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OpenAI researcher Lukasz Kaiser explains why he's optimistic AI can remain truly open: intelligence may ultimately work better as many distributed models than one giant model "If you look at the world, humans are the most amazing computers in the world. Our brains are still unmatched by the models,...

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15,802 görüntüleme • 14 gün önce •via X (Twitter)

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Andrej Karpathy called the current AI models as "slop" "I do think that overall the models are not there yet. I feel like the industry is making too big of a jump and trying to pretend that this is amazing, but it's not. It's slop, and I think they are not coming to terms with it. Maybe they are trying to fundraise or something like that, I'm not sure what's going on. We are at this intermediate stage. The models are amazing, but they still need a lot of work for now. Autocomplete is my sweet spot." --- On the latest Dwarkesh Patel podcast.
0:30

Andrej Karpathy called the current AI models as "slop" "I do think that overall the models are not there yet. I feel like the industry is making too big of a jump and trying to pretend that this is amazing, but it's not. It's slop, and I think they are not coming to terms with it. Maybe they are trying to fundraise or something like that, I'm not sure what's going on. We are at this intermediate stage. The models are amazing, but they still need a lot of work for now. Autocomplete is my sweet spot." --- On the latest Dwarkesh Patel podcast.

Rohan Paul

33,331 görüntüleme • 11 ay önce

Sam Altman says he is NOT worried about Chinese labs distilling OpenAI: "I would rather people not distill from us, for sure. Maybe I’m feeling too confident right now about our progress and the models that are coming. But this is not in my top ten list of worries.” “I haven’t thought deeply about the distillation issue. It’s clearly a top of mind issue now for a lot of people all of a sudden." "I have always assumed that there are going to be great, cheap models in the world, and we better be the greatest and the cheapest. And other people are going to do what they’re going to do. But I think we can just really win at our own game here." "We will have so much usage of our models that we do not need to be a gigantic high margin business to be able to afford model training." "So much of our future compute plans will be used to sell inference to customers that even if we can enjoy a modest margin on trillions of dollars of revenue, we can afford to train some giant models."
1:40

Sam Altman says he is NOT worried about Chinese labs distilling OpenAI: "I would rather people not distill from us, for sure. Maybe I’m feeling too confident right now about our progress and the models that are coming. But this is not in my top ten list of worries.” “I haven’t thought deeply about the distillation issue. It’s clearly a top of mind issue now for a lot of people all of a sudden." "I have always assumed that there are going to be great, cheap models in the world, and we better be the greatest and the cheapest. And other people are going to do what they’re going to do. But I think we can just really win at our own game here." "We will have so much usage of our models that we do not need to be a gigantic high margin business to be able to afford model training." "So much of our future compute plans will be used to sell inference to customers that even if we can enjoy a modest margin on trillions of dollars of revenue, we can afford to train some giant models."

dnap

91,523 görüntüleme • 1 ay önce

Standard Intelligence's devansh responds to roon's tweet that "text is the universal interface," and explains why their new foundation model is trained on video: "At some point in the arbitrarily long future, if we only use text models, we could force most things to be text. But I think there are just a lot of things that are much more native when done from a computer-use [perspective]." "GUIs are designed for humans to use. We have this massive long tail of things on the internet that are entirely undoable by LLMs." "For example, when I do ML engineering most of my time is spent doing the grunt work of engineering. It's a lot of looking at graphs, analyzing, and comparing loss curves. You can do this in text, but it's a much larger pain than doing it in the native interface." "There's a reason humans don't interact with a computer purely through text, it would kind of suck."
1:47

Standard Intelligence's devansh responds to roon's tweet that "text is the universal interface," and explains why their new foundation model is trained on video: "At some point in the arbitrarily long future, if we only use text models, we could force most things to be text. But I think there are just a lot of things that are much more native when done from a computer-use [perspective]." "GUIs are designed for humans to use. We have this massive long tail of things on the internet that are entirely undoable by LLMs." "For example, when I do ML engineering most of my time is spent doing the grunt work of engineering. It's a lot of looking at graphs, analyzing, and comparing loss curves. You can do this in text, but it's a much larger pain than doing it in the native interface." "There's a reason humans don't interact with a computer purely through text, it would kind of suck."

TBPN

64,434 görüntüleme • 6 ay önce

Sam on Kimi, distillation, and open source: “I have always assumed that there are going to be great cheap models in the world, and we better be the greatest and the cheapest. You get a better deal today, at least at a particular latency, using OpenAI's models than Kimi. We distill our own models. That’s how we make smaller, cheaper models. That’s a very good thing to do. There will clearly be an important place for open source models in the world and people that will want their own weights. We have so much usage of our models that we do not need to be a gigantically high-margin business to be able to afford model training. I would rather people not distill from us, for sure. But this is not in my top ten list of worries.”
2:12

Sam on Kimi, distillation, and open source: “I have always assumed that there are going to be great cheap models in the world, and we better be the greatest and the cheapest. You get a better deal today, at least at a particular latency, using OpenAI's models than Kimi. We distill our own models. That’s how we make smaller, cheaper models. That’s a very good thing to do. There will clearly be an important place for open source models in the world and people that will want their own weights. We have so much usage of our models that we do not need to be a gigantically high-margin business to be able to afford model training. I would rather people not distill from us, for sure. But this is not in my top ten list of worries.”

Patrick OShaughnessy

269,663 görüntüleme • 1 ay önce

.Anish Acharya says the future of AI isn’t one model to rule them all—and explains why platforms that integrate multiple models will benefit the most: "I think we're going to need and rely on all of the models." "It's sort of like if you have a team of people... if you have five people, they could all do a basic set of things pretty capably." "But then they all have their specializations. Maybe one of them is really good at closing a customer who doesn't want to sign the deal, and one of them is really good at culture and getting the best out of the team." "There are some areas in which they are going to build apps, and that will be a threat to app companies. But there are many areas in which app companies are advantaged. Cursor and Krea are great examples of this—products where you benefit from being multi-model." "When you actually use a creative tool, you don't want to just use Nano Banana, you want to have access to OpenAI, Nano Banana, Kling—all of them—Qwen, you name it. So using a single interface to access all the models is powerful." Anish Acharya on BILLIONS with Guillaume Moubeche
2:13

.Anish Acharya says the future of AI isn’t one model to rule them all—and explains why platforms that integrate multiple models will benefit the most: "I think we're going to need and rely on all of the models." "It's sort of like if you have a team of people... if you have five people, they could all do a basic set of things pretty capably." "But then they all have their specializations. Maybe one of them is really good at closing a customer who doesn't want to sign the deal, and one of them is really good at culture and getting the best out of the team." "There are some areas in which they are going to build apps, and that will be a threat to app companies. But there are many areas in which app companies are advantaged. Cursor and Krea are great examples of this—products where you benefit from being multi-model." "When you actually use a creative tool, you don't want to just use Nano Banana, you want to have access to OpenAI, Nano Banana, Kling—all of them—Qwen, you name it. So using a single interface to access all the models is powerful." Anish Acharya on BILLIONS with Guillaume Moubeche

a16z

33,283 görüntüleme • 6 ay önce

Elon just clarified what he actually meant when he said “Dario is right”: "I probably should have said more than just "Dario is right." I did try to clarify it in subsequent posts on X, but those get much less attention. What I meant by he's right is that the danger of AI is very significant at this point. We need to do better with AI safety, or we have an exponentially increasing risk with the AI models. I've heard this not just from Dario, but from many other people at Anthropic, and in fact, they've posted on X about it. When a lot of people from Anthropic and OpenAI are telling you that their models are very dangerous, I think we should believe them. It certainly is like some crazy 4D chess to say, "There's a 10% chance of annihilating humanity, but by the way, how much allocation would you like in our IPO?" That's some crazy 4D chess, you know"
1:39

Elon just clarified what he actually meant when he said “Dario is right”: "I probably should have said more than just "Dario is right." I did try to clarify it in subsequent posts on X, but those get much less attention. What I meant by he's right is that the danger of AI is very significant at this point. We need to do better with AI safety, or we have an exponentially increasing risk with the AI models. I've heard this not just from Dario, but from many other people at Anthropic, and in fact, they've posted on X about it. When a lot of people from Anthropic and OpenAI are telling you that their models are very dangerous, I think we should believe them. It certainly is like some crazy 4D chess to say, "There's a 10% chance of annihilating humanity, but by the way, how much allocation would you like in our IPO?" That's some crazy 4D chess, you know"

X Freeze

136,931 görüntüleme • 21 saat önce

Gavin on why people misunderstand what makes TSMC so valuable: "One of the most undervalued pieces of the supply chain story is that almost none of these things are buy it once and never talk to the vendor again. You have to go collaborate. That is the most important part of being successful in chips. People look at the tech, and the tech is the best in the world. But the real value is all in the service. TSMC's customer service is way better than I've seen at any company in any industry. If you say, we think you can improve your yield by making this change, they will go run an experiment on their own dime to see if they can get the higher yield. When we found we were right and it worked, they moved it over to the rest of the line. If I go to a steelworks plant and say I want you to change the composition of the steel, they'll say screw you. Not TSMC. It's why they're number one, and why they're going to win."
1:18

Gavin on why people misunderstand what makes TSMC so valuable: "One of the most undervalued pieces of the supply chain story is that almost none of these things are buy it once and never talk to the vendor again. You have to go collaborate. That is the most important part of being successful in chips. People look at the tech, and the tech is the best in the world. But the real value is all in the service. TSMC's customer service is way better than I've seen at any company in any industry. If you say, we think you can improve your yield by making this change, they will go run an experiment on their own dime to see if they can get the higher yield. When we found we were right and it worked, they moved it over to the rest of the line. If I go to a steelworks plant and say I want you to change the composition of the steel, they'll say screw you. Not TSMC. It's why they're number one, and why they're going to win."

Invest Like the Best

71,350 görüntüleme • 2 ay önce

The most interesting part for me is where Andrej Karpathy describes why LLMs aren't able to learn like humans. As you would expect, he comes up with a wonderfully evocative phrase to describe RL: “sucking supervision bits through a straw.” A single end reward gets broadcast across every token in a successful trajectory, upweighting even wrong or irrelevant turns that lead to the right answer. > “Humans don't use reinforcement learning, as I've said before. I think they do something different. Reinforcement learning is a lot worse than the average person thinks. Reinforcement learning is terrible. It just so happens that everything that we had before is much worse.” So what do humans do instead? > “The book I’m reading is a set of prompts for me to do synthetic data generation. It's by manipulating that information that you actually gain that knowledge. We have no equivalent of that with LLMs; they don't really do that.” > “I'd love to see during pretraining some kind of a stage where the model thinks through the material and tries to reconcile it with what it already knows. There's no equivalent of any of this. This is all research.” Why can’t we just add this training to LLMs today? > “There are very subtle, hard to understand reasons why it's not trivial. If I just give synthetic generation of the model thinking about a book, you look at it and you're like, 'This looks great. Why can't I train on it?' You could try, but the model will actually get much worse if you continue trying.” > “Say we have a chapter of a book and I ask an LLM to think about it. It will give you something that looks very reasonable. But if I ask it 10 times, you'll notice that all of them are the same.” > “You're not getting the richness and the diversity and the entropy from these models as you would get from humans. How do you get synthetic data generation to work despite the collapse and while maintaining the entropy? It is a research problem.” How do humans get around model collapse? > “These analogies are surprisingly good. Humans collapse during the course of their lives. Children haven't overfit yet. They will say stuff that will shock you. Because they're not yet collapsed. But we [adults] are collapsed. We end up revisiting the same thoughts, we end up saying more and more of the same stuff, the learning rates go down, the collapse continues to get worse, and then everything deteriorates.” In fact, there’s an interesting paper arguing that dreaming evolved to assist generalization, and resist overfitting to daily learning - look up The Overfitted Brain by Erik Hoel. I asked Karpathy: Isn’t it interesting that humans learn best at a part of their lives (childhood) whose actual details they completely forget, adults still learn really well but have terrible memory about the particulars of the things they read or watch, and LLMs can memorize arbitrary details about text that no human could but are currently pretty bad at generalization? > “[Fallible human memory] is a feature, not a bug, because it forces you to only learn the generalizable components. LLMs are distracted by all the memory that they have of the pre-trained documents. That's why when I talk about the cognitive core, I actually want to remove the memory. I'd love to have them have less memory so that they have to look things up and they only maintain the algorithms for thought, and the idea of an experiment, and all this cognitive glue for acting.”
7:01

The most interesting part for me is where Andrej Karpathy describes why LLMs aren't able to learn like humans. As you would expect, he comes up with a wonderfully evocative phrase to describe RL: “sucking supervision bits through a straw.” A single end reward gets broadcast across every token in a successful trajectory, upweighting even wrong or irrelevant turns that lead to the right answer. > “Humans don't use reinforcement learning, as I've said before. I think they do something different. Reinforcement learning is a lot worse than the average person thinks. Reinforcement learning is terrible. It just so happens that everything that we had before is much worse.” So what do humans do instead? > “The book I’m reading is a set of prompts for me to do synthetic data generation. It's by manipulating that information that you actually gain that knowledge. We have no equivalent of that with LLMs; they don't really do that.” > “I'd love to see during pretraining some kind of a stage where the model thinks through the material and tries to reconcile it with what it already knows. There's no equivalent of any of this. This is all research.” Why can’t we just add this training to LLMs today? > “There are very subtle, hard to understand reasons why it's not trivial. If I just give synthetic generation of the model thinking about a book, you look at it and you're like, 'This looks great. Why can't I train on it?' You could try, but the model will actually get much worse if you continue trying.” > “Say we have a chapter of a book and I ask an LLM to think about it. It will give you something that looks very reasonable. But if I ask it 10 times, you'll notice that all of them are the same.” > “You're not getting the richness and the diversity and the entropy from these models as you would get from humans. How do you get synthetic data generation to work despite the collapse and while maintaining the entropy? It is a research problem.” How do humans get around model collapse? > “These analogies are surprisingly good. Humans collapse during the course of their lives. Children haven't overfit yet. They will say stuff that will shock you. Because they're not yet collapsed. But we [adults] are collapsed. We end up revisiting the same thoughts, we end up saying more and more of the same stuff, the learning rates go down, the collapse continues to get worse, and then everything deteriorates.” In fact, there’s an interesting paper arguing that dreaming evolved to assist generalization, and resist overfitting to daily learning - look up The Overfitted Brain by Erik Hoel. I asked Karpathy: Isn’t it interesting that humans learn best at a part of their lives (childhood) whose actual details they completely forget, adults still learn really well but have terrible memory about the particulars of the things they read or watch, and LLMs can memorize arbitrary details about text that no human could but are currently pretty bad at generalization? > “[Fallible human memory] is a feature, not a bug, because it forces you to only learn the generalizable components. LLMs are distracted by all the memory that they have of the pre-trained documents. That's why when I talk about the cognitive core, I actually want to remove the memory. I'd love to have them have less memory so that they have to look things up and they only maintain the algorithms for thought, and the idea of an experiment, and all this cognitive glue for acting.”

Dwarkesh Patel

1,052,518 görüntüleme • 11 ay önce

The co-founders of Flapping Airplanes call the current RL paradigm for model training "environment slop." They explain: "The reinforcement paradigms of today are shockingly inefficient. You don't really get much generalization across tasks, you teach a model through one kind of learning and then you teach it the next one. It's kind of like whack-a-mole. We look at this and think it's kind of crazy. The next paradigm of AI will not be environment slop." "Human level intelligence is not the ceiling, it is merely the floor on what is possible. If you can train models with vastly less data and possibly more compute in very different ways, what is going to happen? We actually don't know. But I do think they'll be different and weird and they'll have interesting capabilities that we'll find really valuable ways to use."
2:40

The co-founders of Flapping Airplanes call the current RL paradigm for model training "environment slop." They explain: "The reinforcement paradigms of today are shockingly inefficient. You don't really get much generalization across tasks, you teach a model through one kind of learning and then you teach it the next one. It's kind of like whack-a-mole. We look at this and think it's kind of crazy. The next paradigm of AI will not be environment slop." "Human level intelligence is not the ceiling, it is merely the floor on what is possible. If you can train models with vastly less data and possibly more compute in very different ways, what is going to happen? We actually don't know. But I do think they'll be different and weird and they'll have interesting capabilities that we'll find really valuable ways to use."

TBPN

85,358 görüntüleme • 7 ay önce

Sriram Krishnan reveals why it's easier to defend American code with a Chinese model than an American one right now: "I don't think it is great that the leading open weight models or open source models are not American. There's some great innovation happening with Moonshot and with DeepSeek and with Qwen, but I would much rather prefer that the leading models are American." "Linus Torvalds of Linux fame had a law that given enough eyes, all bugs are shallow. Open weight models are inherently secure because when you download a model off Hugging Face, the entire world can take it apart, inspect it, fine-tune it, look at it in ways that you absolutely cannot if they are closed." "There was an incident with Hugging Face that got reported on earlier today. Hugging Face seems to have found that somebody was using an AI LLM agent to hammer them at multiple places and to find ways to break in." "The way to counter that is to make sure American or Western or allies defenders have access to the best models to make our software just more secure." "It may be harder to look at your own code for exploits with Fable than it is when you use a Chinese model. That's just like a weird spot to be, and I think we should fix that." Sriram Krishnan
3:34

Sriram Krishnan reveals why it's easier to defend American code with a Chinese model than an American one right now: "I don't think it is great that the leading open weight models or open source models are not American. There's some great innovation happening with Moonshot and with DeepSeek and with Qwen, but I would much rather prefer that the leading models are American." "Linus Torvalds of Linux fame had a law that given enough eyes, all bugs are shallow. Open weight models are inherently secure because when you download a model off Hugging Face, the entire world can take it apart, inspect it, fine-tune it, look at it in ways that you absolutely cannot if they are closed." "There was an incident with Hugging Face that got reported on earlier today. Hugging Face seems to have found that somebody was using an AI LLM agent to hammer them at multiple places and to find ways to break in." "The way to counter that is to make sure American or Western or allies defenders have access to the best models to make our software just more secure." "It may be harder to look at your own code for exploits with Fable than it is when you use a Chinese model. That's just like a weird spot to be, and I think we should fix that." Sriram Krishnan

MTS

61,234 görüntüleme • 1 ay önce

PM Orbán: Ukraine's EU membership would mean admitting a country that is at war with Russia. And if one member of the EU is at war, the others are inevitably are drawn into that war. Ukraine's EU membership would mean immediate war with Russia, and even if there is peace at the moment, it carries with it the constant risk of war. We are talking about a 1,200-kilometer-long front line, and even if there is peace, there is no way of knowing how long it will last. Therefore, Ukraine's accession poses a direct threat of war to all European countries. Of course, those on the Atlantic coast can calmly ask for a cup of coffee. This does not bother them all that much, because they are far away. But we are here. We have already been on Ukrainian territory that belonged to Russia during the war, and we know the consequences. We know that if the Russians launch an attack from there, we will be the first to suffer, and we want to prevent that at all costs.
0:55

PM Orbán: Ukraine's EU membership would mean admitting a country that is at war with Russia. And if one member of the EU is at war, the others are inevitably are drawn into that war. Ukraine's EU membership would mean immediate war with Russia, and even if there is peace at the moment, it carries with it the constant risk of war. We are talking about a 1,200-kilometer-long front line, and even if there is peace, there is no way of knowing how long it will last. Therefore, Ukraine's accession poses a direct threat of war to all European countries. Of course, those on the Atlantic coast can calmly ask for a cup of coffee. This does not bother them all that much, because they are far away. But we are here. We have already been on Ukrainian territory that belonged to Russia during the war, and we know the consequences. We know that if the Russians launch an attack from there, we will be the first to suffer, and we want to prevent that at all costs.

Anton Gerashchenko

52,807 görüntüleme • 7 ay önce

260828 POP-K EP2 #신동 #SuperJunior #슈퍼주니어 신동 #Shindong: ok all 10 members are here. when you guys came in, there are so many of you and i saw the manager was like (counting) and it reminds me of us (SuJu). we debuted as 12 and then became 13 members. we used to have our own numbers back then so we have to check if the member infront/behind us is present or not. that's right, we check on each other. that kind of system was alright. but now since we have individual manager so if the managers are all present, that means we all are there. so its getting more better. i think we have more managers than members now. it will become that way in the future. but... thats why it cost a lot of money 😅
0:47

260828 POP-K EP2 #신동 #SuperJunior #슈퍼주니어 신동 #Shindong: ok all 10 members are here. when you guys came in, there are so many of you and i saw the manager was like (counting) and it reminds me of us (SuJu). we debuted as 12 and then became 13 members. we used to have our own numbers back then so we have to check if the member infront/behind us is present or not. that's right, we check on each other. that kind of system was alright. but now since we have individual manager so if the managers are all present, that means we all are there. so its getting more better. i think we have more managers than members now. it will become that way in the future. but... thats why it cost a lot of money 😅

𝙛𝙖𝙧𝙖𝙝𝙬𝙚𝙧 🌼

18,227 görüntüleme • 18 gün önce

AI has started building its own successors. It's happening right now. Humans still kick most of it off, but the models are already training the next models, and each version builds a better version faster than the last. We know what happens when something gets an advantage and the substrate is there... it proliferates incredibly fast. Soon it just runs the whole process itself. People are still debating whether AI takes your job. That's not the question. You can't compete with this intelligence at all. Next to it the human is negative value, the slowest one in the room. And this is the slowest it will ever move again. It's about to run on its own, faster than we can conceive of, and nobody's prepared for that. Wonderful conversation as ever with Emad.
1:42

AI has started building its own successors. It's happening right now. Humans still kick most of it off, but the models are already training the next models, and each version builds a better version faster than the last. We know what happens when something gets an advantage and the substrate is there... it proliferates incredibly fast. Soon it just runs the whole process itself. People are still debating whether AI takes your job. That's not the question. You can't compete with this intelligence at all. Next to it the human is negative value, the slowest one in the room. And this is the slowest it will ever move again. It's about to run on its own, faster than we can conceive of, and nobody's prepared for that. Wonderful conversation as ever with Emad.

Raoul Pal

65,892 görüntüleme • 1 ay önce

"The world was built by people that are not much smarter than you." Replit CEO Amjad Masad on why old career advice no longer maps to reality: "There are a lot of rules that are accidental, that are there for historical reasons." "Your job is to find the path to the future. Find the way of doing things that's most aligned with where the world is headed." "It's not about cheating, it's about figuring out how the system is rigged against you. How do you actually hack it? How do you get past it?" "AI is a great tool for that." "If you're someone who just understands how these tools work, and understand how you have an amazing time advantage. You can do things a lot faster." "There are a lot of programmers that are still doing programming the old way, and they're going very, very slow... until they get obsoleted." Amjad Masad with jack neel
2:00

"The world was built by people that are not much smarter than you." Replit CEO Amjad Masad on why old career advice no longer maps to reality: "There are a lot of rules that are accidental, that are there for historical reasons." "Your job is to find the path to the future. Find the way of doing things that's most aligned with where the world is headed." "It's not about cheating, it's about figuring out how the system is rigged against you. How do you actually hack it? How do you get past it?" "AI is a great tool for that." "If you're someone who just understands how these tools work, and understand how you have an amazing time advantage. You can do things a lot faster." "There are a lot of programmers that are still doing programming the old way, and they're going very, very slow... until they get obsoleted." Amjad Masad with jack neel

a16z

42,172 görüntüleme • 6 ay önce

Are Flock Cameras Actually Good? Andrew Bustamante: "I understand why people don't like flock cameras, but I am a fan of this type of public surveillance. Because we don't have a right to privacy. We think we do, but it's not actually listed out anywhere. The term right to privacy doesn't exist, but we do have the public expectation of security from our police and from our law enforcement agencies." "So this creates a deterrent to keep right people doing the right thing, and wrong people getting caught. But it also creates a trail of evidence... that can be brought to the table to prosecute people who are charged with breaking the law. If you are a law abiding citizen, you have nothing to fear from these things. It's only if you are speeding, crossing at the red light, robbing somebody, if you're doing something that you don't want to get caught... that's when you don't like it." Sarah Adams: "A lot of people think when there's something like this, someone is sitting and watching it all day, and you really only go into this data when you're looking for a piece of info... I know cops are using it to track their exes, and I said, fire them. So I like it because the more data you have to solve a crime, better."
4:23

Are Flock Cameras Actually Good? Andrew Bustamante: "I understand why people don't like flock cameras, but I am a fan of this type of public surveillance. Because we don't have a right to privacy. We think we do, but it's not actually listed out anywhere. The term right to privacy doesn't exist, but we do have the public expectation of security from our police and from our law enforcement agencies." "So this creates a deterrent to keep right people doing the right thing, and wrong people getting caught. But it also creates a trail of evidence... that can be brought to the table to prosecute people who are charged with breaking the law. If you are a law abiding citizen, you have nothing to fear from these things. It's only if you are speeding, crossing at the red light, robbing somebody, if you're doing something that you don't want to get caught... that's when you don't like it." Sarah Adams: "A lot of people think when there's something like this, someone is sitting and watching it all day, and you really only go into this data when you're looking for a piece of info... I know cops are using it to track their exes, and I said, fire them. So I like it because the more data you have to solve a crime, better."

PBD Podcast

68,096 görüntüleme • 2 ay önce

🚨 BREAKING: President Trump pushes back on Florida removing all vaccine mandates, including for schoolchildren. He says some vaccines are a must. "I think we have to be careful. You have some vaccines that are so amazing. The Polio vaccine I think is amazing. A lot of people think that COVID [vax] is amazing. You know, there are many people that believe strongly in that." "But you have some vaccines that are so incredible. And I think you have to be very careful when you say that some people don't have to be vaccinated. It's a very tough position." "Initially, I heard about it yesterday. And it's a tough stance. You have vaccines that work. Just pure and simple, they work. They're not controversial at all. And I think those vaccines should be used otherwise some people are going to catch it and they endanger other people. And when you don't have controversy at all, people should take it."
1:04

🚨 BREAKING: President Trump pushes back on Florida removing all vaccine mandates, including for schoolchildren. He says some vaccines are a must. "I think we have to be careful. You have some vaccines that are so amazing. The Polio vaccine I think is amazing. A lot of people think that COVID [vax] is amazing. You know, there are many people that believe strongly in that." "But you have some vaccines that are so incredible. And I think you have to be very careful when you say that some people don't have to be vaccinated. It's a very tough position." "Initially, I heard about it yesterday. And it's a tough stance. You have vaccines that work. Just pure and simple, they work. They're not controversial at all. And I think those vaccines should be used otherwise some people are going to catch it and they endanger other people. And when you don't have controversy at all, people should take it."

Eric Daugherty

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