In early days of developing SaaS, your focus has to be developing relationship with users, not revenue maximization. Otherwise you will miss out on tremendously valuable feedback.
Must bookmark.
@PunkpEye has put together a huge collection of 300+ MCP server implementations tailored for AI agents! 🤯
This Github repo links AI models to real-world tools such as web browsers, APIs, databases, cloud services, CLIs, & much more!
↳ https://t.co/CX3YywWXFx
@AlexBelogubov It is a tough space/tough problem. I've been working on AIMD app for several months now. Focused on quality beyond anything else. I have good results, but the application got extremely complex to maintain.
I don't know what changed, but AI generated content is taking off the ground big time this month. I am increasingly using https://t.co/ql0f4iGwb8 for my own projects rather than focusing on selling it... and holy guacamoly did I see a shift in Google Search Console this month compared to previous.
Google algo changes?
I've been very quiet. I don't know if it is good for my social presence, but it is been very good for my product growth. Need to find a balance of the two.
Everyone keeps throwing random suggestions at Google. "Google should do X, Y, Z for the best results"
It is not hard to find good results in a small datasets. Everyone seem to ignore that whatever they do must be feasible with trillions of datapoints
Claude vs. OpenAI GPT-4 generated content, side-by-side comparison
- OpenAI GPT-4 https://t.co/jWWUN0hDCe
- Claude 3 (Opus) https://t.co/EV5EiV1uJj
Both of these are outputs of AIMD app. They are not made using a single prompt, but rather using RAG with over a dozen instructions. This allows to test a quite broad range of expectations, such as the adherence to instructions, error rate, speed, etc. Since the two model APIs are mostly compatible, I've decided to compare it side-by-side.
A few interesting observations:
- Claude followed instructions a lot closer than OpenAI. The outline that was provided to the initial instructions is pretty close to the final article structure despite multiple revisions.
- Claude output scored better in terms of use of broader set of data formats (tables, lists, quotes).
- Contrary to many tweets, Claude output is not excessively verbose. Worth mentioning that part of RAG instructions to rewrite content for brevity.
- Claude took 5 minutes to execute 52 prompts. OpenAI took 7 minutes.
– Image inputs (prompts) are generated with respective models, but the actual images are generated using DALLE.
@levelsio@AnthropicAI I've not seen anyone talk about throughput speeds. How are those? thinking of trying this out for https://t.co/t5lqyJirFm, although pretty happy with current LLMs
https://t.co/t5lqyJhTPO is by far the most advanced article generator, using several different LLMs and external APIs to create content that's both easy to read and contains rich data with images, quotations, tables, etc.