Topbots
OCTOBER 10, 2023
After considering the market opportunities and the business value of conversational AI systems, we will explain the additional “machinery” in terms of data, LLM fine-tuning, and conversational design that needs to be set up to make conversations not only possible but also useful and enjoyable. Figure 1: Mental model of an AI system (cf.
Google Research AI blog
JUNE 6, 2023
We fine-tuned a large language model to proactively suggest relevant visuals in open-vocabulary conversations using a dataset we curated for this purpose. We open sourced Visual Captions as part of the ARChat project, which is designed for rapid prototyping of augmented communication with real-time transcription.
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Unite.AI
FEBRUARY 16, 2024
What applies to smart homes does not apply to early learning, from technologies to UX design. BLM (Buddy's language model) — Conversational AI Engine for Children. It focuses on specific educational functionality and is much less versatile than large language models. Safe, fast, and free to operate.
Heartbeat
FEBRUARY 29, 2024
After closely observing the software engineering landscape for 23 years and engaging in recent conversations with colleagues, I can’t help but feel that a specialized Large Language Model (LLM) is poised to power the following programming language revolution.
O'Reilly Media
JULY 25, 2023
I’m a professor who is interested in how we can use LLMs (Large Language Models) to teach programming. What I needed at this time was a UX design consultant, so I wanted to see if ChatGPT could play this role. Do not worry about whether it is feasible to implement the designs.
AWS Machine Learning Blog
MAY 7, 2024
The Hugging Face containers host a large language model (LLM) from the Hugging Face Hub. Apart from that, she is interested in UX design and playing cards. The recording is transcribed to text using Amazon Transcribe and then processed using Amazon SageMaker Hugging Face containers to generate the meeting summary.
Topbots
SEPTEMBER 11, 2023
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, UX designers, data scientists, engineers, and other team members.
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