Key insights

• 💼 Tutorial makers provide clear career paths but may not represent real practitioners' work
• 🔬 Real practitioners run strange experiments with new technology
• 🤖 AI's capability to replace creative jobs was initially controversial but has become more accepted over time
• 🎙️ The speaker describes his own experiments with AI, such as using GPT API and building tools for creative tasks
• 🌐 Evolution of AI technology from Dream Booth to Flux Lures and Auto GPT
• 🧠 Challenges with reasoning and long-term thinking in AI models
• 📈 AI reasoning model scores 83%, impacting chemistry, math, and coding problem-solving
• 📊 Success attributed to distribution, not just skills

Q&A

• What is the main advice provided in the video?

  The main advice is to run your own experiments, make your own decisions, think like a manager, take responsibility for outcomes, focus on finding out what customers truly want, and deliver it. Success comes from being honest with yourself and delivering what customers really want.

• What led to the speaker's improved decision-making and success?

  The speaker's improved decision-making and success came from attributing success to distribution, not just skills, admitting to being wrong about remote work predictions, adapting opinions based on new evidence, focusing on running experiments, making independent decisions, thinking like a manager, taking responsibility for outcomes, and finding out what customers truly want.

• How did the speaker find success in using AI for video content?

  The speaker found success by shifting focus to customer discovery, using AI avatars for video content, and creating distribution using AI-generated content, leading to significant global views. This success led to offering general content services and being recognized as valuable in the changing software landscape.

• How has the job landscape evolved due to AI advancements?

  The job landscape is shifting towards more outcome-oriented work, emphasizing outcomes over inputs. Coding roles may evolve into more outcome-focused positions, and engineers may transition to managerial roles with the rise of new AI models.

• What are the limitations of current AI models?

  The limitations of current AI models include challenges with reasoning, long-term thinking, face swapping, and the need for more advanced models like GPT-3 with enhanced reasoning and problem-solving abilities.

• What are some examples of the speaker's experiments with AI?

  The speaker has experimented with AI, such as using GPT API, building tools for creative tasks, creating automated thumbnails, and employing AI avatars for video content.

• How has AI's capability to replace creative jobs evolved over time?

  AI's capability to replace creative jobs was initially controversial but has become more accepted over time as AI technology has rapidly evolved, leading to advancements in creating automated tasks and enhanced reasoning and problem-solving abilities in AI models.

• What is the video about?

  The video discusses the evolution of AI technology, its impact on creative jobs, the speaker's experiments with AI, limitations of current AI models, and the changing job landscape due to AI advancements.

• 00:00 Many tutorial makers provide clear career paths but real practitioners run strange experiments that may not fit into traditional job molds. The speaker made a video about AI taking creative jobs, which was initially criticized but has become more accepted over time. He discusses his own experiments with AI and the limitations of current models.
• 03:51 AI technology has rapidly evolved from Dream Booth to Flux Lures and Auto GPT, with advancements in creating automated thumbnails and agent-based tasks. The latest model, GPT-3, excels in reasoning and problem-solving, similar to human thinking systems.
• 08:21 AI reasoning model scores 83%, revolutionizing coding and work dynamics. Coding may evolve into a more outcome-focused role. Shift from traditional job dynamics to more outcome-oriented work. Emphasis on outcomes rather than inputs. Job landscape evolving due to AI advancements.
• 12:09 The speaker ran a software company, faced competition, and then shifted focus to customer discovery and building distribution using AI-generated content. They found success in creating and using AI avatars for video content, leading to significant global views. They now offer general content services and are recognized as valuable in the changing landscape of software.
• 15:54 The speaker's success was due to distribution, not just skills. Admits to being wrong about remote work predictions, but stresses the importance of adapting opinions based on new evidence. Stopped listening to others and started trusting gut instincts, resulting in improved decision-making and success.
• 19:22 The main advice is to run your own experiments, make your own decisions, think like a manager, take responsibility for outcomes, and focus on finding out what customers truly want. Success comes from being honest with yourself and delivering what customers really want.