Turing's Tofu #19

📰 This Week in AI & SaaS 📰

• Country singer, Randy Travis–who suffered from a stroke in 2013 which took away his ability to sing–has utilized AI to recreate his voice and has just released his first song–"Where That Came From”. Read more. 

• OpenAI is collaborating with  Stack Overflow–a platform developers use for programming questions–to improve its ChatGPT model responses to software development, programming, and coding questions. Read more. 

• Meta is rolling out new tools for advertisers which will generate new variations of original ads and on-brand headlines and ad copy using AI, which will be available, globally, by the end of this year. Read more.

🌟Turing’s Top Picks 🌟

FEATURED TOOLS 

• Lately: Neuroscience driven AI to power your social media Try it. 🚀

• INK: INK is an AI content assistant that crafts original SEO-optimized articles, descriptions, headlines, and Google ads. Try it. 

• OmniInfer: OmniInfer is an AI image generation API that offers fast and affordable image generation. Try it.  

• KeyTrends: KeyTrends is an AI-powered tool that helps marketers discover trends and traffic opportunities to accelerate their content strategy. Try it. 

Read of the Week: 

 The Possibilities of AI with Sam Altman

One for your ears this week: Stanford Technology Ventures Program interviews OpenAI’s CEO, Sam Altman, about the possibilities of AI, in which he refuses to give a timeline for the development of artificial general intelligence (AGI). Listen to it.

💡 Marketing Moments with Mounier 💡

In this week's edition of "Marketing Moments with Mounier," we are going to jump into a really interesting conversation from Lex Fridman's podcast featuring Yann LeCun, VP and Chief AI Scientist at Meta. LeCun shares profound insights on the future of AI, with particular relevance to marketers and the broader implications for digital strategy.

🌟 Key Points for Marketers:

1. Open Source AI and Proprietary Systems: LeCun emphasizes the potential dangers of AI development being monopolized by proprietary systems, warning of a future where a few large corporations might control the "information diet" of the masses. For marketers, this highlights the critical need for advocating open-source AI technologies to ensure a diverse and competitive landscape, which could foster innovation and prevent any single entity from monopolizing customer data insights.

2. Limits of Large Language Models (LLMs): Critiquing current LLMs like GPT-4, LeCun points out their shortcomings in understanding the physical world and lack of genuine reasoning capabilities. This is crucial for marketers to understand as it tempers expectations of AI's capability in crafting fully autonomous creative and strategic content. Marketers should be aware that while LLMs can augment content creation, they are not yet a substitute for the nuanced understanding that human marketers bring to strategy and brand storytelling.

3. Ethical Considerations in AI Utilization: LeCun touches on the ethical dilemmas of AI in content creation, which initially sparked resistance within his team. For marketers, this is a potent reminder of the ethical landscape surrounding AI technologies. Adopting AI tools requires careful consideration of privacy, data integrity, and the ethical implications of AI-generated content, ensuring that marketing practices remain transparent and trust-worthy.

4. Future of AI in Personalization: Looking forward, LeCun is optimistic about AI's role in personalizing marketing at scale, akin to personalization engines like Netflix and Spotify. This insight is invaluable for marketers looking to harness AI for deeper consumer engagement through customized content and tailored user experiences, potentially transforming how brands interact with their audiences.

📈 Deep Dive: The Role of Embodied AI in Marketing LeCun's discussion on "embodied AI" – suggesting that true intelligence requires a grounding in physical or simulated realities – presents a fascinating paradigm for marketers. This concept could revolutionize customer interaction tools, such as virtual try-ons or immersive digital experiences, which integrate AI to provide more intuitive and engaging consumer interactions.

For those interested in a deeper exploration of how AI can transform marketing strategies and the ethical considerations that come with it, I highly recommend watching the full episode of Lex Fridman's podcast with Yann LeCun.

👇 Watch the full episode here: 

👾 TOFU Quick Bytes: Zenhub Teardown 👾

Zenhub teardown
Founded in 2014, Zenhub is an AI-powered agile project management platform designed for software developers. 

Strategy overview:  Everything from Zenhub’s website, product features, language, and blog content is laser-focused on software developers, which gives them a voice of authority among the developer community and lands them high-quality leads who are actively looking for a solution to their dev-related project management problems.  

Performance Analysis:

• They make around $33.8M in revenue per year 

• They get 138.4K website visitors per month, with the average person visiting 5 pages each time 

• They’ve raised a total of $14.7M in funding over 3 rounds

How have they achieved this? 

Critical Teardown:

What does Zenhub do well?

They integrate with GitHub: Zenhub markets itself as a tool that integrates and works seamlessly with GitHub, one of the biggest code storage, sharing, and management platforms for developers, which will appeal to the majority of developers.  

They publish value-added content: Zenhub regularly creates and publishes useful blogs, whitepapers, case studies, e-books and videos that help solve common developer problems, which positions them as a thought leader and trusted resource in the software development community​​.

They engage with their developer community: Zenhub engages their target audience (on platforms they regularly use, like GitHub) by asking for feedback and incorporating this into new product features which builds loyalty and trust among their users, while also improving the product, showing they’re committed to keep evolving to meet new developer needs.  

 What doesn’t Zenhub do well? 

GitHub dependency: Although it’s a positive that Zenhub integrates with GitHub, it also alienates developers who use other code repositories. They might want to consider integrating with other popular platforms too, like GitLab or Jenkins.   

Customer support: Some reviews complain of poor customer support, which, especially during the onboarding stages can cause friction and result in churn. Perhaps Zenhub might consider integrating an AI chatbot to handle common issues, or provide better training materials to help people use their product effectively and get the most value from it, as quickly as possible. 

Performance issues: When dealing with big projects, some users have reported that the platform can become sluggish and less responsive, indicating that it's not robust enough to handle extensive backlogs or boards with multiple, complex issues. Plus, Zenhub's mobile experience is not as robust as its desktop interface, which can be a limitation for teams that need to manage projects on the go. For example, Zenhub's first contentful paint time (on mobile) is a slow 13.9 seconds, far from Google's ideal 1.8 seconds. To improve, they might want to optimize images, leverage browser caching, and minimize HTTP requests.

AI integration

• Predictive analytics: Zenhub uses AI to analyze historical data on project timelines, task completion rates, and team performance to predict project outcomes and deadlines, or proactively identify bottlenecks.

• Automation: They use AI to automate repetitive tasks within the project management process, such as auto-assigning tasks based on past behavior.

• Reporting: AI is also used to provide more advanced analytics and reporting features, offering insights into project health, team productivity, or resource allocation.

Key takeaways: 

• Focus all your marketing, content, language, and product updates around a specific target market to turn yourself into an authoritative leader in the space, and add value to your core users  

• Engage with your target user base, on platforms they use regularly, by asking them for feedback and then actioning this in new product updates to build loyalty and trust while improving your core offering 

• If you have a small team, consider integrating an AI chatbot to help with common user support issues to prevent frustration and churn 

• Make sure your site and product performance is quick, noone has time to wait these days, so look at optimizing images, leveraging browser caching, and minimizing HTTP requests.

What campaign or content marketing strategy would you like to see torn apart, next? Let me know! 

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