Google's Gemini: A Step Too Far with Misleading Demos?

Last week, Google launched Gemini, its new AI model powering Bard. While the company boasted impressive benchmark results and slick demo videos, the reality behind the videos was less than transparent.

The demos showcased seemingly real-time video analysis and response, but in actuality, the process involved converting videos to stills and feeding them into text prompts. This deliberate misrepresentation likely aimed to convince investors that Google was catching up to ChatGPT, but ultimately, it sacrificed trust.

While Gemini isn't yet at GPT-4 level for cognitive tasks, it's a powerful model that could have impressed the world without the misleading demos. The GenAI landscape benefits from competition, and Gemini's arrival pushes existing providers to improve. However, misrepresenting capabilities ultimately undermines this positive development.

Choosing the right GenAI model isn't about benchmarks; it's about your specific needs. Consider your use case and understand how well each model fits your application. For example:

• Long document analysis: Anthropic's Claude
• Trend research: Perplexity
• Deep cognitive work: GPT-4
• Privacy: Wizard and GPT4ALL
• Quick free output: GPT-3.5
• Research papers: Bard

Moving beyond the "magic of AI" requires understanding the strengths and weaknesses of each model. This becomes increasingly challenging as providers constantly update their offerings. An independent guide can navigate this dynamic landscape, ensuring you have the right tools for your needs.

I’m still exploring Gemini, so far it seems good for content work, with fewer of the ‘tells’ of the GPT models, but as with the previous Bard model it quickly reaches the end of it’s usefulness, it seems to lack the confidence of GPT4 to have a go, instead saying no, and asking for more help.

I’m looking forward to exploring it’s ‘personality’ over the next few weeks and will report back!