Google’s Gemini-Exp-1114 has launched and is getting rave reviews. It beats OpenAIs GPT-4o model hands down.
VIDEO
The BIG new feature is the analysis of video. You can upload video for analysis from your Google drive and off it goes.
Examples include analysis of:
STUDENT PERFORMANCE
Presentation performance
Eye tracking in teaching surgery etc
Coaching on sports performance
Feedback on musical performance
Teacher/lecturer/trainer performance
Compare present with past performance
STUDENT LEARNING
Lecture summarisation
Image, graph, diagram analysis into notes
Generate practical tutorials from tasks/procedures
Vocational tutorials
Pick out key clips
Create branched scenarios from video
TASK ANALYSIS
Behavioural tasks analysis from real world actions
Workflow efficiency - redundant steps in task execution
Performance analysis of meetings
Highlighting health & safety in real world environments
ASSESSMENTS
Assessments created from a lecture
Create video-based assessments
Assessment of student presentation of assignments
Identify specific errors made when doing something
You get the idea.
BREAKTHROUGH
It may lift us out of the current world of teaching and learning, incredibly limited by its focus on ‘text’. We are drowning in a sea of text, yet we know it does little in teaching an assessing actual skills and performance.
MODEL PERFORMANCE
Gemini-Exp-1114 has knocked OpenAI off the top of the Chatbot Arena leaderboard, the de facto goto place for benchmarking. It scored particularly well in Maths, Creative Writing, Longer Query, Instruction Following, Multi-turn and Hard Prompts. This will also help with the video analysis.
LONGER QUERY and Instruction following is a query, prompt or instruction that includes a detailed and extended description of what the user wants the AI to do or generate, allowing you to get the model to follows specific steps, formats, or guidelines in its response.
MULTI-TURN is dialogue with the AI that spans multiple exchanges (turns), where each response builds on the previous ones, remembering prior questions and answers to provide more coherent responses.
HARD PROMPTS are prompts that are intentionally complex, ambiguous, or challenging for the AI to interpret or execute correctly. It is here you expose the model's limitations, so useful in evaluating its boundaries.
CONCLUSION
The competitive race is producing faster better models but more importantly, a new layer of multimodal functionality is making AI far more usable. All of the above show that the new models are improving practical usefulness. AI is moving away from just a model release to something that gives better practical results, especially in education and learning.
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