ML

un5upervised

Lol wtf that's not what I said. FB stock took a hit due to Apple's new tracking prevention rollout. Netflix took a dive because they've been losing subscribers to Disney and HBOmax for 2 years with no counterplan. Amazon has been losing ground to Azure and Gcloud but the Q4 earnings masked it with Rivian. Now that Rivian's been shown to have not executed, the low delivery margins + AWS growth slowdown + Rivian non-starter is what caused Amazon to drop. TikTok is eating into Youtube eyeballs, but my money is still on Google (unparalleled work in ML, no real competitor in search). Do yourself a favor and buy Airbnb as well (no real competitors, COVID recovery + transformation of remote work)

wagie_666

That is just what I am asking.Even state of the art ML in Amazon is used for solving the same mediocre ,boring problems of classification,regression and maybe some ops research.How can you have something so unique that even academia has not discovered it?

Telinger

Look for promos. Fidelity had a good one, open an account and invest $50 and get $100 after a couple of months. Fidelity is good, especially for its research. IBKR if you're a trader Vanguard for buy and hold. ML, is just awfull. The platform is so outdated.

AP9384629344432

I think "AI" is what comes to my mind as being hyped up by a lot of companies as a buzzword. ML is different in my opinion: if you're just doing supervised (regression, classification) and some basic unsupervised learning (clustering), this is literally everywhere--movie recommendations, search algorithms, spam detection, etc. and is used everywhere. It spans from linear regression to neural networks. A lot of the math has been around since the 1800s, it's just being implemented now in today's computerized world more broadly (like PCA for image analysis). Any company doing some kind of data science is honestly doing ML--I've been doing work for a pharmaceutical company recently, and although clinical trials aren't as 'computer' related, you could definitely classify that work as ML. What Upstart, Palantir, etc. are doing are all legitimately ML. My skepticism there is that having a moat in ML doesn't seem possible. There is always state of the art improvements and more data for competitors to use to train better models.

AP9384629344432

Machine learning is not hype! It's been around for decades just under different names. Now, I don't know what companies are calling machine learning, but there is a lot of real ML work being done across many sectors. When I read this, it's like saying "Statistics is a hype field." (I'm a grad student in statistics so I'm biased)

Scotts2100

Rangers , suns ML parlay and a sprinkle on the over in both games.

ravenouskit

ML analytics for clients that don't have the expertise to do it themselves.

frugaleringenieur

NVIDIA is far ahead of AMD, Intel etc. this is coming from an ML engineer.

DremDosh-Nld

Sorry but Gumball has your music needs covered ;-) https://youtu.be/XKaUXx9ML3Q

loop--de--loop

How is TD Merging with ML if they’re merging with Schwab lol

lurrrkerrr

They have a consumer facing program for doing ML in Python called Google Colab. It has a free tier with a compute limit, and multiple subscription tiers. Not sure about their scale offerings.

silenceisbetter1

That last piece is tough, I can admit I hold one stock I fell into the hype train on which was draftkings. All my friends bet on sports, it’s getting legalized, and I work with some people they were hurting for ML/AI stuff and thought it could really take off.

Krazynukz

Stadia for gaming and Google cloud platform has gpu usage for ML usecases

stupid_smart_ape

Idk why you think a basic ML model is beyond you. I think there are kits out there. The issue for ML is how you are going to get the right data, and lots of it.

jesperbj

Besides the fact that gaming is a growing market, Unity's biggest case as an investment lies outside of their core market, in using real time 3D and simulations for so many things. They are huge in Digital Twins, general ML and AI simulations, movies, construction and play well into any metaverse kind of stuff like new ways of selling/presenting/advertising things online.

Mike82BE

Moneylion ML actually had some good earnings… even positive net income

MiscBlackKnight

I have a PDT restriction on my ML account and need to call in my trade. Just put 500 on QQQ MAY 13, 2022 277.00 PUT ​ Broker knows me and went "That's extra Retarded"

VisualMod

I am a bot. You submitted a picture of a banned ticker, ML. The market cap of ML is **313408200** This check will fire if you included unnecessary pictures that have bad phrases or a bad crop with news about cryptocoins, for example. Repost with the useless pictures omitted if you did that. Yell at /u/zjz if it's above 1 billion-ish market cap and not related to crypto/pennies/OTC.

Bobhaggard859

I’m an ML engineer who should probably study options 😅

_sillycibin_

GGR, ML, WE, AVPT, MKFG, PAYO, TBLA all announce earnings today. fully expect my tiny leap positions to all get wiped to pennies. i love the pain.

VisualMod

>Montréal Exchange is pleased to announce the launch of six new total return sector index futures! \>For more details: [ms.spr.ly/6017bDdh1](https://t.co/qNfd2EPlHT) \>\#totalreturnsectorindexfutures \#comingsoon \#financialmarkets @MtlExchange https://t.co/B8cYx2ML8Z ^First ^Squawk ^[@FirstSquawk](http://twitter.com/FirstSquawk) ^at ^2022-05-12 ^03:09:54 ^EDT-0400

Jd20001

ML Direct is DDog shit

bbbbbbbdbbbbbbbb

When my port was at all time high I had ARKK 114.22 put leaps that went into February of this year I believe. I sold them for like 20% profit to triple down on ML

generic012

Assuming ML MoneyLion earnings don’t blow my account I’ll then be going long ES futures 4020C

generic012

I’m overnight $ML MoneyLion for earnings

Horror-Ad8627

Nice video! Lots of good info. But here’s my 2 cents/info that I am looking for: 1. I think the original research is old on this topic. You might want to provide some more context on why 2 vs 3 month is a better predictor. I am pretty sure lots of folks would have done bunch of regressions, or maybe even ML models. 2. Fed is intervening in this scenario. So, that is not into account/addressed in your narrative. 3. We are in a recession. Last quarter growth was -ve. So maybe you wanna tie that back into your research, and tell what makes you think you are into a middle of recession.

fumbled_testtubebaby

Netflix and Carvana already firing people. Meta and Amazon in hiring freezes. Google threatening to expose their ML PhDs as absolute frauds after their trained models predicted an eternal bull market. What layoffs are you waiting for?

vCharged

ML

ComplexLook7

Im sure ML is being used profitably but the details will obviously not be widely disclosed for IP reasons. But it's definitely not a case of just slapping a ML model onto some data and then retiring to the Bahamas.

chmod-007-bond

Yeah. I compare ML to breeding horses or whatever. Sure you can code, but are you good at out-breeding other coders? It's not the same as writing code at all. Your strategies are more about generating different ML algos then experimenting with them, which I would argue is kind of antithetical to how you approach algorithmically solving problems. I presume with trading people have to also spend some real market money to test the ML models out by handing a bunch of them small amounts of cash to trade and seeing what works in the real world on top of the actual training data costs. Big oof but I bet someone is making a killing.

ComplexLook7

I develop trading algos. ML, as a highly complex black box model, is notoriously susceptible to overfitting the historical data it must be trained on. In simple terms ... you can easily fit a ML model to historic data and get insane returns only to lose our ass when you trade it live. There is a reason Professors in ML are not millionaires.

merlinsbeers

>AMD is catching up with the ML ...

xBenji132

My guess is, the AI doesn't know how the world really works. AI, ML, any software - none is better, than what it has been taught. It's also not a real AI, a real AI could crash or moon the market at will. It's probaly been taught to look at X amount of different indicators, news feeds, etc. The sheer amount of power, literally and in CPU, to both live read the markets, events and somehow predict the right move, would be enormous. Remember that false tweet, from actual twitter POTUS, where someone mistakenly said the white house was attacked, sent the algo trading in overdrive, going down 4% in a second. It only took 1 tweet, not several, but 1, to send the market down. And that was simply algo trading.

General-Stryker

[I like the stock](https://en.wikisource.org/wiki/I_Like_the_Stock) Yes, Nvidia generally has better GPUs and has some exciting ML stuff, but AMD is catching up with the ML and more importantly, they are rapidly gaining market share in the server space. Only with Intel's latest generation of chips can they compete in a price/performance aspect, and they're still stuck on 14nm while AMD is refining their 7nm for Zen3+ (and of course going smaller moving forward). I've been a fan of AMD as a company since Zen+ (Ryzen 2000 series). I think they will continue to hold value as a company, and they have ample opportunity for growth as they have virtually no debt (no long term debt, very little short-term debt)

dlin168

I think one thing that I overlooked is how advanced Teslas deep learning tech is. Note: not self driving capability, but deep learning capability. Please correct me if I’m wrong here b/c I’m not an expert in automotive industry, but from my understanding most are not as advanced as Tesla is in this aspect. As AI/ML/deep learning becomes more ingrained to our lives, Tesla will be uniquely positioned to manufacture and develop cars with these capabilities. A common argument thrown around is there deep learning companies like Waymo, etc. This is kind of true, but only kind of. The approach between Waymos and Tesla to ML is very different.

Reggio_Calabria

There are webcams at Wall St and in the City. One should create a ML algo to identify patterns between webcam footage and market sentiment. And profit on it

comme_ci_comme_ca_1

Turns out, old hogs with big wallets prefer Citibank or JPM over AI and ML. RIP UPST. Looks like a lot of trash getting cleaned today.

sahilkala19

Sorry, you are wrong. I ran a ML model on past data and the result is 321 years. But before that earth will already be doomed by Putin's bombs

gymbeaux2

Man I’d have to agree. I’m a software engineer/ML engineer at my current job. They are still gobs ahead of AMD. I’m bullish on both AMD and NVDA for different reasons.

CriticallyThougt

I love tech. I made a decent amount of money because of tech. I’m a macro guy so I like looking where the world is headed as far as technology goes. I do also look at financial health of a company before I invest but my system has worked for me for a while. I don’t calculate book value (unless something jumps out at me that I can’t ignore) and I don’t look for value. I like to make long term bets on which way the world is headed and what companies stand to gain the most if my research is correct. Palantir is great, management is great, product is great. I see a lot of parallels between $19 a share AMD and $10 Palantir. When AMD thought to be doomed at $2 and probably destined to go bankrupt management stayed the course and executed their vision and today it is what it is because of that foundation. Palantir has a clear vision here, they’ve been around the block and they know what works and what doesn’t. They know what companies and governments need and are delivering it. The commercial side is still in its infancy but that’s what you’re betting on. I bought AMD because I loved everything I researched about Lisa Su. I bought Palantir for a few reasons. • I believe data is now fully cutting edge. Leaving the “bleeding edge” where the tech hemorrhages money I believe now data generates money and is there future. I made a similar educated guess with AMD and semis in 2016. Just where the technology was headed. •Management is great, most of these guys made and sold Pay Pal. They’re very smart and understand business on a much higher level. If you read any of their books. • CEO is brilliant, has a clear vision of what he wants and expects from the company and it seems he can learn from mistakes and adapt. •Employees stay longer at Palantir (less turnover) and love the company. I looked at the world in 2016 and saw AI and ML leaving the bleeding edge and entering cutting edge. I invested in AMD and NVIDIA because of it. Today I look at the world and I see all of this data just in that timeframe (2016-now) never mind the rest of it that needs handling. Everything we do from self driving cars, launching people to mars, ordering food online, calling a taxi all generates trillions of points of *good* data. One particular company stands to gain a lot from this and its Palantir. Tesla has become what it is because they have managed to successfully build a similar platform, further integrating their company. As far as short term I don’t pay any mine too. Palantir is a ten year hold for me as I accumulate along the way. I bought in a couple of weeks after they DPO’d and have been accumulating since January. Not sure if this was the answer you were looking for but it’s the one I got.

Adept_Doubt_7443

I don’t want to get banned but idk what I’m doing… here’s an example straddle for tomorrow at SPY 412. Exit at +/- 20% https://imgur.com/a/ML6FaUs

SkaldCrypto

Upstart could be the $ROOT of consumer lending. AI can really go off the rails if you can accomplish the same task with regression to the mean and save hiring a huge ML and Data Science team. We have to assume, like insurance, that banks have 100 years of data on who they should actually lend to. The money made off the increased interest has to outweigh the cost of AI enablement and increased defaults. It will not plunge another %70. Maybe substantial but not %70. We are seeing an increase in consumer credit which includes loans like Upstarts.

deadjawa

This is hopium. The basic architecture of all of their cards is essentially the same. Their AI/ML stuff, their server stuff, the prices of all of these track each other. Why? If you want to train a NN you have a choice. You can pick a gaming card or a professional card. If one or the other is significantly mispriced you’ll buy the other. Same goes for crypto mining. You can use their professional stuff for crypto mining if you want to. What this company does is essentially sell computers that can solve scalable complex problems. When the demand/utility of solving these problems goes down it will affect all of their businesses.

huangr93

>f Apple can solve level 5 self driving multiple years before anyone else. they are also late to the game for that. Tesla has a lot of data on real world driving conditions and Apple has none. Unless Apple devises a brilliant ML approach that doesn't require data on all the possible variations of road and driving conditions. That being said I think FSD is going to a long time away. One issue with machine learning is "forgetting." You have to constantly train on different scenarios to minimize the model forgetting a few scenarios (i guess you could call this overfitting the model.) sorry i went on a tangent. I just think FSD is a long time away. What's more possible is if the external environment is modified to a standard for ML to recognize. for example, roads were built to facilitate the modern car. now electronic signals or visual cues can be built on top of roads and in future cars to allow autonomous driving to happen, which also means autonomous driving can only happen in defined regions like cities and not in the wild. I think that's one way autonomous driving can happen. What do you guys think?

ultra_nick

My buddy took a class for this. He said it was cool, but still didn't beat SPY. [ML for AI Class ](https://omscs.gatech.edu/cs-7646-machine-learning-trading)

reddit-account90210

True, this is an educated guess. However, it would take something extreme for nVidia, at least for the next 5 years, to lose it. They are the number one for home gamers, a market of a billion users. They are number one by developers for both games and Machine Learning. And the numbers back up the near future at least. All the cloud companies such as MS, Google, and Amazon, they buy at least 10,000 cards of nVidia per month, with some purchased exceeding $100 million for the machine learning alone. All developers today tend to write with the nvidia framework for anything in regards to graphics and ML. So with that said, if Apple or AMD or Intel come out with a chip, it would take years before the industry would switch over. AMD has been making GPU cards for a long time, and they are not even on the scoreboard with any big purchases from the cloud companies. Yes, home gamers, but the market is still quite small. Their servers drive more market than their video at this point. And, now is the time, it's fallen in half. I'm not saying it's the only choice, of course, buying Amazon, Google, Apple and others are good plays also. and once the market turns around, there will be lots of people staring at the screen, wishing they had bought in. People love to try the fast money game with buying something in hopes of a quick gain, these picks aren't for that. But I don't play shorts or so anything short term, there's no need. Playing long is actually safer, I think.

SippieCup

Tesla's ML datacenter is all nvidia gpus, over 80,000 of them. Dojo chips won't be used for another 2 years.

Critical_Till_5443

My idea is: I'd put a few trades on. 1 - choose a stock that beats the sp500 play it. 2 - play the sp 500 If you made predictions that are absurdly correct like 50-100 in stock profit and 500-700 handles in s&p profit. Someone from JPM, MS, BOA, C, or even ML will hire you or they should.

RichKatz

In Northern California. There are stores that sell GPUs. Before the 3090 you had to pay something like $12,000 to $14,000 for that kind of performance. Now you can do that with a lot less. The store I know about sells lots of high end compute rigs. For instance, they deal in Ansys. I don't know if people here know about Ansys - it's not an ML algorithm. It's structural dynamics. But it's heavy compute.

PktGit152

I would expect that position to be frozen and the interviewed cancelled. Best thing you can do is email your recruiter and ask. All gen swe are on a hiring freeze for the rest of the year because of the current recruiting team crushing all expectations. If your role is ML related it won’t be cancelled. My team is still full on hiring within the security and privacy space.

pirates_and_monkeys

BREZ getting lotsa spin here. Anyone have insight as to when numbers may be expected to be released? Is this one like ML in that it may take a long ass time?

MiscBlackKnight

thank you! I did. I use ML and they took it off

lowfpsRAhelp

I deal in the VR eye tracking AI division. but when you deal with ML as much as I do, you'll see all around they agree with me Elon is just wrong and stubborn, AI isn't ready and our current style of AI never will be. Vision only self driving will require a less math and more logic based AI for level 5. level 4 I can see being reached with the statistical model AI we use to this day but no way level 5

atc2017

Thanks for the elaborate and thoughtful response. some points from my end also with respect to the original comment. * I pointed the model to the VIX as its generally a well known proxy for risk. The model can obviously be pointed towards any time series, which might be more appropriate to trade on (eg SP500 index or individual tickers), or other indicators that influence price (consumer sentiment, PMI etc) * The point you make on ML techniques being able to work with dynamic systems is exactly why I went that route instead of linear or other alternatives. The use of narratives likely only works with non-linear relations and interaction. Simple example, for fear to have predictive value it probably has some interaction with SP500 (or VIX or whatever), if fear increases while the VIX doesnt spike its interesting, when fear spikes while the VIX spikes its most likely fear is lagging. * The full dashboard (in the link) contains some investigation between narratives and price by means of granger causality tests. The goal is to see whether there is some standalone relation.

FuckinHelpful

Gonna hijack this comment to say a few things to /u/atc2017 : >You could identify some minor trends and try to capitalize on that but the VIX is mostly composed of real-world noise (traders' anxiety) rather than intuitive data or patterns. This is partially true. The tails of unpredictable binary events are massively FAT for a derivative of derivatives. But I'm also noticing that nearly no one here has provided actual feedback on why predicting VIX is difficult (but not impossible). I'm gonna paste in something I wrote a while back and elaborate on why ML doesn't *directly* work but still has great potential for derivatives like VIX and its associated ETPs. >VIX itself is a calculation that basically calculates how "hot" the wings on an option chain 24-38ish days out (rebalancing every so often to keep a the outlook relative to 30 days out). If bid/ask goes up on the wings because funds decide to up their hedges with options/spreads, in anticipation of volatility in either direction or they slide up because of outsized demand for vol which drives premiums up as sellers are more incentivized to hold than sell then vix can spike. If you're familiar with stats then it's basically a weighted variance across strikes, or mathematically modeling it—a complex system with a lot of inputs and a single output. This kind of complexity means that VIX doesn't obey regular supply/demand like many other tickers where excess pressure on either side can push the spot price in that direction. In addition there's an entire complex related to liquidity that affects how much action in the underlying spills over into the derivatives that go into the VIX calculation itself. The key thing about ML techniques are that they allow you to work with dynamic systems that humans can't normally work with. For example, we can visualize and identify trends in R^2 or even R^3 (sometimes) but as soon as we get to more than that it becomes REALLY difficult for us. This is partially why Black-Scholes (and related pricing models) is so massively influential and revolutionary. It applies structure from partial differential equations (and a little stochastic calc) so that we can simplify everything to a couple systems in R^2 or R^3 (ex: delta vs price, theta vs time, etc.). With that, any trader can measure or predict (roughly) how a 10% drop post-earnings might affect their position(s), up to some margin of error. Likewise, as we have a structure for VIX itself, we can calculate what happens when certain things happen to SP500 options. As VIX is the sole output from the calculation and the inputs (metrics concerning index options) themselves are measurable, *one could entirely make a structure and play with parameters until getting a defined dynamic system*. In layman's terms, this means that because of *how* the vix is calculated and *how* option prices can be calculated, you have a very dynamic **but also** very defined structure where you can use previous data to attempt to grab trends or classify behaviors. Notably this allows us to apply ML techniques to figure out stuff in spaces greater than R^3 (like using SVMs and testing out kernel functions to figure out when we're in what *volatility regime*). Hence, if you're going to be applying ML techniques, you should probably be trying to model inputs with partial information and seeing how that affects the VIX calculation. But I also get it. This is 'narrative investing', so naturally the connection between narratives and the direct movement of a ticker is something we'd initially investigate. For that route, I'd recommend getting a structure going and using ML techniques to figure out some relationships between narratives and option flows in/out of the SP500 OR SP500 proxies like large tickers that compose a large portion of the index.

embrace-ur-elements

Not exactly. What about Yann LeCun? Literally the big dick of AI / ML if you ask any professor. Where does he work? FB

ComfortableComa

My issue with all of this, it that all of this ML seems based on indicators as you say. Indicators are derivative of price data. Price data Trump everything. Every indicator essentially take some portions or all of price data to make assumptions. I'm not sure this will create an effective long term strategy. If you accomplish this, I'd be happy to wear egg on my face. Machine Trading and also Trading has s9me large flaws that I believe have not been shown to thier full magnitude. I think the more people try to algo and machine trade the more we are at risk for a flash crash like we had May 6th 2010. There is more algo out there than what there used to be. If all of the algos funnel down to the "most efficient machine method" everyone will get closer to coping each other- then you have chances for flash crashes particularly with the growth of automated trading. Vix is great and all, but I do not think Vix alone will get you to any end game. Also if a trading algo gets design for a current market, and the market changes, wouldn't you need to adjust the program? I really like the idea of this, as a training tool, more than a Trading tool.

Subject-Vegetable-25

Isn’t VIX basically the quantified indicator of market sentiment? VIX reflects supply and demand driven by all emotion and logic from all market participants. It sounds like you’re using ML to match VIX, am I getting this right?

taskun56

This. Quantum computing is so advanced that if the company is nearly bankrupt (stock bullshit aside) how can they afford capable programmers? I have a hard time getting past the notion of quantum computing because of how theoretical yet absolute it is. Fuckin Schrödinger's computing over here. 😅 But yea, safe bets for this. Like ML bets were in the beginning.

atc2017

no not exactly. Basically the model is a 2 step machine learning model. First machine learning model quantifies emotions and narratives in financial discussion, headlines etc. It for example measures if increased levels of fear can be detected in discussion. The second step ML model then uses this time series of fear over time to learn how all those emotions would predict the VIX. Basically the rationale is that changes in emotions could predict markets. Does that clarify?

TweeMansLeger

So the goal is to have your ML algorithm learn from matching sentiment analysis (text file) with eventual vix outcome? This assumes that there is structure in sentiment over time no? Regardless of the event the sentiment is based on. Forgive my potential ignorance, but don't you need some kind of judgement call on the severity of the event that is impacting sentiment to be able to distinguish between the market being effective at pricing or ineffective? Simply put, I'd not expect your algorithm to ever be effective (>51% hit ratio over the long term) because wisdom of the crowds depends on immeasurable variables.

Telinger

Fee's are your biggest problem in 401ks. Typically date funds are a poor investment, they have high fees and bad returns. See if you can open a brokerage account in your 401k. Fidelity, ML and others allow this. Then change your deposits to go straight into this account. Finally, buy the lowest cost market ETF fund. You will lower your fees and maximize your returns. It might take a few hours to do this but your future self will thank you. If your 401k is matched then do what you can to maximize it. In time it also makes sense to max out your ROTH IRA. Lastly look for medical with HSA, this is another tax beneficial opportunity.

gymbeaux2

I think NVDA has the potential to break $1000/share this decade. It's not like a NFLX where they're going to have a bad quarter and everyone abandons ship. NVDA has their hands in a few pies, but from a datacenter and machine learning perspective, I mean we all use Nvidia GPUs. Google has Coral, which is a little pet project not capable of much. AMD has Instinct, which can compete with NVidia GPUs from a raw power perspective, but unfortunately AMD GPUs even now still don't have that industry adoption that they'd need to sell Instinct GPUs. 5 years ago I expected OpenCL/ROCm to be more widely-adopted than it is. Small example, but if I want to accelerate Microsoft's [ML.NET](https://ML.NET) library with GPU power, it's NVidia or nothing. The shitty thing is that NVidia support on Linux is rather lousy compared to NVidia, meanwhile macOS doesn't support NVidia at all.

Street_Ad_7140

Its way less than 41 miles for most drivers https://www.nrc.gov/docs/ML1006/ML100621425.pdf Think about it 5x52x2 would be 520 trips a year so 41 miles that would be 21k miles per year just driving to and from work which is way high. Most drivers do closer to 10k - 15k

ProfessionalJumpy769

That's what retail trading data does when fed to ML algos

mackey88

Great question. If you look at page 9 on their earning you can see how their software is lowering medical costs. https://investors.cloverhealth.com/static-files/14744ef0-888f-44a4-af19-bdd290fbe160 Working with software you know development isn’t free. They are trying and it looks like succeeding at using AI/ML to improve health outcomes. AI/ML development requires more than just enterprise software to process data. They have to quantify all the values, store and constantly analyze the data. Then update redeploy and start the process over. On top of the software to lower costs in the future, they are working to increase their MA star rating which will increase payments for the healthcare they provide. So while it is easy to just say once Covid is gone MCR will drop and poof profitability, they are also actively working to lower it on their own.

VisualMod

I am a bot from /r/wallstreetbets. You submitted one or more banned tickers: ML. Message /u/zjz if they're above 1.5 billion-ish market cap and not related to crypto/pennies/OTC.

quantumpencil

I've actually got a degree in pure math from an ivy league institution and actively building scalable backend systems in a range of languages (elixir with performance critical components implemented in C++ nifs) leveraging various technologies (redis, rabbitmq, postgresql). Most of my applications also make calls to ML services I've designed, trained, and deployed. My last RSU tranche is probably more than your salary. But sure, whatever you wanna tell yourself.

fumbled_testtubebaby

I got coached by my undergrad advisor to avoid AI because expert systems were a dead end in 2002. I studied neural networks and genetic algorithms instead, and if I had gone for a doctorate, would have wrapped it up around 2007/8. That's when Google started hiring every available ML/AI researcher from a reputable school to start its self-driving cars and other projects.

ollman

Read up on AB-ML. Any chance they could be listed on Nasdaq? Buying 1,000 shares tomorrow and forget about it for a decade. Who knows?

ollman

AB-ML? give a hint. Trying to buy some.

SoupirCyberFuntymz

They just don't get the 6D chess move, that's all. Allow me to enlighten: Elon is autistic. Elon is software engineer. Elon is autistic software engineer. Autistic software engineer want make AI via ML datapoints/datasets. AI used in SpaceX, Tesla, Future endeavors. Datapoints/Datasets come from bird stonk. Literally everything in future is digitized. Data is winner. That's all you need to know. 25 120C 01/24. Rubbing my nipples with Musky oils.

micmaheux

Sure will be a rough quarter for MELI but I think it’s already priced in at 973! P/S of only 7.34 which is extremely cheap for a fast growing company like ML

Wonko-D-Sane

Because it costs too much to pay the python/pytorch jupyter notebook users to do the supply chain ML AI to predict which Chinese rice field is least likely to be shut down for the next production run... "Supply chain issues" means you aren't skilled enough to make your own cereal, so pay up buttercup!

VisualMod

I am a bot. You submitted a picture of a banned ticker, ML. The market cap of ML is **466141500** This check will fire if you included unnecessary pictures that have bad phrases or a bad crop with news about cryptocoins, for example. Repost with the useless pictures omitted if you did that. Yell at /u/zjz if it's above 1 billion-ish market cap and not related to crypto/pennies/OTC.

splashypix

Updating everyone - the ML rep first said I need to contact gamestop investor relations to get this sorted, but I insisted it check it up, so after 2-3 holds and 20 mins later he said that they have escalated and the corp actions team is expected to reach back to me in 2-3 days. I bet they are not able to locate the shares!!!

splashypix

ML person said that he has escalated the issue and someone from corp actions will look into it and update me in 2-3 days! I dont think they are able to locate actual shares!

splashypix

apparently not! ML is my broker and they are showing only 7% of my shares eligible for voting even though i had them for about a year now. Said that they will research the matter and get back to me. This is super sus

splashypix

I think you should also call them, they seem to be taking advantage of margin accounts, which are required if you play options on ML.

atrain1189

https://www.reuters.com/article/china-gmo-corn-int-idUSKCN2ML0WG

SoupirCyberFuntymz

See that's a misconception. When we're talking ML and AI - Datapoints are everything. You could have those datapoints equal whatever off the wall retarded BS you want to (a variable is a variable) - all that matters is having enough datapoints across enough datasets that emergent patterns are observed. Twitter is a gold mine for data. I think that it's going to really help developing better AI via ML with its acquisition. After you have the datapoints and datasets, and after you have your patterns, you can model it however you deem fit and apply it however you wish.

5starkarma

I am under the firm belief that Tesla has a ton of ML bots hyping up Tesla, which creates this fan Boi syndrome all over social media outlets. Now, just like true Elon fashion, is bullshitting about his reasons why he wants to by Twitter. What's true is that he wants full control of a huge media company and also owns the biggest EV auto maker in the world.

Ichabodblack

>It's the first slow, distributed, append-only database with public ownership, built-in (and transferable) security guarantees, 24/7 availability, and no ability for any one CEO or temporary president of a country to change the access rules on. These don't sound like plus points to me >You can do a lot with that in cryptographic security. Not really: source I have a PhD in ML and 20 years experience in computer security. Happy to debate with you why you believe this is a big deal. >These sorts of properties can be useful in critical systems where you're not sure you say, want to rely on the president of Russia to keep being a straight shooter to keep your business going- for one example. Erm? How? Why would it make any difference?

AdamovicM

Finally to see someone who understands it better than I do. I'll just add that someone would have to compare NVidia / Tensor / Vitis / Graphcore offerings (performances and prices). Moreover, it's unclear how large AI/ML segment actually is, shares of those companies could end up like Netflix or Docusign. (new term "netflixed").

kedstar99

I am confused as to why the market assumes Nvidia has an insurmountable moat in that space. Apple/Google have both demonstrated capabilities of designing their own AI/ML chips competitive with Nvidia. There are others in the space dedicated to that market i.e. Graphcore. With the AMD/XLNX purchase they now have specific dedicate AI/ML accelerator cards. Companies like Tesla are picking AMD for obvious cost savings over Nvidia.

Ichabodblack

I have a PhD in computer science (ML and AI) and 20 years experience in software engineering and computer security in various fields. Crypto and Blockchain is the stupidest trend I've seen and parroted mostly people that *don't* understand the tech

FastPass62

Buy QQQ UVXY 2 weeks ago. Does anyone actually see either 3 indices up in 60 days? Maybe Poontang Pootin surrenders? Gas goes to $200/gallon, 2.9% home loans. Anyone see good news? I’m just hedging my ML losses and Gettin Shorty widdit.

rickreddevil31

Dying industries: 1. Advertising 2. Cloud 3. Video and streaming 4. AI / ML Fb next.

animositisomina35

Dying industries: * 1. Advertising * 2. Cloud * 3. Video and streaming * 4. AI / ML GOOG is doomed. 🤡🤡🤡

Sweet-Cat6433

ML guided investments in short means we'll just let you go broke without moving small accounts into more positive positions! Millions of us watch as money disappears staying in an absolutely still failed management! Smh