Microsoft’s investment in OpenAI has resulted in ChatGPT-4 powering Bing. However, looking at Microsoft users (defined by Windows PC or MS Tablet users), when presented with blinded responses from different platforms to the same prompts, they preferred GPT-4 and 3.5 over Bing's responses.
The % is calculated as what percentage of time a platform response was chosen from all the preferred choices.
GPT leads both user's platform choice and in blind side-by-side comparison As part of our Pulse IQ Research, we have users compare prompts and responses from different AI platforms in a blind side-by-side comparison. This time, we asked users to review work-related prompts. In the latest round of
Bard and GPT-3.5 are close behind As part of our Pulse IQ research, we have users compare prompts and responses from different AI platforms side by side. In the latest round of comparison, 61% of users preferred responses from GPT-4. Overall Users picked GPT-4 because they perceived the responses
To better understand the AI opportunities that are lower-hanging fruit, it is important to understand what consumers are asking and what types of prompts come naturally to them. Our research shows that 3 out of 4 people (75%) begin with prompts that fall into three types: * Factual (34%) ex. “How
Search is so dominant that it’s stunning to think it could be replaced by something else. But if you can only start in one place, where would you start? We asked that question of 227 US consumers familiar with AI to see which they would use first in nine
In today’s fast-paced app development world, relying on assumptions about what your users need can lead to missed opportunities. Instead of guessing, imagine having access to real-time, user-prioritized feedback to guide your product decisions. Guessing what users want often results in: * Roadmaps that miss the mark with users * Misspent
Generative AI is transforming product development—but not without challenges. It’s enabling teams to work smarter, innovate faster, and enhance user experiences, but navigating its complexities is key to long-term success. Here are five challenges product teams should be aware of when adopting AI: 1) Addressing Bias in AI
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