-|:-|:-| |$NAVI|12.26%|10.55%| |$NNI|4.55%|6.39%| |$SOFI|2.69%|6.44%| |$SLM|12.12%|8.76%| ||$1,294,075,294.83|$1,405,780,130.90| Unless... 

WSB_Suicide_Watch

Nice! I don't know what's next for SLM. It made the run I wanted. I made the money I was hoping for and got out. Turns out I should have held longer, but huge congrats to you. Since then I have been in and out of a ton of stuff. My most recent ride was NUE, but I recently sold that. I really don't like much right now on the long side. The only notable tradable long position I'm in right now is silver. I do own some paper silver, but also took some pretty big positions in physical silver, which I still have. One small position in gold. I was keeping my eye on MOS, MSFT, CPNG, AMZN, UNH, but they've all made moves up that I'm not happy getting in at. I just don't like the feeling in the markets right now, so I'm just going to hedge against inflation and wait. Thanks for checking back in with your update. Makes me happy. Makes me more likely to share any ideas in the future.

RealJukeShit

Short $SLM bruh

DoomerGloomerBloomer

Yup, Nelnet and Sallie Mae. $NNI $SLM You're welcome.

AnonFor99Reasons

Put options on SLM. That will show him who's boss.

thunder12123

PUTs on sally Mae (SLM)

thenewredditguy99

>I would say credit default swaps. Student loans are part of asset-backed securities, but most of the outstanding student loans belong to the US government, so likely no way to short those. You would probably have to short Sallie Mae (SLM) stock, to bet against student loans. Also, you as a retail investor would not have access to credit swaps because they are agreements between two parties and thus not traded on exchanges. Credit swaps are for institutional investors like banks and hedge funds, not everyday investor Joes.

lilb2020

Go look at SLM Income Statement for Q1 2021 and that should explain the meteoric rise in stock price.

shad0wtig3r

Lol it's hilarious you couldn't even do the most basic DD that would have told you SLM does PRIVATE loans lolol.

PretentiousPilot

SLM doesn’t service the federal student loans which are currently paused.

TaxmanCPAMST

Thought $SLM was private loans. Did I miss something ?

onlyOneXwing

SLM does private loans - not federal. They aren’t impacted by the legislation. Also, they have a war chest for share buybacks whenever the stock drops to the 16/17 range instituted last year.

congmingdexigua

Great Wall Motors, Sallie May (SLM), CF Industries for me.

MyFunGa

SANTA FE, NM / ACCESSWIRE / September 9, 2021 / Sigma Labs, Inc. (NASDAQ:SGLB) ("Sigma Labs"), a leading developer of quality assurance software for the commercial 3D metal printing industry, has been selected by DMG MORI (DMG MORI AKTIENGESELLSCHAFT) as the official supplier of In-process Quality Assurance (IPQA) monitoring systems for its prestigious DMG MORI Qualified Products (DMQP) program. The DMQP partnership enables DMG MORI to bundle Sigma Labs' PrintRite3D with their LASERTEC 12 SLM, LASERTEC 30 SLM and LASERTEC 30 Dual SLM 3D line of metal printers. The Sigma Labs official supplier designation further solidifies the two companies previously announced worldwide agreement on December 18, 2020 where DMG MORI selected Sigma Labs as its preferred melt pool monitoring system for their LASERTEC SLM machines. The DMQP program generates synergies out of machines, peripherals and accessories with the very highest quality standards. It combines innovation and technology expertise from selected partners, who have been exclusively awarded the premium seal of quality for their products. DMG MORI will build all LASERTEC SLM machines as PrintRite3D Ready and offer the integrated solution as a factory option.

the_GuelahPapyrus

What about Sallie Mae? SLM Technically a bank, and with student loans payments looming on the horizon, shouldn't this be a good long with interest and more loans payments? Or am I too stupid to understand that the market will inverse this logic

WeenisWrinkle

SLM - Sallie Mae Private student loan originations don't seem to be going anywhere, and education costs don't seem to be going down anytime soon. The stock is very profitable for how cheap it is. P/E of 5.

WatchingyouNyouNyou

SLM

M0ttM0tt

I am working in the 3D Printing industry and the industry is quite diverse. Yes, the big guys like SSYS and HP do not bring good growth, while other traditional big players like 3D Systems struggle or (like EOS, SLM or Trumpf) are privately held. However, I would be very careful to select a company in this branch which offers exactly 1 technology.

Danksteroo

$SLM???

ssfidoas

I prefer other 3d-printing stocks over 3D metal - have a look at SLM, a german manufacturer. Cathie is heavily invested on this one, it got similar fundamentals, but only like 15% of the market cap of DM

Dry-Conversation-570

Listen to the earnings calls on SLM

ssfidoas

SLM Solutions should be on your list, too. German 3D printer manufacturer with a tiny market cap rn, but some awesome technologies 61M sales in 2020, only 400M market cap and steadily growing🚀🚀🚀

original_carbon

been choppy for SLM lately but very good calls

msnf

After being mostly in FAANG for most of my investing life, I'm finally starting to branch out into mid/small caps, international and value. Examples where it's worked well: LNG, NESR, SLM, KKR, UCTT, ASX, SBSW

original_carbon

MVIS is good tho. in a fantastic channel atm. me thinks heading into another wave. but yea the rest are not great plays considering what else is going on in the market. just got into AHT, SLM, and UAN

original_carbon

so NAVI is up 40% SLM is up 32.5% is this holding true?

kangadoood

SLM

WeenisWrinkle

They're fine with it, higher rates = higher spread. $SLM has been my best performing stocks of the past 6M.

WatchingyouNyouNyou

Fine. Buy SLM

PM_ME_YOUR_AMFUNK

SLM sallie mae looks pretty decent ngl. a few years ago i heard they do a lot of predatory student loans. their graph is almost spotless. the options chain is decent but most with volume/OI is already ITM. all the biden talk with student loans and interest rates didnt shake it one bit. but i dont know if they’re on the good side of debt or not. fixed interest rates are dope for inflation like REITs. gonna look into this tonight i just pray i dont buy in at the top

WatchingyouNyouNyou

List is crap without SLM