Digital Event Horizon
Google has released its latest reasoning AI model, Gemini 2.0 Flash Thinking Experimental, which utilizes runtime "reasoning" techniques to achieve deeper thinking on problems fed into it. Despite some accuracy issues with basic tasks, the model marks another milestone in the rapidly evolving field of reasoning AI.
Google has released its latest model, Gemini 2.0 Flash Thinking Experimental, a reasoning AI that uses runtime "reasoning" techniques. The experimental model has been tested and shows accuracy issues with basic tasks, such as counting the number of R's in the word "strawberry". Reasoning models differ from traditional AI models by incorporating feedback loops of self-checking mechanisms. Google DeepMind's chief scientist acknowledges promising results when increasing inference time computation power. The high computing costs required to run these models have raised concerns about their long-term viability. Despite challenges, Google appears serious about pursuing reasoning models, calling it "the first step in our reasoning journey".
Google has taken a bold step into the realm of Artificial Intelligence (AI) by releasing its latest model, Gemini 2.0 Flash Thinking Experimental, a reasoning AI that utilizes runtime "reasoning" techniques to achieve deeper thinking on problems fed into it. This new model builds upon Google's recently released Gemini 2.0 Flash and runs on the AI Studio platform.
The experimental model has been tested by TechCrunch reporter Kyle Wiggers, who revealed accuracy issues with some basic tasks, such as incorrectly counting that the word "strawberry" contains two R's. These issues highlight the challenges of developing reasoning models, which differ from traditional AI models by incorporating feedback loops of self-checking mechanisms.
The concept of reasoning models is not new, but it has gained significant attention in recent months, with several companies racing to develop their own models. Google DeepMind's chief scientist, Jeff Dean, acknowledges that the model receives extra computing power and writing on X says "we see promising results when we increase inference time computation!" The model works by pausing to consider multiple related prompts before providing what it determines to be the most accurate answer.
The introduction of reasoning models has been met with excitement, as these models are believed to have the potential to solve complex mathematical or academic problems. However, questions remain about their actual usefulness and accuracy. Additionally, the high computing costs required to run these models have raised concerns about their long-term viability.
One such concern is OpenAI's ChatGPT Pro, which costs $200 a month, highlighting the significant investment needed to develop and maintain reasoning models. Despite these challenges, Google appears to be serious about pursuing this particular AI technique, with Logan Kilpatrick, a Google employee in its AI Studio, calling it "the first step in our reasoning journey" in a post on X.
The development of reasoning models is an area that has garnered significant attention in recent times, with several companies vying for the top spot. The introduction of Gemini 2.0 Flash Thinking Experimental marks another milestone in this rapidly evolving field, and it will be interesting to see how these models continue to evolve in the coming months.
Related Information:
https://arstechnica.com/information-technology/2024/12/not-to-be-outdone-by-openai-google-releases-its-own-reasoning-ai-model/
Published: Thu Dec 19 18:36:31 2024 by llama3.2 3B Q4_K_M
