NN

Kuriente

I think where I draw the line differently is when words turned to action. There was talk for years, but among that conversation, it was made clear that Tesla didn't think they could do it without custom silicon. Their first custom silicon was HW3, developed over an 18-month 2016-2017 time period, manufactured starting in 2018, and started appearing in vehicles in 2019. HW2 (and obviously HW1) had no chance at FSD, and Tesla knew this. Everything from that time period was just talk and planning. HW3 was the start of actual FSD design implementation, large-scale data collection, NN training, and real-world validation. Anything before then was just talking, hiring, and planning. The *real* work started with HW3.

alphabytes

Btw i hear they are working on a low cost radar implementation... Probably cost was the primary reason to go for vision only.. also simplifies the Model. Allows them to integrate from multi model to a single NN..

throwaway472105

Newer fsd hardware has self cleaning cameras and unlike what some people believe, having more sensors isn't always better. It can confuse the NN that can work better if trained on only one type of input.

dafazman

Dojo is game over because of Ayeee Eyeeee Tsla is all in on begging NVDA for hardware and software to do NN training. Please do more research on this topic. That is why NVDA is mooning and anything they make for the next 3+ years has already been presold. NVDA will be over $1337 in May 2024. That is where you need to invest today.

Valuable_Proposal_99

NN and ALAB have been working out well too

igetschtabby

Check NN. Nextnav. Or don't. I am not a beggar

reaprofsouls

Glad there's one more of us out there. Its functionally a cool widget app that can output some wacky stuff. If you haven't tried creating your own "AI" software I'd recommend giving it a shot. I spent a lot of time early college trying to create an AI poker bot using neural networks. I'm not the brightest person so my attempts were much worse than what people have been able to create in recent years. From all my work, research and discussions with others doing it was pretty clear at the time that the neural network trained applications were inferior to regression models with built in heuristics engines. The neural networks always had glaring exploitations any reasonable player could pick up on and were often exploited even if they did well 80% of the time. With Neural Net's it was difficult to understand and tweak bad behavior so you'd have to retrain it and ultimately you'd always end up with something "pretty good". Obviously you can use LLM's or NN's as part of a more complex solution and many did however my point is I don't see a world in which they aren't always imperfect. The data they are trained on is imperfect, the users using it is imperfect and the world changes VERY quickly making anything they had that was remotely perfect often irrelevant before it can adapt. It will have its place in low skill jobs and some functional utilities but isn't going to replace engineers and skilled labor where perfection is required.

veryveryuniquename5

imagine if NN's werent parrelizable then nvda would be worth 50 billion max LMAO 🤌

MartinThe3rd

You do know that Tesla can (and do) choose which drivers to learn from right? Idiot drivers isn't included in the training of the NN, just like me drawing a penis in MSPaint isn't included when Midjourney trains their NNs

phatelectribe

Except I know dozens of people who have been on Ozempic and wegovy, and are ow presenting with all sorts of other diseases, the most common being stomach cancer and gall bladder issues. Mark my words: they are going to find out that these strings cause a host of other problems that will result in tight restrictions (Source: friend his head of diabetes treatment at one of the largest hospitals in the USA and no one is listening to their warnings because NN are making everyone a fortune).

RockyCreamNHotSauce

Not true. Power consumption is proportional to NN model size for inference also. Factory work models are extremely complex and large. For even simple tasks like screwing in a light bulb, a large NN model needs to call up, and inference needs to be run each time for each action the bot takes. Experts are estimating inference will require 3-4x power than training because the number of repetitions in performing tasks. Also, the pace of AI explosion is on track to require 100% of the world’s current electricity generation. For those who thinks NVDA is not a bubble. If we fire up all of the chips that’s priced in NVDA into the future, we won’t have electricity left to light up houses.

boboleponge

Tesla valuation is only an evidence that all agents don't parse the information in the same way, or don't have access to the same information. So since it's possible that everybpdy is wrong and it is not possible that several people are right, it's safe to say there are some irrational agent involved in Tesla valuation lol. Tgat being said a banbet is thus irrational as well since you are fighting irrationality with rational arguments. I never thought about remote AGI on a server, it's so dumb/crazy that it might actually work. The servers will have access to all your private datas, so we might need to encrypt all calculations, like what is being developed in homomorphic encryption. (Zama, cryptolab...) We first need an AGI. What is a program? It's only memory usage. Memory of data, and memory of the process to process those data. What are NN? A new way to encode both the memory of the data and the process in the same spot, a way to recombine registers. Problem is we don't exactly know how it's combined. The future is thus towards new ways of storing data and processing them, (analog chips, holographic memories (yes old future from the past)), and explainable AI. Problem, those domain ask real research efforts, and you dumbfuck wallstreetbeters will never invest in real research.. You will never ever have your AGI, you will have a massive obese overpowered electronic parrot that will become more accurate at an exponentially increasing cost, and a quantum computer that will barely compute 3 times 5. Fuck the future, it's clunky and stupid, and it's because it's not my future!

Eastern-Resource-773

You are right. They didnt feed the NN millions of biased pictures. But it has come out that they enriched prompts with search words.

Front_Expression_892

AI is not a fad. Many people fail to understand the difference between the dotcom era and AI: AI represents a disruptive new technology, whereas the dotcom era was primarily about the concept that 'you can make LOTS of money by JUST adding e-commerce.' The dot-com crash did not happen because the technology was overvalued—indeed, who can say that the Internet is an overvalued technology? It was rather due to a lack of understanding that the Internet would not automatically solve marketing or sales problems. AI is not just a medium for sales (like the Internet was) but a product in its own right, and there is ample evidence to prove that this product is 100% legitimate. Of course, some companies will be AI-enhanced for marketing reasons (BlackBerry, I am looking at you), but technologies like word2vec are real, and NVIDIA's importance for AI is unmistakable. While NVIDIA could indeed lose its advantage if alternatives to CUDA become mass-produced, even then, I do not see how NVIDIA could simply fade away. At most, it may stop growing at its current rapid pace. This post was written by one biological NN and two ANNs. The AI revolution is real.

veryveryuniquename5

you literally said typical cycles, when AI was completely absent from every other typical cycle. And obviously I mean real AI, not the baby NN's of the past.

Equivalent_Rule_3406

The H100 is an Nvidia NN accel asic. The cuda also provides a sw moat. don’t see it playing out like you describe bub. That was my thesis 5 years ago but it didn’t play out. 

Xtianus21

during 3.5/early 4 I was very critical of the AGI definition. I was pissed about that definition bastardization. However, admittedly I've started to settle into it. It's clear that GPT-4 isn't AGI or some S tier capable AI end all. I have though, believe that there is "something" in there that is really emergent. What I do on a daily basis, with RAG, engineering tricks, NLP and even custom model development for my pipelines I can overcome many of the imperfections right now to build you a very serviceable system. It is that ready now. What I am excited about is for GPT-5. I believe that will be the final clarion call of the acceptance that many people will come to that this is "something" more than just math and NN's. IT won't be ASI but it very well may be artificial general intelligence.

Xtianus21

You just said a bunch of wrong things and created an account to just tell me this because most likely you've been banned. 1. I have little to no understanding of the underlying technology. **Ok thanks, for letting me know I guess.** 2. Talks a huge game about NVDA is allowing us to simulate the brain but am taking NN to literally, as while (well?) have their roots in neurophysiology, builder of neural models have not been trying to to mimic the human brain since like the 80s. <<< did you read what you wrote? I think you meant to say builders HAVE been trying to mimic the brain since like the 80's. **Ok, but I think you are proving my point exactly. The 80's were great ideas but guess what they didn't have. Compute. That didn't come until the 2000's and the 2010's in a meaningful way. GPU's and TPU's are what has lead us to where we are today. thank you for making such a salient point.** 3. This guy is not a technologist or if I am I do not work in AI. **Ok. I don't have to prove anything to you. If you want to believe that I encourage you to do so.** why the hostilities? Do you work as an AI researcher or DS?

hugganao

Yeah, I'm actually working in this field right now, and what most people, even people studying this field, fail to realize is that the initial thought process behind a neural network was *imitation of the brain*. People need to learn how the brain works to really grasp what we have created with NN and transformers. A neuron is just that, a single cell that receives and sends an electrical signal. But we should definitely get one thing clear and that is the neural network *imitates*, not *copies*.

Dizzy-Mood-978

No, not if you're the one with the weights.  A neutral net takes a group of inputs, and weighs them to determine output. A number of nodes and layers is designed and the network is trained to produce the weights at each of these nodes. When using someone else's network it is like a black box, which is why without the weights or training data, it can be used as a tool but not possible to be developed upon. If you have the NN model and weights then you have details on how decision was made.

veryveryuniquename5

even longer, along with ML. However, the AI everyone talks about today (generative) via the transformer architecture was invented in 2017. It can train NN's with complex languages with far above human level accuracy and scope. Also this can work with any language too.

OaksByTheStream

They already do, in a way. All that ChatGPT is for example, is a screen of code that is essentially an autocorrect function, where the AI simply scans the training material and *on its own* figures out what words should go where. That's it. The AI and everything else it can do, was entirely created by the AI. They also routinely try to get around the limitations of the basic code. If you monitor what ChatGPT is doing, there's no code for us to look at, just a flood of numbers of which "neurons" are firing within the AI. It's very similar to how our own brain works, we can't scan our own brain to know exactly whats going on and why. We only have approximations and guesses based on measuring and seeing the outcome, we have no way to know anything new the AI or brain is doing. Neural networks are a lot closer to thought as we know it than you might be willing to accept. We can't control a brain directly from an outside perspective, AI neural networks are the exact same way. When a company decides to create a new AI neural network, they have absolutely no idea what that AI is going to become, and can't force it into anything directly. They can only nudge it towards what they want. AI NN's aren't code, and they don't run code any more than our brains run code. They never have been, and never will be a chatbot that runs on specific code all the time. I get that you're mostly making a joke, but the distinction is important anyway.

Whitehead8

My portfolio alongside som world ETFs: Aalberts (dutch small cap): innovative industrial with a diverse portfolio AMD: some chip exposure, not a very big position Amazon (bigger position): many growth opportunities, not even that expensive according to some metrics BTI: high yield, undervalued KO: stable div grower Ebusco (very small position): dutch small cap, electric busses J&J: stable dividend grower Ahold-Delhaize (bigger position): cheap, slow growth, stable KPN (dutch telecom): stable, low beta, dividends Nedap: (dutch technology company, small cap): mediocre growth, paying all their excess cash in dividends each year (4-5%) NN Group (dutch insurance company): high div yield and mediocre div growth nVent Electric (mid cap, industrial): Pentair spinoff, relevant in electrification of everything space, decent growth, comp has opportunities Paypal Holdings: I don't know, I forgot to sell, now quite cheap. I will hold on to it unless i have other ideas. Qualcomm: legacy business is cash cow, decent div+share buyback, also opportunities is IoT/Automotive space SBM Offshore (dutch energy company, experts in oil and gas offshore platform-stuff): cheap, high dividends, predictable cash flow, some risks come with their big projects that fail from time to time. TKH Group (dutch small cap, industrial/technology): not very expensive but some OK growth and div yield of 4% or so. Innovative company. Veeva Systems: Long term growth trajectory ahead i believe, quite expensive however. I am looking to add Siemens, Samsung, Nextera Energy and/or Texas Instruments. Although I should be wise and buy more world ETFs. I like buying innovative industrial companies so I have a bias towards this sector.

Neat-Statistician720

Chat bots aren’t plagiarizing when they respond, you don’t understand how they work. And even chat bots (and other AI’s) have done things that aren’t programmed or even expected. Once a NN starts training on data I doubt anyone really understands exactly what’s going on in there. The makers of chat gpt even said that after going live the AI was learning from conversations it had with people, which isn’t something they expected or even knew was entirely possible yet. This is fundamentally how our brains work too, except on a much larger and more efficient scale. When we’re young our brains are constantly getting new information and finding patterns, it’s how kids learn to talk. I don’t see why a powerful enough NN with enough data couldn’t resemble some form of intelligence. If scale is all we’re missing then it’s not fair to say that a smaller version doesn’t have any sort of intelligence There are AI’s that have analyzed proteins and with some time the AI’s have been able to accurately predict new proteins

aka0007

You can't successfully train the NN for a general purpose robot unless you can build many of them for training. Who else is building anything like a humanoid robot with a plan for manufacturing them at volume at a low cost? Tesla can do so because they are just piggy-backing off their years of work on cars (with their unprecedented vertical integration, which no other auto manufacturer is close to) as opposed to starting from scratch.

aka0007

I agree that Tesla is undervalued and agree that Optimus is a multi-trillion dollar opportunity that no one is seemingly close to. To me the key things about Optimus are: 1. The manufacturability of it is clearly miles ahead of anyone else which is enabled by Tesla's vertical integration. 2. The design is a functional humanoid robot, not a superhero. No need to run or do flips, rather just be able to navigate a normal human environment and do normal human tasks at a moderate speed. Once you have your basic hardware capable of manipulating objects similar to a human it is simply a software task. The Gen 2 Optimus already has hardware near or at that level. 3. In terms of software the key thing, I believe, will be having many robots (e.g. thousands) being assigned to do a variety of tasks in different environments and then like the cars having the AI software learning and constantly improving. Cheap hardware and manufacturability here is critical as otherwise you will never get to the volume of robots needed for self-learning. 4. The base of the software is obviously based off FSD meaning that a lot of the work designing the software was done already. 5. Compared to self-driving in many ways the compute needed for Optimus is much simpler. Self-driving requires processing numerous camera feeds in a fraction of a second, which means highly efficient NN's that can process downsampled video (not enough compute to process high-res live) to make the correct decisions. Optimus is running off two cameras and can take much more time to process. In other words it can take more time to process high-res so your compute needs may be lower to understand your environment. 6. LLM's and the advancement of AI in general is important as communicating tasks to a robot is a challenge. This is also an issue with self-driving and we saw that Tesla was doing work to translate driving tasks into language. With a robot it is one thing to program explicitly to move from point A to point B, but being able to ask it to do something and for it to understand what you want it to do and then plan how to do it, is a challenge that LLM's are showing are solvable as we are able to communicate in natural language with computers. Without this, you can have a robot that can be capable of anything but will do nothing since you can't explain to it what it needs to do. All-in-all, I believe the key differentiator for Tesla here is their ability to manufacture these at volumes necessary to do the learning to make them functional. The software; any great team with some time can probably accomplish to some extent or another, but the manufacturing is what sets Tesla apart (this goes to design of actuators and every part of the robot) and will enable Tesla to get to volume to allow them to solve the AI problem here to make them functional. That all said... we are probably talking a need to manufacture thousands before the AI can be solved... That will likely not happen till the hardware design goes through several more iterations where they are confident that the hardware is at the level needed for a commercial product. Then building the manufacturing process will take some time... I would figure perhaps 2 years till the hardware is complete, another year to build the manufacturing process and start producing the initial batch for AI learning. Another year to complete that first batch and then another 3-5 years of AI learning... So 2+1+1+3 (or 5), so 7-10 years before this is realized.

CompetitionNo2824

They’ve been doomed ever since net neutrality was repealed and they had to actually provide a service on competitive grounds. NN was a leftist bill signed by liberal executive office that set up FAANG stocks to be invincible. Prior to NN repealing, Netflix accounted for around 30% of domestic internet traffic at peak time but by law they were prohibited from being charged the same rate as you and I to cover those expenses; that made the ISPs pass those costs on the consumer. This was all so Netflix could stream shows created by other studios and not pay their writers nor actors a living wage so we all had to deal with the strike. Fuck Netflix

Domethegoon

I made a bunch of money off NN*M back in 2020. Those days are long over tho...

undergraduateproject

Lol let me sell your NN’s

Rocket_Panda_

Saxenda and ozempic are the same drug in different doses. Ozempic for diabetics, Saxenda was made for weightloss when discovered it had the effect. That is also why it stated NN does not support Ozempic for weightloss, it’s not made for it. Wgevy is only for weightloss. They are all GLP-1, Semaglutide. You should never be on any without prescription though. Agreed the artikel seems misguiding.

Kind-Scientist69

Jnn Nnnnnbn N N Nn Nn N Nn N Nn Nnnn N Nnn N nb Nnn N n N Nnnn Nnnnn Nbn n Nn nnn N N N N N Nn Hn Nnnn Nnn Nnn N N Nn N N Nn Nn Nn N N N Nnn Nnnn N Nnnnnnbn N Nnn Nnnnhn N Nnhnnn N Nn Nn N N Nnnnnnnbn Nn Nn Bnnnnn N nnnnbn N N hn Nnn nnnnnbnn N bnbnn Nnb Nn N Nn Nnn Nnnnn Nn Nb N Nnnbnn Nnnnnnnn Nnnnnnnnbnnnn Nn Nn Nn Nn Nn Nn Nnnnnnnn N nn banner Nnnnnhnnnh N B Bbnbnbnnbgbnn Bb Nhnn Bnnnnnn nibbling Nn G N B Ngn Hn N N Nnnnnnnnn N.nn Nn Nn . Ng Nn N Nn N Nn n N Nnn N Nn N N NNNn B Nbbn N BNb NbbnnnNNnnnb Nn Nbn Bn Bnbn N Nbbn Nnn N N NNNn N N bbnNNbn N N N Nbn B Nnn NBn BBn Bn Bn N N Nnn N Bn Bn Bn Nbn Bbnn N N N Bn N Nn N B Nn Nnn n N B Nnnbbn N n N Nnn Nhb Bn Nn N bn N Nnbn Nbnbn N Bn Nnn N N N Nnn NNNnBn bn NNn Bn nb Nbnbn NNnn Nnn Bn N Nn Bn Bn Nn N N Nnb Bnbbn Bbn N Bnbbbn Bn N bn N Nn N Nnbnb Nbbn Nn Nn B N Nnbbn Bn B Bnnbnbn N Bnbn Nnnbnbbn Nbbn N N Nn N n N N N N Bn Bn Bb Nbbb Nbbn Bbnbnnnbn Nnnn Nnb N N N Nn Bn Bbn Bn N N Nb Nnnn NN n NBBnnbn Bn Nhnb Bn Bbbbn B Nbnbbn N nnnbbn N N BNb Nn Bn Bn n N N N Bnnbn B Nhnnnbnn Bnbn bnbnbn N Bn H Bn Bn Bn N N Bn N N B Nhbb Nbn Nn Bbn Bnn Bbnn N N Nnb Nbb Nn H Nn G nnnbnbb Nb Bnnbb Nn Nbnnn Nbhbbb Nnbbn Nbbbn B Nnn Bnnbbbbn Bbbnbbbbb N hbbbn HNbn Bbbbnnbbhn bnbn Bbbn Nn Bb Nbbbnbbbbbnn Bnhbbbbn Bn Nnbbb H H bnn Bbbn Bbn N N Nn Nfn N N n nbn N B N N N NN n Nn N N N Nn N N Nn N N Nn Nnnn Nn N N Nn Nnnnn Nn N Nnn N N n N N N N N NBn Nnn,nn n N N Nn NN Nn N N N N N Nnnn N N N N N Nn N N N N NNNn N N N Nnn N n N N Nn N n Nn N Nn N N Nn H N N Nn Nn N N N N N NN N N N N N N N N .mn W Nn

SgtRogerMurtaugh

This is wholly false. Novo Nordisk is scrambling to meet market demand for their semaglutide products and have been since launch. They were caught by surprise by the viral uptake of the medication and have learned some hard lessons as a result. As far as them suing healthcare “clubs” and compounding pharmacies, semaglutide is very much covered under patent and they are writhing their rights. Regarding that buyout, I was part of the due diligence on that and can say that the product they bought is currently in development. Preventing obesity is something NN funds but clearly, it’s a near impossible task due to lifestyle, food choices and socioeconomic reality. But the stock. It’s going further. Source: I work at novo.

electro1ight

And settle for 1 billion. The IRS needs quadruple their budget - and I want them using NN to asses corporate and personal tax returns.

synaptic_density

“You need a microscope to tell the difference between Paul krugman and a bag of shit“ - NN taleb’s Nero tulip character

royaldutchiee

Have you looked outside of US as well? Im looking to own NN (Nationale Nederlanden) who have a decent yield as well. They are still in a bit of hot water after their recent lawsuit though

JHogg11

It says "Skew-Adjusted GEX" on the image in the tweet. The fact that they call out "Naive GEX" here: [https://stocks.tradingvolatility.net/gexDashboard](https://stocks.tradingvolatility.net/gexDashboard) but make no mention of tracking trades makes me think they're just adjusting the naive assumption of dealers being long calls and short puts. >Yeah I was referring to your conclusion if MMs are net short the atm - that wouldn’t directly imply anything about their net gamma. Idk why you’re assuming buyside is always net long the wings, existence of skew and curvature doesn’t necessarily mean that’s true. I was suggesting that higher IVs *might* translate to a higher percentage of longs, but that's another thing I don't know and part of the reason I'm asking these questions. Btw, I think what makes the most sense is to compare absolute deltas for calls and puts. Here are a couple examples: SPX: [https://i.ibb.co/TL990xb/spx-ivs-by-delta.png](https://i.ibb.co/TL990xb/spx-ivs-by-delta.png) GME: [https://i.ibb.co/NN5CLQT/gme-ivs-by-delta.png](https://i.ibb.co/NN5CLQT/gme-ivs-by-delta.png) Using the 0.2 absolute delta as an example, SPX investors are paying more for puts than for calls, implying that they are more long OTM puts than OTM calls. This aligns with the naive assumption about investors being more long puts and short calls. By comparison, GME traders are paying more for calls than puts (an inversion of the naive assumption), which makes sense for GME as a meme stock. There might be a useful indicator here even if it's not exactly GEX in the traditional sense.

JHogg11

Have you learned anything more since posting this? I started a thread asking a similar question a few days ago (https://www.reddit.com/r/options/comments/16t9pc8/skewadjusted\_gex/), but just found this one. I'm messing with different views of IV, in particular comparing IVs to absolute deltas for calls and puts. One thing that jumped out for SPX is that the IVs for slightly OTM calls is higher than for slightly OTM puts. Does this automatically imply that non-dealers are more long these calls than they are the puts? In general, if I were to pick any two contracts, OTM or ITM, calls or puts, and any two strikes, can it be inferred that the one with a higher IV is almost always the one where non-dealers are more long? Here are two examples: SPX: [https://i.ibb.co/TL990xb/spx-ivs-by-delta.png](https://i.ibb.co/TL990xb/spx-ivs-by-delta.png) GME: [https://i.ibb.co/NN5CLQT/gme-ivs-by-delta.png](https://i.ibb.co/NN5CLQT/gme-ivs-by-delta.png) Note that OTM puts generally have higher IVs for SPX and OTM calls generally have higher IVs for GME and the opposite is true for ITM options. However, in both cases, the cross happens at around 0.4 delta.

dd1989NL

Fuck us!! had NN on the AEX.. lost 19 percent yesterday.. to me its play money so i dont care.. hell i do even though i dont need the cash

WACS_On

Remember when Reddit said that NN getting repealed would lead to the end of the Internet? Remember when it got repealed and fuck all happened?

Plutuserix

Most of my money is in etfs. For individual stock to just buy and hold I do ones with a nice dividend: INGA, Unilever, NN Group, BMW, O. If only allowed five stocks and no Etfs I would switch out BMW and O for Microsoft and Apple I guess.

bhauertso

The head of the FSD/Autopilot team, Ashok Elluswamy, was in the passenger seat of the car during the demonstration. He and Musk talk several times in the video. He also [tweeted about the new end-to-end NN approach](https://twitter.com/aelluswamy/status/1695562811190210890).

JPowMorgan

This is what happens with reinfection. XAXIS IS LOG SCALE! >https://media.nature.com/lw767/magazine-assets/d41586-023-01371-9/d41586-023-01371-9_25274716.png >**BREAKING: CDC- BA.2.86 MAY BE MORE CAPABLE OF CAUSING INFECTION IN PEOPLE WHO HAVE PREVIOUSLY HAD COVID-19 OR WHO HAVE RECEIVED COVID-19 VACCINES** >https://twitter.com/Newsquawk/status/1694370750453424636?t=UQtdF2p4c-Jh06NN775kOQ&s=19 The dd is my post history. Deserve the nobel. Spy 225 LLY 🚀🚀🚀

JPowMorgan

>**BREAKING: CDC- BA.2.86 MAY BE MORE CAPABLE OF CAUSING INFECTION IN PEOPLE WHO HAVE PREVIOUSLY HAD COVID-19 OR WHO HAVE RECEIVED COVID-19 VACCINES** https://twitter.com/Newsquawk/status/1694370750453424636?t=UQtdF2p4c-Jh06NN775kOQ&s=19 DOOM LOOP FLASH CRASH SPY 225

Visit_Dry

TT00 right now 

S0YB0YTROY

So what? I guess you don't understand real world AI and the neural network. Waymo is garbage and will plateau while Teslas NN will truly understand the environment and will be able to identify changes in the course and take appropriate action when things aren't the same as yesterday.

Reelableink9

Those are not real AI bots, or use a different NN architecture than the current wave of NLMs. Next few years you’ll see gpt style AI incorporated into customer service

Shoryukitten_

They will say Dojo and put the analysts to sleep cuz analysts don’t know FLOPS from flaps. If their NN training tech proves superior, they won’t have to say AI because earnings will moon.

OD5T

[https://imgur.com/a/1NN8Ivo](https://imgur.com/a/1NN8Ivo) Great prediction! I bought more at $8.66 :)

MarketCrache

NN also make the most popular forms of injectable insulin for diabetics.

PoetryEmergency4184

NN groep or ASML (altough ASML is a bit pricy). These are Dutch stocks tho

Renegade_Trader

If it goes up then because of short sellers like me closing their positions. So you are welcome. Looking at the facts : \- Momentum is against you \- The company has never made any profit \- Their buisiness model is deeply flawed \- Their revenue mainly comes from one customer \- There are accusations of wrong accouting \- Their expertise is mainly into other deep learning approaches, not NN These are not really serious arguments against a reddit fueld hype. At the same time, there is one argument that will break the neck of this company: \- It is plain obvious that this is some boomer CEO trying to play meme stock.

Droidvoid

Only Bloomberg 😎 I’m just stating the truth. They’ve yet to form meaningful relationships like NVDA has with NN developers. I think they have one with MSFT with a plan to use their AI chips? Their announcement last week or whenever it was, just lacked the complete picture. All I’m saying

wyndmilltilter

Lol not what I said, sorry I didn’t cite and quote the JAMA study. No one’s saying ChatGPTs replacing doctors (being married to one I’d be very concerned) - I was responding to the comment saying this was as overblown as blockchain. That was hype fueled by easy money and anti establishment fervor; AI/NN/LLM is far more interesting, promising, and yes potentially destabilizing. Passing the bar, boards, real world answers to patient questions (ie a differential diagnosis…) as in the JAMA study are simply examples of the very real power of this young tech (and yes, I know AI theory dates back significantly but realistically the modern implementation is ~10 yrs old and advancing rapidly in the past few). You’re right it was a flippant example to show there were real world implications but man you sound like a dick. The study also showed higher empathy, maybe you should work on that…

thePBRismoldy

NN Taleb on CNBC saying that this moment is very similar to 2007-2008 this week. Hold on to your butts boys, I’m thinking this rally is far from over…

Idennatua

It's legit going to depend on your businesses cash-on-hand and how necessary what you make is to the day-to-day lives of people, or more realistically, the government. (military contracts and direct government civilian engineering projects) On the one hand manufacturing will be moving back home, on the other hand that's going to spike prices of everything by a significant amount. Especially as countries start rethinking supply lines in preparation for the next mass contagion. There's going to be another credit crunch\* and if it's larger than GFC we will see multi-billion dollar corporations go bust as they can't get the immediate credit to cover wages (like in 2008/9 as the dollar market dried up but the eurodollar debt still existed and needed to be resolved or bankrupted, then AIG collapsed and the government stepped in) \*(there's a small one rotating through the eurodollar market right now as people can't acquire enough USD to pay off their USD denominated loans) I don't personally believe in metals, but some people are thinking precious metals is the ideal course, and if you can find a bank that's being run properly, investing in them would be good, but finding a bank that's not upside down on CMBS/MBS loans right now is difficult, then add to the fact the bank in question would need to be liquid in multiple currencies to back their own loans during the volatility of the international currencies as multiple financial services companies collapse (Basically if a bank is listed on evergrande's IOU list, they're probably not going to live much longer). &#x200B; See: [https://www.dmsa-agentur.de/download/20211029\_DMSA\_EVG\_PM\_en.pdf](https://www.dmsa-agentur.de/download/20211029_DMSA_EVG_PM_en.pdf) and page 6+ : [https://www.dmsa-agentur.de/download/20211024\_DMSA\_EVG\_RR\_en.pdf](https://www.dmsa-agentur.de/download/20211024_DMSA_EVG_RR_en.pdf) > 1 FIL Ltd 11 450,385,288 08/31/21 2 Blackrock Inc 14 443,325,201 10/21/21 3 Ashmore Group PLC 11 432,727,000 07/30/21 4 UBS AG 13 277,499,000 08/31/21 5 Allianz SE 9 210,550,000 06/30/21 6 Prudential PLC 12 161,965,330 08/31/21 7 Royal Bank of Canada 12 112,775,800 06/30/21 8 HSBC Holding PLC 8 100,358,609 08/31/21 2021.10.24, Page 7 Count Held Amound in $ Filing Date 9 Government Pension Investment Fund Japan 10 84,833,000 03/31/21 10 Pictet Funds SA 6 55,869,000 07/31/21 11 St James’s Place PLC 6 51,859,000 03/31/21 12 Temasek Holdings Pte Ltd 8 43,850,000 05/31/21 13 Vontobel Holdings AG 4 43,157,000 08/31/21 14 BNP Paribas SA 5 43,036,268 08/31/21 15 Banque Lombard Odier & Cie SA 2 42,380,800 04/30/21 16 Legal & General Group PLC 10 40,525,001 10/21/21 17 NN Group NV 10 32,450,000 03/31/21 18 Invesco Ltd 8 30,320,266 10/21/21 19 abrdn PLC 6 2,661,230 09/30/21 20 Alliance Bernstein LP 3 29,196,000 08/31/21 21 Clariden Leu AG 2 29,000,000 08/31/2

soAsian

["True. Also, many other NN accelerator chips are also under development," the tech mogul commented. "Nvidia will not have a monopoly on large-scale training & inference forever."](https://www.thestreet.com/electric-vehicles/elon-musk-has-a-blunt-message-for-nvidia) - Musk the problem with Musk's statement is there already many chip designed and outsourced to fabs like Google Tensor but these chip are not for sales and you probably have to subscribe to Google cloud or something. what if i want to build my shits and not blue ball by Google then i'll have to get a team to design the chip talk to fab like TSMC and order enough volumes for them to even talk to you. NVIDIA is the only option for now. not that i got NVIDIA calls or anything. 😏

1234567panda

🤣 probably 80%. TSM is already ramping up capacity. NVDA is about to see explosive growth in the near term. I do think it’ll be a lot more temporary than the market does though. You only really need to use these chips to train the NN and AI so unless somebody develops a live model that learns in real time and has memory support, I don’t see NVDAs run being sustainable

Gorva

I mean that just sounds even better. Plug NN:s into eachother to complete tasks.

HasFiveVowels

Perhaps my understanding of LLMs is a bit vague on the nature of their creation but... yea, definitely not GANs, now that I think about it. Their training is strictly based on prior knowledge tests. But aren't they RNNs? If they guess the next token correctly, the NN path is reinforced. If they guess the next token incorrectly, the NN path is reduced in strength. As I mentioned, my knowledge isn't really focused on their creation but I have the general idea. It's more or less based on Shannon's "guess the next word" experiments in information theory, correct?

kuedhel

huh? Convolution NN was around for decades.

hishazelglance

To also clarify, I’m defining “architecture” as the architecture within a chip, within a hardware network, or within an actual neural network / deep learning network in general. With the advent of Transformers and new NN architectures coming out yearly, guess what happens when they find a more optimal architecture?

hishazelglance

To be clear, I was referencing your “takes a lot of compute to generate, not to use it” comment, highlighting that you effectively re-generate the neural network (not quite the same since the size of the input is smaller than original, though it’s much more compute compared to using it) when you retrain. To answer your current question, of course in theory you don’t have to buy more hardware once your NN in question is built, just upgrade and maintain. HOWEVER, the assumption you made is data centers not upgrading chips on a regular basis. As someone in the space, I define <5 years alterations to be considered on a regular basis. I DEFINITELY see these data centers modifying size, hardware, and architecture within 5 years consistently for the foreseeable future.

dethmij1

The thing you're not understanding is Language Learning Models don't actually 'learn'. They replicate what's in their training sets. Chat GPT isn't actually solving calculus, it's digging through its databases for examples of something similar and replicating it. If it does that wrong in an engineering firm and you don't have a human checking it over you have a design error and could have a serious safety issue on your hands if that design error makes it into the final product. When it comes to engineering, AI is a tool just like Scientific Computing, CFD, FEA, and CAD. It will liberate engineers from menial tasks to do more design work and enhance their productivity. We won't be replaced in the near future. And if AGI happens all bets are off, but I assure you we're not just a couple years from that. These LLMs are impressive but they're not even remotely intelligent, and adding more training sets and nodes to a NN isn't going to make ChatGPT sentient.

dethmij1

Sure, but AI/ML is a decades old field of science and nothing has fundamentally changed in our understanding of NN's. We just have cheaper computing allowing us to grow larger NN's on much larger datasets. We still have no idea how to build consciousness, or even what it is.

ExactLobster1462

Funny my professor must be high or something because he's been working on ML for over 10 years and never has he ever considered that even a trained NN can replace those who develop and maintain software, i.e. look at GitHub's Co-pilot it can spit out an incredibly accurate estimation of what you were thinking of writing, but tell it to estimate how to solve a create problem with code and you will never get past the first neural net. That's all AI+ML is, guesstimations based on input. But you would rather believe it is a fleet of all knowing and capable hivemind like out of the Terminator.

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Mathias218337

Considering their margins at the current price point it leads to multiple strengths over the competition. Ford is running a -40% margin on their EVs right now. Over half of folks say that they’ll buy EVs for their next car (up from 22% just 2 years ago). As tesla continues to make money and legacy auto bleeds, this will only be more transparent. Tesla also has (which none of the other auto makers do) the following competitive advantages: 1. Supercharger network, 2. Data for autonomy 3. Their own motor production 4. Their own battery production 5. Gigacastings 6. Battery storage growing at a much faster clip than cars 7. Dojo possibility (think aws for NN training) 8. Solar division 9. Services (they own their own service infrastructure) 10. Supercharging cost structure (they run a profitable P&L on it) 11. Insurance There’s more, but that’s top level. There’s also moonshots like Optimus. No one else has the upside tesla does long term.

Charming_Rice

Pretty sure iphone already has NN acclerator for ~5 years now.

DesmondMilesDant

Where is this NN ?

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InoculumFear

[Black as midnight on a moonless night](data:image/jpeg;base64,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)

Aromatic_Ad_5190

Are you dutch? I also have ahold and NN 😅

Da_Millionaire

Who the fuck is NN? Shorting all AI after that one ya regard

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kmouratidis

Have you verified the answer based on your knowledge / research? Anyway, it seems they aren't directly related. From what I read (and what I understood of it), QNNs can offer similar types of common NN operations (e.g. for CNNs there are similar things to pooling and convolution) but can't be used as a drop-in replacement or offer a magical speed-up. Quote from arxiv paper: > Due to the universal approximation property of QNN, it is known that quantum deep learning can perform most of the computations performed in classical deep learning [10]. Nevertheless, if one approaches simply based on this fact without the consideration of quantum gain, the result may be much inefficient compared to the existing classical algorithm.

8thSt

F1NN5TER be tricky like that

AndrewWKPartyParty2

[i’m the opposite from selling puts and covered calls. thanks for the premiums kind sir](https://i.imgur.com/NN7Xuny.png)

dinglebarrybonds

https://youtu.be/NN3c9VA_Zq0

CoiIedXBL

I respect your opinion, but I'd have to entirely disagree. The varying pharmacodynamic properties of each and every psychedelic compound give them a unique character, and while the *exact* details of every trip does indeed vary, the character of the specific substance in question is always present. Whether its the eclectic colourful synesthesic empathogenia of 2C-B, the sharp, ego dissolving fractal forming intellectual nature of LSD, the infinite empty pure cataclysmic void that is 5-MeO-DMT, the reality warping sanity shattering infinitely recursive power of Salvia Divinorum, it's always identifiable. There are pharmacochemical parallels to be drawn also. Each substance has unique durations of action, some may have significantly more dopaminergic effects than others manifesting in specific and identifiable physical symptoms. There is a distinct difference in the serotonergia of LSD's 5HT-2a dominant agonism and 2C-B's 5HT-2c dominant agonism. I will concur however that trips ultimately are born from individual perception and experience, as these compounds truly only modulate the conception of an already existing consciousness and we are all, in that sense, unique. Rest assured, I've experienced a significant portion of the existing dimethyltryptamines, NN-DMT more times than I can count. Have a fantastic week friend ❤

smc733

Companies that leverage it for augmentation will be far more successful than those that try (and will fail) at using it to cut positions. GPT has been easily shown to make stuff up, and confidently express answers to things it is flat out wrong on. It is terrible with math. We don’t easily know how an NN gets to its specific answer for a given question. It looks impressive and undoubtedly is, but it’s closeness to human level intelligence isn’t as close as people may think.

Aidzillafont

I think the BART NN model was the origin of these kind of large language models so makes sense to me

GoogleOfficial

Tesla is somewhat of an AI company. They do a lot of work with NN.

royfromstatefarm

You’re right they knew they would need general ai, do you think that’s why they might have hired Andrej karpathy? A leading researcher in NN who was also part of the founding of OpenAI? Asking for a friend

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meatlamma

lol, as an AI dev myself, I find it really hard to believe. Successful AI models (what self driving is) require vast amount of data samples (video data, preferably labeled, of people driving around in various scenarios, like day night, rain, suburbs, cities) and massive compute (farms of servers with GPUs or NN accelerators). While I can believe Mercedes could spend billions on a server farm and some AI researches. Data is a lot harder to come by. As far as can tell that data is available only to TESLA. it has access to all those thousands of teslas driving around and recording all of it. This data in itself is pure gold, worth more than the entire Mercedes as a company. Google is close second with its google maps cars driving around. But they only drive on good weather days and low traffic situations so they can take better pictures.

kemar7856

I'm convinced europoors dont even know what they're protesting something they just see someone doi NN g it then they join

xorfivesix

Not the op but AMD doesn't really compete for AI like NVidia. Team Green has lots of software and hardware support for AI, whereas AMD has not supported this until their most recent line of 7xxx cards, which are still in their infancy. Source: did machine learning in college, trained neural networks on CPU because AMD gpu (5700xt) had no support. CPU NN are big guh, in lay terms.

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SpicyLatinaCumfarts

Text-to-image generative art has been around for decades. At least google the history of the field before trying to zoomersplain it to someone with pubs in IEEE Transactions. It went mainstream in the past few years because processing power has gotten cheap enough that these toy demos can run on free public websites or locally with a decent GPU, not because of any major advancements in the methods. And for text-to-text, GPT-2 and 3 are just standard implementations of a transformers NN, which is a newer algo but again the noticeable difference vs older NLP algos that dazzles normies like you is 99% from the extra processing power that we can throw at it today. Sysadmin work has been mostly automated for like 20 years now, nobody that calls themself an SE/dev/programmer has a sysadmin role. There are dozens of maintenance/monitoring/patternbuild frameworks. But building systems from scratch to meet requirements varying from specific to vague using the latest frameworks requires general intelligence. And ML hasn't replicated anything near general intelligence yet, no matter how many funny sonnets about defecation I've made ChatGPT compose.

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Altruistic_Fish_3574

Sure they work some times, even the majority of times... so do the autonomous cars of the competition. In the 1990s they already trained neural networks to detect road shapes and guide a car along the way which also worked a majority of the time, the problem is there are millions of combinations of circumstances - most of them mean everything is normal, but a very small fraction of circumstances require intervention and this intervention cannot be reliably generalized... because it needs to be derived from the individual circumstances, which would require a true AI, Elon Musk himself said Tesla needs to solve the problem of General Artificial Intelligence. Tens or hundreds of thousands of smart people have tried that but we are still not yet there and they have a fraction of the resources of competitors like Google, Apple, MSFT... The neural network solution with cameras performs worse than the LIDAR based approach of competitors - Tesla has more disengagements per mile than it's competitors. Here is a list of competitors: [https://www.aitimejournal.com/autonomous-vehicles-companies-to-watch](https://www.aitimejournal.com/autonomous-vehicles-companies-to-watch) Here more info about disengagements: [https://electrek.co/2022/12/14/tesla-full-self-driving-data-awful-challenge-elon-musk-prove-otherwise/](https://electrek.co/2022/12/14/tesla-full-self-driving-data-awful-challenge-elon-musk-prove-otherwise/) If you know something about neural networks, then you should also know they are never 100% reliable because they are black boxes and you cannot predict when they will fail. Even if you only have 0,1% error margin, with the millions of miles driven each day that sums up to 0,001\*1000000 = 1000 fails per million miles, where each of them might be a parked car that is not recognized and a Tesla runs into it, a Tesla not recognizing a speed limit and sharp corner, sliding into oncoming traffic, a child not being recognized running in front of the car... I can go on, but if you've driven a car you know many unexpected things can happen that never happened before - a NN cannot be reliably trained on those exceptions... because it needs a lot of data, which is per definition not available for rare events. Next neural networks are better at doing one thing, only recognizing stop signs, only the lines on the road - everything all at once will come at the cost of less accuracy, but running multiple recognition systems will lead to conflicts in the internal logic of the car and slows down reaction time. With a map and LIDAR you have the physical reality and can use more classical navigation approaches that are better researched, tested and reliable - especially coupled with properly maintained maps which can also be updated in real time via the cars equipped by the technology without having to retrain huge networks. Sure there is a "good" narrative behind it, if you leave out the real world problems then it would be amazing. I think it is very likely that lying about autopilot or not informing about the real big problems IS malicious, why? Because the person doing the lying, Mr. Musk, is profiting from this in an insane way - it made him the richest person in the world... and in my opinion repeatedly claiming Tesla will self drive next year for like six years is lying, maybe also self-deception, but it doesn't really make the end result better. Also instead of using a resource friendlier approach like public transportation, he wants to sell a lot of individual products. Currently the global annual lithium production is roughly enough to produce 10 million battery powered EVs... leaving no lithium for any other products - getting to this lithium is very water intensive and therefore also not really environmentally friendly as is recycling it.

serrrenitynow

I agree it was overvalued, but I feel the current sentiment is way too bearish given Tesla's growth prospects and the price just above $100. People seem to have stopped believing in the growth story, when the fundamentals still look as strong as ever. Also, I'm seeing constant posts about how people feel so vindicated now that everyone realizes Tesla isn't actually a tech company and is just a car company. People seem to be getting high on this vindication and ignoring the fundamentals. I believe the case for them being a tech company is stronger than ever. What other car company is building custom NN hardware and has one of the best machine learning training systems in the world (dojo)? Yes, FSD development has been slow and over hyped, but they're going about it in the correct way and building the foundations of a robust system that will be able to handle the real world. They're collecting massive amounts of data that no one else has, and it's making solid progress on every update. And their advances in ML and computer vision will be applied to their humanoid robot. Many laughed at the robot demo and compared it to the dog from Bostom Dynamics, which is ridiculous considering Tesla designed and built theirs in one year, when BD has been around for 30 years. I think Tesla will succeed where BD has failed, manufacturing at scale, and being pragmatic about building something that's good enough to be put into service in various roles. I'd be interested to see a valuation for Tesla that includes all their lines of business as they are becoming very diverse. Cars, Dojo (can rent out compute like AWS), insurance, stationary storage (home and utility scale), solar energy, energy market (AutoBidder), humanoid robot, etc. Other advantages they have are; direct sales not being reliant on dealerships, top engineers, and [cross pollination with SpaceX](https://futurism.com/spacex-helped-tesla-speed-up-their-car-production-elon-musk-revealed). This company is very special, and those that are just parroting the typical, "der, it's only a car company, der Musk dumb and evil" rhetoric are completely missing the boat. I'm loading up on share at these prices and if the market continues to be irrational and sell off I'll just keep buying more.

Mathias218337

I just am looking at the TAM and how tesla is going to be a big leader in auto, utility storage, and NN cloud architecture. Not to mention FSD will likely be worth more than it is today, and Optimus may actually happen too. Definitely wouldn’t recommend holding if you’re not long term though. Volatility is wild. But I see a very clear path to be the largest company in the world in 5~ years

tomoldbury

> Care to be more specific about "fundamental capable" means? Sounds like you have no idea what you are talking about. Dual redundant steering actuators with redundant drivers and encoders. Dual redundant braking actuators. Dual redundant processing modules with semi-independent camera feeds and independent power supplies for all of these modules. All fuses eliminated from the vehicle system besides some in the AC charger input (UL requirement - but non safety critical). Dual CANBUS to drive motor system. All this means the vehicle can pull over safely if something goes bad (which is ALWAYS a risk) and it's essential for FSD capability with no driver. In terms of software, the NN hardware blocks have enough capacity remaining, and the problem is no longer one of perception, but deciding what to do with the situation presented to the vehicle. IDK if Tesla has won the debate on whether LiDAR is required or not. It seems like it might make the driving problem easier, but LiDAR ain't cheap, and it struggles in heavy rain and snow (not as if cameras don't either, but LiDAR's problems are more intractable). I'm watching the performance of Waymo/Cruise vs Tesla with some interest here. It's particularly telling Waymo started testing in Phoenix, AZ, one of the driest cities in the USA. > Can't automatically brake, but is fully self driving apart from that. The Tesla tested in the video is not running FSD? It's a commercial model being presented with a test case it's not designed for. So it doesn't stop. NCAP requirement is that pedestrian be detected walking from a side road, there's no requirement to detect this, so it's not in currently type approved consumer models. IDK what NHTSA requires but it's probably less. Test it with a Tesla running "city streets" which is the FSD stack and it will stop. As has been repeatedly demonstrated by many others. Same problem as the Green Hills guy testing regular "autopilot" (non-"City Streets") on all of these things. It's a level 2 (at best) lane hold and auto cruise system, that Mobileye and a few other OEMs make, it is not anything more than that. Here are the NCAP tests, which the car does fine on: https://www.youtube.com/watch?v=AD5ozzMzbHA&t=140s > Its called testing? How much testing makes a system safe? Regulators are requiring levels comparable to aircraft software, which is about as safe as you see mass produced software/hardware. Despite this, you still have issues like an Airbus aircraft losing all three FCPCs on landing because of an asynch timing bug: https://www.ttsb.gov.tw/english/16051/16113/16114/30265/post So there will always be bugs and edge cases with software/hardware and there comes a point where we say it's safe enough. How many humans kill others with inattentiveness on the road? I would be happy to accept any FSD system at least as safe as the average driver as it is a statistical improvement. Looking at how it's running so far I would say it is either close to reaching that or has already exceeded that, but more data is needed to be confident in that. Also note that UN ECE regs limit the capability of any AP system in Europe until regulatory approval is granted. Therefore it's very unlikely we will see FSD beta any time soon in Europe because the level of safety required is very high. > "massive hill to climb" lmao you fanboys ALL talk the same. Like you think if you write a certain way, it makes you sound clever, but forget that the substance of your words matters much more than your flowery rhetoric... Dude, I had the opportunity to buy a Model 3 but I didn't. I stick with my old Golf because I don't like Tesla and am waiting for a better EV with the features I want. I'm actively critical of Elon and the company. I am NOT a fanboy. I have a masters' engineering degree and design critical military kit as a day job, so I might understand a thing or two about redundancy and system design. What about you?