Discussion on Gemini vs OpenAI. FCC's decision to ban AI voices in robocalls. Experimentation with AI-driven conversational analytics. Analyzing data with generative AI models. Reflections on using models in schools. Supporting teachers with prompt engineering guide.
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Quick takeaways
The FCC banned the use of AI voices in robocalls to prevent misinformation and misrepresentation of individuals.
Google's Gemini AI models, while promising, still need refinement to catch up with the capabilities of OpenAI's Chat GPT models, but offer multimodal functionality for various applications.
Deep dives
FCC ruling on AI voices in robo calls
The FCC made a ruling about AI voices in robo calls, following an incident where an AI voice clone of President Biden was used to make robo calls. The ruling aims to ban or penalize the use of AI voices in these automated phone calls to prevent misinformation and misrepresentation of individuals.
Comparison of Gemini and Chat GPT
Gemini, Google's latest wave of AI models, including Gemini Pro and Gemini Advanced, is being compared to OpenAI’s Chat GPT models. While Gemini shows promise, it is still seen as having rough edges and needs refinement to catch up with the capabilities of Chat GPT. It is anticipated that Google will address these issues and improve the performance of Gemini in the near future.
The rise of multimodality in AI models
There is a growing trend in AI models towards multimodality, where models combine multiple modes of data representation such as text, image, and speech. This trend is seen in models like Google's Gemini, which supports image-based interactions, as well as other models focused on image editing, text-to-speech, and automatic speech recognition. The integration of multimodality offers more diverse and powerful functionality for various applications.
The emergence of AI-driven data analytics
AI models are being increasingly used in data analytics, with models like Chat GPT and SQL Coder assisting in generating SQL queries for data analysis. These models leverage the strength of generating code or SQL, which traditional language models are proficient at, to enhance data analysis capabilities. This approach allows users to interact with databases and receive analytics results through a natural language prompt, bridging the gap between generative AI and traditional data science techniques.
Google has been releasing a ton of new GenAI functionality under the name “Gemini”, and they’ve officially rebranded Bard as Gemini. We take some time to talk through Gemini compared with offerings from OpenAI, Anthropic, Cohere, etc.
We also discuss the recent FCC decision to ban the use of AI voices in robocalls and what the decision might mean for government involvement in AI in 2024.
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