Today's Guide to the Marketing Jungle from Social Media Examiner... | Presented by |  |
Next month is Artichoke and Asparagus Month, Alluser! Are you a mayonnaise or butter dipper?
In today's edition:
Want more subscribers for your show? Are you using the right title to attract your target audience?
5 Tips to Title an Audio or Video Podcast
When choosing a podcast name, prioritize simplicity and accessibility. Give your show a straightforward title that's easy to say, write, and remember. While creativity has its place, clarity should be your primary goal. Complex or uniquely spelled titles may prevent listeners from sharing your podcast, even if they enjoy it.
Here are five tips to get you on the right path:
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Titles that are four words or less tend to stand out and perform the best. This length also ensures that your title will likely fit your cover art.
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Include a descriptor for your target audience. For example, include "parents" in the title if your podcast is for parents.
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Think about the adjectives your audience might use to describe how listening to you transforms their lives. Those words can make good title elements.
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Figure out the phrases someone would use to search for a podcast like yours and use that language rather than industry terminology.
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When you combine all these elements, put the most important words upfront so they don't get cut off in search results and podcast listings.
Today's tip was inspired by Jerry Potter, a featured speaker at Social Media Marketing World.
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Custom AI Models vs ChatGPT: Securing Your Data
Data security and intellectual property protection represent crucial concerns, especially for businesses with valuable proprietary domain knowledge that forms their competitive advantage.
While many users trust AI providers not to train their models on sensitive data shared through APIs, there's no absolute certainty about how your data is used, and there's an important distinction between "protected" and truly secure data to consider. While these services may offer security from external access, the AI providers have complete visibility into all data sent through their APIs.
Without proper monitoring and structural safeguards, sensitive information sent through API calls is "out there," and terms of service for AI tools, including platforms like Jasper AI, place the responsibility for data protection on the users.
For organizations with strict security requirements, custom AI models offer several options:
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Walled-off models that ensure data never leaves the organization's IT infrastructure
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Models that operate without internet connectivity
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Fully on-premise solutions for organizations with previous security breaches, hosting everything on local machines accessible only through internal networks
Pro Tip: Hugging Face provides a valuable leaderboard that tracks public, private, and open-source models and shows their various licensing arrangements.
Which Open Model is Right For You?
Two prominent open-source options for building custom AI models are Mistral and Llama.
In side-by-side comparisons, Mistral has generally demonstrated superior performance across multiple metrics, including faster processing speeds and better performance with smaller models.
Both models come in different sizes or tiers with varying weights that affect computer storage requirements, hardware specifications, and inference speed.
Mistral shows particular strength in processing unstructured or "messy" language, such as social media content. Llama 3 is a capable generalist model and benefits from extensive community support, particularly through resources like the Llama Lounge subreddit.
Open models like Mistral and Llama are rapidly closing the performance gap compared to ChatGPT and Claude. In some specialized domains, such as healthcare and technical areas, these open models can even outperform their proprietary counterparts, though ChatGPT maintains a significant lead in general applications.
The 4 Components for Creating Custom AI Models
A custom AI model comprises four distinct components that work together.
A Secure Data Repository: The first component is on-premise storage or storage within a cloud solution. The data stored here should be specifically structured and tagged to support particular use cases incorporating AI.
The AI Model: Options include localized solutions like Mistral or Llama 3 that operate independently of internet connectivity. You can fine-tune these models to learn from specific datasets or implement a RAG approach for information processing.
What is RAG? Retrieval Augmented Generation (RAG) is the key to accurate AI responses.
RAG involves retrieving data from a specified source and augmenting the AI model's generation process with this information. This technology appears in popular AI platforms like ChatGPT and Claude. Users who upload documents such as Excel sheets or PDFs utilize RAG functionality, creating a temporary data source the AI can reference while generating responses.
Many users mistakenly envision ChatGPT as having a comprehensive knowledge base stored in the cloud. However, while these models have extensive general knowledge, they lack access to specific business information unless explicitly provided through RAG. Without proper guidance, AI models may attempt to fill knowledge gaps by making assumptions, leading to "hallucinations" - instances where the AI generates plausible but incorrect information.
You don't need to mention RAG by name in your prompts specifically. Instead, you can simply instruct the model to "only pull data from these sources" or "do not make anything up," with additional commands like "don't lie" or "don't extrapolate."
The User Interface: Customizations might include buttons, reference materials, or other features to match your business needs. For example, not every custom AI model requires a chat interface. The interface should reflect your business processes.
The Analytics Layer: This layer captures and analyzes user interactions with the system and represents valuable intellectual property for the business.
Today's advice provided with insights from Yash Gad, a featured guest on the AI Explored podcast.
Instagram Test Surfaces Unseen Story Highlights: IG confirmed it is testing a new feature that displays unseen Story Highlights at the end of the Stories tray, which appears at the top of users' feeds. The feature will show Story Highlights from the previous week that users haven't yet viewed. Users will only see these unseen Story Highlights after viewing all current Stories in their tray, which means those who follow many accounts may not reach the Highlights section. Source: TechCrunch
Meta AI Now Available on Instagram: Users can interact with Meta AI through voice commands by asking questions or making requests, with the AI providing spoken responses or relevant media. Other platform features include helping users find the right words in conversations by giving advice and suggestions when tagged in private or group chats; photo editing capabilities that allow users to modify images by adding, removing, or changing elements through natural language commands; personalized themes generation for individual and group chats, which users can access through their chat details; an image generation feature called "Imagine me as..." that allows users to see themselves in various creative scenarios by uploading their photos. Users can share AI-generated images through Instagram Stories, and access suggested prompts or create their own. Source: Instagram
Updates for Affiliates on Meta Platforms: Meta is enhancing creator monetization through expanded affiliate link integration across its platforms. The update introduces prominent affiliate link displays in Reels at the bottom of the video interface. Text posts and comments now feature new formatting for affiliate links, increasing their visibility beyond traditional URL placements in captions. A new auto-detection system identifies affiliate links from select domains, prompting creators to use the "paid partnership" label and auto-filling product information. The system streamlines the affiliate process through two main publishing paths: the "earn money" option in Reels and videos and Post Settings for photos and text content. The update is now available globally to all Pages and Professional Profiles, offering a timely opportunity for increased affiliate sales during the holiday season. Source: Facebook for Creators via Facebook
YouTube Shopping Affiliate Program Expands to India: Content creators can tag products from retailers like Flipkart and Myntra in their videos, Shorts, and live streams. Creators earn revenue when viewers purchase tagged products through retailer websites. Creators can enhance their content with YouTube Shopping features like timestamps, allowing them to direct viewers to shop at specific moments. Source: YouTube
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