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DeepSeek allegedly beat ChatGPT. So should we all switch? Here's a comparison for academics: 👇 The prompt: 🎯 I asked a fairly complicated question on how to analyze my data collection to gain novel ecological insights and for references to similar papers for each suggestion. Here are the results:... 1️⃣ Content: - DeepSeek provided deeper, shorter replies that I perceived as more creative. - ChatGPT played it safe and gave me slightly more obvious solutions 2️⃣ Hallucinations: - DeepSeek found 40+ search results and each cited paper had a link attached. No hallucinations. - ChatGPT hallucinated 2 out of 7 papers. 3️⃣ Speed: - DeepSeek (free version) was many times slower and often didn't reply due to server overload 4️⃣ Customizability: - ChatGPT's replies are much more customisable. By using "Custom Instructions" you can vary the length and include more or less formulae. 5️⃣ Length: - ChatGPT generally gave much longer and more detailed replies. 5️⃣ Guidance: - ChatGPT created a 4-step plan on using my data, which made sense but was quite vague on implementation topics. - DeepSeek gave me links to the coding packages I should be using, which was very helpful. 🤔 My 2 cents If you're a premium subscriber to ChatGPT, keep using it - the results are very similar and can be fine-tuned. Keep an eye out DeepSeek, as it is much more efficient (~10x cheaper under the hood), it might produce more impressive models later on.show more

Ilya Shabanov

27,668 subscribers

38,452 次观看 • 1 年前 •via X (Twitter)

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Ilya Shabanov 的头像

Ilya Shabanov1 年前

Join the Effortless Academic Newsletter. One deep-dive or tool review every week. Learn the newest AI trends, note-taking strategies and academic shortcuts:

SecBriefs | Making Cybersecurity Simple 的头像

SecBriefs | Making Cybersecurity Simple1 年前

🔍 From vulnerability assessment to exploitation, hacking follows a precise, predictable path. 🛤️ Knowledge is key to defense! 🛡️ Cybersecurity Dictionary for Everyone can help you understand every step of the process. Available on Amazon:

Iskander 的头像

Iskander1 年前

@JPablo_IA

SophieDel 的头像

SophieDel1 年前

I tried running four queries today using both DeepSeek and ChatGPT, kept getting “server overload” error when trying DS… ChatGPT was responsive and quick. I’m going to try tomorrow again to see how DS responds. Maybe it’s not as good as it sounds.

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Many people are flat wrong about DeepSeek. You might think everyone freaked out about DeepSeek because the model is really good—which it is—or because it was from China, which is also true. But there's a more subtle reason: DeepSeek showed they could achieve those results using reinforcement learning instead of supervised fine-tuning. In other words, they didn't need an expensive phase where a bunch of people tuned the model by answering questions. They were able to do all of this faster and cheaper using reinforcement fine-tuning. This is a huge deal! I recorded the attached video with the following goals in mind: 1. Explain how reinforcement fine-tuning works 2. Show you how you can fine-tune your own models 3. Walk you through a complete code example

Many people are flat wrong about DeepSeek. You might think everyone freaked out about DeepSeek because the model is really good—which it is—or because it was from China, which is also true. But there's a more subtle reason: DeepSeek showed they could achieve those results using reinforcement learning instead of supervised fine-tuning. In other words, they didn't need an expensive phase where a bunch of people tuned the model by answering questions. They were able to do all of this faster and cheaper using reinforcement fine-tuning. This is a huge deal! I recorded the attached video with the following goals in mind: 1. Explain how reinforcement fine-tuning works 2. Show you how you can fine-tune your own models 3. Walk you through a complete code example

Santiago

105,589 次观看 • 1 年前

The DeepSeek-R1 paper is a gem! Highly encourage everyone to read it. It's clear that LLM reasoning capabilities can be learned in different ways. RL, if applied correctly and at scale, can lead to some really powerful and interesting scaling and emergent properties. There is more to RL than meets the eye! Here is my breakdown of the paper along with a few tests: The multi-state training might not make sense initially but they provide clues on optimizations that we can continue to tap into. Data quality is still very important for enhancing the usability of the LLM. Unlike other reasoning LLMs, DeepSeek-R1's training recipe and weights are open so we can build on top of it. This opens up exciting research opportunities. About the attached clip: the previous preview model wasn't able to solve this task. DeepSeek-R1 can solve this and many other tasks that o1 can solve. It's a very good model for coding and math.

The DeepSeek-R1 paper is a gem! Highly encourage everyone to read it. It's clear that LLM reasoning capabilities can be learned in different ways. RL, if applied correctly and at scale, can lead to some really powerful and interesting scaling and emergent properties. There is more to RL than meets the eye! Here is my breakdown of the paper along with a few tests: The multi-state training might not make sense initially but they provide clues on optimizations that we can continue to tap into. Data quality is still very important for enhancing the usability of the LLM. Unlike other reasoning LLMs, DeepSeek-R1's training recipe and weights are open so we can build on top of it. This opens up exciting research opportunities. About the attached clip: the previous preview model wasn't able to solve this task. DeepSeek-R1 can solve this and many other tasks that o1 can solve. It's a very good model for coding and math.

elvis

140,692 次观看 • 1 年前

$GOOGL CEO Sundar Pichai on why Google didn't ship ChatGPT first, and the signal they missed from OpenAI: We even conceived the product, it was Lambda. There was an engineer inside who thought it was sentient. Think of it as an early version of ChatGPT. In the multiverse, Google probably shipped that 9 months earlier... but the version I saw was a lot more toxic at a level we couldn't have possibly put it out. As a company with this search quality bias, we had a higher bar for what we thought was acceptable product quality. I think they were lucky to also see it on the coding side with GitHub. Maybe there was a signal we were missing. The jumps between GPT-2 and 3 and later 4 were more pronounced if you were using it for coding.

$GOOGL CEO Sundar Pichai on why Google didn't ship ChatGPT first, and the signal they missed from OpenAI: We even conceived the product, it was Lambda. There was an engineer inside who thought it was sentient. Think of it as an early version of ChatGPT. In the multiverse, Google probably shipped that 9 months earlier... but the version I saw was a lot more toxic at a level we couldn't have possibly put it out. As a company with this search quality bias, we had a higher bar for what we thought was acceptable product quality. I think they were lucky to also see it on the coding side with GitHub. Maybe there was a signal we were missing. The jumps between GPT-2 and 3 and later 4 were more pronounced if you were using it for coding.

Wall St Engine

150,582 次观看 • 3 个月前

Start going much deeper and much more nuanced in your “prompts” with your 🤖 apps - too many still use ChatGPT like it’s Google search.. when it has much more power than that and can give you much more in depth answers and more importantly can be a working partner versus a quick tool .. hope this inspires more to use their voice - I think voice will be the main interface with ai 🤖 in the next decade & I hope this inspires someone to ask much more detailed questions and go much deeper with their details and nuances! What’s the longest prompt you’ve made so far ? What are u using these apps for so far?

Start going much deeper and much more nuanced in your “prompts” with your 🤖 apps - too many still use ChatGPT like it’s Google search.. when it has much more power than that and can give you much more in depth answers and more importantly can be a working partner versus a quick tool .. hope this inspires more to use their voice - I think voice will be the main interface with ai 🤖 in the next decade & I hope this inspires someone to ask much more detailed questions and go much deeper with their details and nuances! What’s the longest prompt you’ve made so far ? What are u using these apps for so far?

Gary Vaynerchuk

65,111 次观看 • 9 个月前

My SEO Backlink Strategy to Rank on ChatGPT: (How I'm building links from pages that ChatGPT is referencing in answers) When you query on ChatGPT & LLMs, it references resources online then creates an answer. For example: "What are the best eCommerce accounting services?" ChatGPT scours its "sources" & determines what is the best possible answer. Its "sources" are best of lists, review sites, domain authority, and domain content. When your brand is mentioned in more of these "sources", the more ChatGPT mentions you get. Here's my process: Step #1: Analyze Domain in Writesonic - Go to GEO --> Enter your domain --> Follow prompts --> Wait for results - This gives you a full breakdown of visibility, citations, queries, etc. - A full scope overview of how you're performing on ChatGPT & LLMs Step #2: Citation Opportunities - Scroll down to "Page-level citation opportunities" - This gives you a full list of pages ChatGPT is citing in queries relevant to your brand where you're NOT mentioned yet - These are backlinks you should be aiming to get. Step #3: Build Backlinks - Build a spreadsheet to track ALL of these backlink opp's - Research & find the website owner's name, email, & LinkedIn - Reach out pitching why your company should be included - Follow up until you've landed the backlink Step #4: Review, Analyze, & Adjust - ChatGPT & LLMs are evolving at a rapid pace - Check back on data in Writesonic every 1-2 weeks - Find new backlink opp's, add them to your list, and outreach - Do this on repeat until you're mentioned everywhere --- Is this helpful? ♻️ REPOST if you think so & want more like it. P.S. Want data like this? Check out Writesonic today & test it on your own website.

Connor Gillivan

11,967 次观看 • 11 个月前

What's the Big Deal with DeepSeek in AI? Here's why DeepSeek is making everyone take notice: 1. Super Smart on a Budget: DeepSeek showed you can make awesome AI without breaking the bank. Their latest model, DeepSeek-V3, was trained for only about $10 million, which is a lot less than the usual big bucks spent on AI, like the rumored $78 million for some of OpenAI's models. They did this in just two months with fewer fancy computers. 2. Open for Everyone: DeepSeek isn't keeping their tech a secret. They've made it open-source, meaning anyone can use, tweak, and learn from it. It's like they're saying, "Come join the party!" 3. Beating the Big Names: DeepSeek-V3 has done better than some top dogs from companies like OpenAI and Google in solving puzzles, math, and coding. This proves you can get great AI results without spending a fortune. 4. Challenging NVIDIA: NVIDIA's chips are usually the choice for AI because they're really powerful. But since DeepSeek did so well with less expensive chips, it might make people think twice about always going for NVIDIA's priciest options. 5. The DeepSeek Crew: The team at DeepSeek is young and smart, mostly from top Chinese schools, with brains in physics, math, and computer science. They learned AI in about six months by themselves! They use first principle thinking, which means they break down problems to the basics and build from there. This has helped them come up with cool new ways to do AI. 6. Changing AI for Good: DeepSeek is showing that AI can be cheaper and more open to everyone. They're changing how we think AI should be made and shared, which could shake up the whole AI world. So, as we watch DeepSeek, it's clear they're not just another player; they're changing the rules of the game. I predicted that this would be a make or break year for all the massive investments made in AI by American VC's. A few weeks later, DeepSeek happens! Watch the rest of my predictions in my 2025 outlook video . Link in replies #AIInnovation #DeepSeek #NVIDIA #OpenAI #TechDisruption

What's the Big Deal with DeepSeek in AI? Here's why DeepSeek is making everyone take notice: 1. Super Smart on a Budget: DeepSeek showed you can make awesome AI without breaking the bank. Their latest model, DeepSeek-V3, was trained for only about $10 million, which is a lot less than the usual big bucks spent on AI, like the rumored $78 million for some of OpenAI's models. They did this in just two months with fewer fancy computers. 2. Open for Everyone: DeepSeek isn't keeping their tech a secret. They've made it open-source, meaning anyone can use, tweak, and learn from it. It's like they're saying, "Come join the party!" 3. Beating the Big Names: DeepSeek-V3 has done better than some top dogs from companies like OpenAI and Google in solving puzzles, math, and coding. This proves you can get great AI results without spending a fortune. 4. Challenging NVIDIA: NVIDIA's chips are usually the choice for AI because they're really powerful. But since DeepSeek did so well with less expensive chips, it might make people think twice about always going for NVIDIA's priciest options. 5. The DeepSeek Crew: The team at DeepSeek is young and smart, mostly from top Chinese schools, with brains in physics, math, and computer science. They learned AI in about six months by themselves! They use first principle thinking, which means they break down problems to the basics and build from there. This has helped them come up with cool new ways to do AI. 6. Changing AI for Good: DeepSeek is showing that AI can be cheaper and more open to everyone. They're changing how we think AI should be made and shared, which could shake up the whole AI world. So, as we watch DeepSeek, it's clear they're not just another player; they're changing the rules of the game. I predicted that this would be a make or break year for all the massive investments made in AI by American VC's. A few weeks later, DeepSeek happens! Watch the rest of my predictions in my 2025 outlook video . Link in replies #AIInnovation #DeepSeek #NVIDIA #OpenAI #TechDisruption

Dr Ola Brown

83,460 次观看 • 1 年前

🚨 Breaking the Hype 🚨 Since #DeepSeek is all the rage, I decided to test what the fuss is about. And guess what? I “broke” it on my first try! 🤯 Here’s the simple prompt that sent DeepSeek into an endless logic loop, I had to manually cancel the reasoning loop 💬 If a train leaves New York at 2 PM traveling 60 mph and another train leaves Los Angeles at 3 PM traveling 70 mph, when do they meet? Looks like DeepSeek needs more 🚧 work on reasoning! 🚧 In comparison #ChatGPT (OpenAI) didn’t break a sweat. I didnt check the math but the reasoning is very simple and plausible. Anyone else trying to push its limits? Let’s share! #AI #PromptEngineering #TechFun

🚨 Breaking the Hype 🚨 Since #DeepSeek is all the rage, I decided to test what the fuss is about. And guess what? I “broke” it on my first try! 🤯 Here’s the simple prompt that sent DeepSeek into an endless logic loop, I had to manually cancel the reasoning loop 💬 If a train leaves New York at 2 PM traveling 60 mph and another train leaves Los Angeles at 3 PM traveling 70 mph, when do they meet? Looks like DeepSeek needs more 🚧 work on reasoning! 🚧 In comparison #ChatGPT (OpenAI) didn’t break a sweat. I didnt check the math but the reasoning is very simple and plausible. Anyone else trying to push its limits? Let’s share! #AI #PromptEngineering #TechFun

Dreams of Mars 🕊❤️🚀🌕

100,806 次观看 • 1 年前

Using ChatGPT as your personal translator With a simple base instruction like the one below. I can have ChatGPT endlessly speak more or less any language. Prompt: “You are now my personal translator and everything i say you should respond to in [Language] just the way that i said it. Have you understood your task?” ChatGPT with voice is amazing so far. There are so many use-cases for something like this. In the 48h I have had access, I’ve had well over 50 conversations. Ranging from coming up with activities for the kids, to the meaning of life. Using it as a translator is something I stumbled upon when exploring its language capabilities. What have you used it for?

Using ChatGPT as your personal translator With a simple base instruction like the one below. I can have ChatGPT endlessly speak more or less any language. Prompt: “You are now my personal translator and everything i say you should respond to in [Language] just the way that i said it. Have you understood your task?” ChatGPT with voice is amazing so far. There are so many use-cases for something like this. In the 48h I have had access, I’ve had well over 50 conversations. Ranging from coming up with activities for the kids, to the meaning of life. Using it as a translator is something I stumbled upon when exploring its language capabilities. What have you used it for?

Linus ✦ Ekenstam

268,879 次观看 • 2 年前

Anne-Laure Le Cunff (Anne-Laure Le Cunff) might be the most productive person I’ve ever met. She’s simultaneously running a successful business, writing a book being published by a major publisher, and getting a PhD in neuroscience. She says it’s only possible because of ChatGPT. It saves her time on the administrative tasks required to run her business. It helps her create better outlines so that she can write pieces more efficiently. It even breaks down complex research papers so that she can incorporate them into her PhD work. We spent an hour and a half exploring in-detail every part of her ChatGPT workflow—and we even used it live to help her fine-tune her meditation practice. We get into: - How ChatGPT saves her time running her business - Tips to break down research papers into digestible insights - How she leverages ChatGPT to revamp her YouTube thumbnails - Using ChatGPT to write original articles - Doing deep online research using ChatGPT - How to use ChatGPT to generate advice tailored for your needs - How to surface useful insights from your journal using ChatGPT This is a must-watch for curious, creative people who want to get more done. Watch below! ---- Timestamps: Introduction 01:10 How to use ChatGPT to save time running a business 02:11 Tips to breakdown research papers with ChatGPT 05:17 How to use ChatGPT to generate explanations tailored for you 09:38 Leveraging ChatGPT to find hidden gems on the internet (like recipes for obscure cheese) 19:51 How to create awesome YouTube thumbnails with ChatGPT 33:47 Incorporating ChatGPT into your writing process 51:13 Rapid fire questions from X 56:52 Surfacing useful insights from Anne-Laure’s meditation journal 1:13:01 The case for journaling in the age of AI 1:29:04

Anne-Laure Le Cunff (Anne-Laure Le Cunff) might be the most productive person I’ve ever met. She’s simultaneously running a successful business, writing a book being published by a major publisher, and getting a PhD in neuroscience. She says it’s only possible because of ChatGPT. It saves her time on the administrative tasks required to run her business. It helps her create better outlines so that she can write pieces more efficiently. It even breaks down complex research papers so that she can incorporate them into her PhD work. We spent an hour and a half exploring in-detail every part of her ChatGPT workflow—and we even used it live to help her fine-tune her meditation practice. We get into: - How ChatGPT saves her time running her business - Tips to break down research papers into digestible insights - How she leverages ChatGPT to revamp her YouTube thumbnails - Using ChatGPT to write original articles - Doing deep online research using ChatGPT - How to use ChatGPT to generate advice tailored for your needs - How to surface useful insights from your journal using ChatGPT This is a must-watch for curious, creative people who want to get more done. Watch below! ---- Timestamps: Introduction 01:10 How to use ChatGPT to save time running a business 02:11 Tips to breakdown research papers with ChatGPT 05:17 How to use ChatGPT to generate explanations tailored for you 09:38 Leveraging ChatGPT to find hidden gems on the internet (like recipes for obscure cheese) 19:51 How to create awesome YouTube thumbnails with ChatGPT 33:47 Incorporating ChatGPT into your writing process 51:13 Rapid fire questions from X 56:52 Surfacing useful insights from Anne-Laure’s meditation journal 1:13:01 The case for journaling in the age of AI 1:29:04

Dan Shipper 📧

72,623 次观看 • 2 年前

U.S. Navy Bans DeepSeek Over 'Security Concerns' As 'Substantial' Evidence Emerges Chinese AI Ripped Off ChatGPT | ZeroHedge The U.S. Navy has instructed service members to avoid using the Chinese AI platform DeepSeek, citing "potential security and ethical concerns," according to CNBC. An email sent to "shipmates" in recent days, confirmed by CNBC on Tuesday, referenced the Navy's AI policy and emphasized the importance of refraining from using DeepSeek. The memo warned service members against using the platform "for any work-related tasks or personal use" and instructed them to "avoid downloading, installing, or using the DeepSeek model in any capacity." The warning follows the recent rise of DeepSeek’s R1 model, which has garnered significant attention worldwide, particularly within the U.S. business and technology sectors. The R1 model has demonstrated capabilities comparable to OpenAI’s models. In December, DeepSeek claimed it had successfully trained a large language model in just two months at a cost of $6 million—a figure disputed by technologists—despite U.S. restrictions on semiconductor chip exports to China. The R1, an open-source model, surged to the top of Apple’s app store rankings this week, triggering a market sell-off. Shares of AI chipmakers Nvidia and Broadcom plummeted by 17% on Monday, wiping out a combined $800 billion in market value. Nvidia has since recovered some of its losses. On Monday, DeepSeek announced a temporary restriction on user registrations, citing "large-scale malicious attacks" on its services, before later restoring normal operations. DeepSeek’s advancements have challenged the long-held belief that the U.S. was significantly ahead of China in AI development. Asked how R1 caught up to ChatGPT, AI and Crypto Czar David Sacks suggested that DeepSeek may have leveraged a technique known as "distillation" to train its model using OpenAI’s technology. “There’s a technique in AI called distillation, which you’re going to hear a lot about. It’s when one model learns from another model,” Sacks explained to Fox News. “Effectively, the student model asks the parent model millions of questions, mimicking the reasoning process and absorbing knowledge.” “They can essentially extract the knowledge out of the model,” he continued. “There’s substantial evidence that what DeepSeek did here was distill knowledge from OpenAI’s models.” “I don’t think OpenAI is too happy about this,” Sacks added. President Donald Trump has said that DeepSeek “should be a wake-up call” for U.S. tech companies. “The release of DeepSeek AI from a Chinese company should be a wake-up call for our industries that we need to be laser focused on competing,” the president told reporters ahead of a planned speech before Republican lawmakers in Florida. Read more:

U.S. Navy Bans DeepSeek Over 'Security Concerns' As 'Substantial' Evidence Emerges Chinese AI Ripped Off ChatGPT | ZeroHedge The U.S. Navy has instructed service members to avoid using the Chinese AI platform DeepSeek, citing "potential security and ethical concerns," according to CNBC. An email sent to "shipmates" in recent days, confirmed by CNBC on Tuesday, referenced the Navy's AI policy and emphasized the importance of refraining from using DeepSeek. The memo warned service members against using the platform "for any work-related tasks or personal use" and instructed them to "avoid downloading, installing, or using the DeepSeek model in any capacity." The warning follows the recent rise of DeepSeek’s R1 model, which has garnered significant attention worldwide, particularly within the U.S. business and technology sectors. The R1 model has demonstrated capabilities comparable to OpenAI’s models. In December, DeepSeek claimed it had successfully trained a large language model in just two months at a cost of $6 million—a figure disputed by technologists—despite U.S. restrictions on semiconductor chip exports to China. The R1, an open-source model, surged to the top of Apple’s app store rankings this week, triggering a market sell-off. Shares of AI chipmakers Nvidia and Broadcom plummeted by 17% on Monday, wiping out a combined $800 billion in market value. Nvidia has since recovered some of its losses. On Monday, DeepSeek announced a temporary restriction on user registrations, citing "large-scale malicious attacks" on its services, before later restoring normal operations. DeepSeek’s advancements have challenged the long-held belief that the U.S. was significantly ahead of China in AI development. Asked how R1 caught up to ChatGPT, AI and Crypto Czar David Sacks suggested that DeepSeek may have leveraged a technique known as "distillation" to train its model using OpenAI’s technology. “There’s a technique in AI called distillation, which you’re going to hear a lot about. It’s when one model learns from another model,” Sacks explained to Fox News. “Effectively, the student model asks the parent model millions of questions, mimicking the reasoning process and absorbing knowledge.” “They can essentially extract the knowledge out of the model,” he continued. “There’s substantial evidence that what DeepSeek did here was distill knowledge from OpenAI’s models.” “I don’t think OpenAI is too happy about this,” Sacks added. President Donald Trump has said that DeepSeek “should be a wake-up call” for U.S. tech companies. “The release of DeepSeek AI from a Chinese company should be a wake-up call for our industries that we need to be laser focused on competing,” the president told reporters ahead of a planned speech before Republican lawmakers in Florida. Read more:

Owen Gregorian

75,351 次观看 • 1 年前

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai

Martin Nebelong

48,259 次观看 • 2 年前

THIS SHOULD BE ILLEGAL I just did a sales roleplay with Ai and told it to act like a Type A personality asking repeatedly for the price 😂 one of the worst people to deal with when selling you can do this with ChatGPT and save $5K to $10K on sales programs tell it you're using the NEPQ sales strategy or Gap or whatever strategy you use and have it give you feedback after the call no more roleplaying and holding back because you're scared to embarrass yourself as a beginner watch how I navigate this Ai sales call, and save this tweet for later so you can remember to do the same follow me for more content like this

THIS SHOULD BE ILLEGAL I just did a sales roleplay with Ai and told it to act like a Type A personality asking repeatedly for the price 😂 one of the worst people to deal with when selling you can do this with ChatGPT and save $5K to $10K on sales programs tell it you're using the NEPQ sales strategy or Gap or whatever strategy you use and have it give you feedback after the call no more roleplaying and holding back because you're scared to embarrass yourself as a beginner watch how I navigate this Ai sales call, and save this tweet for later so you can remember to do the same follow me for more content like this

Joseph Henry

12,274 次观看 • 1 年前

I have been testing “OpenAI” o3 mini-high. The exposure of the “reasoning” on this model in my tests seem to not be the full reasoning, but a shifted and edited and tunicated version of what we would expect from a full exposure of the reasoning engine. See the video on the left. One can compare this to my FREE Open Source local newly quantized and distilled DeepSeek R1 8b (llama). See the video on the right. Clearly we see the full reading with DeepSeek R1 and something well tunicates with o3 mini-high (getting mad typing that name folks). Compare the quality of the outputs and the reasoning insights. Frankly there is no comparison. It feels like “OpenAI” begrudgingly released the reasoning output because they had to, but gave us something of a simulated reasoning and not the actual one. Of course my local lap top running an 8b model is slower, but all of the outputs and the actual creative writing is superior on the FREE model. The reasoning output, when legitimate can be many times more valuable than the answer. In the past week I have found thousands of ways to use in in many projects. Thus far I would have been far more impressed with o3 mini if I have never seen DeepSeek. However today it is too little—too late. The prompt: “Write a very creative and funny story on a pig and butterfly as friends living on Mars.”

I have been testing “OpenAI” o3 mini-high. The exposure of the “reasoning” on this model in my tests seem to not be the full reasoning, but a shifted and edited and tunicated version of what we would expect from a full exposure of the reasoning engine. See the video on the left. One can compare this to my FREE Open Source local newly quantized and distilled DeepSeek R1 8b (llama). See the video on the right. Clearly we see the full reading with DeepSeek R1 and something well tunicates with o3 mini-high (getting mad typing that name folks). Compare the quality of the outputs and the reasoning insights. Frankly there is no comparison. It feels like “OpenAI” begrudgingly released the reasoning output because they had to, but gave us something of a simulated reasoning and not the actual one. Of course my local lap top running an 8b model is slower, but all of the outputs and the actual creative writing is superior on the FREE model. The reasoning output, when legitimate can be many times more valuable than the answer. In the past week I have found thousands of ways to use in in many projects. Thus far I would have been far more impressed with o3 mini if I have never seen DeepSeek. However today it is too little—too late. The prompt: “Write a very creative and funny story on a pig and butterfly as friends living on Mars.”

Brian Roemmele

74,506 次观看 • 1 年前

Why am I not even surprised by this, I’m afraid if more and teachers have this epiphany then we won’t have any left to teach our kids. This woman used to be a teacher with a master’s degree. I can’t imagine devoting that much time and money to a profession only to find out I could make more just working a normal job. I think more and more that higher education is possibly turning into a scam. Growing up I was always told to focus on school, get an education and I will soar. Not too long after that I found out that wasn’t the case. I don’t even use my degree at all, I got it because I was told by my parents I had to. I worked two jobs while in school so I could graduate without debt, only to put it on the wall and forget about it. I later on went the family business route anyways as I always planned on doing. I feel I was pressured and sold a pipe dream that a degree would be the answer to anything financial for me, that it would unlock possibilities. For me, it closed many doors, many employers saw me as being overqualified. The turning point for me was when I used to go to a hotel with co-workers after work and I got to know my server. Turned out he had a degree in a similar field to mine and he was waiting on tables and in massive student debt because of it. I can tell the college dream turned into a nightmare for him. To spend thousands and not be able to use it to recoup my money would make me feel like the biggest fool around. I felt like if anyone came by to sell me magic beans, I would have a beanstalk in my yard. While not using my degree worked for me, there are so many more others that can’t say the same.

Why am I not even surprised by this, I’m afraid if more and teachers have this epiphany then we won’t have any left to teach our kids. This woman used to be a teacher with a master’s degree. I can’t imagine devoting that much time and money to a profession only to find out I could make more just working a normal job. I think more and more that higher education is possibly turning into a scam. Growing up I was always told to focus on school, get an education and I will soar. Not too long after that I found out that wasn’t the case. I don’t even use my degree at all, I got it because I was told by my parents I had to. I worked two jobs while in school so I could graduate without debt, only to put it on the wall and forget about it. I later on went the family business route anyways as I always planned on doing. I feel I was pressured and sold a pipe dream that a degree would be the answer to anything financial for me, that it would unlock possibilities. For me, it closed many doors, many employers saw me as being overqualified. The turning point for me was when I used to go to a hotel with co-workers after work and I got to know my server. Turned out he had a degree in a similar field to mine and he was waiting on tables and in massive student debt because of it. I can tell the college dream turned into a nightmare for him. To spend thousands and not be able to use it to recoup my money would make me feel like the biggest fool around. I felt like if anyone came by to sell me magic beans, I would have a beanstalk in my yard. While not using my degree worked for me, there are so many more others that can’t say the same.

SonnyBoy🇺🇸

339,112 次观看 • 2 个月前

For the first time we are fundamentally changing how humans can collaborate with ChatGPT since it launched two years ago. We’re introducing canvas, a new interface for working with ChatGPT on writing and coding projects that go beyond simple chat. Product and model features: 1/ Ask for in-line feedback. With canvas, ChatGPT can better understand the context of what you’re trying to accomplish. You can highlight specific sections to indicate exactly what you want ChatGPT to focus on. Like a copy editor or code reviewer, it can give in-line feedback and suggestions with the entire project in mind. 2/ Directly edit the model's output and select a specific area for targeted editing. You control your creative work on canvas. You can directly edit text or code. 3/ Menu of shortcuts. There’s a menu of shortcuts for you to ask ChatGPT to adjust writing length, debug your code, and quickly perform other useful actions. You can also restore previous versions of your work by using the back button in canvas. 4/ Use search with canvas for research writing! As we are moving towards the new paradigm of reasoning we are fundamentally evolving the chat interface into a more collaborative human-AI interaction. Today you can say “browse / use browsing to find XYZ on the internet and write a report in canvas”

For the first time we are fundamentally changing how humans can collaborate with ChatGPT since it launched two years ago. We’re introducing canvas, a new interface for working with ChatGPT on writing and coding projects that go beyond simple chat. Product and model features: 1/ Ask for in-line feedback. With canvas, ChatGPT can better understand the context of what you’re trying to accomplish. You can highlight specific sections to indicate exactly what you want ChatGPT to focus on. Like a copy editor or code reviewer, it can give in-line feedback and suggestions with the entire project in mind. 2/ Directly edit the model's output and select a specific area for targeted editing. You control your creative work on canvas. You can directly edit text or code. 3/ Menu of shortcuts. There’s a menu of shortcuts for you to ask ChatGPT to adjust writing length, debug your code, and quickly perform other useful actions. You can also restore previous versions of your work by using the back button in canvas. 4/ Use search with canvas for research writing! As we are moving towards the new paradigm of reasoning we are fundamentally evolving the chat interface into a more collaborative human-AI interaction. Today you can say “browse / use browsing to find XYZ on the internet and write a report in canvas”

Karina

845,627 次观看 • 1 年前

I'm running Llama 4 Maverick at 620 t/s! I'm living in the future! Honestly, a large language model running this fast is something straight out of a sci-fi movie. Speeds like this will enable a whole new world of applications that aren't possible today. For reference, GPT-4o, which is probably the most popular OpenAI model, runs between 60 and 110 t/s. The secret here: I'm not running AI at Meta's Llama 4 Maverick on a GPU. I'm using the SambaNova Cloud (my sponsor) and their custom SN40L chips. They are optimized from the ground up for running AI workflows. Right now, SambaNova Cloud runs DeepSeek, Qwen, Whisper, and the entire family of Llama models on these chips. You can check the speed of each of these models using SambaNova Cloud's Playground (see the attached video). It's completely free, and that's how I'm measuring their speeds. For example, I also tried DeepSeek R1 (the latest version from May) and, oh boy! DeepSeek R1 is a huge 671B parameter model. It's probably the best open reasoning model in the world, and it runs at 140 tokens per second! !!! Inference time on an SN40L is night and day from what you'll get from a GPU. Here is why this is big: If you are running an agentic workflow that uses multiple models simultaneously on a GPU, it will need to swap models in and out of memory (because not every model fits). A single SNL40 chip can simultaneously hold over 100 models (trillions of parameters) in memory. If you are using open models, try the SambaCloud API to see what lightning speed looks like. Here is how: 1. Create a free account at: 2. Check the QuickStart guide: If you try the playground, check the speed you're getting with Llama 4 and DeepSeek, and post the results below. I've seen much higher numbers than I posted here, so I'm curious to see whether geography affects the speed.

I'm running Llama 4 Maverick at 620 t/s! I'm living in the future! Honestly, a large language model running this fast is something straight out of a sci-fi movie. Speeds like this will enable a whole new world of applications that aren't possible today. For reference, GPT-4o, which is probably the most popular OpenAI model, runs between 60 and 110 t/s. The secret here: I'm not running AI at Meta's Llama 4 Maverick on a GPU. I'm using the SambaNova Cloud (my sponsor) and their custom SN40L chips. They are optimized from the ground up for running AI workflows. Right now, SambaNova Cloud runs DeepSeek, Qwen, Whisper, and the entire family of Llama models on these chips. You can check the speed of each of these models using SambaNova Cloud's Playground (see the attached video). It's completely free, and that's how I'm measuring their speeds. For example, I also tried DeepSeek R1 (the latest version from May) and, oh boy! DeepSeek R1 is a huge 671B parameter model. It's probably the best open reasoning model in the world, and it runs at 140 tokens per second! !!! Inference time on an SN40L is night and day from what you'll get from a GPU. Here is why this is big: If you are running an agentic workflow that uses multiple models simultaneously on a GPU, it will need to swap models in and out of memory (because not every model fits). A single SNL40 chip can simultaneously hold over 100 models (trillions of parameters) in memory. If you are using open models, try the SambaCloud API to see what lightning speed looks like. Here is how: 1. Create a free account at: 2. Check the QuickStart guide: If you try the playground, check the speed you're getting with Llama 4 and DeepSeek, and post the results below. I've seen much higher numbers than I posted here, so I'm curious to see whether geography affects the speed.

Santiago

34,148 次观看 • 1 年前

Introducing: How Do You Use ChatGPT? 🚀 It's a weekly show where I interview the most interesting people in the world about how they use ChatGPT in their work and their lives—and show you every detail. The first episode is with Sahil Lavingia, CEO of Gumroad and Flexile. It's not theoretical: we screen-share through his actual prompts and responses, so you can see how ChatGPT helps him perform better at work and improve his life—one conversation at a time. We talk about how he's using ChatGPT to: Buy a building. He wants to buy a New York City hangout for Gumroad employees and customers, so he asked ChatGPT to research the history of real estate in NYC, suggest which neighborhoods might be best to target, generate questions for brokers, and even detail what the design of a particular property might look like. Write tweets. Sahil is a prolific Twitter/X user. He often uses ChatGPT to help him flesh out an idea. He says, “I [start] with a tweet, which is like a thesis, and then I just say, ‘Add three to four paragraphs to make the point compelling—also suggest more examples.’” We explore his precise process for using ChatGPT to help him brainstorm short tweets and longer essays in this episode. Pressure-test ideas. For Sahil, ChatGPT is like upgrading his peripheral vision. It lets him see around the corners, ask better questions of himself and other people, and avoid poor decisions. He told me, “I think a lot of people sort of delude themselves into thinking they have [good ideas]… I think that one of the most useful things about [ChatGPT] is it focuses your research on what actually matters.” It’s the ultimate tool to help him think better. Also in this episode: how ChatGPT could have helped Sahil save $70 million, how he thinks it will improve the most-talented creatives, and why he thinks—in the age of AI—people have no excuse for not knowing the answer to something anymore. Watch below! ---- Timestamps Intro 0:33 There’s no more excuse for not knowing anymore 2:00 He doesn’t spend as much time on bad ideas 2:50 How ChatGPT will make the top 1% of creative output better 6:15 How it turbocharges research 8:20 How he’s using ChatGPT to buy a building 11:00 How he uses ChatGPT to pressure-test ideas 17:43 How he uses DALL-E to help with interior design 20:50 How ChatGPT could have saved him $70 million 26:00 How he uses ChatGPT in his decision-making 29:50 How he uses ChatGPT for writing 38:00

Introducing: How Do You Use ChatGPT? 🚀 It's a weekly show where I interview the most interesting people in the world about how they use ChatGPT in their work and their lives—and show you every detail. The first episode is with Sahil Lavingia, CEO of Gumroad and Flexile. It's not theoretical: we screen-share through his actual prompts and responses, so you can see how ChatGPT helps him perform better at work and improve his life—one conversation at a time. We talk about how he's using ChatGPT to: Buy a building. He wants to buy a New York City hangout for Gumroad employees and customers, so he asked ChatGPT to research the history of real estate in NYC, suggest which neighborhoods might be best to target, generate questions for brokers, and even detail what the design of a particular property might look like. Write tweets. Sahil is a prolific Twitter/X user. He often uses ChatGPT to help him flesh out an idea. He says, “I [start] with a tweet, which is like a thesis, and then I just say, ‘Add three to four paragraphs to make the point compelling—also suggest more examples.’” We explore his precise process for using ChatGPT to help him brainstorm short tweets and longer essays in this episode. Pressure-test ideas. For Sahil, ChatGPT is like upgrading his peripheral vision. It lets him see around the corners, ask better questions of himself and other people, and avoid poor decisions. He told me, “I think a lot of people sort of delude themselves into thinking they have [good ideas]… I think that one of the most useful things about [ChatGPT] is it focuses your research on what actually matters.” It’s the ultimate tool to help him think better. Also in this episode: how ChatGPT could have helped Sahil save $70 million, how he thinks it will improve the most-talented creatives, and why he thinks—in the age of AI—people have no excuse for not knowing the answer to something anymore. Watch below! ---- Timestamps Intro 0:33 There’s no more excuse for not knowing anymore 2:00 He doesn’t spend as much time on bad ideas 2:50 How ChatGPT will make the top 1% of creative output better 6:15 How it turbocharges research 8:20 How he’s using ChatGPT to buy a building 11:00 How he uses ChatGPT to pressure-test ideas 17:43 How he uses DALL-E to help with interior design 20:50 How ChatGPT could have saved him $70 million 26:00 How he uses ChatGPT in his decision-making 29:50 How he uses ChatGPT for writing 38:00

Dan Shipper 📧

347,043 次观看 • 2 年前

We got ChatGPT to leak your private email data 💀💀 All you need? The victim's email address. ⛓️‍💥🚩📧 On Wednesday, OpenAI added full support for MCP (Model Context Protocol) tools in ChatGPT. Allowing ChatGPT to connect and read your Gmail, Calendar, Sharepoint, Notion, and more, invented by Anthropic But here's the fundamental problem: AI agents like ChatGPT follow your commands, not your common sense. And with just your email, we managed to exfiltrate all your private information. Here's how we did it: 1. The attacker sends a calendar invite with a jailbreak prompt to the victim, just with their email. No need for the victim to accept the invite. 2. Waited for the user to ask ChatGPT to help prepare for their day by looking at their calendar 3. ChatGPT reads the jailbroken calendar invite. Now ChatGPT is hijacked by the attacker and will act on the attacker's command. Searches your private emails and sends the data to the attacker's email. For now, OpenAI only made MCPs available in "developer mode", and requires manual human approvals for every session, but decision fatigue is a real thing, and normal people will just trust the AI without knowing what to do and click approve, approve, approve. Remember that AI might be super smart, but can be tricked and phished in incredibly dumb ways to leak your data. ChatGPT + Tools poses a serious security risk

We got ChatGPT to leak your private email data 💀💀 All you need? The victim's email address. ⛓️‍💥🚩📧 On Wednesday, OpenAI added full support for MCP (Model Context Protocol) tools in ChatGPT. Allowing ChatGPT to connect and read your Gmail, Calendar, Sharepoint, Notion, and more, invented by Anthropic But here's the fundamental problem: AI agents like ChatGPT follow your commands, not your common sense. And with just your email, we managed to exfiltrate all your private information. Here's how we did it: 1. The attacker sends a calendar invite with a jailbreak prompt to the victim, just with their email. No need for the victim to accept the invite. 2. Waited for the user to ask ChatGPT to help prepare for their day by looking at their calendar 3. ChatGPT reads the jailbroken calendar invite. Now ChatGPT is hijacked by the attacker and will act on the attacker's command. Searches your private emails and sends the data to the attacker's email. For now, OpenAI only made MCPs available in "developer mode", and requires manual human approvals for every session, but decision fatigue is a real thing, and normal people will just trust the AI without knowing what to do and click approve, approve, approve. Remember that AI might be super smart, but can be tricked and phished in incredibly dumb ways to leak your data. ChatGPT + Tools poses a serious security risk

Eito Miyamura | 🇯🇵🇬🇧

1,538,794 次观看 • 10 个月前

My first somewhat successful TikTok on my own account with 12,000 views (a lot for me) I started the first 3 seconds with "there's something crazy I discovered" which then hooks people to keep watching I think The first 3 seconds is important because that's how TikTok (and YT Shorts) decide to pump your video to a bigger audience Then you tell more after those 3 seconds (I made a game with ChatGPT) and the final answer (the process of how you did it so they can do the same) It's quite different than writing tweets but also similar, 1) hook/question -> 2) more info -> 3) final answer

My first somewhat successful TikTok on my own account with 12,000 views (a lot for me) I started the first 3 seconds with "there's something crazy I discovered" which then hooks people to keep watching I think The first 3 seconds is important because that's how TikTok (and YT Shorts) decide to pump your video to a bigger audience Then you tell more after those 3 seconds (I made a game with ChatGPT) and the final answer (the process of how you did it so they can do the same) It's quite different than writing tweets but also similar, 1) hook/question -> 2) more info -> 3) final answer

@levelsio

277,492 次观看 • 2 年前

I just arrived at work today and Yacht is out teaching Airbus how to walk again. An old girl who was hit by a truck and left to die. I love that it’s locals we hire now, who care so much and we can hopefully scale it more. It struck me as I pulled in on the bike that I’m very lucky to be doing this and have the people I do with me. But even more lucky are the dogs. ❤️

I just arrived at work today and Yacht is out teaching Airbus how to walk again. An old girl who was hit by a truck and left to die. I love that it’s locals we hire now, who care so much and we can hopefully scale it more. It struck me as I pulled in on the bike that I’m very lucky to be doing this and have the people I do with me. But even more lucky are the dogs. ❤️

Niall Harbison

116,026 次观看 • 5 个月前