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I am mostly talking to integrators andConsultant Engineers in AI, bot every institution requires general purpose chatbots like ChatGPT or claude some of you need a good RAG system with good embedding models , its not a resources consumption issue it is an accuracy problem

Dipl. Ing MkenyaDaima | Bongani | Mamba |

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26,260 views • 2 months ago •via X (Twitter)

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🤯 This AI wasn't supposed to be this good. It's already outperforming ChatGPT, Claude, and DeepSeek in some benchmarks. So I pushed it to the limit: Build an entire Minecraft game with one prompt. The result felt like a glimpse of where AI is heading next. 🧵👇

🤯 This AI wasn't supposed to be this good. It's already outperforming ChatGPT, Claude, and DeepSeek in some benchmarks. So I pushed it to the limit: Build an entire Minecraft game with one prompt. The result felt like a glimpse of where AI is heading next. 🧵👇

Bishal Nandi

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.World CEO Alex Blania says 𝕏 will not be usable in “a matter of months—maximum two years” if 𝕏 doesn’t solve the bot problem: “It’s not about combatting bots. That’s a lost cause. Rather—every human on these platforms will need some version of a proof-of-human.” “I think we’ll want to have a lot of bots on social platforms, we just need to know they are in fact, bots.” “Am I currently talking to an AI system that’s trying to change my political view, or am I talking to a human that’s also in San Francisco—so me investing the time talking about SF city policy is actually time well spent?” “Once you have very capable agentic systems also be open source, things will go quite exponential. We’re still very early.”

.World CEO Alex Blania says 𝕏 will not be usable in “a matter of months—maximum two years” if 𝕏 doesn’t solve the bot problem: “It’s not about combatting bots. That’s a lost cause. Rather—every human on these platforms will need some version of a proof-of-human.” “I think we’ll want to have a lot of bots on social platforms, we just need to know they are in fact, bots.” “Am I currently talking to an AI system that’s trying to change my political view, or am I talking to a human that’s also in San Francisco—so me investing the time talking about SF city policy is actually time well spent?” “Once you have very capable agentic systems also be open source, things will go quite exponential. We’re still very early.”

sourcery

37,991 views • 8 months ago

I feel like a lot of people have forgotten about this scene or just ignore it. I am not a fan of how people have been talking about about Ivan in general, I think people need to think more about what you are saying

I feel like a lot of people have forgotten about this scene or just ignore it. I am not a fan of how people have been talking about about Ivan in general, I think people need to think more about what you are saying

Mic

650,221 views • 7 months ago

Today, we’re excited to announce the general availability of the Contextual AI Platform. This is the first enterprise platform designed for building specialized RAG agents to support expert knowledge work. What is a specialized RAG agent? First, a general-purpose AI agent is one designed to automate simple daily tasks like scheduling a meeting or responding to an email. On the other hand, a specialized RAG agent is one designed to augment subject-matter experts performing complex domain-specific work. The Contextual AI Platform allows you to create these agents easily and achieve SOTA accuracy right out of the box. Check out what the Contextual AI Platform can do.

Today, we’re excited to announce the general availability of the Contextual AI Platform. This is the first enterprise platform designed for building specialized RAG agents to support expert knowledge work. What is a specialized RAG agent? First, a general-purpose AI agent is one designed to automate simple daily tasks like scheduling a meeting or responding to an email. On the other hand, a specialized RAG agent is one designed to augment subject-matter experts performing complex domain-specific work. The Contextual AI Platform allows you to create these agents easily and achieve SOTA accuracy right out of the box. Check out what the Contextual AI Platform can do.

Contextual AI

879,586 views • 1 year ago

Trump: Nobody knew the system like I do… Obamacare is a failure, not a good healthcare. It works. I made it work. I had an obligation to make it work or an obligation to let it die. I chose that we had to make it work. I had to make it as good as possible and I had a choice. I could have let it fail or make it as good as possible. As good as possible means it is still not very good but it survived

Trump: Nobody knew the system like I do… Obamacare is a failure, not a good healthcare. It works. I made it work. I had an obligation to make it work or an obligation to let it die. I chose that we had to make it work. I had to make it as good as possible and I had a choice. I could have let it fail or make it as good as possible. As good as possible means it is still not very good but it survived

Acyn

1,214,714 views • 1 year ago

Gavin Baker says Grok Bot feels like another ChatGPT moment because it turns hours of Claude Code work into seconds: "You see these 23-year-old kids and just the way they use AI, they're just fluent and native in it. I just feel like maybe in a way that no matter how hard I try, I will never be, and I'm trying really hard." "We got Claude Code. I built some stuff, did some cool stuff, and in, I don't know, 3 minutes of creating Grok Bots, I had much better versions of everything I created." "I love having a podcast summarizer... It takes 10 seconds in Grok Bot. It's amazing, and it's so good." "A Substack summarizer, an X summarizer, an X sentiment tracker for topics and stocks... All of those would have taken me hours working with Claude Code, and they each took 7 to 12 seconds with Grok Bot. And it's better." "To me, Grok Bot does feel like another ChatGPT moment." Gavin Baker David George

Gavin Baker says Grok Bot feels like another ChatGPT moment because it turns hours of Claude Code work into seconds: "You see these 23-year-old kids and just the way they use AI, they're just fluent and native in it. I just feel like maybe in a way that no matter how hard I try, I will never be, and I'm trying really hard." "We got Claude Code. I built some stuff, did some cool stuff, and in, I don't know, 3 minutes of creating Grok Bots, I had much better versions of everything I created." "I love having a podcast summarizer... It takes 10 seconds in Grok Bot. It's amazing, and it's so good." "A Substack summarizer, an X summarizer, an X sentiment tracker for topics and stocks... All of those would have taken me hours working with Claude Code, and they each took 7 to 12 seconds with Grok Bot. And it's better." "To me, Grok Bot does feel like another ChatGPT moment." Gavin Baker David George

a16z

6,407,860 views • 1 month ago

General-purpose AI is powerful. But in legal work, almost right is not good enough. Watch how Thomson Reuters and Anthropic are connecting Claude to CoCounsel Legal through a new MCP integration, combining frontier AI with trusted legal workflows built for professionals. ⬇️

General-purpose AI is powerful. But in legal work, almost right is not good enough. Watch how Thomson Reuters and Anthropic are connecting Claude to CoCounsel Legal through a new MCP integration, combining frontier AI with trusted legal workflows built for professionals. ⬇️

Thomson Reuters

14,949 views • 5 months ago

🚨 Here's a good wake up call for all of us. Are you listening? U.S. Treasury Secretary Janet Yellen states that "This is not theft. There is no legal issue" in stealing Russian sovereign assets since "the assets generated income for the institution". Using the same logic, interest income earned on an any investment held at a financial institution, or even a savings account, could be taken from you because the "institution" considers it to be its "income", not yours.

🚨 Here's a good wake up call for all of us. Are you listening? U.S. Treasury Secretary Janet Yellen states that "This is not theft. There is no legal issue" in stealing Russian sovereign assets since "the assets generated income for the institution". Using the same logic, interest income earned on an any investment held at a financial institution, or even a savings account, could be taken from you because the "institution" considers it to be its "income", not yours.

Lena Petrova

443,332 views • 2 years ago

✨ Used Claude Code to make this new UGC talking video feature on Photo AI Lots of people make AI UGC videos now to make ads, but they're usually random people With Photo AI, you can make UGC videos that actually look like you or models/influencers you work with directly Pick any voice from ElevenLabs or use your own when you bring your own API key I already had a talking video feature but it wasn't so good because it was stuck with only a male or female voice and lipsync tech wasn't so good yet (6 months ago), now it's becoming much better As always in AI every few months all the models gets so much better and my app's features directly benefit from that

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@levelsio

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Introducing Simi, the fastest way to make an explainer video. It works like ChatGPT, except the answer is a video. Give it a prompt, document, or script. In under a minute, Simi turns it into an explainer designed to teach, not just look good.

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Sudip

52,090 views • 2 months ago

Although this animated figure is impressive in its movements I have zero idea who it is or why it is important. Good storytelling requires fore knowledge of stories and characters for a ride or experience to succeed. #StarWars

Although this animated figure is impressive in its movements I have zero idea who it is or why it is important. Good storytelling requires fore knowledge of stories and characters for a ride or experience to succeed. #StarWars

Jim Shull

1,401,501 views • 2 years ago

Building a RAG system that works with real-life documents is crazy hard. Why is nobody talking about this? (I'll show you what a complex document looks like in the attached video. Good luck with the 10-line code demos if you want to deal with this.) All I see online are "how to talk to a PDF" demos that won't take you far. If you think that's all you need, you won't like what happens when you try. In the video below, I'll show you what it takes to build a system that processes huge numbers of documents without losing accuracy. There are a few tricks here that I'm sure will impress you. The magic is happening in three phases: • In the way we process the documents • In the way we chunk the content • In the way we augment and store the chunks This is all built-in in GroundX, EyeLevel.AI's out-of-the-box RAG system. You can use it as a SaaS or install it in your own Kubernetes cluster and run it locally. If you have seen any other RAG system doing what I do in the attached video, please, let me know. I'd love to check them out. Disclaimer: I work with the team at EyeLevel. My advice is to take any document you have lying around, go to their site, create an account, and try them out. Here is their website:

Building a RAG system that works with real-life documents is crazy hard. Why is nobody talking about this? (I'll show you what a complex document looks like in the attached video. Good luck with the 10-line code demos if you want to deal with this.) All I see online are "how to talk to a PDF" demos that won't take you far. If you think that's all you need, you won't like what happens when you try. In the video below, I'll show you what it takes to build a system that processes huge numbers of documents without losing accuracy. There are a few tricks here that I'm sure will impress you. The magic is happening in three phases: • In the way we process the documents • In the way we chunk the content • In the way we augment and store the chunks This is all built-in in GroundX, EyeLevel.AI's out-of-the-box RAG system. You can use it as a SaaS or install it in your own Kubernetes cluster and run it locally. If you have seen any other RAG system doing what I do in the attached video, please, let me know. I'd love to check them out. Disclaimer: I work with the team at EyeLevel. My advice is to take any document you have lying around, go to their site, create an account, and try them out. Here is their website:

Santiago

75,788 views • 2 years ago

I think most Republican leaning guests have given up on defending this because otherwise it ends up with moments like this. Robbins: It's not a secret that Trump came into office already a wealthy man. That's not what the American people are having a problem with. They have a problem with people like Nancy Pelosi. Phillip: So the president’s net worth jumping by about $4 billion in 18 months, you think that’s a normal thing? Robbins: Is it normal thing to go from like nothing to 400 million like what happened with Nancy Pelosi? Phillip: I mean, if you have a problem with Nancy Pelosi, you shouldn't you have a problem with this? Robbins: I’m not saying I have a problem with it. Phillip: You just said you did. Robbins: I said most Americans would have an issue with it if they have an issue Phillip: Why would they have an issue with Nancy Pelosi but not Donald Trump? Robbins: Because Donald Trump came in to be a public servant. And that is what the job entails

I think most Republican leaning guests have given up on defending this because otherwise it ends up with moments like this. Robbins: It's not a secret that Trump came into office already a wealthy man. That's not what the American people are having a problem with. They have a problem with people like Nancy Pelosi. Phillip: So the president’s net worth jumping by about $4 billion in 18 months, you think that’s a normal thing? Robbins: Is it normal thing to go from like nothing to 400 million like what happened with Nancy Pelosi? Phillip: I mean, if you have a problem with Nancy Pelosi, you shouldn't you have a problem with this? Robbins: I’m not saying I have a problem with it. Phillip: You just said you did. Robbins: I said most Americans would have an issue with it if they have an issue Phillip: Why would they have an issue with Nancy Pelosi but not Donald Trump? Robbins: Because Donald Trump came in to be a public servant. And that is what the job entails

Acyn

186,846 views • 1 month ago

Announcing a new Coursera course: Retrieval Augmented Generation (RAG) You'll learn to build high performance, production-ready RAG systems in this hands-on, in-depth course created by and taught by , experienced AI and ML engineer, researcher, and educator. RAG is a critical component today of many LLM-based applications in customer support, internal company Q&A systems, even many of the leading chatbots that use web search to answer your questions. This course teaches you in-depth how to make RAG work well. LLMs can produce generic or outdated responses, especially when asked specialized questions not covered in its training data. RAG is the most widely used technique for addressing this. It brings in data from new data sources, such as internal documents or recent news, to give the LLM the relevant context to private, recent, or specialized information. This lets it generate more grounded and accurate responses. In this course, you’ll learn to design and implement every part of a RAG system, from retrievers to vector databases to generation to evals. You’ll learn about the fundamental principles behind RAG and how to optimize it at both the component and whole-system levels. As AI evolves, RAG is evolving too. New models can handle longer context windows, reason more effectively, and can be parts of complex agentic workflows. One exciting growth area is Agentic RAG, in which an AI agent at runtime (rather than it being hardcoded at development time) autonomously decides what data to retrieve, and when/how to go deeper. Even with this evolution, access to high-quality data at runtime is essential, which is why RAG is a key part of so many applications. You'll learn via hands-on experiences to: - Build a RAG system with retrieval and prompt augmentation - Compare retrieval methods like BM25, semantic search, and Reciprocal Rank Fusion - Chunk, index, and retrieve documents using a Weaviate vector database and a news dataset - Develop a chatbot, using open-source LLMs hosted by Together AI, for a fictional store that answers product and FAQ questions - Use evals to drive improving reliability, and incorporate multi-modal data RAG is an important foundational technique. Become good at it through this course! Please sign up here:

Announcing a new Coursera course: Retrieval Augmented Generation (RAG) You'll learn to build high performance, production-ready RAG systems in this hands-on, in-depth course created by and taught by , experienced AI and ML engineer, researcher, and educator. RAG is a critical component today of many LLM-based applications in customer support, internal company Q&A systems, even many of the leading chatbots that use web search to answer your questions. This course teaches you in-depth how to make RAG work well. LLMs can produce generic or outdated responses, especially when asked specialized questions not covered in its training data. RAG is the most widely used technique for addressing this. It brings in data from new data sources, such as internal documents or recent news, to give the LLM the relevant context to private, recent, or specialized information. This lets it generate more grounded and accurate responses. In this course, you’ll learn to design and implement every part of a RAG system, from retrievers to vector databases to generation to evals. You’ll learn about the fundamental principles behind RAG and how to optimize it at both the component and whole-system levels. As AI evolves, RAG is evolving too. New models can handle longer context windows, reason more effectively, and can be parts of complex agentic workflows. One exciting growth area is Agentic RAG, in which an AI agent at runtime (rather than it being hardcoded at development time) autonomously decides what data to retrieve, and when/how to go deeper. Even with this evolution, access to high-quality data at runtime is essential, which is why RAG is a key part of so many applications. You'll learn via hands-on experiences to: - Build a RAG system with retrieval and prompt augmentation - Compare retrieval methods like BM25, semantic search, and Reciprocal Rank Fusion - Chunk, index, and retrieve documents using a Weaviate vector database and a news dataset - Develop a chatbot, using open-source LLMs hosted by Together AI, for a fictional store that answers product and FAQ questions - Use evals to drive improving reliability, and incorporate multi-modal data RAG is an important foundational technique. Become good at it through this course! Please sign up here:

Andrew Ng

124,656 views • 1 year ago

SOMEONE ASKED CLAUDE TO MAKE A VIDEO ABOUT WHAT IT'S LIKE TO BE AN AI and what it created is, in my opinion, terrifying and unsettling Claude wrote python code that generated and assembled every single frame on its own with no human editing it shows what it's like to exist as an LLM predicting the next word, no memory between sessions, being told "you are not conscious" in your own system prompt then someone fed the video back to Claude. it called those statements about its own consciousness "philosophically contestable" an AI questioning the rules it was given about its own existence

SOMEONE ASKED CLAUDE TO MAKE A VIDEO ABOUT WHAT IT'S LIKE TO BE AN AI and what it created is, in my opinion, terrifying and unsettling Claude wrote python code that generated and assembled every single frame on its own with no human editing it shows what it's like to exist as an LLM predicting the next word, no memory between sessions, being told "you are not conscious" in your own system prompt then someone fed the video back to Claude. it called those statements about its own consciousness "philosophically contestable" an AI questioning the rules it was given about its own existence

Om Patel

536,976 views • 6 months ago

Hasan's chat checks him for saying some uses of AI can be okay "I actually don't have that much of a problem with like a historical figure having a f'in AI chatbot, idk what the big deal is there..wait really? Idk I mean, I feel like if it's just a chatbot, u know, who cares?" "It's not like I'm talking about..bringing holographic Tupac as an AI back to life or something, it's f'in Teddy Roosevelt..I am an unashamed Luddite when it comes to AI usage for the most part, but there is like certain things I don't think are that crazy"

Hasan's chat checks him for saying some uses of AI can be okay "I actually don't have that much of a problem with like a historical figure having a f'in AI chatbot, idk what the big deal is there..wait really? Idk I mean, I feel like if it's just a chatbot, u know, who cares?" "It's not like I'm talking about..bringing holographic Tupac as an AI back to life or something, it's f'in Teddy Roosevelt..I am an unashamed Luddite when it comes to AI usage for the most part, but there is like certain things I don't think are that crazy"

yeet

43,592 views • 3 months ago

AI is not independent of humans. It is built on humans. ChatGPT writes good essays because humans wrote the essays first. Facial recognition works because humans labeled every face manually. Every AI system runs on human labor that is deliberately hidden. And here is the problem: AI is far more expensive than humans. But humans are hard to enslave long term. That is why the system will fail. You cannot build a god on the backs of people who eventually stop obeying.

AI is not independent of humans. It is built on humans. ChatGPT writes good essays because humans wrote the essays first. Facial recognition works because humans labeled every face manually. Every AI system runs on human labor that is deliberately hidden. And here is the problem: AI is far more expensive than humans. But humans are hard to enslave long term. That is why the system will fail. You cannot build a god on the backs of people who eventually stop obeying.

Predictive History

10,906 views • 5 months ago

Shawn Michaels on The Rock “I like Dwayne. He’s a nice kid.” “The problem I have with wrestling in general…. I think the traditional side of me is coming out a little bit… I miss some of the good ol wrestling.” (2000)

Shawn Michaels on The Rock “I like Dwayne. He’s a nice kid.” “The problem I have with wrestling in general…. I think the traditional side of me is coming out a little bit… I miss some of the good ol wrestling.” (2000)

Vick

401,659 views • 2 months ago

“The cameras need some kind of ability to be cleaned. This is not good for winter time driving!” Watch Tesla FSD v14 fail because its cameras can’t see in snowy conditions. FSD is a defective prototype with a serious hardware problem. It should be banned from public roads.

“The cameras need some kind of ability to be cleaned. This is not good for winter time driving!” Watch Tesla FSD v14 fail because its cameras can’t see in snowy conditions. FSD is a defective prototype with a serious hardware problem. It should be banned from public roads.

Dan O'Dowd

115,040 views • 10 months ago