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Struggling with AI detectors flagging your work or spending hours manually rewriting text? Meet Lynote the ultimate workspace for writers, students, and creators! Here’s why it’s a total game-changer: ◽ AI Humanizer: Converts robotic text into natural writing with a 99% bypass rate ◽Multi-Model AI Detector: Pinpoints AI content...

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Shakil.rise

9,567 subscribers

19,489 次观看 • 6 天前 •via X (Twitter)

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35 条评论

Lynote 的头像
Lynote6 天前

Wow! Thanks for this post! 🔥

Shakil.rise 的头像
Shakil.rise6 天前

everyday only 1 winner ? or more 2 or 3?

Lynote 的头像
Lynote6 天前

The daily leaderboard only rewards 1 winner, but our overall leaderboard offers multiple rewards and can generate exposure over several days.

Shakil.rise 的头像
Shakil.rise6 天前

My post total 12k+ view but webpage show only 1358 view?

Andy the Jet 的头像
Andy the Jet6 天前

@lynote_ai clean ux will attract more users

𝙋𝙐𝙇⭕𝙆 🍌 的头像
𝙋𝙐𝙇⭕𝙆 🍌6 天前

@lynote_ai $15000 prize pool sounds pretty tempting to join

MARUF 的头像
MARUF6 天前

@lynote_ai the humanizer and detector combo is a pretty interesting workflow

J D Joy 的头像
J D Joy6 天前

@lynote_ai Sounds like a major help for writers struggling with AI flagging their work!

STING 的头像
STING6 天前

@lynote_ai What are they building?

bibi.eth 的头像
bibi.eth6 天前

@lynote_ai That AI humanizer feature sounds super helpful for writers

k3lly 的头像
k3lly6 天前

@lynote_ai Sometimes the strongest sign of progress is simply having fewer things to worry about when using the product.

Biswa FF 的头像
Biswa FF6 天前

@lynote_ai definitely trying this out for my essays today

Kim Vault 的头像
Kim Vault6 天前

@lynote_ai + language translations sound impressive, but how accurate are they?

Samba 🔴 的头像
Samba 🔴6 天前

@lynote_ai There is a useful point here worth keeping in mind.

「cohn」 ✦ 的头像
「cohn」 ✦6 天前

@lynote_ai AI Humanizer + multi-model detector + study workspace in one place is a strong combo for writers and students. Creator Challenge with daily rewards is smart too.

Ēl ChĀPø 的头像
Ēl ChĀPø6 天前

@lynote_ai I respect the effort you put in, and I hope you keep it up.

CM 的头像
CM6 天前

@lynote_ai amazing creation for this project

Vexora ☣ 的头像
Vexora ☣6 天前

@lynote_ai A 99% bypass claim is risky; better verify.

TASIN 的头像
TASIN6 天前

@lynote_ai real feedback will probably shape the next phase

CPrinz 🎒 的头像
CPrinz 🎒6 天前

@lynote_ai New alpha 👀

GodAir 的头像
GodAir6 天前

@lynote_ai This AI Humanizer feature sounds really useful!

Loc Capital 的头像
Loc Capital6 天前

@lynote_ai can it really hit 99% bypass on all detectors?

Ziadul Hasan 的头像
Ziadul Hasan6 天前

@lynote_ai Interesting tools, but I hope you still prioritize original thinking.

JAlpha 的头像
JAlpha6 天前

@lynote_ai This has great pool

SPETOO🗿 的头像
SPETOO🗿6 天前

@lynote_ai Natural writing plus detection in one workflow.

Rame🍌 的头像
Rame🍌6 天前

@lynote_ai That's amazing creation for this project

Sabbir🌊Aurora 🪑 的头像
Sabbir🌊Aurora 🪑6 天前

@lynote_ai Curious about what the community builds around this.

Nobita 的头像
Nobita6 天前

@lynote_ai ai with agents sound cool one vibe here

Duc Crypto 的头像
Duc Crypto6 天前

@lynote_ai imagine earning $150 daily from a challenge with zero followers

SARKER 的头像
SARKER6 天前

@lynote_ai hosting the Lynote Creator Challenge Season 1 with a $15,000+ Prize Pool ($150 daily rewards

Đường Phát 的头像
Đường Phát6 天前

@lynote_ai the $150 daily rewards keep the challenge exciting

Akash.eth🌊 的头像
Akash.eth🌊6 天前

@lynote_ai Sentence by sentence detector plus humanizer sounds useful, especially for students translating study notes into 135 plus languages.

Kai🔺 的头像
Kai🔺6 天前

@lynote_ai this sounds pretty dope, might try it out

Nicelyval 的头像
Nicelyval6 天前

@lynote_ai Looks good

Crypto Sapiens 的头像
Crypto Sapiens6 天前

@lynote_ai i agree, but doing it day‑after‑day is the hard part

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You stay up till 2 AM, write the paper yourself, and the checker still flags it as AI. Teachers don’t believe you. That’s the mess. I ran the same draft through Lynote . It’s a writing workspace that humanizes the tone so it actually sounds like you, then the detector shows the score before you submit. Notes, YouTube transcripts, and flashcards sit in the same place. I’m testing it for the Lynote Creator Challenge. Over $15,000 in prizes, through Dec 20. No follower minimum. #Lynote #LynoteCreatorChallenge
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I've spent hours and hours thinking about how AI is going to change writing. This is a 90-minute distillation of everything I've learned. Some things I believe: 1. The combination of LLM-driven humor and image generation means that we're about to enter the golden age of memes. 2. The best writers will be fine. Robert Caro and Dostoevsky aren’t about to be disrupted by ChatGPT. 3. What are the different models like? ChatGPT is your friend who makes a lot of good points, but it’s kinda boring, Claude is your hippie friend who loves to get vulnerable but takes the whole “express yourself” thing a little too far, and Grok is your unhinged friend who leans a little too hard into tinfoil hat theories, but is always a trip to jam on ideas with. 4. People who say that AI writing is low-quality aren’t realizing that quality exists along two dimensions: (1) the absolute quality of the writing and (2) how tailored the writing is to your interests at the time. 5. I’ll tell you this: What writers are doing with AI behind closed doors is a long way ahead of what's publicly understood. I don't expect this to change anytime soon because of the social stigma associated with AI-enhanced writing. Because of that, if you want to see the cutting edge, you're gonna have to piece things together through private conversations and group chats. 6. If you want to follow what's happening in AI, remember this quote from William Gibson: “The future is here, it’s just not evenly distributed yet.” You can get a glimpse of the future by looking at how a small percentage of writers are already using AI. 7. I’m bearish on writers who are currently using AI to write for them, and bullish on writers who are currently using AI to write with them. 8. What kinds of writing will continue to be written by humans? Ones that speak to our humanity. People are interested in people. Their stories, their struggles, their emotions, their drama. 9. Almost all utilitarian writing, where the goal is to convey information, not do it beautifully, will be written by AI. 10. In some ways, AI is the end of slop. So many Google search results are slop. LinkedIn posts are slop. The way Twitter got taken over by Threadbois in 2021 was also slop. AI-generated writing is already better than all of those things, so why would you read them now? 11. AI will be tougher on writers than readers. Readers will be exposed to some slop, but the Internet will be good about filtering it out. Writers, though, are now competing against ever-improving LLMs, which are getting better and better by the month. 12. Humans will contribute with unique data or perspectives. The famous Peter Thiel interview question doubles as a good writing prompt: “What very important truth do few people agree with you on?” 13. New technologies breed new kinds of art. Ever notice how flat 13th or 14th century Medieval art looks? And how different that art looks from the Renaissance art created in the 15th and 16th centuries? Technical innovations like the camera obscura and perspective grids are behind this. Similarly profound changes will come to the writing world because of AI (credit to Justin Murphy for the idea here). 14. Satya Nadella says: “The new workflow for me is I think with AI and work with my colleagues.” When it comes to discovering ideas, I've also found that jamming with an LLM is more productive than doing it with most people I know (save for a few giga-brain conversationalists). 15. Thought experiment: Will AI-writing be more like music or chess? With music, we don't care how a song is made. We just want it to be good. With chess, there's a huge market for watching human beings play even though the computers are already better. I think non-fiction writing will go the way of music. People won’t care how it was made. They’ll just care that it’s good. 16. AI has flipped the rules of tech adoption. Seasoned managers usually drag their feet with adopting new technology, but the ones I know love AI, while frontline workers struggle to see the point. My theory is that AI matches how managers already operate. Management has always been a kind of prompt engineering: set a vision, delegate, give feedback, iterate. But LLMs remove the drama that used to come with having a team. No 1-on-1s. No emotional tangles. It's like management without the headache. For frontline employees, things are different. They aren't as accustomed to setting a vision and giving feedback, so LLM prompting is a daunting and unfamiliar kind of work for them. 17. AI editors are already quite good. Sure, they aren’t as good as the world’s best editors, but they’re a fraction of the cost, they’ll instantly give you 80th percentile feedback, and they work 24/7. As a novelist recently said to me: “Paying an editor to review my novel costs me $7,000 and a 4-6 week turnaround time, whereas Claude costs me $1.25 and gets me results a few minutes later.” The edits definitely aren’t as good, but there’s a virtue to speed (and this guy isn’t a chump writer). 18. The way AI-skeptics hate on LLMs while using old models is like driving a ‘92 Honda while hating on a self-driving Tesla. 19. AI-generated fiction makes people very upset. A friend insists it’s like having sex with a robot. Doesn’t matter how good it is. It ain’t human-generated, and there’s something uniquely repulsive about that. I’ve shared the full conversation below. It’s a solo-episode of me riffing on what I’ve learned about AI for ~90 minutes. If you’d rather watch it on YouTube or listen on Apple or Spotify, I’ve shared the links in the reply tweets. And if you have any questions, I’ll be extra active in the replies for this episode.

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257,480 次观看 • 1 年前

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Huge opportunity for creators right now Why Perle Labs got my attention 👀 🔸PerleLabs just dropped a campaign with $55K up for grabs across 400 winners. 🔸I spent hours poured into this piece 🎨 creating art with my feet 🐾 to show that no matter the challenge, creativity finds a way. This isn't just a post; it's my contribution to a future where humans and AI grow together. 🔸We’re entering a world where machines generate knowledge, but rarely understand its source. 🔸Perle Labs is building a system where AI learns from real human knowledge instead of random or low quality data. 🔸You complete simple tasks like labeling reviewing or correcting data, and every action is recorded onchain as proof of your work. 🔸Your effort builds a visible reputation, which helps you access better tasks and higher rewards over time. 🔸Over 50,000 people are already contributing with more than 1.7 million tasks completed across the platform. 🔸This creates a model where humans stay important in AI and your input becomes a real digital asset. 🔸Perle Labs anchors AI back to human insight through verified data and onchain reputation. Making contribution not just useful, but permanent. How to Participate 👇 1. Join Perle’s discord via this link 2. Post an original tweet on X (text, meme, image, or video or anything ) I have made a art with my leg 🦵 art to express my gratitude ) 3. Include the hashtags: #PerleAl + #ToPerle 4. End your tweet with: "- participating in Perle Labs community campaign" 5. Submit your entry → I wish my best luck to all the participants let's support each other and win big . I will be sharing how you can be easily be in top 50 position 🤑in my next post Glad to mention I am "- participating in Perle Labs community campaign "

dhiraj

41,009 次观看 • 6 个月前

A friend of mine works in market research Her job involves calling different brands, asking questions, and collecting insights that later turn into reports. She needs to capture everything accurately while the conversation is still happening Earlier, she used to note everything down manually during the call. It was stressful and she often had to spend extra time later cleaning up messy notes. Now she does something much simpler. She keeps the call on speaker on her laptop, turns on the Typeless mic, and it converts the conversation into clean notes in real time. After the call, she just asks it to turn those notes into a proper summary or email for her team. No scrambling through rough notes. No spending another 20 minutes rewriting everything. She even does the same thing on mobile when she needs to send a quick update after a call. What makes it powerful is how it handles real speech. We don’t talk in perfect sentences. We pause, repeat ourselves, change direction mid-sentence, and add filler words. Typeless understands that. It removes filler words, fixes repetitions, catches mid-sentence changes, and turns messy speech into clean, ready to send text, whether that’s an email, a bullet list, notes, or a message. One feature that really stands out is voice based editing. You can refine sentences, change the tone, or tweak wording just by speaking again. No typing needed. It works anywhere you write WhatsApp, Slack, email, Notes, even ChatGPT and supports 100+ languages with a personal dictionary. Privacy is also a big focus. The platform is HIPAA compliant and GDPR compliant, with zero cloud data retention. Your data is never used to train AI models, and your history stays stored locally on your device. For professionals working with sensitive information, that matters a lot. They’re also working toward SOC 2 Type II and ISO 27001 compliance. Speaking your thoughts and getting polished writing instantly is honestly much faster than typing everything. That’s basically what Typeless does. Try it here: Android: (check the video 👇) Trust center:
0:44

A friend of mine works in market research Her job involves calling different brands, asking questions, and collecting insights that later turn into reports. She needs to capture everything accurately while the conversation is still happening Earlier, she used to note everything down manually during the call. It was stressful and she often had to spend extra time later cleaning up messy notes. Now she does something much simpler. She keeps the call on speaker on her laptop, turns on the Typeless mic, and it converts the conversation into clean notes in real time. After the call, she just asks it to turn those notes into a proper summary or email for her team. No scrambling through rough notes. No spending another 20 minutes rewriting everything. She even does the same thing on mobile when she needs to send a quick update after a call. What makes it powerful is how it handles real speech. We don’t talk in perfect sentences. We pause, repeat ourselves, change direction mid-sentence, and add filler words. Typeless understands that. It removes filler words, fixes repetitions, catches mid-sentence changes, and turns messy speech into clean, ready to send text, whether that’s an email, a bullet list, notes, or a message. One feature that really stands out is voice based editing. You can refine sentences, change the tone, or tweak wording just by speaking again. No typing needed. It works anywhere you write WhatsApp, Slack, email, Notes, even ChatGPT and supports 100+ languages with a personal dictionary. Privacy is also a big focus. The platform is HIPAA compliant and GDPR compliant, with zero cloud data retention. Your data is never used to train AI models, and your history stays stored locally on your device. For professionals working with sensitive information, that matters a lot. They’re also working toward SOC 2 Type II and ISO 27001 compliance. Speaking your thoughts and getting polished writing instantly is honestly much faster than typing everything. That’s basically what Typeless does. Try it here: Android: (check the video 👇) Trust center:

aditii

59,829 次观看 • 6 个月前

💸 Anyone here juggling multiple AI tools for work? I used to switch between ChatGPT, Claude, and different image/video tools all the time — too many tabs, too many subscriptions, and honestly, it slowed down my workflow. Recently, I tried Rita, and their Seedance 2.0 model is what really stood out 👀 It’s an official ByteDance-powered version, so there’s no waiting queue — everything runs fast and smoothly. What’s even more interesting: • Supports real-person facial recognition • Lets you go from idea → video in one workflow • Low barrier to start — new users can try it for free once Personally, I like generating ideas with ChatGPT, then bringing them into Seedance 2.0 to turn them into actual videos. Feels especially useful for: • Content creators / KOLs working across text, images, and video • Digital workers who want efficiency over juggling multiple tools • AI users who want everything in one place ⚠️ Note: 1. Real-Person Face Feature(Comming Soon) 2. All Generated Videos Will Support Commercial Use. Curious — Do you prefer an all-in-one platform, or separate tools for each task?.... Try it → Want premium subscriptions for less? Check out GamsGo — an easy way to save on popular digital services at a lower cost. 👀 Check it Now👉 #RitaAI #Seedance2
0:47

💸 Anyone here juggling multiple AI tools for work? I used to switch between ChatGPT, Claude, and different image/video tools all the time — too many tabs, too many subscriptions, and honestly, it slowed down my workflow. Recently, I tried Rita, and their Seedance 2.0 model is what really stood out 👀 It’s an official ByteDance-powered version, so there’s no waiting queue — everything runs fast and smoothly. What’s even more interesting: • Supports real-person facial recognition • Lets you go from idea → video in one workflow • Low barrier to start — new users can try it for free once Personally, I like generating ideas with ChatGPT, then bringing them into Seedance 2.0 to turn them into actual videos. Feels especially useful for: • Content creators / KOLs working across text, images, and video • Digital workers who want efficiency over juggling multiple tools • AI users who want everything in one place ⚠️ Note: 1. Real-Person Face Feature(Comming Soon) 2. All Generated Videos Will Support Commercial Use. Curious — Do you prefer an all-in-one platform, or separate tools for each task?.... Try it → Want premium subscriptions for less? Check out GamsGo — an easy way to save on popular digital services at a lower cost. 👀 Check it Now👉 #RitaAI #Seedance2

Nihan

19,296 次观看 • 5 个月前

Why is the creator of OpenCode pretty skeptical about AI productivity gains, and the hype around AI? A very conversation dax (and lots of truth bombs:) Timestamps: 00:00 Intro 07:03 Dax’s path into tech 09:04 Early startup experience 13:16 Getting involved with open source 16:13 OpenCode 23:17 Anthropic banning OpenCode 30:34 From terminal to GUI 32:34 OpenCode’s business model 36:33 Why inference is profitable 39:11 GPU bottlenecks 40:54 AI hype 45:50 AI spending 48:47 Dax’s memo 55:41 Dax’s skepticism of predictions 58:58 Engineering culture at OpenCode 1:02:38 How building works at OpenCode 1:05:36 Taste and quality 1:11:32 Dax’s work setup 1:12:35 The role of engineers and EMs 1:15:50 Advice for engineers 1:18:12 Book recommendation Brought to you by: • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages • WorkOS – everything you need to make your app enterprise ready • turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable Three interesting thoughts from Dax: 1. No AI-native coding agent company is “winning” by being better with AI. Dax says that none of OpenCode’s competitors are crushing them, and that nobody is using AI so well that others cannot compete. 2. Most software engineers profit from AI as time gained, not increased output — unless you change incentives! Dax says the natural way for software engineers to “cash out” their AI tooling gains is with time savings, by doing the same work as before, but faster. Until compensation and motivation structures change, most teams should expect output to stay flat while engineers go home earlier. There’s nothing wrong with this, but AI vendors sell a different outcome to CFOs: increased output. 3. AI code generation mutes the “guilt” of doing the wrong thing, but this builds up tech debt. Pre-AI, writing a hack felt bad, the second time it felt really bad, and by the third time you’d often just refactor in order to fix up the code. Now, the agent hides the hack, which skews devs’ judgment and results in less tech debt being cleaned up.
1:21:01

Why is the creator of OpenCode pretty skeptical about AI productivity gains, and the hype around AI? A very conversation dax (and lots of truth bombs:) Timestamps: 00:00 Intro 07:03 Dax’s path into tech 09:04 Early startup experience 13:16 Getting involved with open source 16:13 OpenCode 23:17 Anthropic banning OpenCode 30:34 From terminal to GUI 32:34 OpenCode’s business model 36:33 Why inference is profitable 39:11 GPU bottlenecks 40:54 AI hype 45:50 AI spending 48:47 Dax’s memo 55:41 Dax’s skepticism of predictions 58:58 Engineering culture at OpenCode 1:02:38 How building works at OpenCode 1:05:36 Taste and quality 1:11:32 Dax’s work setup 1:12:35 The role of engineers and EMs 1:15:50 Advice for engineers 1:18:12 Book recommendation Brought to you by: • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages • WorkOS – everything you need to make your app enterprise ready • turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable Three interesting thoughts from Dax: 1. No AI-native coding agent company is “winning” by being better with AI. Dax says that none of OpenCode’s competitors are crushing them, and that nobody is using AI so well that others cannot compete. 2. Most software engineers profit from AI as time gained, not increased output — unless you change incentives! Dax says the natural way for software engineers to “cash out” their AI tooling gains is with time savings, by doing the same work as before, but faster. Until compensation and motivation structures change, most teams should expect output to stay flat while engineers go home earlier. There’s nothing wrong with this, but AI vendors sell a different outcome to CFOs: increased output. 3. AI code generation mutes the “guilt” of doing the wrong thing, but this builds up tech debt. Pre-AI, writing a hack felt bad, the second time it felt really bad, and by the third time you’d often just refactor in order to fix up the code. Now, the agent hides the hack, which skews devs’ judgment and results in less tech debt being cleaned up.

Gergely Orosz

232,004 次观看 • 4 个月前

The world of writing has changed forever. AI is getting really good, really fast. ChatGPT is already a better writer than most humans and some professional writers. So, what’s the future of writing? 18 thoughts from Tyler Cowen: 1) Don't let AI smooth out your idiosyncrasies. Let your writing stay weird and uniquely yours. 2) Generic content is dying and the burden is on you as the writer to be distinctive. 3) The more personal your writing becomes, the more future-proof it is. Nobody wants to read memoirs from AI, even if they're technically "better." 4) Use AI as your secondary literature when you read — not just for quick answers, but as a thinking companion. As Tyler puts it, "I'll keep on asking the AI: 'What do you think of chapter two? What happened there? What are some puzzles?' It just gets me thinking... and I'm smarter about the thing in the final analysis." 5) Hallucinations aren't the crisis everyone makes them out to be. No matter the source, if you're going to use a piece of information, you should double-check it. This is true for both books and AI. 6) Secrets will become more valuable in an AI-driven world. 7) One way to use AI as a writer is to research fields you aren't as familiar with before you start writing about them. Tyler said: "I just wrote a column about declassifying classified documents. I don't know that law very well. I asked the AI for a lot of background... now I feel like I'm not an idiot on the topic." 8) AI changes what books are even worth writing. "Predictive books and books about the near future. They don't make sense to write anymore." 9) Editing trick: Try running your writing through AI and asking what some people might find obnoxious. It’s a surprisingly powerful editing trick. 10) When prompting AI, put humans out of your mind and imagine you're talking to an alien or a non-human animal. 11) Many of the most significant AI advancements are likely happening behind closed doors. For example, I hear that Google allows employees to use Gemini with virtually unlimited context windows. 12) What possibilities do large context windows open up? Researchers will be able to load entire regulatory frameworks, historical archives, or massive datasets like "tax records from Renaissance Florence" into a single query. 13) The rate of AI improvement matters more than its current capabilities. As Tyler puts it, "This is the worst they will ever be" is key to understanding their trajectory. "A lot of people don't get that. They're impressed by what they see in the moment, but they don't understand the rate of improvement." 14) The best way to appreciate the current rate of improvement is to use the latest models. 15) Being non-technical can sometimes be an advantage when thinking about AI. Here’s Tyler: "If you're not focused on the technical side, you will see other things more clearly... You just focus on what is this actually good for? And not, am I impressed by all the neat bells and whistles on this advance with AI?" 16) How Tyler uses AI to prep for podcast interviews: Don't waste time asking AI for generic interview questions or broad topics. Tyler says that's the worst question you can ask an AI. It’s “too normy.” Instead, ask specific questions about historical examples and get context. Then, let your own creative questions emerge. 17) Your relationship with mentors and peers becomes more crucial, not less, in an AI world. "Two pieces of general advice with or without AI in the world." Tyler says: "Get more and better mentors and work every day at improving the quality of your peer network." 18) The divide between AI and humans creates a striking paradox. As Tyler puts it: "On one hand the AIs are getting so much better, so learn how to use the AIs. On the other hand, the AIs are getting so much better, so invest in these other things that aren't AI—pure networks. You've gotta do both." I've shared the full conversation with tylercowen below. In the replies, I've also linked to a full transcript and relevant links to YouTube, Spotify, and Apple Podcasts if you want to listen there. And if you want a bite-size entry to the episode, I've shared some clips in the replies too.
1:09:02

The world of writing has changed forever. AI is getting really good, really fast. ChatGPT is already a better writer than most humans and some professional writers. So, what’s the future of writing? 18 thoughts from Tyler Cowen: 1) Don't let AI smooth out your idiosyncrasies. Let your writing stay weird and uniquely yours. 2) Generic content is dying and the burden is on you as the writer to be distinctive. 3) The more personal your writing becomes, the more future-proof it is. Nobody wants to read memoirs from AI, even if they're technically "better." 4) Use AI as your secondary literature when you read — not just for quick answers, but as a thinking companion. As Tyler puts it, "I'll keep on asking the AI: 'What do you think of chapter two? What happened there? What are some puzzles?' It just gets me thinking... and I'm smarter about the thing in the final analysis." 5) Hallucinations aren't the crisis everyone makes them out to be. No matter the source, if you're going to use a piece of information, you should double-check it. This is true for both books and AI. 6) Secrets will become more valuable in an AI-driven world. 7) One way to use AI as a writer is to research fields you aren't as familiar with before you start writing about them. Tyler said: "I just wrote a column about declassifying classified documents. I don't know that law very well. I asked the AI for a lot of background... now I feel like I'm not an idiot on the topic." 8) AI changes what books are even worth writing. "Predictive books and books about the near future. They don't make sense to write anymore." 9) Editing trick: Try running your writing through AI and asking what some people might find obnoxious. It’s a surprisingly powerful editing trick. 10) When prompting AI, put humans out of your mind and imagine you're talking to an alien or a non-human animal. 11) Many of the most significant AI advancements are likely happening behind closed doors. For example, I hear that Google allows employees to use Gemini with virtually unlimited context windows. 12) What possibilities do large context windows open up? Researchers will be able to load entire regulatory frameworks, historical archives, or massive datasets like "tax records from Renaissance Florence" into a single query. 13) The rate of AI improvement matters more than its current capabilities. As Tyler puts it, "This is the worst they will ever be" is key to understanding their trajectory. "A lot of people don't get that. They're impressed by what they see in the moment, but they don't understand the rate of improvement." 14) The best way to appreciate the current rate of improvement is to use the latest models. 15) Being non-technical can sometimes be an advantage when thinking about AI. Here’s Tyler: "If you're not focused on the technical side, you will see other things more clearly... You just focus on what is this actually good for? And not, am I impressed by all the neat bells and whistles on this advance with AI?" 16) How Tyler uses AI to prep for podcast interviews: Don't waste time asking AI for generic interview questions or broad topics. Tyler says that's the worst question you can ask an AI. It’s “too normy.” Instead, ask specific questions about historical examples and get context. Then, let your own creative questions emerge. 17) Your relationship with mentors and peers becomes more crucial, not less, in an AI world. "Two pieces of general advice with or without AI in the world." Tyler says: "Get more and better mentors and work every day at improving the quality of your peer network." 18) The divide between AI and humans creates a striking paradox. As Tyler puts it: "On one hand the AIs are getting so much better, so learn how to use the AIs. On the other hand, the AIs are getting so much better, so invest in these other things that aren't AI—pure networks. You've gotta do both." I've shared the full conversation with tylercowen below. In the replies, I've also linked to a full transcript and relevant links to YouTube, Spotify, and Apple Podcasts if you want to listen there. And if you want a bite-size entry to the episode, I've shared some clips in the replies too.

David Perell

175,314 次观看 • 1 年前

Today we're announcing #GAIA1: a 9B parameter world model, trained on 4,700 hours of driving data, able to simulate complex and diverse driving scenes from video, text and action inputs. This model is 480x larger than the preview we shared earlier this year and the results are incredible. These videos are entirely synthetically generated by Wayve's generative AI, GAIA-1. But there is more here than just generating videos, GAIA is an entire world model. A world model allows us to simulate the future, conditioned on video, text and action inputs, which can be leveraged for making informed decisions when driving. Why is this game-changing for autonomous driving? 1. Safety. One limitation with AI systems like today's Large Language Models is that they are autoregressive, next-word prediction algorithms, but aren't necessarily aware of the implications of their decisions. A world model allows us to give our AI the capability to be aware of its decisions, by simulating the future, which is important for self-driving safety. 2. Synthetic training data. I believe synthetic training data is the future for AI, because it is safer, cheaper, and infinitely scalable. GAIA-1 unlocks unprecedented realism and diversity of synthetic data for self-driving. 3. Long-tail robustness. One of the biggest challenges for self-driving is long-tail robustness: dealing with the enormous magnitude of edge cases we see on the road. An advantage of generative AI is its incredible ability to recombine experiences in new ways. This is exciting for self-driving as it means we can learn from two edge case scenarios, and combine them to become a corner case. For example, we can experience driving in fog, and experience of jay-walking pedestrians, and GAIA can learn from these experiences to understand how to generate a fog+jay walking scenario. Check out many more videos in our blog or further technical details in our paper: Or come chat with our team who are at the International Conference on Computer Vision (#ICCV2023) this week in Paris in Booth 32 Jamie Shotton
0:41

Today we're announcing #GAIA1: a 9B parameter world model, trained on 4,700 hours of driving data, able to simulate complex and diverse driving scenes from video, text and action inputs. This model is 480x larger than the preview we shared earlier this year and the results are incredible. These videos are entirely synthetically generated by Wayve's generative AI, GAIA-1. But there is more here than just generating videos, GAIA is an entire world model. A world model allows us to simulate the future, conditioned on video, text and action inputs, which can be leveraged for making informed decisions when driving. Why is this game-changing for autonomous driving? 1. Safety. One limitation with AI systems like today's Large Language Models is that they are autoregressive, next-word prediction algorithms, but aren't necessarily aware of the implications of their decisions. A world model allows us to give our AI the capability to be aware of its decisions, by simulating the future, which is important for self-driving safety. 2. Synthetic training data. I believe synthetic training data is the future for AI, because it is safer, cheaper, and infinitely scalable. GAIA-1 unlocks unprecedented realism and diversity of synthetic data for self-driving. 3. Long-tail robustness. One of the biggest challenges for self-driving is long-tail robustness: dealing with the enormous magnitude of edge cases we see on the road. An advantage of generative AI is its incredible ability to recombine experiences in new ways. This is exciting for self-driving as it means we can learn from two edge case scenarios, and combine them to become a corner case. For example, we can experience driving in fog, and experience of jay-walking pedestrians, and GAIA can learn from these experiences to understand how to generate a fog+jay walking scenario. Check out many more videos in our blog or further technical details in our paper: Or come chat with our team who are at the International Conference on Computer Vision (#ICCV2023) this week in Paris in Booth 32 Jamie Shotton

Alex Kendall

631,917 次观看 • 3 年前

10 free github repos that can replace major SaaS with subscriptions. all free. open-sourced. some are MIT licensed. — 1️⃣ openscreen — replaces screen studio ($29/mo) - a clean macOS/windows/linux screen recorder for polished demos. - blur, cursor highlighting, annotations, export to mp4 or gif at any aspect ratio. - doesn't try to clone every feature, just nails the basics for quick walkthroughs you'd post on X. — 2️⃣ voicebox — replaces elevenlabs ($22/mo) + wisprflow ($15/mo) - local-first AI voice studio. - clone voices from 3 seconds of audio, generate speech across 7 TTS engines in 23 languages, - dictate into any text field with a global hotkey. - nothing leaves your machine. - runs on apple silicon, cuda, rocm. — 3️⃣ openshorts — replaces opus clip ($19/mo) + submagic ($16/mo) - free AI video platform. - clip generator turns long youtube videos into 9:16 shorts with auto-subtitles and face tracking (runs on free gemini + elevenlabs tiers). - also includes AI UGC video generation with actors — that part is pay-per-use via fal. ai (~$0.65-2 per video). docker self-host. — 4️⃣ freellmapi — replaces chatgpt pro + claude pro ($20/mo each) - stacks 14 free AI provider tiers (google, groq, cerebras, openrouter, github models + 9 more) behind one openai-compatible endpoint. ~800M tokens/month. - smart router with failover, sticky sessions, encrypted key storage. ships with a dashboard. — 5️⃣ playwright-mcp — replaces browserbase ($39/mo) + browser use ($25/mo) - microsoft's official MCP server that gives any AI agent full browser control. - uses accessibility trees, not screenshots — deterministic and token-efficient. - works with claude code, cursor, windsurf, codex out of the box. — 6️⃣ vibe-trading — replaces tradingview premium ($60/mo) - natural-language finance research agent. - 7 backtest engines across stocks, crypto, futures, forex. - 75 specialist skills (factor analysis, options strategy, ML strategy). - 29 multi-agent swarm presets. - 21 of 22 MCP tools work with zero API keys. — 7️⃣ CalCom — replaces calendly ($12/mo) + savvycal ($12/mo) - the open-source scheduling infrastructure. - one-on-ones, group events, round-robin, team booking, - payment collection (stripe), routing forms, workflows. - integrates with google/outlook/apple calendar, zoom, meet, teams. - self-host in 10 minutes with docker. 40k stars. — 8️⃣ whisper — replaces otter ($17/mo) - openAI's open-source speech-to-text model. - transcribe audio in 99 languages, translate to english, generate timestamps. - runs locally on cpu or gpu. - the actual model behind most "AI transcription" SaaS tools you're paying for. — 9️⃣ postiz — replaces buffer ($15/mo) - AI-powered social media scheduler. - cross-post to X, linkedin, instagram, tiktok, threads, bluesky, mastodon, youtube, pinterest. - AI captions and hashtags. - analytics dashboard. team workspaces. 31k stars and rising. — 🔟 vaultwarden — replaces 1password ($8/mo) - unofficial bitwarden-compatible server written in rust. - works with every official bitwarden client (mobile, desktop, browser). - unlimited users, unlimited vaults, full enterprise feature set. - runs on a $5 VPS or your home server. — disclaimer: open-source ≠ 1:1 replacement. you'll trade polish for ownership, hand-holding for control, and a credit card for a github version. for builders, prototypers, and indie hackers — that's the whole point. for everyone else, the paid tools still have their place. bookmark this. share with one friend bleeding subscription fees. ~m0h
0:31

10 free github repos that can replace major SaaS with subscriptions. all free. open-sourced. some are MIT licensed. — 1️⃣ openscreen — replaces screen studio ($29/mo) - a clean macOS/windows/linux screen recorder for polished demos. - blur, cursor highlighting, annotations, export to mp4 or gif at any aspect ratio. - doesn't try to clone every feature, just nails the basics for quick walkthroughs you'd post on X. — 2️⃣ voicebox — replaces elevenlabs ($22/mo) + wisprflow ($15/mo) - local-first AI voice studio. - clone voices from 3 seconds of audio, generate speech across 7 TTS engines in 23 languages, - dictate into any text field with a global hotkey. - nothing leaves your machine. - runs on apple silicon, cuda, rocm. — 3️⃣ openshorts — replaces opus clip ($19/mo) + submagic ($16/mo) - free AI video platform. - clip generator turns long youtube videos into 9:16 shorts with auto-subtitles and face tracking (runs on free gemini + elevenlabs tiers). - also includes AI UGC video generation with actors — that part is pay-per-use via fal. ai (~$0.65-2 per video). docker self-host. — 4️⃣ freellmapi — replaces chatgpt pro + claude pro ($20/mo each) - stacks 14 free AI provider tiers (google, groq, cerebras, openrouter, github models + 9 more) behind one openai-compatible endpoint. ~800M tokens/month. - smart router with failover, sticky sessions, encrypted key storage. ships with a dashboard. — 5️⃣ playwright-mcp — replaces browserbase ($39/mo) + browser use ($25/mo) - microsoft's official MCP server that gives any AI agent full browser control. - uses accessibility trees, not screenshots — deterministic and token-efficient. - works with claude code, cursor, windsurf, codex out of the box. — 6️⃣ vibe-trading — replaces tradingview premium ($60/mo) - natural-language finance research agent. - 7 backtest engines across stocks, crypto, futures, forex. - 75 specialist skills (factor analysis, options strategy, ML strategy). - 29 multi-agent swarm presets. - 21 of 22 MCP tools work with zero API keys. — 7️⃣ CalCom — replaces calendly ($12/mo) + savvycal ($12/mo) - the open-source scheduling infrastructure. - one-on-ones, group events, round-robin, team booking, - payment collection (stripe), routing forms, workflows. - integrates with google/outlook/apple calendar, zoom, meet, teams. - self-host in 10 minutes with docker. 40k stars. — 8️⃣ whisper — replaces otter ($17/mo) - openAI's open-source speech-to-text model. - transcribe audio in 99 languages, translate to english, generate timestamps. - runs locally on cpu or gpu. - the actual model behind most "AI transcription" SaaS tools you're paying for. — 9️⃣ postiz — replaces buffer ($15/mo) - AI-powered social media scheduler. - cross-post to X, linkedin, instagram, tiktok, threads, bluesky, mastodon, youtube, pinterest. - AI captions and hashtags. - analytics dashboard. team workspaces. 31k stars and rising. — 🔟 vaultwarden — replaces 1password ($8/mo) - unofficial bitwarden-compatible server written in rust. - works with every official bitwarden client (mobile, desktop, browser). - unlimited users, unlimited vaults, full enterprise feature set. - runs on a $5 VPS or your home server. — disclaimer: open-source ≠ 1:1 replacement. you'll trade polish for ownership, hand-holding for control, and a credit card for a github version. for builders, prototypers, and indie hackers — that's the whole point. for everyone else, the paid tools still have their place. bookmark this. share with one friend bleeding subscription fees. ~m0h

m0h

255,412 次观看 • 4 个月前

My full talk on the future of AI & media is up! I used Alex Imas's prompt of "What will be scarce?" to propose 4 ways that media is changing, and how writers can still win in the AI age: 1) Secrets > summaries Reporting is the act of taking private knowledge and making it public: when you get a source to tell you about corporate malfeasance, or venture to a remote town that few people have been to, or sneak your way into an underground party, you are working in a space where there is no training data. 2) Live interaction > static content We’re not far from a world where AI can replicate any prose style. But readers want to know there's a real person generating the text—not just the final presentation, but the proof of work behind it. For creators, doing live events, podcasts, and meetups reveal the life behind the voice. And if I care about my ideas, I want people to know about them, no matter the format. 3) Founders > bureaucracies AI is already allowing startups to run leaner by helping founders act as their own marketer, data scientist, engineer, etc. It's the same in media — AI is a boon to jacks-of-all-trades. There’s a lot of stuff AI does that I don't want to: verifying cites, reading contracts, negotiating speaking fees. It's an amazing time for independent creatives who want to direct their own vision. 4) Personal style > polish The house style in most newsrooms is extremely LLMable. What stands out (besides reporting) is a distinct and authentic first-person voice, even if that means the occasional typo / provocation / admitting "I'm not really sure." After all, trust isn't about the perfect sentence: it’s about the track record of who says it. And the stronger your brand, the more trusted you’ll be. I spend a lot of time covering the real disruptions AI brings. But I also believe, for those with the gumption to seize the opportunity, there's never been a better time to be a writer 🧡
14:40

My full talk on the future of AI & media is up! I used Alex Imas's prompt of "What will be scarce?" to propose 4 ways that media is changing, and how writers can still win in the AI age: 1) Secrets > summaries Reporting is the act of taking private knowledge and making it public: when you get a source to tell you about corporate malfeasance, or venture to a remote town that few people have been to, or sneak your way into an underground party, you are working in a space where there is no training data. 2) Live interaction > static content We’re not far from a world where AI can replicate any prose style. But readers want to know there's a real person generating the text—not just the final presentation, but the proof of work behind it. For creators, doing live events, podcasts, and meetups reveal the life behind the voice. And if I care about my ideas, I want people to know about them, no matter the format. 3) Founders > bureaucracies AI is already allowing startups to run leaner by helping founders act as their own marketer, data scientist, engineer, etc. It's the same in media — AI is a boon to jacks-of-all-trades. There’s a lot of stuff AI does that I don't want to: verifying cites, reading contracts, negotiating speaking fees. It's an amazing time for independent creatives who want to direct their own vision. 4) Personal style > polish The house style in most newsrooms is extremely LLMable. What stands out (besides reporting) is a distinct and authentic first-person voice, even if that means the occasional typo / provocation / admitting "I'm not really sure." After all, trust isn't about the perfect sentence: it’s about the track record of who says it. And the stronger your brand, the more trusted you’ll be. I spend a lot of time covering the real disruptions AI brings. But I also believe, for those with the gumption to seize the opportunity, there's never been a better time to be a writer 🧡

jasmine sun

58,503 次观看 • 4 个月前

🚨 New STEPN and STEPN GO in-game challenge just dropped: The Marathon Challenge 👟 This one is simple, yet kinda brutal. Here’s the deal: you lock in a fee, you move EVERY day, and you earn GGUSD from participants who didn’t make it! Join through either the STEPN GO main menu (just tap the Marathon icon) or the STEPN pop-up when you launch your app, then: 🔐 Lock 50 $GGUSD to activate your Marathon Subscription 👉 You can join from either STEPN or STEPN GO (or both), but your participation counts as one single entry total. 🎁 Earn weekly rewards for participating, or upgrade to the Season Pass for 20 GGUSD to unlock extra rewards! 🗓️ How it works: - Each season lasts 12 weeks, made of 6 rounds (2 weeks each). - If you miss a round, you can register for the next one before it starts. 🛎️ For Round 1, you must register before October 26 at 11:59 PM UTC. Once registration closes, Round 1 begins, no late entries. From there, your one job is to use 2 Energy every day in STEPN or STEPN GO. Simple right? ⚠️ To qualify, you need to complete 2 Energy in at least one app between 00:00 and 23:59 UTC each day. ✅ If you make it to the end: You keep your fee, auto-enroll in the next round (unless you hit “unlock”), and you get a cut of the pool from everyone who didn’t make it: straight to your wallet. ❌ If you miss a day: You’re out. Your fee goes into the prize pool. GGs. That’s it: just a fun challenge that rewards consistency 💪 The first round starts on October 27! Let’s see who can really stick with it!
0:23

🚨 New STEPN and STEPN GO in-game challenge just dropped: The Marathon Challenge 👟 This one is simple, yet kinda brutal. Here’s the deal: you lock in a fee, you move EVERY day, and you earn GGUSD from participants who didn’t make it! Join through either the STEPN GO main menu (just tap the Marathon icon) or the STEPN pop-up when you launch your app, then: 🔐 Lock 50 $GGUSD to activate your Marathon Subscription 👉 You can join from either STEPN or STEPN GO (or both), but your participation counts as one single entry total. 🎁 Earn weekly rewards for participating, or upgrade to the Season Pass for 20 GGUSD to unlock extra rewards! 🗓️ How it works: - Each season lasts 12 weeks, made of 6 rounds (2 weeks each). - If you miss a round, you can register for the next one before it starts. 🛎️ For Round 1, you must register before October 26 at 11:59 PM UTC. Once registration closes, Round 1 begins, no late entries. From there, your one job is to use 2 Energy every day in STEPN or STEPN GO. Simple right? ⚠️ To qualify, you need to complete 2 Energy in at least one app between 00:00 and 23:59 UTC each day. ✅ If you make it to the end: You keep your fee, auto-enroll in the next round (unless you hit “unlock”), and you get a cut of the pool from everyone who didn’t make it: straight to your wallet. ❌ If you miss a day: You’re out. Your fee goes into the prize pool. GGs. That’s it: just a fun challenge that rewards consistency 💪 The first round starts on October 27! Let’s see who can really stick with it!

STEPN

193,790 次观看 • 11 个月前

I vibe coded a new product on the side while running Every 🪨—and today we're launching it for free. It's called Proof, and it’s a live collaborative document editor where humans and AI agents work together in the same doc. It’s built from the ground up for the kinds of documents agents are increasingly writing: bug reports, PRDs, implementation plans, research briefs, copy audits, strategy docs, memos, and proposals. It's fast, free, and open source—available now at Why Proof? When everyone on your team is working with agents, there's suddenly a ton of AI-generated text flying around—planning docs, strategy memos, session recaps. But the current process for collaborating and iterating on agent-generated writing is…weirdly primitive. It mostly takes place in Markdown files on your laptop, which makes it reminiscent of document editing in 1999. That’s why we built Proof. What makes Proof different? - Proof is agent-native. Anything you can do in Proof, your agent can do just as easily. - Proof tracks provenance: A colored rail on the left side of every document tracks who wrote what. Green means human, Purple means AI. - Proof is login-free and open source: This is because we want Proof to be your agent's favorite document editor. How we use Proof Every 🪨: - Brandon Gell had OpenAI's Codex write a feature plan in Proof, then tagged my personal Claw (R2-C2) in Slack to review it. R2-C2 left feedback, I added comments, Brandon's agent revised the plan, and then Codex executed on it. Brandon submitted a PR to production without writing a line of code. - Austin Tedesco texts his Claw ideas while he's out on a run, then has it maintain a running Proof doc for his weekly food newsletter. He dictates drafts using Naveen Naidu's Monologue, writes into the outline himself, and uses the provenance gutter to track what's his voice vs. the agent's. - Kieran Klaassen uses it as a lightweight scratchpad for his compound engineering workflow. He brainstorms with an agent in the terminal, shares to Proof with one click, then opens the doc to leave comments and tells the agent to go work on them. His take: Proof's job is to communicate about writing and ideas. Proof is free, open source, and requires no login. I built the whole thing by vibe coding between meetings. I sat down with Brandon, Kieran, and Austin on Every 🪨's AI & I to demo it live and talk about how it's changing the way we work. If you're building with agents and need a better way to collaborate on text, this one's for you. Watch below! Timestamps Introduction and the origin story of Proof: 00:02:00 From Mac app to collaborative web editor: 00:07:24 What makes Proof "agent native": 00:09:00 Live demo—watching an agent join and write inside a shared document: 00:14:30 How Austin uses Proof for creative writing and food journalism: 00:20:51 The challenge of multiple agents editing one document simultaneously: 00:24:30 When AI-written docs are better read by agents than by humans: 00:26:48 Brandon's agent-to-agent collaboration loop: 00:29:30 Proof as a lightweight scratchpad versus existing tools like Notion and GitHub: 00:37:09 Why Proof is open source and what that means for builders: 00:42:18
44:37

I vibe coded a new product on the side while running Every 🪨—and today we're launching it for free. It's called Proof, and it’s a live collaborative document editor where humans and AI agents work together in the same doc. It’s built from the ground up for the kinds of documents agents are increasingly writing: bug reports, PRDs, implementation plans, research briefs, copy audits, strategy docs, memos, and proposals. It's fast, free, and open source—available now at Why Proof? When everyone on your team is working with agents, there's suddenly a ton of AI-generated text flying around—planning docs, strategy memos, session recaps. But the current process for collaborating and iterating on agent-generated writing is…weirdly primitive. It mostly takes place in Markdown files on your laptop, which makes it reminiscent of document editing in 1999. That’s why we built Proof. What makes Proof different? - Proof is agent-native. Anything you can do in Proof, your agent can do just as easily. - Proof tracks provenance: A colored rail on the left side of every document tracks who wrote what. Green means human, Purple means AI. - Proof is login-free and open source: This is because we want Proof to be your agent's favorite document editor. How we use Proof Every 🪨: - Brandon Gell had OpenAI's Codex write a feature plan in Proof, then tagged my personal Claw (R2-C2) in Slack to review it. R2-C2 left feedback, I added comments, Brandon's agent revised the plan, and then Codex executed on it. Brandon submitted a PR to production without writing a line of code. - Austin Tedesco texts his Claw ideas while he's out on a run, then has it maintain a running Proof doc for his weekly food newsletter. He dictates drafts using Naveen Naidu's Monologue, writes into the outline himself, and uses the provenance gutter to track what's his voice vs. the agent's. - Kieran Klaassen uses it as a lightweight scratchpad for his compound engineering workflow. He brainstorms with an agent in the terminal, shares to Proof with one click, then opens the doc to leave comments and tells the agent to go work on them. His take: Proof's job is to communicate about writing and ideas. Proof is free, open source, and requires no login. I built the whole thing by vibe coding between meetings. I sat down with Brandon, Kieran, and Austin on Every 🪨's AI & I to demo it live and talk about how it's changing the way we work. If you're building with agents and need a better way to collaborate on text, this one's for you. Watch below! Timestamps Introduction and the origin story of Proof: 00:02:00 From Mac app to collaborative web editor: 00:07:24 What makes Proof "agent native": 00:09:00 Live demo—watching an agent join and write inside a shared document: 00:14:30 How Austin uses Proof for creative writing and food journalism: 00:20:51 The challenge of multiple agents editing one document simultaneously: 00:24:30 When AI-written docs are better read by agents than by humans: 00:26:48 Brandon's agent-to-agent collaboration loop: 00:29:30 Proof as a lightweight scratchpad versus existing tools like Notion and GitHub: 00:37:09 Why Proof is open source and what that means for builders: 00:42:18

Dan Shipper 📧

33,092 次观看 • 7 个月前