Even if you know everyone’s pronouns are she/her, for instance, you don’t know how everyone identifies in terms of gender. □ More importantly, people-however well intentioned-often use the term “ladies” problematically and harmfully to refer to groups of people they assume to be women, incorrectly and harmfully assuming gender identity based on others' physical appearance, names, or pronouns. □And, while some women are attempting to reclaim the term “ladies," many women do not identify with or enjoy being referred to that way or the associations with white, upper class, heterosexual, conformity to stereotypical femininity norms the term often continues to convey. Using the term "lady" can unintentionally signal and reinforce the idea that some women are *not* worthy of respect. For many folx, the term "lady" still carries connotations of enforcing narrow, exclusionary versions of policing who conforms well enough to be worthy of respect. □The term “lady” was historically used to identify “respectable” white, upper-class women and to enforce norms around gender, race, class, ability, and sexuality in ways that privileged some (white, wealthy, cisgender, heterosexual, able-bodied) women and contributed to the marginalization, exclusion, and subordination of others (women of color, working and poor women, LBQP+ women, trans women, women with disabilities). You can book me here: /book-meĪnother reminder from your friendly neighborhood Women's Studies PhD as you're creating content for and writing about women during #WomensHistoryMonth and beyond: Using the term "ladies" to refer to groups of professional women likely doesn't convey the friendliness or collegiality you might think it does. If you want to learn more, I keynote all over the country about building an online business and turning virality into money. But going viral with no systems in place to make the most of that virality is bad business. The perfect time to go viral too: we launched our podcast Financial Feminist in May, the #1 Business podcast in the country on its debut. We were able to leverage these subscribers into new customers - revenue off our products, affiliate partners, influencer partnerships, etc. In addition to our email subscribers (who we continually send emails to today) and our web traffic - we saw a massive spike in our Instagram followers AND got national press coverage from Buzzfeed, CNBC, TIME, and more.Įven two years later, the BuzzFeed article is STILL sending subscribers to us. In a week, this video had over 4M views (now over 7M.) The video drove hundreds of thousands of people to our website. This video took me less than 10 minutes to make. I went on to describe the importance of investing, and how to get started. On a random night, I produced an off-the-cuff video about how, as a 26-year-old at the time, I would retire with more than $6M. Now, how did we get 100,000 people over 7 days to successfully complete the 8-step quiz and give us their email? The LP and the email sequences helped us promote both affiliate and our products. This quiz was not only for email acquisition, but put new customers into a nurture funnel based on a specific financial goal (paying off debt, investing, etc.) ![]() We compiled our free and paid resources by "money personality", and delivered the results via email and an LP: This lead to at least $500,000 in additional revenue - no paid ads required.Ī month prior, my team and I spent an entire week building a quiz. I used TikTok to get 100,000 email subscribers in ONE week. Human-like language functionality backed by computational and knowledge horsepower □ This points to so many applications that my head is exploding. ▶ There's an animated avatar delivering your answers (cool) ![]() ▶ James uses Hugging Face for the integration-fun to say :) ▶ Whenever GPT gets stuck (too much computation, too much inference, too much specific knowledge required), it can "phone a friend" (Wolfram | Alpha) You need to watch the video, but some spoilers: In the video linked in the first comment, IBM Quantum Developer Advocate James Weaver demos an integration he's built between GPT 3.5 and Wolfram | Alpha. How can LLMs (large-language models that we learned about in part 1) overcome their limitations? By calling on a large-scale computational knowledge graph, of course! Why? I think because I linked to YouTube. My ChatGPT part 1 got 35,000 impressions and My ChatGPT part 2 got 1,000 impressions. LinkedIn HATES when you link to off-site content.
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