创意玩具 | Make & Play 海外科技/AI人工智能/创业/娱乐/ChatGPT

Host: Tracy (@tracyyxchen), Roger (@rogerzhufilm) This podcast episode explores the recent funding trends in AI startups, the challenges faced by smaller startups when competing against big players like Microsoft and Meta, the concept of prompt engineering and its future, the implications of AGI development, the definition of AI and its performance level, the potential of AI in content creation, the concept of machine unlearning in large language models, and the use of AI in PDFs. The conversation also touches on the collaboration between Meta and RayBan, the developments of big tech companies in AI, and the difficulty of finding tech products that live up to their promises. Takeaways AI startups have been raising billions of dollars in funding, but concerns about a potential bubble arise due to the lack of revenue in many startups. Smaller startups face challenges when competing against big players like Microsoft and Meta, leading to dissolution for some teams. Prompt engineering may become less relevant as large language models like OpenAI simplify the prompts process, but there will still be special use cases for prompt engineering. The development of AGI and its implications for humans' existence and prompt engineering are topics of ongoing debate. The definition of AI and the desired performance level of AI are discussed, with predictions of fully functioning models fulfilling 99% of desired capabilities in the next two years. AI has the potential to revolutionize content creation, with advancements expected in generating scripts, 3D models, and videos. Machine unlearning, the ability to make models forget specific data, is a topic of interest for the future as the need to forget confidential or harmful content arises. AI features in software like ReadCube and Adobe Acrobat enhance the use of AI in PDFs, allowing for Q&A interactions and understanding complex documents. Tracking the AI advancements of big tech companies such as Meta, Apple, and Google is important, and finding tech products that deliver on their promises can be challenging. Outlines 00:00 The Funding Landscape for AI Startups: Evaluations Soaring to New Heights 03:33 Startups and AI Trends: Dissolving Startups, Impressive AI Demos, and Learning Prompts 07:17 The Future of Prompt Engineering and the Evolution of Large Language Models 10:59 Thoughts on Prompt Engineering and AGI Arrival 13:46 Progress towards Advanced AI and the Future of Content Creation 16:25 The Future of AI Content Creation and Machine Unlearning 18:21 Machine Unlearning in 2024: Can We Make Models Forget? 21:12 Unlearning Techniques and AI Companions 24:32 AI and Technology Innovations Discussed, Rabbit R1 Mentioned

Host: Tracy (@tracyyxchen), Roger (@rogerzhufilm)This podcast episode explores the recent funding trends in AI startups, the challenges faced by smaller startups when competing against big players like Microsoft and Meta, the concept of prompt engineering and its future, the implications of AGI development, the definition of AI and its performance level, the potential of AI in content creation, the concept of machine unlearning in large language models, and the use of AI in PDFs. The conversation also touches on the collaboration between Meta and RayBan, the developments of big tech companies in AI, and the difficulty of finding tech products that live up to their promises.TakeawaysAI startups have been raising billions of dollars in funding, but concerns about a potential bubble arise due to the lack of revenue in many startups.Smaller startups face challenges when competing against big players like Microsoft and Meta, leading to dissolution for some teams.Prompt engineering may become less relevant as large language models like OpenAI simplify the prompts process, but there will still be special use cases for prompt engineering.The development of AGI and its implications for humans' existence and prompt engineering are topics of ongoing debate.The definition of AI and the desired performance level of AI are discussed, with predictions of fully functioning models fulfilling 99% of desired capabilities in the next two years.AI has the potential to revolutionize content creation, with advancements expected in generating scripts, 3D models, and videos.Machine unlearning, the ability to make models forget specific data, is a topic of interest for the future as the need to forget confidential or harmful content arises.AI features in software like ReadCube and Adobe Acrobat enhance the use of AI in PDFs, allowing for Q&A interactions and understanding complex documents.Tracking the AI advancements of big tech companies such as Meta, Apple, and Google is important, and finding tech products that deliver on their promises can be challenging.Outlines00:00The Funding Landscape for AI Startups: Evaluations Soaring to New Heights03:33Startups and AI Trends: Dissolving Startups, Impressive AI Demos, and Learning Prompts07:17The Future of Prompt Engineering and the Evolution of Large Language Models10:59Thoughts on Prompt Engineering and AGI Arrival13:46Progress towards Advanced AI and the Future of Content Creation16:25The Future of AI Content Creation and Machine Unlearning18:21Machine Unlearning in 2024: Can We Make Models Forget?21:12Unlearning Techniques and AI Companions24:32AI and Technology Innovations Discussed, Rabbit R1 Mentioned

This episode is sponsored by: gratitudejournal.ai Try it here: app.gratitudejournal.ai The magic power of keeping a gratitude journal. Join by contact: [email protected]

This episode is sponsored by: gratitudejournal.aiTry it here: app.gratitudejournal.aiThe magic power of keeping a gratitude journal. Join by contact: [email protected]