also referred to as: meta
includes Facebook Messenger, Facebook Marketplace, Facebook AI Research, Facebook M
66 statements across 38 episodes · 26 bullish · 11 bearish · 36 people on the record · first statement Jun 20, 2023 by George Hotz · said 344 times in 102 episodes since 2023 · across every show →
Mentions by year, the whole family
brought up most by Shawn Wang (89), Nikhila Ravi (10), Lin Qiao (9), Ari Morcos (9), Thomas Scialom (8), Alessio Fanelli (8), Vibhu Sapra (6), Nathan Lambert (6)
tap a year for its mentions
2026 56 mentions in 26 episodes 2 per episode
- Marc Andreessen introspects on Death of the Browser, Pi + OpenClaw, and Why "This Time Is Different"
- Scaling Past Informal AI - Carina Hong, Axiom Math
- The Agent-Native Cloud: 3M Users, 100K Signups/Wk, Data Centers, & Death PRs — Jake Cooper, Railway
- Simulating Humanity: from Generative Agents to 8 Billion Digital Twins — Joon Sung Park, Simile AI
- 🔬 "The Most Innovative Diffusion Research Is Happening in Drug Discovery, Not Image Generation"
- Agent Inference at the "Speed of Light" — How NVIDIA moves like a $4.3 Trillion Startup
- Inside AI’s $10B+ Capital Flywheel — Martin Casado & Sarah Wang of a16z
- Captaining IMO Gold, Deep Think, On-Policy RL, Feeling the AGI in Singapore — Yi Tay
- 18 more episodes that year, every mention in 2026 →
2025 123 mentions in 36 episodes 3 per episode
- The AI Agenda: GPT5 leaks and the business of AI News — Steph Palazzolo, The Information
- Better Data is All You Need — Ari Morcos, Datology
- The RLVR Revolution — with Nathan Lambert (AI2, Interconnects.ai)
- SAM 3: The Eyes for AI — Nikhila & Pengchuan (Meta Superintelligence), ft. Joseph Nelson (Roboflow)
- 2024 Year in Review: The Big Scaling Debate, the Four Wars of AI, Top Themes and the Rise of Agents
- Steve Yegge's Vibe Coding Manifesto: Why Claude Code Isn't It & What Comes After the IDE
- World Models & General Intuition: Khosla's largest bet since LLMs & OpenAI
- Why RL Won — Kyle Corbitt, OpenPipe (acq. CoreWeave)
- 28 more episodes that year, every mention in 2025 →
2024 141 mentions in 31 episodes 5 per episode
- Why Compound AI + Open Source will beat Closed AI — with Lin Qiao, CEO of Fireworks AI
- Open Source AI is AI we can Trust — with Soumith Chintala of Meta AI
- Training Llama 2, 3 & 4: The Path to Open Source AGI — with Thomas Scialom of Meta AI
- [LLM Paper Club] Llama 3.1 Paper: The Llama Family of Models
- The Winds of AI Winter (Q2 Four Wars of the AI Stack Recap)
- Segment Anything 2: Memory + Vision = Object Permanence — with Nikhila Ravi and Joseph Nelson
- [Paper Club] Molmo + Pixmo + Whisper 3 Turbo - with Vibhu Sapra, Nathan Lambert, Amgadoz
- Answer.ai & AI Magic with Jeremy Howard
- 23 more episodes that year, every mention in 2024 →
2023 24 mentions in 9 episodes 3 per episode
- The State of Silicon and the GPU Poors - with Dylan Patel of SemiAnalysis
- Ep 18: Petaflops to the People — with George Hotz of tinycorp
- RAG is a hack - with Jerry Liu of LlamaIndex
- Generating your AI Media Empire - with Youssef Rizk of Wondercraft.ai
- Beating GPT-4 with Open Source Models - with Michael Royzen of Phind
- The End of Finetuning — with Jeremy Howard of Fast.ai
- RWKV: Reinventing RNNs for the Transformer Era
- FlashAttention-2: Making Transformers 800% faster AND exact
- 1 more episode that year, every mention in 2023 →
Everything said about Facebook, oldest first
Jun 20, 2023 negative
Oct 20, 2023 negative
Howard: Meta 'blew it' on Code Llama due to catastrophic forgetting
“So Code Llama was a, I think it was like a five hundred billion token fine-tuning of Llama II using code. And also prose about code that Meta did. And honestly, they kind of blew it. Because Code Llama is good at coding, but it's bad at everything else.”
Dec 5, 2023 neutral
Jan 11, 2024 neutral
Lambert: Only 20% to 40% of Meta's Llama RLHF data is useful
“I do think that if we had all the llama data, we wouldn't know what to do with all of it. Like, probably, like, 20 to 40% would be pretty useful for people, but not the whole data set. Like, a lot of it's probably kind of gibberish, because they had a lot of d…”
Jan 11, 2024 positive
Lambert: Meta Used Rejection Sampling to Bootstrapping Llama 2 RLHF
“Llama started their RLHF process with this to get some signal out of preference data. That preference data went into a reward model, and then the reward model did a good enough ranking that it was, like, essentially superpowered instruction tuning based on rew…”
Jan 11, 2024 neutral
Feb 7, 2024 bullish
Future Llama models will match frontier GPT models if progress slows
“As AI progress slows down, so if we get like Llama-IV, Llama-V for example, maybe it's a comparable at that point, like GPT-V or GPT-VI, like, It made it to the point where it was like, look, I just want to use Lama. Like, it's, you know, safe for me to, you k…”
Feb 19, 2024 bullish
Only Tech Giants Will Build In-House AI Infrastructure Long-Term
“I think a lot of these companies over in the long run, like, you know, they're accepted maybe super big ones, like, you know, the Facebook and Google, they're always gonna build their own ones, but like everyone else, like some extent, you know, I think they'r…”
Feb 28, 2024 positive
Mar 6, 2024 neutral
Chintala: Time and data constrain Meta LLM releases more than GPUs
“So, I think the, it's all a matter of time. I think time is the biggest bottleneck. It's like, when do you stop training the previous one, and when do you start training the next one? And how do you make those decisions? The data, do you have net new data, bet…”
Mar 6, 2024 positive
Chintala: Meta built FAIR because AI capabilities rate-limited Meta's product development
“And for, then, like, the thesis was very simple. It was, like, AI is currently rate-limiting Meta's ability to do things. Our ability to build various product integrations, moderation, various other factors. Like, AI was the limiting factor, and we just wanted…”
Mar 6, 2024 bullish
May 31, 2024 positive
Huang: Curriculum context expansion outperforms full-length training from scratch
“If you train a model on a shorter context and you progressively increase that context to, like,
You know, the final limit that you have, like, 32 K is usually the limit of Lama two was that long.
It actually performs better than if you try to train 32 K the …”
Jun 25, 2024 neutral
Jul 5, 2024 neutral
Jul 5, 2024 bullish
Yi Tay: Llama 3 shows Meta may have caught up to Google
“So I think I don't really follow, like, fine much, but I think that, like, Lama Tree actually shows that, like, kind of, like, Meta got a pretty, like, a good stack around training these models you know, like, oh, and I've even started to feel like, oh, they a…”
Jul 5, 2024 neutral
Jul 23, 2024 bullish
Scialom: Llama 3 Scaled Pre-Training to 15 Trillion Tokens
“It's the same recipe done in terms of architectures and training than LAMA-II, but we put so much effort on scaling the data and the quality of data. There's now 15 triant tokens compared to two triants, so it's another magnitude there as well, including for t…”
Jul 23, 2024
Meta changed Llama 3's pre-training data mixture mid-training run
“What happened is we changed the data mix during the training of Lama three with some findings that happened in the... Training is long, so you have to do something while it's training. And what the team did, I was working on my side of motion post-training, bu…”
Jul 23, 2024 positive
Scialom: Meta Used Llama 2 to Filter and Tag Llama 3 Pre-Training Data
“LAMA was the best, at the time, before LAMA Free, the best model we had access to legally, to labelize the web and select what are the good tokens and the bad tokens. The additional thing is that it also enabled to have a topic tag, Like, is it about law? Is i…”
Jul 23, 2024
Jul 23, 2024 positive
Scialom: Meta expanded Llama 3's vocabulary size to support multilingual capabilities
“Lama III compared to Lama II is multilingual, has multilingual capabilities. We worked on that. And so, because you have languages that are not just Latin languages like English, there's a lot of different characters you want to include them to represent, like…”
Jul 23, 2024
Jul 23, 2024
Jul 23, 2024 positive
Jul 29, 2024 positive
Meta used stepwise reward models and Monte Carlo Tree Search for Llama 3.1
“They actually went the extra step to, no pun intended, to actually train stepwise reward models. That's kind of crazy, no? I mean, they wanted each step in the chain of thought to be so good that they actually took the extra effort to train step, to train step…”
Jul 29, 2024 positive
Aug 17, 2024 neutral
Nov 25, 2024 neutral
Nov 25, 2024 bearish
Shawn Wang doubts Meta's Llama Stack will win broad developer adoption
“I've been a little bit more doubtful on Lama stack. I think you've been more positive. Basically, it's just like the meta version of whatever HuggingFace offers, you know, or TensorRT, or BLM, or whatever the open source opportunity is. But like, to me, it's n…”
Dec 13, 2024 neutral
Mohan: Codeium's office housed Ghost Autonomy and 'Silicon Valley' exterior shoots
“It previously was being leased by, I think, Facebook slash WhatsApp. And then immediately after that Ghost Autonomy, and then now here we are, and we also, you know, I guess one of the things that the landlord told us was this was the place that they shot all …”
Dec 22, 2024 neutral
Robinson: Original DiT Research Showed Compute Scaling Outweighed Hyperparameters
“This is so interesting because the original diffusion transformer paper from Facebook actually showed that, in fact, the specific hyperparameters of the transformer didn't really matter that much. What mattered was that you were just increasing the amount of c…”
Dec 24, 2024 positive
Meta research: Sub-1B language models benefit more from depth than width
“For example, they find that depth is more important than width, so it's more important to have models that have, like, more layers than just making them more wide. They also find that GQA helps, that tie-in the embedding helps, so I think it's a nice study ove…”
Dec 24, 2024 neutral
Jan 19, 2025 negative
Mar 28, 2025 negative
Shah: Meta and LinkedIn keep social and professional graphs aggressively closed
“Right now our information, all of us nodes are in the social graph at Meta or the professional graph at LinkedIn, both of which are actually relatively closed and actually very annoying ways. Like very, very closed, right? Especially LinkedIn.”
Jul 11, 2025
Speak's pronunciation coach fine-tunes Meta's wav2vec on proprietary phonetic transcripts
“We have for English only right now, a pronunciation coach that is basically like a fine-tuned version of WaveDeVec, which is a meta model, but we basically fine-tune it on a bunch of our own phonetic transcripts, like fine-tuned data.”
Jul 14, 2025 bearish
Jul 23, 2025 bullish
Jul 28, 2025 neutral
Jul 31, 2025 positive
Lambert: Top AI talent is dramatically cheaper than GPU clusters
“Talent is cheaper than GPUs by a dramatic margin, and At the end of the day, it's like, okay, if we're spending this much, they go to the room and they stare in the mirror and you're like, wait, it might not actually be that ridiculous to spend this money on t…”
Jul 31, 2025 negative
Jul 31, 2025 bullish
Aug 6, 2025 negative
Palazzolo: Meta should focus on app integration over frontier models
“Maybe what's actually good for their P&L and their finances is to not focus so much on building these, like, insane, huge, state-of-the-art models, which they've obviously struggled with more recently, but it's to take things that are, you know, 70, 80, like, …”
Aug 29, 2025 bullish
Morcos: Meta's metaverse bet will pay off in the long run
“I think the one that's still really up in the air is a metaverse, but I would actually argue that I think that's going to end up paying off in the long run. I think the Ray-Ban glasses pretty darn cool. And a lot of the foundations of what was in reality labs …”
Aug 29, 2025 bearish
Morcos: Frontier AI lab data teams are systematically under-resourced
“I think you, what you see in all the frontier labs is that they have data teams. And if you talk to the folks that work on those data teams, what you'll kind of systematically hear is that typically they're under resourced relative to the gains that they're de…”
Aug 29, 2025 neutral
Morcos: Yann LeCun was never defining Meta's AI strategy
“I don't think he was ever you know, or at least not since the beginning in a role where he was defining AI strategy for Meta. I don't think that's the role he wanted at any point. You know, I think he really wanted to be doing that research, and I think, so I …”
Aug 29, 2025 neutral
Morcos: Zuckerberg personally approved high-risk AI training datasets at Meta
“When I was at Meta, certainly legal stuff around data sets was very challenging and becoming increasingly challenging, and there are a number of situations where, you know, the only person that could approve things was Zuck because of the scale of the risk, I …”
Dec 12, 2025 bullish
Swyx: Priscilla Chan will have more impact on humanity than Zuckerberg
“My quick hot take in, in a single sentence is if Priscilla Chan gets Half of what she wants to do done. She will have more impact on humanity than Mark Zuckerberg, right? The Facebook will just be a funding mechanism for the greatest bio research work done in …”
Dec 18, 2025
Ravi: Meta's SA-Co Benchmark Has Over 200,000 Unique Concepts
“If you look at the size of these benchmarks, the previous benchmark, Peng Chuan mentioned, Elvis, that everyone uses, it has about 1.2 K unique concepts and the benchmark that we created, which we're calling segment anything with concepts or Seiko, COCO for sh…”
Dec 18, 2025
Dec 18, 2025 neutral
Dec 18, 2025 positive
Ravi: Meta built SAM 3 using open-source community contributions to SAM 2
“In SAM-III we did leverage many of the open source contributions people have made on top of SAM-II.
There were new data sets, there were new benchmarks,
There were new kind of inference time optimizations.
We adopt a lot of the things that the community builds…”
Dec 18, 2025 neutral
Dec 18, 2025 positive
Zhang: Fine-Tuned Llama 3.2 Achieved Superhuman Vision Verification Performance
“We kind of fine-tune our, kind of, for example, NAMA's 3.2 with our, kind of, verification, human annotated verification data. We get, kind of, superhuman performance on these two verification tasks, and then we do not need human on these two tasks. Let's furt…”
Dec 18, 2025 neutral
Ravi: Meta Achieved Fully Automated Annotation in SAM 1, Not SAM 2
“Getting to that fully automated data engine is something that we tried to do in SAM too. We actually didn't get to that fully automated approach. In SAM one, we did, we, you know, But the SA-I-B dataset that we released was fully annotated automatically. We di…”
Feb 24, 2026 bearish
Feb 26, 2026 neutral
Mar 24, 2026
Kulik: Academic Labs Must Avoid Problems Solvable by Brute-Force Compute
“For sure, Microsoft, Meta, those ones are kind of like the companies that have basically infinite resources, and as an academic, I don't have infinite resources, you know, but we have an interest in problems that, you know, haven't crossed the radar of those c…”
Mar 30, 2026 positive
Lample: Post-training breakthroughs like DPO were impossible without open LLaMA
“And if you look at many of the techniques that were developed after, for instance, Temma was open source, like all these post-training approaches like even DPOD, like performance optimization, all of this were done by people that had access to this model, and …”
Jun 17, 2026 positive
Jun 25, 2026 positive
Jun 30, 2026
Jul 16, 2026 negative
Aug 21, 2026 positive
Park: Facebook data better captures human baseline state than LinkedIn or Twitter
“If we were to look at purely social media, like if you really, you know, if I were, you know, if I had to really pick, Facebook likely is interesting because I actually do think it is most sort of a default version of people because you go to LinkedIn, it's ve…”