TheCUBE Pod analysts John Furrier and Dave Vellante discuss the Intel Foundry spinout, AI tsunami and Oracle-AWS cloud moves, plus more.

Intel Foundry spinout, AI tsunami and Oracle-AWS cloud moves - SiliconANGLE

metric has value 1 when Prometheus can reach the pod to collect/scrape the metrics. It might be useful to monitor pod's readiness(in some case) if the scraping is done through the k8s service. But it causes a false positive when Prometheus scrapes directly from the pod. up This is the request flow when the metric scraping is done via Kubernetes service. In here, the kubernetes service work as a load balancer to route the scraping request to pods. So each time, Prometheus can collect the metric from 1 pod. But this setup will not be able to tell how many pods are ready. That's when scraping directly from pod comes into the picture With this topology, prometheus can reach all the pods and the metric of each pod will have the value 1, even when the pods are not in the ready state or their readiness probes are failed. This does not happen with the scraping through Kubernetes service because Kubernetes service won't send the request to un-ready pods, it returns 503 instead. up To avoid this false positive, we need to introduce a custom gauge metric which will indicate the readiness of the pod. I choose the descriptive name for that. But how do we update the value of the metric? pod_readiness In the above picture, I use one servlet filter to catch the HTTP response from the actuator and set the pod_readiness metric's value accordingly. Once the metric is collected from pods, we can design some Prometheus queries to monitor the number of ready pods and fire the alert if necessary. Cheers

When You Can't Rely on the Prometheus Up Metric

Nik Storonsky, founder of Revolut, shared bold and controversial views in his recent podcast. He talked about hiring, work-life balance, and the challenges of scaling a global business. His words hit close to home for me as an entrepreneur, and I’d like to share my take on some of the points he raised. The "Self-Guided Missile" Philosophy Nik has a straightforward rule: hire "self-guided missiles." These are people who set their own goals, execute flawlessly, and deliver results without needing much guidance. If they don’t prove themselves in three months, they’re not the right fit. I fully agree with this. Finding such people is hard, but it’s possible. I’ve had the chance to work with individuals like this, and they are game-changers for any team. However, identifying them takes time and effort. Hiring isn’t just about interviews; it’s about spotting that rare mix of independence and drive. When you find them, they’re worth every moment spent searching. Work-Life Balance: Is It Overrated? Nik’s take on balance is simple: it’s not for everyone. He believes success comes from sacrifice and imbalance. To win in the "big sport" of business, you need to focus 100% on your goals, even if it means giving up other parts of life. I tend to agree with him. It’s not a lifestyle that suits everyone, but it’s the reality of competing at the highest level. Building something impactful requires this kind of focus. If you’re willing to embrace it, the rewards can be extraordinary. Global Ambition: A Bold Vision Revolut wants to be the #1 fintech player in 40 markets with 30 million active users by 2027. That’s ambitious, and I respect it. Their product quality and speed of execution are inspiring. Scaling globally isn’t easy—it requires navigating different cultures, regulations, and markets. But their progress so far shows they know how to execute. When I hear goals like this, I feel motivated. Ambition, when paired with execution, is a force that can move mountains. Exploring New Frontiers Nik mentioned biotech and genetics as industries he’d like to explore. It reminded me of Walter Isaacson’s biography of Steve Jobs, where Jobs predicted these fields would drive the next breakthroughs. I couldn’t help but wonder: has Nik read that book? If I had the chance to explore a completely new field, I’d choose something similar. These areas promise innovation that could change the world, and I believe the next big thing will come from there. Passion vs. Progress When asked why he does what he does, Nik’s answer was simple: “What else is there to do?” His mindset resonated with me. Success isn’t always about passion; sometimes it’s about the need to keep moving forward. It’s the thrill of building, solving problems, and creating something new that keeps us going. And yes, it’s enough. Final Thoughts Listening to Nik’s podcast made me reflect on my own journey. His approach to hiring, work-life balance, and ambition is sharp, clear, and unapologetic. These are lessons every entrepreneur should think about, even if they don’t agree with everything. What do you think about Nik’s ideas? Would you embrace an imbalanced life for the sake of success? Let me know in the comments. Let’s discuss! https://www.youtube.com/watch?v=IXubBqd8uXs&embedable=true Nik Storonsky , founder of Revolut, shared bold and controversial views in his recent podcast. He talked about hiring, work-life balance, and the challenges of scaling a global business. His words hit close to home for me as an entrepreneur, and I’d like to share my take on some of the points he raised. Nik Storonsky The "Self-Guided Missile" Philosophy The "Self-Guided Missile" Philosophy Nik has a straightforward rule: hire "self-guided missiles." These are people who set their own goals, execute flawlessly, and deliver results without needing much guidance. If they don’t prove themselves in three months, they’re not the right fit. I fully agree with this. Finding such people is hard, but it’s possible. I’ve had the chance to work with individuals like this, and they are game-changers for any team. However, identifying them takes time and effort. Hiring isn’t just about interviews; it’s about spotting that rare mix of independence and drive. When you find them, they’re worth every moment spent searching. Work-Life Balance: Is It Overrated? Work-Life Balance: Is It Overrated? Nik’s take on balance is simple: it’s not for everyone. He believes success comes from sacrifice and imbalance. To win in the "big sport" of business, you need to focus 100% on your goals, even if it means giving up other parts of life. I tend to agree with him. It’s not a lifestyle that suits everyone, but it’s the reality of competing at the highest level. Building something impactful requires this kind of focus. If you’re willing to embrace it, the rewards can be extraordinary. Global Ambition: A Bold Vision Global Ambition: A Bold Vision Revolut wants to be the #1 fintech player in 40 markets with 30 million active users by 2027. That’s ambitious, and I respect it. Their product quality and speed of execution are inspiring. Scaling globally isn’t easy—it requires navigating different cultures, regulations, and markets. But their progress so far shows they know how to execute. When I hear goals like this, I feel motivated. Ambition, when paired with execution, is a force that can move mountains. Exploring New Frontiers Exploring New Frontiers Nik mentioned biotech and genetics as industries he’d like to explore. It reminded me of Walter Isaacson’s biography of Steve Jobs, where Jobs predicted these fields would drive the next breakthroughs. I couldn’t help but wonder: has Nik read that book? If I had the chance to explore a completely new field, I’d choose something similar. These areas promise innovation that could change the world, and I believe the next big thing will come from there. Passion vs. Progress Passion vs. Progress When asked why he does what he does, Nik’s answer was simple: “What else is there to do?” His mindset resonated with me. Success isn’t always about passion; sometimes it’s about the need to keep moving forward. It’s the thrill of building, solving problems, and creating something new that keeps us going. And yes, it’s enough. Final Thoughts Listening to Nik’s podcast made me reflect on my own journey. His approach to hiring, work-life balance, and ambition is sharp, clear, and unapologetic. These are lessons every entrepreneur should think about, even if they don’t agree with everything. Listening to Nik’s podcast What do you think about Nik’s ideas? Would you embrace an imbalanced life for the sake of success? Let me know in the comments. Let’s discuss! https://www.youtube.com/watch?v=IXubBqd8uXs&embedable=true https://www.youtube.com/watch?v=IXubBqd8uXs&embedable=true

Learnings From Nik Storonsky’s Podcast: The Self Guided Missile Philosophy and Scaling to 50M Users

Læring fra Nik Storonskys podcast: The Self Guided Missile Philosophy and scaling to 50M Users

Lecciones del podcast de Nik Storonsky: La filosofía de los misiles autoguiados y cómo escalar hasta 50 millones de usuarios

निक स्टोरोन्स्की के पॉडकास्ट से सीखें: स्व-निर्देशित मिसाइल दर्शन और 50 मिलियन उपयोगकर्ताओं तक विस्तार

Tanulságok Nik Storonsky podcastjából: Az önvezérelt rakéta filozófiája és az 50 millió felhasználóra való méretezés

Pelajaran dari Podcast Nik Storonsky: Filosofi Rudal Berpemandu Mandiri dan Peningkatan hingga 50 Juta Pengguna

Lezioni dal podcast di Nik Storonsky: la filosofia dei missili autoguidati e la scalabilità a 50 milioni di utenti

למידה מהפודקאסט של ניק סטורונסקי: פילוסופיית הטילים המודרכת עצמית והרחבה ל-50 מיליון משתמשים

Nik Storonsky のポッドキャストから学んだこと: 自己誘導ミサイルの哲学と 5,000 万人のユーザーへの拡張

ការរៀនពីផតឃែស្ថរបស់ Nik Storonsky៖ ទស្សនវិជ្ជាកាំជ្រួចដឹកនាំដោយខ្លួនឯង និងធ្វើមាត្រដ្ឋានដល់អ្នកប្រើប្រាស់ 50 លាននាក់

Boyekoli uta na Nik Storonsky’s Podcast: Philosophie ya Missile oyo etambwisami yango moko mpe bokasi ya monene kino na basaleli ya 50M

Lessen uit de podcast van Nik Storonsky: de filosofie van de zelfgestuurde raket en opschalen naar 50 miljoen gebruikers

Уроки подкаста Ника Сторонски: философия самонаводящихся ракет и масштабирование до 50 млн пользователей

Have you ever felt overwhelmed trying to make sense of dense notes or wished you could listen to them like a podcast while on the go? In this article, I’ll share the tool that could help you turn text into engaging audio podcasts; I believe it could help you learn new things faster and more effectively. Why Turning Notes into Podcasts Is a Game-Changer Did you know that over 50% of people prefer podcasts as their primary way of learning? Podcasts are portable, easy to consume, and perfect for multitasking. But creating a podcast used to feel like a daunting task — until now. Whether you’re a student trying to review lecture notes or a professional preparing for a big presentation, converting written material into something engaging takes time and effort. For me, the challenge was turning long, complex notes into something I could review effortlessly. I wanted to take these notes and transform them into a format I could absorb while driving, exercising, or just relaxing. That’s where NotebookLM came in. What Is NotebookLM and How Does It Work? NotebookLM is an AI-powered tool designed to help users simplify, organize, and transform their notes. Think of it as a smart assistant for your learning process. One of its standout features is the ability to convert text into audio — essentially creating podcasts from your notes. Here’s how I used it: 1. Upload your content: I started by uploading my notes, articles, or YouTube video links into NotebookLM. 2. AI Analysis: The AI analyzed the material, breaking it into clear, logical sections. This was great because it identified the key points I needed to focus on. 3. Text-to-Audio Conversion: The tool converted the notes into an audio format. But here’s the cool part: it wasn’t just a robotic reading. The AI added natural pacing, emphasis, and tone, making the audio feel like a professionally narrated podcast. 4. Download and Listen: Within minutes, I had a polished audio file that I could download and listen to anywhere — on my phone, in the car, or even during a walk. You also can get a shareable link that you can open on any device with the internet connection. The process was so intuitive that I barely had to do any editing, which saved me hours of work. Another cool feature is that you can Customize Audio Overview. You can specify the focus and add instructions for your podcast. This means you can focus on a specific aspect of the subject. This is the example of the podcast: https://notebooklm.google.com/notebook/1076c05e-4438-41db-b44c-2335d5859c24/audio Why NotebookLM Is Perfect for Learners and Creators Before NotebookLM, I often felt stuck. My notes would pile up, and the thought of reviewing them felt overwhelming. But now, I can turn my notes into audio, plug in my headphones, and listen to it on the go or before bedtime. This tool has made learning not just easier but enjoyable. I’ve retained more information because I can revisit the audio anytime. This tool isn’t just for people like me who want to review notes on the go. It’s also great for: Students: Simplify your study material into audio for easier revision.
Professionals: Prepare presentations or training sessions while multitasking.
Content Creators: Turn your ideas into podcasts effortlessly, saving time and boosting productivity. NotebookLM bridges the gap between written and spoken content, making it accessible to everyone. Video DEMO: How to Use NotebookLM Podcast https://youtu.be/fPsugPu9lqI?si=CzreDmclFqbwBSVP&embedable=true The most beautiful part is that NotebookLM is entirely free. So give it a shot and share with me your experience. Cheers! Have you ever felt overwhelmed trying to make sense of dense notes or wished you could listen to them like a podcast while on the go? In this article, I’ll share the tool that could help you turn text into engaging audio podcasts; I believe it could help you learn new things faster and more effectively. Why Turning Notes into Podcasts Is a Game-Changer Did you know that over 50% of people prefer podcasts as their primary way of learning? Podcasts are portable, easy to consume, and perfect for multitasking. But creating a podcast used to feel like a daunting task — until now. 50% of people prefer podcasts Whether you’re a student trying to review lecture notes or a professional preparing for a big presentation, converting written material into something engaging takes time and effort. For me, the challenge was turning long, complex notes into something I could review effortlessly. I wanted to take these notes and transform them into a format I could absorb while driving, exercising, or just relaxing. That’s where NotebookLM came in. What Is NotebookLM and How Does It Work? NotebookLM is an AI-powered tool designed to help users simplify, organize, and transform their notes. Think of it as a smart assistant for your learning process. One of its standout features is the ability to convert text into audio — essentially creating podcasts from your notes. NotebookLM NotebookLM Here’s how I used it: Here’s how I used it: 1. Upload your content : I started by uploading my notes, articles, or YouTube video links into NotebookLM. Upload your content 2. AI Analysis: The AI analyzed the material, breaking it into clear, logical sections. This was great because it identified the key points I needed to focus on. AI Analysis: 3. Text-to-Audio Conversion: The tool converted the notes into an audio format. But here’s the cool part: it wasn’t just a robotic reading. The AI added natural pacing, emphasis, and tone, making the audio feel like a professionally narrated podcast. Text-to-Audio Conversion: 4. Download and Listen : Within minutes, I had a polished audio file that I could download and listen to anywhere — on my phone, in the car, or even during a walk. You also can get a shareable link that you can open on any device with the internet connection. Download and Listen The process was so intuitive that I barely had to do any editing, which saved me hours of work. Another cool feature is that you can Customize Audio Overview. You can specify the focus and add instructions for your podcast. This means you can focus on a specific aspect of the subject. This is the example of the podcast: https://notebooklm.google.com/notebook/1076c05e-4438-41db-b44c-2335d5859c24/audio https://notebooklm.google.com/notebook/1076c05e-4438-41db-b44c-2335d5859c24/audio https://notebooklm.google.com/notebook/1076c05e-4438-41db-b44c-2335d5859c24/audio Why NotebookLM Is Perfect for Learners and Creators Before NotebookLM, I often felt stuck. My notes would pile up, and the thought of reviewing them felt overwhelming. But now, I can turn my notes into audio, plug in my headphones, and listen to it on the go or before bedtime. This tool has made learning not just easier but enjoyable. I’ve retained more information because I can revisit the audio anytime. This tool isn’t just for people like me who want to review notes on the go. It’s also great for: Students: Simplify your study material into audio for easier revision. Professionals: Prepare presentations or training sessions while multitasking. Content Creators: Turn your ideas into podcasts effortlessly, saving time and boosting productivity. Students: Simplify your study material into audio for easier revision. Students: Professionals: Prepare presentations or training sessions while multitasking. Professionals: Content Creators : Turn your ideas into podcasts effortlessly, saving time and boosting productivity. Content Creators NotebookLM bridges the gap between written and spoken content, making it accessible to everyone. Video DEMO: How to Use NotebookLM Podcast https://youtu.be/fPsugPu9lqI?si=CzreDmclFqbwBSVP&embedable=true https://youtu.be/fPsugPu9lqI?si=CzreDmclFqbwBSVP&embedable=true The most beautiful part is that NotebookLM is entirely free . So give it a shot and share with me your experience. NotebookLM is entirely free Cheers!

I Turned Notes Into A Podcast: How to Use NotebookLM Podcast DEMO

Podcast content is growing each year, with over 4.5 million active podcasts globally — and nearly 30 million episodes published in 2023 alone — the challenge of discovering relevant content has become increasingly complex. Podyssey emerged as a solution to this challenge, with its AI-driven approach to podcast curation and personalization. Ahmad Saleem, co-founder and CEO of Podyssey aims to set new standards for how listeners find and engage with relevant podcast content. "In the 1980s and 90s, the antidote to a mid-life crisis was starting a suburban band. Now it is starting a podcast.” Historically, the only way to find relevant podcast content was by manually searching through titles of shows and episode descriptions, relying heavily on ratings, reviews, and basic categorization. But these traditional discovery methods have proven insufficient as the volume of content continues to increase. Listeners often find themselves overwhelmed by choices or stuck in content bubbles, missing out on potentially valuable podcasts that fall outside of their usual listening patterns. “As a listener, the task of shifting through this new content is onerous and daunting. In fact, just finding that content you already like is becoming more and more daunting,” comments Saleem. “This is largely because there is more content to sift through; but also because the method for doing so is increasingly outdated.” Podyssey's approach puts curated content discovery at the forefront. At its heart lies a powerful and unique search engine that leverages cutting-edge technology to understand the actual discussions within podcasts. This isn't just an incremental improvement – it's a complete paradigm shift in how listeners find and consume podcast content. "Traditional platforms have to rely on the genre or content classifications applied by the podcaster to their content," explains Saleem. “This approach might have worked in simpler times, but today's podcast landscape defies such basic categorization. Take Joe Rogan's podcast, for instance – trying to pin it down to a single genre is like trying to fit a square peg in a round hole. The reality is that podcast content has become more genre-fluid than ever before, particularly in long-form formats.” The technical innovation behind Podyssey is substantial. The platform employs a sophisticated combination of audio recognition algorithms and natural language processing, utilizing bi-encoders and cross-encoders to analyze user queries. This goes beyond simple keyword matching, allowing the system to understand the intent behind searches and deliver more relevant results, even without exact matches. "There is nothing else like Podyssey out there," according to Saleem. "We are the only podcast platform that allows listeners to curate their listening based on the content being discussed." This means listeners can finally break free from the constraints of genre-based discovery. Podyssey goes beyond search capabilities. By studying listener behavior – from search patterns to engagement rates with specific clips – the platform creates highly detailed user profiles that enable complete personalization. Instead of sitting through a three-hour episode for ten minutes of relevant content, users can enjoy sixty minutes of carefully curated material drawn from various sources, all focused on their specific interests. The company’s journey is about more than just improving podcast discovery – it's about reimagining the entire podcast ecosystem. While traditional platforms have remained relatively unchanged since the industry's inception, Podyssey represents a fundamental shift in how both creators and listeners engage with podcast content. By removing artificial boundaries and putting content relationships at the center of the experience, Podyssey isn't just participating in the podcast revolution – it's leading it. The message is clear: the future of podcast discovery has arrived, and it's time for listeners to break free from the constraints of traditional platforms. Podyssey stands ready to ensure that every listener can find exactly what they're looking for – and discover content they never knew they needed. Podcast content is growing each year, with over 4.5 million active podcasts globally — and nearly 30 million episodes published in 2023 alone — the challenge of discovering relevant content has become increasingly complex. Podyssey emerged as a solution to this challenge, with its AI-driven approach to podcast curation and personalization. Ahmad Saleem, co-founder and CEO of Podyssey aims to set new standards for how listeners find and engage with relevant podcast content. Podyssey "In the 1980s and 90s, the antidote to a mid-life crisis was starting a suburban band. Now it is starting a podcast.” "In the 1980s and 90s, the antidote to a mid-life crisis was starting a suburban band. Now it is starting a podcast.” Historically, the only way to find relevant podcast content was by manually searching through titles of shows and episode descriptions, relying heavily on ratings, reviews, and basic categorization. But these traditional discovery methods have proven insufficient as the volume of content continues to increase. Listeners often find themselves overwhelmed by choices or stuck in content bubbles, missing out on potentially valuable podcasts that fall outside of their usual listening patterns. “As a listener, the task of shifting through this new content is onerous and daunting. In fact, just finding that content you already like is becoming more and more daunting,” comments Saleem. “This is largely because there is more content to sift through; but also because the method for doing so is increasingly outdated.” Podyssey's approach puts curated content discovery at the forefront. At its heart lies a powerful and unique search engine that leverages cutting-edge technology to understand the actual discussions within podcasts. This isn't just an incremental improvement – it's a complete paradigm shift in how listeners find and consume podcast content. "Traditional platforms have to rely on the genre or content classifications applied by the podcaster to their content," explains Saleem. “This approach might have worked in simpler times, but today's podcast landscape defies such basic categorization. Take Joe Rogan's podcast, for instance – trying to pin it down to a single genre is like trying to fit a square peg in a round hole. The reality is that podcast content has become more genre-fluid than ever before, particularly in long-form formats.” The technical innovation behind Podyssey is substantial. The platform employs a sophisticated combination of audio recognition algorithms and natural language processing, utilizing bi-encoders and cross-encoders to analyze user queries. This goes beyond simple keyword matching, allowing the system to understand the intent behind searches and deliver more relevant results, even without exact matches. "There is nothing else like Podyssey out there," according to Saleem. "We are the only podcast platform that allows listeners to curate their listening based on the content being discussed." This means listeners can finally break free from the constraints of genre-based discovery. Podyssey goes beyond search capabilities. By studying listener behavior – from search patterns to engagement rates with specific clips – the platform creates highly detailed user profiles that enable complete personalization. Instead of sitting through a three-hour episode for ten minutes of relevant content, users can enjoy sixty minutes of carefully curated material drawn from various sources, all focused on their specific interests. The company’s journey is about more than just improving podcast discovery – it's about reimagining the entire podcast ecosystem. While traditional platforms have remained relatively unchanged since the industry's inception, Podyssey represents a fundamental shift in how both creators and listeners engage with podcast content. By removing artificial boundaries and putting content relationships at the center of the experience, Podyssey isn't just participating in the podcast revolution – it's leading it. The message is clear: the future of podcast discovery has arrived, and it's time for listeners to break free from the constraints of traditional platforms. Podyssey stands ready to ensure that every listener can find exactly what they're looking for – and discover content they never knew they needed.

The Future of Podcast Curation: Podyssey's AI-Driven Approach to Content Discovery

https://www.youtube.com/watch?v=0cn3VBjfN8g&embedable=true&transcript=true&long=true

"The Person Who Controls the Algorithm Controls the World, Right?" Mark Cuban on the Lex Fridman Pod

"যে ব্যক্তি অ্যালগরিদম নিয়ন্ত্রণ করে বিশ্বকে নিয়ন্ত্রণ করে, তাই না?" লেক্স ফ্রিডম্যান পডে মার্ক কিউবান

„Wer den Algorithmus kontrolliert, kontrolliert die Welt, oder?“ Mark Cuban im Lex Fridman Pod

"La persona que controla el algoritmo controla el mundo, ¿verdad?" Mark Cuban en el Pod Lex Fridman

« La personne qui contrôle l'algorithme contrôle le monde, n'est-ce pas ? » Mark Cuban sur le module Lex Fridman

"वह व्यक्ति जो एल्गोरिथम को नियंत्रित करता है वह दुनिया को नियंत्रित करता है, ठीक है?" लेक्स फ्रिडमैन पॉड पर मार्क क्यूबन

「アルゴリズムをコントロールする人が世界をコントロールする、そうでしょう？」レックス・フリードマン・ポッドのマーク・キューバン

"알고리즘을 지배하는 사람이 세상을 지배하는 거겠죠?" Lex Fridman Pod의 Mark Cuban

"A pessoa que controla o algoritmo controla o mundo, certo?" Mark Cuban no Lex Fridman Pod

«Человек, который управляет алгоритмом, контролирует мир, верно?» Марк Кьюбан в капсуле Лекса Фридмана

"Algoritmayı Kontrol Eden Kişi Dünyayı Kontrol Eder, Değil mi?" Lex Fridman Pod'da Mark Cuban

"Người điều khiển thuật toán sẽ điều khiển thế giới, phải không?" Mark Cuban trên Lex Fridman Pod

“控制算法的人就控制了世界，对吧？”马克·库班在 Lex Fridman 播客上说

https://www.youtube.com/watch?v=jvqFAi7vkBc&embedable=true&transcript=true&long=true

"Compute is Going to the Currency of the Future," says Sam Altman on the Lex Fridman Podcast 

লেক্স ফ্রিডম্যান পডকাস্টে স্যাম অল্টম্যান বলেছেন, "কম্পিউট ভবিষ্যতের মুদ্রায় যাচ্ছে"

„Compute wird zur Währung der Zukunft“, sagt Sam Altman im Lex Fridman Podcast

"La informática se está convirtiendo en la moneda del futuro", dice Sam Altman en el podcast Lex Fridman

"Le calcul devient la monnaie du futur", déclare Sam Altman sur le podcast Lex Fridman

लेक्स फ्रिडमैन पॉडकास्ट पर सैम ऑल्टमैन कहते हैं, "कंप्यूट भविष्य की मुद्रा की ओर जा रहा है।"

「コンピューティングは未来の通貨になりつつある」とサム・アルトマン氏がレックス・フリッドマン・ポッドキャストで語る

Lex Fridman Podcast에서 Sam Altman은 "컴퓨팅은 미래의 통화로 변모하고 있습니다."라고 말합니다.

“A computação está indo para a moeda do futuro”, diz Sam Altman no Lex Fridman Podcast

«Вычисления становятся валютой будущего», — говорит Сэм Альтман в подкасте Lex Fridman.

Lex Fridman Podcast'inde Sam Altman "Bilgi İşlem Geleceğin Para Birimi'ne Gidiyor" diyor

Sam Altman nói trên Lex Fridman Podcast: “Máy tính đang hướng tới tiền tệ của tương lai”

Sam Altman 在 Lex Fridman 播客上表示：“计算将成为未来的货币”

92 Stories To Learn About Hackernoon Podcast

I write a newsletter called Above Average, where I talk about the second-order insights behind everything that is happening in big tech. If you are in tech and don’t want to be average, . subscribe to it A lot of people want podcasts transcribed and read instead of listening to them. We can go one level up and even extract insights from the podcasts as well using Open AI API. Here’s my tweet exchange, which provoked this experiment. So here is what we are going to do. And it will be slightly different from what I suggested in the tweet. The goal is to pick a YouTube video and get a transcription of that video, and then using prompt engineering, we extract insights, ideas, book quotes & summaries, etc., To Summarize, we achieve our goal in three steps: Step 1: Select a YouTube podcast video Step 2: Transcribe the video Step 3: Get Insights from the transcription Step 1: Select a YouTube podcast video A recent podcast conversation that broke YouTube was Jeff Bezos on Lex Friedman's podcast. So, for this exercise, I will pick this . video Step 2: Transcribe the video I used langchain along with Open AI’s audio-to-text model whisper to transcribe the youtube video. As usual you would need your OpenAI secret key to use the following script. YouTubeAudioLoader import os
import sys
import openai

from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv()) # read local .env file
openai.api_key  = os.environ['OPENAI_API_KEY']


## youtube video's audio loader - langchain 
from langchain_community.document_loaders.blob_loaders.youtube_audio import YoutubeAudioLoader
from langchain_community.document_loaders.generic import GenericLoader
from langchain_community.document_loaders.parsers import OpenAIWhisperParser #, OpenAIWhisperParserLocal

url="https://www.youtube.com/watch?v=DcWqzZ3I2cY&ab_channel=LexFridman"
save_dir="outputs/youtube/"
loader = GenericLoader(
     YoutubeAudioLoader([url],save_dir),
     OpenAIWhisperParser()
 )
docs = loader.load()
print(docs[0].page_content[0:500])

# Specify the file path where you want to save the text
file_path = "audio-transcript.txt"
try:
    with open(file_path, 'a', encoding='utf-8') as file:
        for doc in docs:
            file.write(doc.page_content)
    print(f'Large text saved to {file_path}')
except FileNotFoundError:
    print(f"Error: Input file '{file_path}' not found.")
except Exception as e:
    print(f"An error occurred: {e}") You might see the following error while running this script, and I pasted the solution that works in case you are using a Windows system. Postprocessing: and not found. Please install or provide the path using –ffmpeg-location. ERROR: ffprobe ffmpeg Running this script will generate the transcript and store it in a text file audio-transcript.txt. Step 3: Extract insights from the conversation To extract insights, I am using Open AI API, and here is the script. The code loads the transcript text and passes it along with a prompt designed to extract insights, people & books. To get more interesting things out of this conversation, you can come up with a more interesting prompt. Note that the file name is slightly different because I had to cut the transcript to a short length since my completion query to Open AI API exceeded my TPM limits. import os
import sys
import openai
import shutil
from pprint import pprint

from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv()) # read local .env file
openai.api_key  = os.environ['OPENAI_API_KEY']

client = openai.OpenAI()

file_path = "audio-transcript-copy.txt"
try:
    with open(file_path, 'r', encoding='utf-8') as file:
        long_text = file.read()
    print(f'{file_path} is rad')
except FileNotFoundError:
    print(f"Error: Input file '{file_path}' not found.")
except Exception as e:
    print(f"An error occurred: {e}")

prompt2 = f"""
You will be provided with text deilimited by triple quotes.
The given text is a podcast transcript.

Provide the host and guest name.
Summarize the transcript in to 10 points.

If there are any people referred in the transcript. Extract the people mentioned and list them along with some info about them in the following format
1. Person 1's Name: Person 1's profession or what he or she is known for or the context in which he or she was referred to.
2. Person 2's Name: Person 2's profession or what he or she is known for or the context in which he or she was referred to.
...
2. Person N's Name: Person N's profession or what he or she is known for or the context in which he or she was referred to.
If the transcript doesnt contain refereces to any people then simply write \"No people referred to in the conversation.\"

Extract the books mentioned and list them in the following format.
1. Book 1's Title: Context in which the book was referred to.
2. Book 2's Title: Context in which the book was referred to.
...
N. Book N's Title: Context in which the book was referred to.
If the transcript doesnt contain refereces to any books then simply write \"No books referred to in the conversation.\"

IF you find any inspiration quotoes complie them in to a list.

\"\"\"{long_text}\"\"\"
"""

response = client.chat.completions.create(
  model="gpt-4",
  messages=[
    {
      "role": "user",
      "content": prompt2
    }
  ],
  temperature=0.7,
  #max_tokens=64,
  #top_p=1
)

print(response.choices[0].message.content) Here is what the output I got: Result: Lex Freidman & Jeff Bezos Podcast Summary Can provide a service to podcasters to generate smart transcripts with insights. This would be a B2B play. AI PRODUCT IDEA ALERT 1: Instead of a service to podcast creators, it could be B2C customers who listen to podcasts and want to read through podcasts and create their own library of insights. AI PRODUCT IDEA ALERT 2: Expect both these ideas to be used by existing podcast hosting companies like Spotify & launch these ideas as new features. If I was a Product Manager in any such companies I would be pitching them by now. That’s it for day 5 of 100 Days of AI. Follow me on , for latest updates on 100 days of AI or & Check out Twitter LinkedIn bookmark this page Day 4: How to Use ChatGPT to be More Productive? Also published . here

100 Days of AI Day 5: Transcription and Extracting Insight from Podcasts with OpenAI

If you don’t know, I write a newsletter called Above Average, where I talk about the second-order insights behind everything that is happening in the big tech. If you are into tech and want to be above average, . subscribe to it I have always admired Scott Galloway's newsletter, No Mercy, No Malice. One unique thing Scott does with his newsletter is that he hired his friend George Hahn to convert the newsletter into a podcast, which is published every week in his podcast feed . here I don’t have a friend like George Hahn, but I know AI voices have become very life-like with recent advances. So I thought, why not convert my newsletter into a podcast? So, I played around and wrote a script to use Open AI’s text-to-speech API to convert my newsletter post into its audio version. To follow along and use this script, you need Open AI credits and an Open AI Secret Key. Here is the code I used. from openai import OpenAI


client = OpenAI()
client.api_key = 'YOUR SECRET KEY'
txt = """1/ Google is the dark horse in AI

Only Google can mess up a good thing multiple times. Google has struggled to play the perception game that has turned against it after the launch of ChatGPT and with Sathya’s offense on all things AI.

Google released an impressive Gemini AI preview series and the success lasted for two days. Before media started to observe that the demo is not so much as a demo but series of well constructed prompts. Or a series of good demos complied to one great demo.

This is obviously putting Google back again in the perception wars of AI. The keyword here is perception.

If everything is perception & marketing than nothing in the world will be a surprise. In case of Google in AI, don’t let the perception confuse you. Google is still the dark horse in AI. Google was talking about AI in every Pixel device launch since last 5 years while the tech industry and VCs were saying that Crypto is the next big thing.

The day to day news cycle exists to take your attention and make you click & confuse you. AI is a continuous innovation not a discontinuous one. Google has strong fundamentals in AI and the AI cycle is much longer than 12 months of ChatGPT. Google has shipped more AI products via Gmail, Google Search, Ads and most importantly Google Pixel than any other company. So just because Google has failed to market itself doesn’t mean its a loser in AI.

Google is still a dark horse in AI."""

response = client.audio.speech.create(
    model="tts-1",
    voice="onyx",
    input=txt,
)

response.stream_to_file("output.mp3") The newsletter post I took in this example is from . Here is the output . this edition result it generated The result was not as good as George Hahn’s voice, but it’s much better than most of the audio book out there. This idea can be expanded further to create a product that takes a new newsletter when published, converts it automatically to a podcast, and publishes it in the podcast feed. George Hahn as a Service. AI PRODUCT ALERT: That’s it for day 1 of AI. Follow me on for the latest updates on 100 days of AI or . Twitter bookmark this page Also published . here

100 Days of AI Day 1: From Newsletter to Podcast, Leveraging AI for Audio Transformation

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