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

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 podcast episode explores significant developments in the electric vehicle market, including Xiaomi's entry with an affordable and Porsche-inspired car, Apple's decision to halt their EV project, and Tesla's challenges with device integration. The discussion also touches on luxury electric cars like the Porsche Taycan and the popularity of flexible screen technology, with a focus on Samsung's foldable phones. Additionally, the episode highlights the Norwegian Sovereign Wealth Fund's massive size and impact on the country's economy and discusses Alibaba's strategy to refocus on its core e-commerce business.

Takeaways

• Xiaomi's affordable electric vehicle, resembling luxury brand Porsche, is generating buzz in the market.
• Apple's decision to halt their EV project raises questions about safety concerns and user experience.
• Porsche Taycan is considered a symbol of luxury and status in the electric vehicle industry.
• Flexible screen technology, exemplified by Samsung's foldable phones, is gaining popularity.
• Norwegian Sovereign Wealth Fund's management of a significant amount of money showcases challenges faced by other countries.
• Alibaba aims to refocus on its core e-commerce business to regain market share.

Outlines

Xiaomi Enters the Electric Vehicle Market, Drawing Comparison with Porsche00:00

Apple Stops EV Project, Xiaomi's Impressive Launch, and Tesla's Integration Struggles02:28

Porsche Taycan and the Downturn of Flexible Screens06:40

Flexibility of Screens and the Norwegian Sovereign Wealth Fund09:50

Alibaba's New Direction and Focus on Market Share12:22

Host: Tracy (@tracyyxchen), Roger (@rogerzhufilm)
This podcast episode explores various topics related to technology and entrepreneurship. The speakers discuss the importance of fast response times in hardware products, such as the Rabbit R1 AI hardware and Groq, and the potential benefits of augmented reality (AR) devices in productivity. They also analyze the pricing strategies of AI models, including the uniform pricing of $20 per month and the visual aesthetics of Cloud. Additionally, the challenges faced by ride-sharing apps in attracting both drivers and passengers are explored, with a focus on Didi's successful implementation. The episode concludes with a discussion on the consequences of stealing internal documents from tech companies and the importance of ethical conduct.

Takeaways

• Fast response times are crucial for hardware products, such as the Rabbit R1 AI hardware and Groq, to provide a better user experience.
• Augmented reality (AR) devices have potential in improving productivity, but their high cost may limit their adoption in schools.
• The pricing strategy of AI models, like the uniform price of $20 per month, may not accurately reflect their capabilities and performance.
• Cloud's UI design, resembling a traditional newspaper, may appeal to users who prefer a human-centered interface.
• Attracting both drivers and passengers is a challenge for ride-sharing apps, and strategies are needed to break the "deadlock" situation.
• The importance of ethical conduct in business is emphasized, and the serious legal consequences of stealing internal documents from tech companies are highlighted.

Host: Tracy (@tracyyxchen), Roger (@rogerzhufilm)

This podcast episode explores the rise of Perplexity AI, a chatbot that has garnered attention for its impressive performance. The speakers question Perplexity AI's valuation and compare it to ChatGPT, discussing the potential impact of the network effect and different company focuses. The episode also examines the success of Rivian, an electric vehicle company that is competing with larger companies like Tesla, highlighting the potential benefits of focusing on a specific niche. The speakers conclude by discussing the government's potential support for Rivian and the challenges faced by Chinese EV companies.

Takeaways

• Perplexity AI's success may be driven by the network effect, similar to social media recommendations.
• Rivian's focus on a specific niche in the electric vehicle market allows it to compete with larger companies like Tesla.
• The government may support Rivian to prevent Tesla from becoming the only major EV company in the US.
• Chinese EV companies face challenges due to tariffs.
• AI-generated content may impact Google's search algorithm.

Outlines

PerplexityAI: A Unicorn with a Browser Plugin00:00

Perplexity AI vs. ChatGPT: Network Effect and Focus Drive Success02:17

Rivian: A Smaller Company Competing with the Giants03:54

Rivian's Government Support and the Future of EV Companies in the US05:06

Q & A

Q: How do you think about Perplexity AI?

A: I feel ChatGPT also has the same capability. It has a browser plugin and it also starts with a chat.

Q: What is the difference between perplexity AI and OpenAI?

A: Perplexity AI focuses on search and optimizes the user experience, while OpenAI focuses on being a platform and wants others to use its capabilities to build other things.

Q: What is the relationship between Rivian and Tesla?

A: Rivian is a smaller company that is more focusing on one specific area and trying to be the best in that, while Tesla is a larger, more comprehensive company that's maybe 90% good at everything.

Q: What is the reason why the government wants to keep Rivian alive?

A: Because they don't want Tesla to be the only pure EV company in the US, which could lead to antitrust lawsuits.

This podcast episode explores the potential and challenges of using AI tools like Sora and Apple Vision Pro for video creation. The speakers highlight the advantages of Sora in generating realistic videos with physics-based movements, and discuss the potential cost limitations of the tool. They speculate about the use of AI-generated videos for prototyping, and compare the rapid progress in the AI world to the development of mobile internet technology.

Takeaways

• Sora has the potential to revolutionize video creation with realistic and physics-based video generation.
• AI-generated videos can serve as prototypes or drafts for real-world video production.
• Mid-Journey's success in image generation suggests the potential for disrupting stock photo websites.
• The gap between China and the US in AI technology and human power may be smaller than previously thought, as evidenced by the dual roles of Chinese AI professors.

Outlines

Sora: A Revolutionary AI Tool for Creating Realistic Videos
00:00

Sora: A Potential Game-Changer in Video Production
02:49

AI Video Generation: Sora and Apple Vision Pro, MidJourney's Hardware and Collaboration with Xtrader
06:21

Mid-Journey and China's AI Investment Landscape
09:22

Chinese AI Professors' Dual Roles: Balancing Research and Startups
12:26

Q & A

Q: What are the advantages of Sora over Pica Labs?

A: Sora can support as long as 60 seconds, and the details are so real. And it seems like every movement of those objects, they follow the physics in real life.

Q: What kind of business are you going to use as generative videos?

A: One example is that like, you know, before this, when people have to shoot like a movie or like a well-made video, first they need to make like a a screenplay so that's like drawings of static frames so now with Sora you can probably generate like a pseudo like draft of the video rather than just have like static like hand drawn images so that improves like the drafting stage for filming Movies or videos.

Q: Do you think like, Sora could be combined with Apple Vision Pro?

A: Yeah, I can definitely see the use of that. Again, I think both of these two products they have very similar in terms of like just even as a first version the quality are amazing.

Q: Is there any government funding for the development of AI in China?

A: I believe that's the case, yeah. All the major investors are, you could say, like public companies, but not like government or national affiliated, yeah.

Q: So I don't know like how much time does he have to run his company.

A: I feel this is like, it's a very common thing for Chinese professors to also have some startups. So I don't know like how much time you can spend on research versus running the company.

大家好，这是一档《创意玩具》旗下的新栏目《科技周会Standing Meeting》。
新栏目的链接在此：https://www.xiaoyuzhoufm.com/podcast/65b6bb880bef6c207451ef55

我会邀请一起创业做AI项目的伙伴们和他/她们的朋友们一起来录制。

节目内容主要是周会闲聊AI和各种业界新闻的部分录音。

主播：Tracy @tracyyxchen , Roger @rogerzhufilm
Tracy的Youtube频道：https://www.youtube.com/@startupStoriesWithTracy

00:00 介绍Intro

02:15 苹果Vision Pro

07:45 CHI大会历年的赞助商

15:30 参观完DC车展的一些感想

本期节目来自我去年参加友台《金子的书房》

录制的一期节目，感谢收听，并欢迎关注友台厂牌的一系列播客节目：

《罗丧失和金子的客厅》

《旷野地图》

《旷野地雷》

原节目Shownotes

重磅！本期金子邀请了景观设计半路出家设计跨行业的AI应用，产品成功服务于上市公司的然然和就职于AI创业公司的Roger，来和大家聊聊人工智能创业的那些事儿！

两三年前就听说，然然跟导师和整个课题组在研究“大事”：通过AI自动生成景观设计的平面图、模型、甚至效果图……到了今年，gpt横空出世后，又听说他们的产品，已经服务了景观行业的上市公司……

这也太酷了吧，必须拉上Roger一起采访他！

主播：然然（地球研究所ppt），Roger（创意玩具主播）、金子

剪辑：金子

封面设计师：Eric

从电脑小白到AI大神的进化历程：

02:35 然然：始于酒吧喝酒，目的是快速做作业？

04:46 Roger：生物机械博士学代码，从GIS调参开始！

07:32 算法应用初尝试：20多次实验，发动整个课题组描图，耗时半年才搞出来！

10:39 硬件、技术支持……做算法应用需要哪些外部条件？

14:14 景观行业的AI应用，降本增效是最大目的？

17:09 从0基础自学AI的思路和方法？

21:04 代码不用自己写，人人都是产品经理？用new bing和chatgpt的注意事项

算法应用的机会与风险：

24:34 年初chatgpt横空出世，对算法创业者造成了怎样的冲击？

27:43 从质疑到超高预期，发SCI都担心跟不上革新速度？

32:15 中美国的AI应用场景，有何不同？

37:02 为什么选择读博，而不是借着算法的东风转行？

43:16 为企业服务的AI工具和为个人服务有何差别，它们能成为替代白领的绘图工具吗？

47:35 面向公众的免费服务初体验：半小时就匆忙下架！

49:52 中美 AI 应用的商业化难点

53:59 风景园林，数字化浪潮中它为什么总是最慢的那一个？

58:18 景观的“臭毛病”：轴线关系，“小清新”绘图风格……AI模型能听懂么？

1:01:07 AI应用的机会与风险点

1:08:22 万一创业失败，还可以做自媒体啊！请关注👇

然然的b站/小红书：地球研究所ppt，公众号：凡尔赛landscape LAB

Bgm: Jebase - Turtle Beach

欢迎大家添加微信公众号：金子的书房——跟踪最新的播客速递，加入我们的“会客厅”，与海内外热辣的朋友们一起挖掘当代年轻人的工作、情感、生活话题~

感谢友台《一听感觉时间》来做客，一起漫谈电视剧《繁花》的种种，是一次愉快的聊天。

大家好，欢迎来到新一季的节目，我们邀请到了Xmind公司旗下产品Chatmind团队的两位朋友，来与我们分享这款AI驱动的思维导图产品背后开发，运营的有趣故事。

https://chatmind.tech/

嘉宾：

Judith，Chatmind 产品负责人

严格，Xmind AI 业务负责人

摘要：

00:00 背景介绍

02:35 产品想法的起点？

05:45 典型的用户场景是？

一句话生成思维导图

12:01 如何做营销推广？

用心打磨产品，让用户自然爱上

18:55 思维导图的一些案例分享

21:00 如何在AI飞速发展的时代做好产品迭代？

长期主义

28:23 对未来AI的畅想？以及对其它开发团队/初学者的建议？

BGM:
https://www.fiftysounds.com/
A Long Walk
The Quiet Morning

感谢中信出版的合作邀请，欢迎在小宇宙评论区参加《生成式人工智能》实体书抽奖活动

00:00 解析生成式人工智能的基本概念以及ChatGPT等生成式人工智能的出现对全球的影响。

1. 决策式vs生成式人工智能对比
2. 为何我们常听到的大数据，大模型在生成式人工智能发展中非常重要？
3. 英国德勤(Deloitte)的报告中预测，世界的人工智能产业规模会从2017年的6900亿美元增长至2025年的64000亿美元，2017—2025年的复合增长率将达到32.10%

05:48 介绍生成式模型的基础原理，包括Transformer模型和Diffusion模型，并讨论这些模型如何用于生成各种内容。

1. 简单讲一下深度学习
2. 简单讲一下Transformer到GPT模型
3. 另一方面，diffusion模型以及文生图应用如Midjourney的发展
4. 受到本书启发，我尝试用GPT写了一个咖啡行业投研报告的大纲 07:43
5. 个人使用Midjourney的一些体会，以及小tips 10:13
6. 使用github copilot辅助代码开发
7. Code Interpreter demo 13:21

17:22生成式人工智能现存的担忧和未来展望

1. 数据和算力的局限
2. 生产力革命 20:39
3. 数据隐私 23:07

节目中提到的:

AI创造的岗位

主播：Roger

监制：严格