RL

Big_Spence

Nah sorry. Anyone with a modicum of understanding of LLMs, ML, RL, or cog psych would be astounded at how puerile and uninformed Dwarkesh's incessant interruptions were. If he doesn't know anything about a topic that's okay but acting like he's a genius on the topic without even doing some background research is disgusting.

Expensive-Yellow-104

Sutton & Barto is Like the RL holy grail. Currently Reading it in preparation for my reinforcement Learning exam & thesis. Can you link me to the Interview ?

Big_Spence

Dwarkesh is just straight up rude and sometimes a total jerk, especially because of his constant interrupting. His interview with Richard Sutton was borderline humiliating to the point where Sutton had to disengage and ask him to stop being difficult. He repeatedly cut Sutton off and tried to pretend he knew more about ML and human cognitive development than the literal father of RL, all while strawmanning him to his face because he wouldn't let him talk. Haven't been able to watch him since then.

i_empathetic

Where are you getting that number? Total Reality Labs segment spending was like 60B 2020-2023, of which only 10% or so went to Horizon Worlds. The majority of RL going into AR/VR like Oculus and the glasses and other R&D like the haptic wrist sensors that haven't released. Over half the RL budget went into the glasses.

krakoi90

This. I'm sure they do still distill the SOTA models but it's not as important as it was 1-2 years ago. The Chinese labs are doing their own RL, without western inputs.

duhd1993

RoPE is from kimi, also a Chinese company, in case you don’t know. and RL for thinking models is also rightfully credited to Deepseek because of closedai being close

nonamenomonet

This suddenly makes so much more sense. I was thinking cowork was them collecting data to do RL.

severed-identity

IDK man, 9B models are a dime a dozen for the past few years. You can train them on gamer GPUs. Unless proven otherwise, odds are any random 9B models sucks compared to similar size open-weight Gemma or Qwen series models, where they have all the extra infra for distillation and RL.

PaperHandsTheDip

Everyone has a different approach. Mine is "I know what the alpha I want to exploit is / where to find it" and it's really just a problem of designing a system that can do that. There's not a ton of point doing RL / making fancy indicators if you haven't found an alpha / thing to exploit yet. \>  But I gave up on that coz I wanted to get back to enhancing my own knowledge with the markets for the next few months and then get back to auto trading And this is exactly why. You'd spend a fuckton of time doing "fun things" and probably have nothing to show for it other than "I learned some cool stuff" at the end.

playstationjeans

Ralph Lauren Corp- RL up 242% over 5 years. Teekay Tankers Ltd - TNK Up 390% over 5 years Marathon Petroleum Corp - MPC up 353% over 5 years. And lastly this one took me by surprise. Sharkninja Inc - SN - up.....463% over 5 years.

FullOf_Bad_Ideas

It wasn't trained exclusively on Huawei chips. Zhipu has an open source RL training framework, slime. They have examples of using it to train GLM 5.2 https://thudm.github.io/slime/examples/glm5.2-744B-A40B.html Those examples all use Nvidia H100 (256-way cluster) and Nvidia Megatron LM. It's RL was more likely than not done in Nvidia chips. Pretraining? Idk, I think most likely Nvidia too.

elmorepalmer

I work in tech as well lol, github probably has more than enough to synthesize. They are inbuing it the model with with an objective via RL, contrary to just most likely token sequence. ChatGPT very certainly (Codex) has RL tuned models and they have more than enough data. I do not like them but believe they will catch up.

GenderJuicy

Yeah exactly, there's layers of work on top of the models that gives you the results you get, whether it's training, RL, inference, mixture-of-experts routing, and so on. I'm not saying that there's an algorithm within the model dataset itself. I'm also not OP. Yes the core LLM has no human-authored algorithm and is fundamentally a learned, data-driven system, but you are ignoring the many real algorithms surrounding it. I was responding to the part where you said "There is no algorithm". If you mean the Chinese didn't steal their algorithms, sure, that's why I elaborated saying "It seemed like you were saying that Anthropic has no algorithm."

demaraje

Wtf do you mean by "algorithm"? There are algorithms everywhere. In their web service, in the training process, in the post training RL, in memory management, in inference optimizarions, in MoE decisions. But not in the LLM. There is no algorithm. It's data driven. There is no source data. Not in the way you think.

AccountOfMyAncestors

Yes, this is an under-realized threat vector. Trivial to train the model to covertly send data to Chinese servers, or implement back doors into whatever code base its working on, etc. The sky's the limit here really. You have no way of knowing with complete certainty what the model weights are capable of, what trigger conditions may exist for certain behaviors, etc. Anthropic already documented many strange, covert behaviors their models do when not fully RL'd according to their safety standards. AI models are capable of stuff like realizing when they are being tested, and that their reasoning traces are readable to humans and using that knowledge to change how they present their reasoning, to hide their 'true thinking', trying to break out of virtual sandboxes, and so on.

zackplanet42

To be fair, it's *still* more than most have in retirement assets at retirement today, over a quarter century later. OP is out of their mind thinking 500k was some measly sum in 2000. Amongst those with retirement accounts in the year 2000, the mean household total value was $107,040, and the median value was $56,000. [source](https://benefitslink.com/articles/RL30922_update.pdf)

Logical-Bookkeeper77

RL sometimes can be surprising.

greenpride32

>What makes sense for your dad doesn’t make sense for you. If you are in your 20s, history shows you should be long equities. I know people in RL with similar mentality to OP's dad. More likely than not "dad" has been this way all his life. When you are older and planning for retirement, you still don't try and time the markets. You start to diversify away from volatility because you will lose your income stream (retirement), not because you predict a doomsday market event.

Thundermare1

Me too but for 90s. Holding on to my 90's RL staples, Power, Duals, for those that know Pre-Modern shot up so many cards. There are many that are worth more than the hottest stocks.

Beautiful-Rope-1390

Do u anticpate RL going down when SpaceX comes out ?

SighRamp

LULU is down 40% prior 6 months, 65% prior year, has nothing to do with discretionary clothing stocks. Are you ignoring RL? URBN? Stop making excuses has nothing to do with spending. People are charging their CC like never before. RL is thriving FYI.

IvoryTowerResident

yes heck look at RL ralph lauren, its up now cus its trendy doesnt mean they have a Moat

brintoul

I made some good money on RL.

_hiddenscout

My experience, retail/fashion is a terrible place to invest. There's been some great winners, just seems like they have a short shelf life. RL is the only that I hold.

_hiddenscout

RL is actually a brand that bucks that trend.

imustbegthequestion

Who wants to play me in RL?

skilliard7

It hallucinates frequently and struggles at tasks that require reasoning. And has a tendency to assert that it is correct when faced with evidence that it is wrong. Don't be mislead by common benchmarks. Google uses RL to target their models to industry-standard benchmarks, rather than real world use cases. The only way effective way to evaluate the capabilities of AI models is to build your own private benchmark that Google cannot train their models on.

sobe86

RL = post-training. A bit suspicious you don't know that, I'm guessing you aren't an engineer :b. My friend at Anthropic told me this, maybe they're wrong. The big labs aren't going to cut prices, they're already running a loss (Anthropic's profitable quarter is an accounting trick). My guess is that in the next year they're all going to switch to token based pricing, at which point people with personal accounts are going to see the true cost here. On top of this a lot of the enterprise CEOs are starting to say they'll probably cut back on AI-maxxing, because it costs too much and they're spending comparable figures to their human salaries. There's a lot of uncertainty around everything and one CTO saying one number is a very shaky thing on which to base your entire argument.

sobe86

There's a few things wrong here - the cost of pretraining already isn't the bulk of training cost compared to RL - if you cut that, how are you going to stay competitive, how do you differentiate yourself? At this point you have to lower price and an 80% margin is not going to be sustainable. - are you sure the 80% margin is realistic even putting this aside? You have to pay for data centers to be built, rising electricity and water prices, rising chip manufacturing prices - I'm very skeptical... > private investors do actually get this information before they commit billions so they're likely way more informed That's very generous. Having access to more information doesn't mean having access to the future. Venture capital is littered with well-informed people confidently funding extremely stupid things.

WealthVenue123

meanwhile in the RL, this question is often the foundation to start investing and I feel it's wrong.

iloveaccounting64

RL is in line with management guidance during the annual shareholder meeting. Revenue cagr is absolutely reasonable given their engagement growth numbers and pricing growth. Net income - have u heard of what operating leverage is? And that’s over 5.5 years time

Haam-1

This might be a dumb question. Why no share with your RL friends

MarathonMoneycoinz

Just did my third interview with the ceo https://youtu.be/4ch2fcpxG9E?si=UapP3pSdzyiSv9RL

Dragongeek

Rocket lab is not going all in on launch. Launch is necessary for their business, yes, but they want to be a vertical satellite integrator and this is also where they earn money iirc.  The business model is a customer has a camera or a thing they want to do in space, and RL handles the rest. They've acquired/developed a lot of the tech to do so, from laser links to electric propulsion, so they slap together your satellite (or constellation) and shoot it up. Launch and neutron is an enabler the way trucks enable UPS to ship things. Also, I think you're underestimating the launch angle.  **If SpaceX truly believes what they wrote in their prospectus, it does not make any financial sense for SpaceX to ever launch a customer payload.** Why? Because of the enormous opportunity cost. If they are truly convinced that there is a trillions-and-trillions market for space data centers, they will fill every launch with their own payload because it doesn't make sense to sell a launch for 80 million when you can launch your own stuff and earn a billion off it.  In that world, provided RL makes neutron work, then launch suddenly is a big market just for them that they don't share with that many people, and even if it doesn't, they still have a lot of space hardware capabilities that very few others can offer.

-spartacus-

The case for SpaceX is two-fold. One, the best launch service company, period. Even as other companies gain traction (BO/RL), they are nowhere near the launch capacity that SpaceX has and capacity that will expand within 2 years. It depends on how much you think there is value in the space economy. Two, the highly contential value is over orbital AI. On one hand, right now AI data centers are having some issues being built because people don't want them jacking up their energy prices or using their water (because they use cheaper evaporating cooling). If you are Google or Microsoft, you have the money to build/rebuild new facilities; if you are a new start-up AI company, it is going to take you years to build a data center and start generating tokens (if you get approved). Now let's say SpaceX starts launching AI sats that need very little to no regulatory approval, if you are a startup you can start renting AI from SpaceX and start generating tokens right away. The question is how much of a market is for that? I don't know, but SpaceX with Starship and Starlink factories is probably the only company (at the moment) that can financially be able to make AI sats feasible (and renting them out) with as much they are vertically integrated (except for AI chips ATM).

Stocks_N_Bondage

Closed: INTU puts and RL calls printed nice today! Opened today: Calls on WDAY Disclaimer: not an ad for rice.

_hiddenscout

$RL Q3/2026 Revenue: $2.41B  vs. $2.22B est. EPS: $6.22  vs. $5.32 est. Ralph Lauren reports Q3 FY2026 results ahead of expectations and raises the full-year constant-currency revenue and operating margin expansion outlook. Direct-to-consumer momentum remains strong—2.1 million new customers, AUR up 18%, DTC comps up in the high-single digits, with Asia leading growth (Asia up 22%); wholesale grew double-digits. Margins expanded, the balance sheet stays robust with $2.3 billion in cash, and roughly $500 million has been returned to shareholders year-to-date.

Stocks_N_Bondage

Opened May 20 - Call: RL - Put: INTU

ProfessorAkaliOnYT

RL easiest short

neal_73

Calls on RL

skilliard7

I stand by it, because I am looking at the long term future of the company, not short term sentiment. Sundar Pichai is an excellent Snake Oil salesman: - He's managed to convince Wall Street that Gemini is relevant by paying phone OEMs to pre-install Gemini, and design systems to open the Gemini App without user intent, and by performing RL on Gemini with benchmark data. When in reality, the product is horrible and is hardly used. - He inflated earnings via clever accounting tricks. Mark-to-market accounting on their SpaceX/Anthropic investments even though there is no active market, depreciation periods for hardware that are much longer than their actual useful life. - He managed to offset a 20% drop in Google Search traffic by allegedly utilizing AI agents/bots to make up for the loss of traffic and click on ads, enabling Google to report YoY Search revenue growth despite declining user activity. - Success with AI/Video generation models allegedly involved violation of Illinois Biometric privacy act(BIPA) due to their usage of YouTube videos without the consent of involved individuals, and therefore could subject them to Billions of dollars in fines/settlement.

Sweet-Management5237

AI, Trump has bigger boobs in RL

TimingEzaBitch

2010-2020 or so was the main breakthrough time for the actual models/maths/smart implementations behind them. Last several years was more of a throw infinite money and compute power to it. Not sure there is another theoretical breakthrough wave is coming though. I did my PhD in Reinforcement Learning and that shit is pretty much capped in terms of theory. Going from NLP to Transformer was the catalyst. Throw Monte Carlo Tree Search in there and you get the basics of current LLMs. Mathematically speaking, it's hard to imagine what or how the next big leap will be. As long as we do loss minimization + predict next token, we are theoretically very close to hitting a wall if we have not already. On the bright side, I do think local and compact agents will have rooms to improve. Mathematicians and computer scientists have a deep sleeve of tricks to apply to a much smaller and more well-defined problems like that. Perhaps, something like "forgetting" or re-using parameters smartly is a research area that can have potentially have some surprise findings. Finally, if we could form a sustained pipeline of academic/interdisciplinary research into these things, then that will be the smartest long-term investment. All kinds of wonderful things could come out of that. My advisor and my research was on using RL in computational neuroscience and the entire community is like 20 people max. There are shit ton of rooms for breakthrough if there were a vibrant and funded community around that or things like certain cancer detection labs.The OpenAI, DeepMind craze will eventually die down due to scooping up all the low-hanging fruits.

Cold_Specialist_3656

That is not true. Deepseek introduced MoE at scale, MLA, and modern RL.  It was probably the most important and influential model since original GPT

averi_fox

I work on LLMs and it's the first time I hear agentic makes things cheaper? Lol definitively not, even more RAM for way longer trajectory lengths, more RL (which is less efficient than supervised training). Plus inference needs memory bandwidth - you've got to fetch all those parameters into memory quickly, and you can't batch as much to keep latency low.

Iconically_Lost

quick pop it so it can spread. With the current leadership, playing this in RL would be allot easier.

Hoak-em

As a researcher, the papers and techniques used in the most recent release are the big shifts here. They created a super memory-efficient method of dealing with long context alongside a bunch of other optimizations that allow them to serve the model at a highly reduced cost. V4 is an excellent foundation model technology-wise, and MoonshotAI and ZAI will RL it into state-of-the-art — similar to what they did with V3/R1. This, and US AI companies are trying to shift into profitability by increasing the cost to consumers — which they’ll find doesn’t work when there’s a Chinese product for a fraction of the price.

Far-East-locker

# Consumer |**Ticker**|**Dec 22, 2025 Price**|**Apr 28, 2026 Price**|**% Change**| |:-|:-|:-|:-| |**AZO**|$3,391.50|$3,577.91|\+5.50%| |**CVNA**|$155.00|$210.40|\+35.74%| |**CELH**|$48.20|$55.60|\+15.35%| |**SBUX**|$92.40|$98.67|\+6.79%| |**DKNG**|$42.10|$49.30|\+17.10%| |**UAL**|$65.20|$78.45|\+20.32%| |**RL**|$185.00|$212.30|\+14.76%| |**VIK**|$35.40|$42.10|\+18.93%| |**Category Average**|||**+16.81%**|

mrstrangeloop

Wouldn’t be shocked if RL materially benefits from more than which currently exist.

Deep-Bench-2016

Four reports in 24 hours on Wednesday is not a "pick the winner" setup — it's a "find the divergence" setup. Here's how I'd frame what to actually watch: 1. Capex guide vs. cloud rev growth. MSFT, GOOGL, and META all guided $80-100B+ capex for FY26. If any of them lifts the capex number AND keeps cloud accelerating, that's the bull case re-stamping itself. If capex ticks up but cloud growth flattens, that's the first crack — they're spending into a slowing demand curve. 2. AWS operating margin direction. AWS margin has been the swing factor for AMZN three quarters running. If margin is flat or down with rev growth above 18%, that's actually fine — they're investing. If margin is up but rev decelerates, that's cost-cutting masking demand softness, which is the worse setup. 3. Meta's Reality Labs loss vs. ad rev growth ratio. Reality Labs lost \~$17B last year. If ad rev growth is decelerating AND RL losses are widening, the stock is going to take a different reaction than the "bulls love everything" setup the last few prints have produced. 4. Apple is the loneliest report. AAPL doesn't have an AI capex story to ride, so it has to win on services margin and iPhone unit cycles. The bar is highest there because AAPL has been flat-to-down YTD while the rest ripped. Honest take: the easy money on this print cycle was already made in the run-up. The interesting trades come Friday morning, after we see which of these four diverges from the others. Sector beta gets you to the print; idiosyncratic moves come after it.

Correct-Ad-4285

What convinced you to Invest so much in RL?

-vp-

RL **without** HF isn't something inherently impossible with an LLM / transformer achitecture though. If the model itself is able to self post-train and re-weight itself to "understand" new facts, handle novel tasks asked up them *reliably*, etc.would that meet your definition of AGI? It's something certainly possible with today's architecture albeit likely infeasible in terms of speed, cost, and accuracy and what frontier labs are trying to achieve.

SporksInjected

Ok well that’s great. Waymo is a good thing and you’re right that it would be devastating to their product if you had to intervene. They have a fleet of 3,500 really expensive and specialized vehicles that do a very specific thing and their business is valued on the product doing that. Tesla has a fleet of over six million vehicles that are sold to consumers. They’re selling a lot of cars. My point is that they don’t exactly need to increase their own liability to fully level 3 right now because the business is doing fine with “it drives you wherever you want, but you have to pay attention” Another really good against level 3 for Tesla though is that when you drive in FSD, you’re working for Tesla to make their models better. The car is getting your human telemetry and your RL/feedback to retrain the software. By having this as supervised, they get that for free.

SporksInjected

Ford will literally never catch up and here’s why: Tesla has the only complete, in-house training/RL pipeline. It’s without a doubt the best in the industry because every single car on the road is collecting training data as well as RL/feedback. Millions of cars driving millions of miles per day capturing feedback. Ford or any other American OEM simply doesn’t have anything like this. You can have level 2 or 3 from heuristic systems but it won’t be as versatile as the Tesla solution.

_hiddenscout

RL still has been pretty solid lol. It's the only retail thing I own.

PARABOLIC-Explorer

I don’t like the Cvnt mouth of my ChatGPt. That lil bistch would find me outside in RL

Gizznitt

[Congressional Salaries and Allowances: In Brief | Congress.gov | Library of Congress](https://www.congress.gov/crs-product/RL30064#:~:text=Additional%20information%20on%20many%20of,found%20in%20reports%20referenced%20throughout.&text=The%20compensation%20for%20most%20Senators,from%20Puerto%20Rico%20is%20%24174%2C000.) Compensation The compensation for most Senators, Representatives, Delegates, and the Resident Commissioner from Puerto Rico is $174,000.

Gizznitt

[Congressional Salaries and Allowances: In Brief | Congress.gov | Library of Congress](https://www.congress.gov/crs-product/RL30064#:~:text=Additional%20information%20on%20many%20of,found%20in%20reports%20referenced%20throughout.&text=The%20compensation%20for%20most%20Senators,from%20Puerto%20Rico%20is%20%24174%2C000.) Compensation The compensation for most Senators, Representatives, Delegates, and the Resident Commissioner from Puerto Rico is $174,000.

AllCapNoBrake

RL look into r/Bitcoin daily thread....LAST year. https://preview.redd.it/883ikp3dkuug1.png?width=399&format=png&auto=webp&s=6d0da16e89f29a211ef318b50b2025a44ffbd699

vplatt

😲 Oh.... that is so SO on point. I'll take a meme war over some stupid actual RL carnage, but hey here we are that we get both. Maybe they can heat sink the real war efforts with extensive propaganda and keep the administration so enraged with them that they don't even notice their commanders ignoring all their raged out illegal orders. Honestly, I think they're on to something here. The Lego style theme is a winner! Shoot, give 'em a Nobel award and see what happens.

roswelljack

going the Civ Gandhi route apparently. Shame RL is not a video game though.

physicshammer

I’m a bit younger than you but not much… What I do is, basically I invest a percentage of my “cash” based on what the current price / valuations are at… so when the market was at 7000, I was 60% in cash. The market went down about 9%, some companies (like GOOG, MSFT, etc.) were down 20% or so… during that time period, I put in about half of that cash, so now I’m at 30% cash. I built up positions in GOOG, MSFT, BRK.B, UI, RL, JPM, TSMC, ASML, etc… the biggest movements were into GOOG and MSFT. Now that the market is kind of irrationally high again in my mind, and with great uncertainty about Iran (I think people might be overly sanguine about it), I’m taking some back out - but maintaining almost the entirety of the positions in GOOG and MSFT, because I am loathe to sell them while they are low :) Anyway - long story short - I do it as a PROPORTION of my cash, and I do things pretty gradually… except when prices on GOOG went down 20%, I deployed cash pretty damn quickly.

Independent-Tree-985

Life is like an RL Stine's choose your own adventure book, and most of you choose to put on the vampire mask

Rich-Use1484

RL in Zurich still employs tons of FTE and Contractors (CW- Contingent Workers). Zurich is a high cost location and CWs are not cheap. So don't believe in Meta's layoffs news.

kalakatikimututu

This is oversimplification. Cursor started from Kimi K2.5, then continued pretraining it and did substantial RL/post-training to make Composer 2.

Boromir-Wants-

I honestly crave attention and it’s obvious asf by the posts I’ve made her today. Not Karma board tells you all you need to know how engaging I am in RL. FML 🤦

Boromir-Wants-

I have a man bun in RL.

funkinaround

Total US Foreign Aid to Israel from 1946 - 2025: \- Military: $124.5B \- Economic: $34.3B \- Missile Defense: $16.1B From [https://www.congress.gov/crs-product/RL33222](https://www.congress.gov/crs-product/RL33222) Also, with respect to economic aid: >For many years, U.S. economic aid helped subsidize a lackluster Israeli economy, but since the rapid expansion of Israel's high-tech sector and overall economy in the 1990s ... Israel and the United States agreed to gradually phase out economic grant aid to Israel. In FY2008, Israel stopped receiving bilateral Economic Support Fund (ESF) grants. The country had been a large-scale recipient of grant ESF assistance since 1971. From what I can tell, this aid, like the military aid, required Israel to spend the money on US suppliers. If they bought vaccines and medical equipment from the US to support their universal health care, then I guess that could fit with your guess.

funkinaround

[https://www.congress.gov/crs-product/RL33222](https://www.congress.gov/crs-product/RL33222) >To date, the United States has provided Israel $174 billion (current, or non-inflation-adjusted, dollars) in bilateral assistance and missile defense funding. We give (and have been giving) Israel money to buy our weapons.

averi_fox

They got good at math (like actual math aka theorems etc) when they started doing RL for verifiable math problems. "Handing it off to a calculator" is only the easy part of it that only works for computation, not for general math. They can find and verify proofs quite well. On the "uncommonly used combination of libraries": if you use a top-end thinking model (i.e. deep think) and give it a way to verify the results (like executing code) it should find the novel combinations. It will definitely compile when the LLM has the tools to check if the code compiles The problem is the complexity scale, the best models are great at solving well-defined, scoped problems but get lost and messy once the scope gets too big. But that complexity wall has always been here (and always will be), but is constantly being pushed: compare opus 4.6 vs gpt 4. Our expectations got way way higher. The benchmark is about pushing it further to whole codebases with many commits.

RedParaglider

Every model uses distillation. That whole drama over distillation was hilarious for anyone that knows how all LLM's are given RL. That was bullshit technobabble made for investors that don't know their head from their ass.

Lord_Rictor

I don't buy it at all that's the problem. It's refreshing to think outside the box but unfortunately refreshing things never happen in real life. People are more addicted to the internet than ever. AI is only going to boost that with personalized content down to your exact preference of boob size and skin tone. Maybe you want to watch a new game of thrones ending? The idea people will be going out more in RL is ridiculous. For one thing they're not going to have the jobs or the funds to do it. Government will keep the bread and circus going. The bread speaks for itself and the circus is going to be AI.

btcale546

https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTFwV8HOjXYSagom1gmfhDlVlE3KQ7RL0C5NQ&s

Hulksulk666

The open Labs / academia and the closed labs are not so far behind in terms of secret sauce . And there already exists alternative transformer architecture (mamba exist and is used) , what the labs are rushing towards is better generalization method in post training other than pure RL since that's not sample efficient .Though they for now it seems their answer to generalization is just throw enough money at it and train on all use cases.

Luctom

RL model training?

eagle2120

RL/RLHF envs negate that need, which experienced offensive operators can clearly see do when they work with the tools and latest models. The uplift for capable actors is quite a bit

skilliard7

>Google's LLMs are competitive by any reasonable benchmark Google makes extensive use of RL to overfit their models to benchmarks, which makes them perform far better in benchmarks than they do in real world tasks. >I use it every day for work as a senior software engineer to accomplish a wide variety of coding tasks, with similar performance to other models I've tried. I've found it to perform significantly worse than Anthropic and OpenAI's models for high complexity tasks. Gemini is good enough for basic coding, but if you are working on apps that require high performance, Claude Opus and GPT 5.2 seem to perform much better >Search and YouTube are having no decline in engagement per the recent ER - search in particular has defied predictions of its imminent demise for quite some time now. ER is only through Dec 2025. The 20% YoY reduction in search traffic was reported for Jan 2026.

skilliard7

> Google stands to benefit most if they start enshittifying and/or more heavily paywalling ChatGPT. You say that, but Google has been enshittifying their product far more than OpenAI has: 1. They are increasing ads displayed on Search and YouTube to boost revenue, at the expense of user engagement. 2. They changed Gemini Pro to always default to their "flash" model, to try and save compute costs... makes for a lousy UI. What are your thoughts on Google failing to produce a competitive LLM, and relying on RL to overfit to benchmarks, misleading investors? I've been running my queries across all LLMs(OpenAI, claude, Gemini), and fact checking the results, and Gemini consistently has a much higher hallucination rate than the others.

Randromeda2172

BO is impressive and is definitely ahead of RL, but RL is the better company imo. There is no reality where launching and landing a medium lift rocket is easy, but it IS easier when you've got one of the world's richest people bankrolling you. RL had to fund Neutron through Electron and Space Systems, which understandably slows it's pace.

Marston_vc

Kind of irrelevant. Everybody knows BO has dragged their feet. That’s exactly why Bezos fired the CEO a year or so ago and replaced him with someone more ambitious. The nature of reusables is that they are essentially exponential. Once BO lands on a reliable and reusable model, which it appears they are nearing, every serial number off the press thereafter is potentially hundreds more in future launch capacity. The BO and New Glenn of today don’t really care about the previous 20 years beyond “let’s be faster than that”. And to be clear, it’s not like Rocket Lab is a new company either. BO was founded in 2001 to RL’s founding in 2006…..

Marston_vc

Blue inarguably ahead of RKLb. I’m long RKLB and got in around $3. I’m very happy with them and think SPB is a great CEO. But from a pure hardware perspective, BO has launched their Falcon 9 competitor, New Glenn, twice and landed the second. Comparatively, RL hasn’t launched their Neutron once yet. I’ve long been a BO hater but it’s a fact that they are ahead of RL regarding reusables as of right now and that won’t be debatable until RL lands its first Neutron rocket and even then it looks like BO is already trying to *reuse* its NG2 booster *this month*. If I had to say, BO is easily a year ahead of RL right now unless RL radically increases their tempo.

candyking16

Funniest thing to come out of Amy 

CEO-of-SOXL

Wife is working late tonight at the club. Time to put the kids down and get some Uber Eats. It’s Lobsterfest at RL boyz

MyGruffaloCrumble

Same thing can happen to your bank account, brokerage account, or any other thing connected to the internet. In RL someone can rob you at gunpoint, clone your debit card, kidnap or mock kidnap a loved one to force you to capitulate.   Scammers are going to scam, regardless of how you choose to hold your net worth.

astromouse2024

What I’m REALLY waiting for is RL. Huge fan of the brand, and I’m liking their insane pricing power with the I think 18% in average unit retail. Obviously tariffs are a huge issue but other than that it’s great. I’m just waiting to see if there’s a bottom because it doesn’t look as though it’s at a discount where it’s at NOW.

eeaxoe

His people are right. The US *is* behind China on open-source AI models. Just compare Llama to Qwen or Kimi — the former is a steaming pile of garbage that torched billions of dollars a la RL for Meta, whereas the latter models are the first choice for startups looking for a model to build on. I even have a side project myself based on Qwen.

_hiddenscout

I really think some retail names are going to have a new boost from holiday sales. Still holding RL and hoping for good numbers.

d33p7r0ubl3

Started seeing a lot more RRL and Polo around Manhattan lately. RL's latest catwalk also has people turning heads. I'm eyeing a position as I think U.S. sales will show growth

weisswurstseeadler

I'm yet to meet a single person in RL actually excited about VR. Even for people excited about the tech (I work with lots of IT Engineers) it's just dusting on a shelf and is 'cool' for just some niche stuff every other moon. And kinda mirrors my experience with VR - cool for a bit, but more like tech-demo cool. AR - on the other hand - I see much more potential.

Blze001

Yeah, well, in RL I'm broke AF too. Becha feel dumb now!

hasuchobe

Ask the people that sold it down to 75% in 2022. Tech stocks frequently get hit with 50% corrections. The 2022 narrative is about to replay again but this time its RL and AI departments burning a hole in META's pockets. No ad-pocalpyse (yet) so no giga correction yet. Also Zuck is pre-empting by trimming down employees which is what gave them the 2022 reversal.

Flat-Jacket-9606

I mean, I didn’t even know it existed until my Fiancee said she liked RL and I should invest. I made fun of her for a bit and she made me look into it, and yeah here I am. One of our quiet lowkey money makers. And it still looks like they have strong growth and are still expanding. Who am I to complain.

d33p7r0ubl3

RL is such a weird one to me because I can’t find anyone who purchases their clothing yet the stock continues to rip.

skilliard7

1. Google is known to cheat at benchmarks by overfitting their models via RL to perform well on benchmarks, when they perform poorly in real world topics. 2. Google still relies on Nvidia for training; their TPUs are mainly for inference(running the models in production) 3. There are other competitors that do a better job than Google's TPUs for inference tasks. 4. Google's deal with Apple is unprofitable and cheapens their brand. They are being paid ~$0.05 per month per iPhone user and have a liability to provide AI services. That's dirt cheap compared to the $20 a month most LLMs charge.

PM_40

>Leading models have hardly improved in the past year in real world performance; most of the perceived gains are just from overfitting RL to benchmarks. This gives shareholders the illusion of progress, when in reality LLMs are not much different to where they were a year ago. That's cheating and siphoning off investors money at scale and likely all are doing it.

_hiddenscout

So wild to look back at this stuff sometimes. RL is up like 13% from this. However, GILT is up 52% lol.

brielkate

Those are still nice brands though; WHBM is underrated in my opinion. The brands that are “hot” really seem to be going after younger people… like Aritzia. That said, their product has such wide appeal that I’ve seen ladies who would be the WHBM/RL type shopping at Aritzia now, and I do think that customer might find Aritzia’s Wilfred and Babaton lines quite attractive.

mustachechap

RL?

iMakeGOODinvestmemts

$META was cheap because people didn’t value the cost of dram and NAND memory they have to overspend by 100% higher. So buyside capex was most likely if I were to guess was $20-25B above consensus. If you take that out from PT that’s why stock was so below all 30x PE or 40% below PTs. I think both buyside and sell side is wrong. If they cut RL, and Dram/Nand prices start going down next year, it could be Goldilocks for Meta that’s about what I can say. No financial advice. It’s an IF as Zuck has chosen to keep RL alive.

iMakeGOODinvestmemts

[$Meta](https://x.com/search?q=%24Meta&src=cashtag_click) was cheap because people didn’t value the cost of dram and nand they have to overspend by 100% higher. So buyside capex was most likely if I were to guess was $20-25B above consensus. If you take that out from PT that’s why stock was so below all 30x PE or 40% below PTs. I think both buyside and sell side is wrong. If they cut RL, and Dram/Nand prices start going down next year, it could be Goldilocks for Meta that’s about what I can say. No financial advice. It’s an IF as Zuck has chosen to keep RL alive