Challenges and Considerations in AI Service Pricing and Adoption

If you are running an AI service, whether large or small, one must address the nexus of the high compute costs and the expensive nature of providing such offerings. Companies like Microsoft and GitHub have responded to this challenge by introducing AI Copilot services at various price points, catering to consumer demand. The key question is whether consumers perceive AI as a mere productivity enhancement or an essential service.

Potential Revenue Growth and Pricing Model: Successfully portraying AI as indispensable opens the door to significant revenue growth. However, the current pricing model, relying on recurring revenue from flat-rate fees, may require reevaluation as adoption rates rise.

Indispensable Features of AI Services: To be considered indispensable, AI services must deliver the following key aspects:

  •  Easy updating of factual knowledge.
  •  Providing truthful outputs with proper and complete attribution.
  •  Ensuring reliable control of dialogue.
  •  Ensuring reliable control of social and ethical appropriateness.

Assuming the AI services can deliver the indispensable features outlined above, the industry is not there yet. A shift towards a per-usage payment model could become necessary to manage compute costs and maintain profitability.

Long-term success in the AI market will depend on striking the right balance between pricing, consumer perception, and service delivery.


Companies need to address the challenges posed by high compute costs while convincing consumers of AI’s essential role beyond mere productivity enhancement. Establishing AI services as indispensable is the challenge , the win = significant revenue growth.

B&C Networks

In another timeline we would guide to an upcoming media m&a landscape.
That implies demand. If what Iger, Redstone and others are saying now
come to manifest there will be a lot of networks up for grabs with few suitors.

Couple that with a crippling actor and writer strike and you have the equivalent
of thousand year storm in broadcast and cable.

The landscape starts to look like a fire sale.  I did a rough projection just looking
at a few stakeholders and being conservative….

Hype Cycle for Artificial Intelligence, 2023

Generative artificial intelligence and ChatGPT have elevated AI discussions to new levels, pushing interest to boardrooms and heads of state alike. Data and analytics leaders must stay on top of the trends and track the trajectory of innovations to create credible cases for investment.

Links from early surf set

Pan, tilt, generate…

In another lifetime, I edited video on 3/4 inch media on Sony RM-440 editing machines.  If we wanted something like this prompt generates we had to do a table top shoot that had manual physical panning and tilting.  The next step would be the editing – this took hours if not days.   Here we have it in a paragraph of text.

I have a high-resolution panoramic image that I’d like to convert into a video. The video should have a 3:2 aspect ratio and the image should fill the entire video, even if some of the sides are cut off. The video should start at the center of the image, pan smoothly to the right until it reaches the edge, then return to the center. From there, it should pan smoothly to the left until it reaches the other edge, and then return to the center again. The video should be created using the imageio library in Python, saving the frames directly to a video file instead of storing them in a list. The frame step should be 8 pixels. If necessary, the edges of the image can be cropped so that the size of the image is divisible by the frame step. Please find the image attached image.

META’s take on Twitter

 META’s take on Twitter

Meta has a long history of mimicking products and product features of competitors.
Most if not all of the efforts have been met with meh.  Will this time be different?

We are in a brief moment of time between the products announcement and its debut.
What are the expectations?  There are some clear wins that could help insure success.  

  • – Keeping the Core Functionality: To make Threads a game-changer, it must retain Twitter’s essential features that made it successful: real-time, open, and free. These three elements formed the backbone of Twitter’s survival until it fell into the wrong hands, eroding its legacy value and driving away intelligent users. 
  • – Embracing Real-Time Openness: Streamlining Onboarding and Data Usage: To make transitioning to Threads seamless, an import function to import social graphs and a user-friendly API are crucial. Users should be able to effortlessly bring their connections from other platforms to Threads. 
  • – Privacy Opportunity – Be there, be square, don’t be a data pig. Prioritize user privacy and avoid excessive data collection,  EU regulations and others are scoping to new data realities for platforms.  Why collect unnecessary information. Be smart about retention and use cases.  Ban individual targeted advetisting from the start.
  • – Utility Fork for Governments and Organizations: To cater to different user segments, Threads can create a separate utility fork designed specifically for governments and organizations. This fork can include features such as user agent identification, media authentication, and dedicated tools tailored to their unique needs, making Threads a versatile platform for a wider user base. 
  • – Empowering Users with Curation and Tuning Features:  Give users the ability to curate their content and fine-tune their feeds. Allowing users to filter out unwanted content and customize their preferences will enhance their sense of ownership and personalization, leading to a more enjoyable and tailored experience.   Twitter tried to this a platform level which was not the optimal path. 
  • Enhancing Functionality: Bookmarks for saving and revisiting important posts will greatly enhance the user experience. Improved video uploading capabilities to ensure a smooth and hassle-free process, along with realistic durations, 
  •  – Gradual Monetization Approach:  The platform should be ad-free for a initial period of time, allowing users to fully appreciate its value. After this initial period, a commercial layer can be introduced, ensuring ads are relevant but without invasive targeting, striking a balance between revenue generation and preserving the organic user experience.

AI round-up security, economics, scraping, open-source, video generation

Open Letter from Security and Privacy Researchers in relation to the Online Safety Bill

The economic potential of generative AI: The next productivity frontier

Stability AI CEO Emad Mostaque, in an interview with Peter H. Diamandis for the Moonshots and Mindsets Podcast, said that in the next five years, there will be no human programmers. He also said that by the end of next year (2024), ChatGPT will be available on phones and won’t require an internet connection to run. The CEO also highlighted how AI is growing at a rapid pace.

Google the AI  scraping game is on 
  publicly accessible sources  For example, we may collect information that’s publicly available online or from other public sources to help train Google’s languageAI models and build products and features like Google Translate, Bard, and Cloud AI capabilities. Or, if your business’s information appears on a website, we may index and display it on Google services.

Open-source “Davids” are taking on GPT-4 and other Goliaths Open-source LLMs are a possible antidote to Microsoft and Google’s control of chatbots like GPT-4

We’re starting to see the first open-source *video* generation models 

Time traveler

Time traveler = Nam June Paik,
Image – Triangle, Trinity 1998  One of the Three mixed media prints (silkscreen and offset)
Each print 40 x 50 cm (15¾ x 19¾”)