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Over the past few months, we have discussed the AI engineer’s toolkit for building reliable LLM products multiple times. We believe that combining RAG, prompting, and fine-tuning will be key to developing scalable solutions with generativeAI. If this sounds interesting, reach out in the thread!
This inspired him to build Buddy, a fictional character that kids can actually converse with through the power of generativeAI. What applies to smart homes does not apply to early learning, from technologies to UXdesign. To make this approach work, we are designing Buddy as a game with a story and a universe.
I'd come across AI transcribers before, but not one as user-friendly with so many features! In this MeetGeek review, I'll explain what MeetGeek is and who it's best for. Product & UXDesigners: Transcribe brainstorming sessions, feedback, and design discussions.
Figure 3: Knowledge graphs explicitly encode relationships between entities, reducing the guesswork in your AI system Instead of relying purely on statistical correlations, an AI system enriched with knowledge graphs can: Validate predictions against domain-specific rules (e.g., Infer missing information (e.g.,
The model serves as a tool for the discussion, planning, and definition of AI products by cross-disciplinary AI and product teams, as well as for alignment with the business department. It aims to bring together the perspectives of product managers, UXdesigners, data scientists, engineers, and other team members.
Right now, we still mostly hope we can hop over some unresolved issues with AI (i.e., let the AI figure this out), but we could always resort to working on the data/API/logic layer instead. Just to explain what I mean by 3. – say you would like to extract data from an invoice or some kind of form.
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