Generative AI
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Generative AI
- 陌生人社交痛点:1)供给不足,男女比大概为4:6,单个女生同一时间跟个别高质量男生社交,很多男生得不到社交资源;2) 匹配效率低下,匹配之后很难破冰,匹配后发生聊天的概率只有50%,女生回复的还要腰斩,男生发消息后女生回复比例是40%,女生发消息后男生回复的比例是90%;3)流量分配失衡,80%的社交资源掌握在20%的用户手中,特别是长相好看的
- Soul原有解法:1)多元化玩法、构建优质内容创作者生态;2)基于兴趣的匹配系统、丰富画像标签体系、去中心化、去颜值化;3)弱化LBS社交、推荐系统兼顾长尾群体
- Soul+AI的解法:1)AI虚拟人,承接得不到社交资源的男性的需求,支持多模态交互、拟人化程度高兼具工具属性、具备人设/形象/声音、AI自主运营高质内容,2)建立用户的AI数字分身代理,解决效
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【SaaS+AI】
- Vertical SaaS是最好的做产品的机会 :1)找到垂直行业,持续获得用户内部/反馈且对模型训练有用的数据,垂类数据更容易对模型通过reward改进,让产品效果提升更快;2)获客成本相对低,尤其是后续拓展产品
- 重视how to access to data :如果SaaS企业非常重视AI,就一定要建立数据飞轮,用户的数据相当于免费标注:找人标注会很贵,但如果用户数据本身就是标注,就可以大幅提高迭代效率(如特斯拉)带着B2B2C、挖掘C端需求的思维做saas产品,比如客服 saas 的价值是解决C端问题
- 做企业级客户要非常非常有耐心 :PMF、POC周期都很长,针对十万美元客单以上的企业级客户,需要满足的第一点核心需求不是产品,而是合规(数据来源、意识形态等),第二
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The programmer Simon Willison has described the training for large language models as “money laundering for copyrighted data,” which I find a useful way to think about the appeal of generative-A.I. programs: they let you engage in something like plagiarism, but there’s no guilt associated with it because it’s not clear even to you that you’re copyi... See more
Ted Chiang • Why A.I. Isn’t Going to Make Art | the New Yorker
We are all products of what has come before us, but it’s by living our lives in interaction with others that we bring meaning into the world
Ted Chiang • Why A.I. Isn’t Going to Make Art | the New Yorker
Thinking of AI as talent rather than tech opens up an expansive yet familiar vocabulary for introducing this game-changing new teammate into our workplaces.
Some of the ways that AI is more HR than IT…
• AI is a long-term investment, requiring development and training in order to adapt, improve, and create new value over time.
• AI can be a dynamic, i
Mike Arauz • August Newsletter: Start Thinking of AI as Talent, Not Tech. 🤖
Start by releasing AI from the limiting mental model of “technology.” Start thinking of AI as talent, not tech.