app / likes
Spark
“Um, the only thing I like out of, out of Codex is the, is like Spark and like yeah.”
Public evidence record
Shawn Wang
Host · Latent Space
- Claims
- 500
- Episodes
- 64
- Shows
- 1
- Named items
- 20
Books, apps, and tools
The evidenced stack.
app / uses
Bank of America
“Yeah. I got, I got the tool. Uh, what, like, I hate, I use Bank of America. I hate bank, I hate the app. Mm-hmm. I hate the web. All banking websites just horrible.”
other / likes
Wiki approach
“I like the, the Wiki approach. Uh, my, I’m actually like, uh, you know, obviously I spent some my time at cognition, which, uh, you, you know very well.”
person / uses
Ted Chiang
“You were very excited because I read Ted Chiang over the holidays and I was very inspired by this short story called Understand, which apparently is, like, pretty old.”
app / uses
Overcast
“I used to use Overcast. So it would just link to the Overcast page.”
other / uses
Snip
“By the way, we use the snip count as a proxy for popularity, right? Because we have download counts, but for example, platforms like Spotify re-host our MP3 file.”
other / recommends
The Peel
“I think I strongly recommend Jack Bridger's Scaling DevTools, as well as Turner Novak's The Peel.”
other / recommends
Scaling DevTools
“I think I strongly recommend Jack Bridger's Scaling DevTools, as well as Turner Novak's The Peel.”
app / uses
AI News
“So that's what basically I use AI News for. I have a lot of prompts and a lot of steps and a lot of criteria and O1 just kind of checks through each kind of systematically.”
tool / built
Bolt.new
“It's funny because I built on top of the fork of Bolt.new that already has the multi LLM thing.”
other / uses
XML
“I use XML in other models as well, and it's just a really nice way to make sure that the thing that ends is tied to the thing that starts. That's the only way to do code fences where you're pretty sure example one start, example one end, that is one cohesive unit.”
app / uses
DevIn
“I used to tell people go to the DevIn demo and look at the four things that they offer and say each of those things is a startup.”
Claim ledger
What Shawn said.
28 transcript-backed records
01 / prediction
‘Cause it’s a statistical thing, but as long I don’t know if regulators understand that, you cannot extrapolate from a single incident, but we do because that’s all we have to go on.
“‘Cause it’s a statistical thing, but as long I don’t know if regulators understand that, you cannot extrapolate from a single incident, but we do because that’s all we have to go on.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
02 / prediction
Um, I do think, like, uh, it is interesting that, uh, for a while I was, I was considering the theory that models capped out at two, 2 trillion, and I think that’s proving to be wrong.
“Um, I do think, like, uh, it is interesting that, uh, for a while I was, I was considering the theory that models capped out at two, 2 trillion, and I think that’s proving to be wrong.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
03 / prediction
I think the personalization turn that is coming, um, will be big. And I don’t know what that looks like because like basically we’re kind of, we feel kind of tapped out on the memory side of things.
“I think the personalization turn that is coming, um, will be big. And I don’t know what that looks like because like basically we’re kind of, we feel kind of tapped out on the memory side of things.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
04 / prediction
One of my theories is that because the proofs takes so long, it’s actually just a proxy for long horizon reasoning and coherence and planning.
“One of my theories is that because the proofs takes so long, it’s actually just a proxy for long horizon reasoning and coherence and planning.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
05 / prediction
I think you, you had [00:01:00] cloud agents before, but this was like, you give cursor a computer, right?
“I think you, you had [00:01:00] cloud agents before, but this was like, you give cursor a computer, right?”
- Speaker
- Shawn Wang
- Episode
- Cursor's Third Era: Cloud Agents
- Publisher
- Latent Space
06 / prediction
So obviously has a research team. And my thesis is like you just, every agent lab is going to have a router because you’re going to be asked like, what’s what.
“So obviously has a research team. And my thesis is like you just, every agent lab is going to have a router because you’re going to be asked like, what’s what.”
- Speaker
- Shawn Wang
- Episode
- Cursor's Third Era: Cloud Agents
- Publisher
- Latent Space
07 / prediction
One way I was thinking about kicking on this conversation is we will likely release this right after CoreWeave IPO.
“One way I was thinking about kicking on this conversation is we will likely release this right after CoreWeave IPO.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
08 / prediction
I think literally the, like the information just published a, like, this is something that they're worried about, which is when operator or whoever accesses your website on behalf of you, how does it indicate that it's not you, but it's, it's an agent of you.
“I think literally the, like the information just published a, like, this is something that they're worried about, which is when operator or whoever accesses your website on behalf of you, how does it indicate that it's not you, but it's, it's an agent of you.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
09 / prediction
But like the real features come when you actually turn on the AI stuff. And so the reason I got snipped, because I got fed up with Overcast not implementing any AI features at all.
“But like the real features come when you actually turn on the AI stuff. And so the reason I got snipped, because I got fed up with Overcast not implementing any AI features at all.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
10 / prediction
Yeah, it's a it's really, I think, a really nice to have. But all I'll say is that my friend Corey Quinn says that anything that can be used as a database will be used as a database.
“Yeah, it's a it's really, I think, a really nice to have. But all I'll say is that my friend Corey Quinn says that anything that can be used as a database will be used as a database.”
- Speaker
- Shawn Wang
- Episode
- ⚡️The new OpenAI Agents Platform
- Publisher
- Latent Space
11 / prediction
There's always the question of the, are you a point solution or are you the sort of all in one? And I think the point solutions tend to win quickly, but then the only ones have a very tight cohesive experience.
“There's always the question of the, are you a point solution or are you the sort of all in one? And I think the point solutions tend to win quickly, but then the only ones have a very tight cohesive experience.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
12 / prediction
So likewise at Meta, likewise at OpenAI, likewise at the other labs as well. So like the GPU ultra rich are going to keep doing that because I think partially it's an article of faith now that you just need it.
“So likewise at Meta, likewise at OpenAI, likewise at the other labs as well. So like the GPU ultra rich are going to keep doing that because I think partially it's an article of faith now that you just need it.”
- Speaker
- Shawn Wang
- Episode
- Latent.Space 2024 Year in Review
- Publisher
- Latent Space
13 / prediction
Because vision models tend to just consume the whole image, if you are able to sort of focus on images based on the query, I think that, like, can get you a lot of extra performance.
“Because vision models tend to just consume the whole image, if you are able to sort of focus on images based on the query, I think that, like, can get you a lot of extra performance.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
14 / prediction
I noticed that, you know, I think the promise of general purpose agents has kind of died.
“I noticed that, you know, I think the promise of general purpose agents has kind of died.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
15 / prediction
I think in theory, we should be able to like run tests because you can run the full backend.
“I think in theory, we should be able to like run tests because you can run the full backend.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
16 / prediction
You get short-term gains by having specialists, domain specialists, and then someone just needs to train like a 10x bigger model on 10x more inference, 10x more data, 10x more model perhaps, whatever the current scaling law is. And then it supersedes all the individual models because of some generalized intelligence slash world knowledge.
“You get short-term gains by having specialists, domain specialists, and then someone just needs to train like a 10x bigger model on 10x more inference, 10x more data, 10x more model perhaps, whatever the current scaling law is. And then it supersedes all the individual models because of some generalized intelligence slash world knowledge.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
17 / prediction
I think you're helping. Like, you're paving the road to AGI.
“I think you're helping. Like, you're paving the road to AGI.”
- Speaker
- Shawn Wang
- Episode
- Agents @ Work: Lindy.ai
- Publisher
- Latent Space
18 / prediction
I mean, I'm aware of them, but I think I'm excited to see how all distillation works. That's something that we've been doing like, I don't know, I've been like doing it between our models for a while And I've seen really good results like I've done back in a day like from GPT 4 to GPT 3.
“I mean, I'm aware of them, but I think I'm excited to see how all distillation works. That's something that we've been doing like, I don't know, I've been like doing it between our models for a while And I've seen really good results like I've done back in a day like from GPT 4 to GPT 3.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
19 / prediction
I think that's the main learning I have from Devin. They cracked that. Actually, there was no foundational planning breakthrough.
“I think that's the main learning I have from Devin. They cracked that. Actually, there was no foundational planning breakthrough.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
20 / prediction
I actually always wanted to take like a selfie and go like, you know, POV, you're about to revolutionize the world of agents because we have two of the most awesome hiring agents in the house.
“I actually always wanted to take like a selfie and go like, you know, POV, you're about to revolutionize the world of agents because we have two of the most awesome hiring agents in the house.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
21 / prediction
So when you, when you quantize things, obviously you're going to lose precision because you just have less bits to store information in.
“So when you, when you quantize things, obviously you're going to lose precision because you just have less bits to store information in.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
22 / prediction
I think that translation between natural language, English versus code, and back and forth, I think is actually a really ripe source of synthetic data.
“I think that translation between natural language, English versus code, and back and forth, I think is actually a really ripe source of synthetic data.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
23 / prediction
It's weird because like, I guess with segment anything too, it's like 4D because you solve time, you know, you started with 3D and now you're solving the 4D.
“It's weird because like, I guess with segment anything too, it's like 4D because you solve time, you know, you started with 3D and now you're solving the 4D.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
24 / prediction
They will be building on architectures like Mobile LM and Small LM, which basically innovate in terms of shared weights and shared matrices for small models so that you just optimize the amount of file size and memory that you take up. And I think just general trend on device models, the only way that intelligence too cheap to meter happens is everything happens on device.
“They will be building on architectures like Mobile LM and Small LM, which basically innovate in terms of shared weights and shared matrices for small models so that you just optimize the amount of file size and memory that you take up. And I think just general trend on device models, the only way that intelligence too cheap to meter happens is everything happens on device.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
25 / prediction
To me, you know, I'm not exactly sure what you guys did, but like, I feel like when people say synthetic data, there needs to be different categories of synthetic data now, because I think there's so many different usage of this thing.
“To me, you know, I'm not exactly sure what you guys did, but like, I feel like when people say synthetic data, there needs to be different categories of synthetic data now, because I think there's so many different usage of this thing.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
26 / prediction
You even shared your job description, your reading list, and your interview loop. So, , if anyone's looking to hire AI engineers, I expect this to be the definitive piece and definitive podcast covering it.
“You even shared your job description, your reading list, and your interview loop. So, , if anyone's looking to hire AI engineers, I expect this to be the definitive piece and definitive podcast covering it.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
27 / prediction
You're very much known for sort of cognitive architectures, and I think, like, a lot of the AI research has been focused on simulating the mind, or simulating consciousness, maybe.
“You're very much known for sort of cognitive architectures, and I think, like, a lot of the AI research has been focused on simulating the mind, or simulating consciousness, maybe.”
- Speaker
- Shawn Wang
- Publisher
- Latent Space
28 / prediction
Now you just match the other two guys. And so that puts An insane amount of pressure on what gpt5 is going to be because it's just going to have like the only option it has now because all the other models are multimodal all the other models are long context all the other models have perfect recall gpt5 has to match everything and do more to to not be a flop
“Now you just match the other two guys. And so that puts An insane amount of pressure on what gpt5 is going to be because it's just going to have like the only option it has now because all the other models are multimodal all the other models are long context all the other models have perfect recall gpt5 has to match everything and do more to to not be a flop”
- Speaker
- Shawn Wang
- Publisher
- Latent Space