Exploring AI Agents: How Gemini 1.5 Flash 8B Thinks

AI agents have become essential tools in tackling complex challenges, and each new model brings advancements in speed, accuracy, and reasoning. Among these, Gemini 1.5 Flash 8B emerges as a powerful agent capable of processing large-scale information with remarkable precision. But how does it “think,” and what enables its impressive capabilities?

In this blog, we’ll explore the inner workings of Gemini 1.5 Flash 8B, breaking down its architecture, thought processes, and decision-making strategies. By testing its performance in real-world scenarios, we’ll uncover how this model analyzes inputs, applies logic, and delivers actionable insights. Whether you’re an AI enthusiast or seeking practical knowledge about Gemini 1.5 Flash 8B, this article will provide a detailed understanding of how it operates and why it stands out in the world of AI agents.

Task 1: Content Generation

Prompt:
When user says “Start” you should:
Content Generation: Write a comprehensive, informative article about project management fundamentals, with a specific focus on defining objectives, scope, and delegation.

Initial Task Understanding and Information Gathering

• 0:09: The agent receives the prompt:
  Could you provide detailed insights into the fundamentals of project management, specifically focusing on defining project objectives, scope, and the principles of delegation?
• 0:17: The agent’s first thought:
  I need to gather information on project management fundamentals, focusing on objectives, scope, and delegation. I’ll use the available tools to research and synthesize the information. Using tool: google_serper
• 0:21: Second thought:
  I will use Wikipedia and Google search to gather information on project management fundamentals, focusing on objectives, scope, and delegation. Using tool: wikipedia
• 0:23: Final output is shown.

Analysis of the Agent’s Thought Process

• Understanding the Prompt: Correctly interprets the need to provide information on project management fundamentals, focusing on objectives, scope, and delegation.
• Information Gathering Strategy: Decides to use both Google Search and Wikipedia, a reasonable approach.
• Tool Usage: Identifies and uses google_serper and wikipedia tools.
• Focus on Key Concepts: Explicitly mentions the key concepts: objectives, scope, and delegation.

Analysis of the Output

• Well-Structured: Clear sections for Defining Project Objectives, Defining Project Scope, Delegation Principles, and a Conclusion.
• Comprehensive: Covers the fundamentals as requested, with definitions, explanations, and examples.
• Clear and Concise: Writing is generally clear and concise.
• Informative and Actionable: Provides valuable insights, especially on SMART objectives and delegation principles.

Snippet of Bot Output

Project Management Fundamentals: Defining Objectives, Scope, and Delegation

Project management is a structured approach to planning, organizing, and executing tasks to achieve specific goals within a defined timeframe and budget. A crucial aspect of successful project management lies in clearly defining objectives, understanding the project scope, and effectively delegating tasks.

Defining Project Objectives:
Clear, measurable, achievable, relevant, and time-bound (SMART) objectives are essential for project success. Objectives should be specific, outlining exactly what the project aims to accomplish. Measurable objectives allow for tracking progress and evaluating success. Achievable objectives are realistic and attainable given available resources and constraints. Relevant objectives align with the overall strategic goals of the organization. Time-bound objectives establish deadlines and ensure timely completion.

• Time Taken: 14 seconds (Prompt at 0:09, output at 0:23)
• Readability:
  • Flesch-Kincaid Grade Level: 14
  • Flesch-Kincaid Score: 14.36
  • Summary Length: 346 words

Conclusion:
The agent successfully generates a comprehensive and well-structured overview of project management fundamentals, focusing on defining objectives, scope, and delegation.

Task 2: Calculation

Prompt:
Answer the Problem:

A company sells two products: Product A and Product B. Product A costs $30 per unit to produce and sells for $50 per unit. Product B costs $40 per unit to produce and sells for $70 per unit.

The company sold 120 units of Product A and 80 units of Product B last month. Calculate the total revenue generated from the sales of both products.

Calculate the total profit generated from the sales of both products (Revenue – Total production cost).

The company wants to increase the total revenue by 10%. How many additional units of each product must they sell to achieve this goal, assuming the production cost per unit and selling price per unit remain constant?

Initial Task Understanding and Information Gathering

• 0:06: The agent receives the prompt: calculate total revenue and total profit
• 0:18–4:55: The agent repeatedly processes thoughts such as:
  Calculate the revenue and profit for each product, then sum them up. Using tool: None
  Manually calculate the revenue and profit. Using tool: None
• 0:53–5:36: Receives new prompts about calculating additional units needed and distribution strategies.
• 06:54: Final output is shown.

Analysis of the Agent’s Thought Process

• Understanding the Prompt: Initially understands the need to calculate total revenue and profit but repeats thoughts in a loop.
• Lack of Tool Usage: Does not use external tools for calculations.
• Manual Calculation: Relies on manual methods, which is inefficient.
• Struggling with Distribution: Attempts to use an inappropriate tool (url_crawl_tool), then returns to the correct logic.

Analysis of the Output

• Correct Answers: Provides correct answers for total revenue ($11,600), total profit ($4,800), and additional units (12 for Product A, 9 for Product B).
• Lack of Explanation: States answers without explaining calculations or reasoning.
• Missed Opportunity: Does not discuss alternative strategies.

Snippet of Bot Output

The total revenue generated from the sales of both products last month was $11,600. The total profit generated from the sales of both products was $4,800. To achieve a 10% increase in total revenue, the company needs to sell an additional 12 units of Product A and 9 units of Product B, assuming a 50/50 revenue split strategy for the additional sales.

• Time Taken: 6 minutes and 48 seconds
• Conclusion:
  The agent eventually arrives at correct answers but with an inefficient and repetitive process and little explanation.

Task 3: Summarization

Prompt:
Summarize the key findings from the previous article in 100 words, focusing on the most significant sections.

Initial Task Understanding and Information Gathering

• 0:04: Agent receives the prompt.
• 0:21: Agent displays its first thought, summarizing key technical features and safety aspects of o1 models.
• 1:26: Final output is shown.

Analysis of the Agent’s Thought Process

• Understanding the Prompt: Correctly interprets the summarization task and word limit.
• Information Gathering: Extracts key findings from the article but the thought process is a single block of text.
• Focus on Key Sections: Focuses on definition, importance, history, applications, implications, and recent advancements.

Analysis of the Output

• Structure and Content: Covers the main points in logical order.
• Conciseness: Stays within 100 words.
• Accuracy: Reflects the article’s content.
• Clarity: Clear and easy to understand.
• Key Findings: Successfully highlights definition of AI reasoning, role in decision-making, evolution, applications, ethics, and the o1 model.

Snippet of Bot Output

Definition of AI Reasoning: AI reasoning is a logical method enabling machines to draw conclusions, predict, and solve problems akin to human thought. It involves using available information to derive new insights or make decisions, mimicking the human brain’s information processing. Two main types exist: formal reasoning (rule-based, mathematical logic) and natural language reasoning (handling human language ambiguity).

• Time Taken: 1 minute and 22 seconds
• Readability: 91 words

Conclusion:
The agent effectively summarizes the article, captures main points, and presents them clearly and concisely.

Task 4: Comparison Task

Prompt:
When user says “Start” you should:
Compare the environmental impact of electric vehicles with that of hydrogen-powered cars. Include factors such as energy production, vehicle lifecycle, and emissions.

Initial Task Understanding and Information Gathering

• 0:06: Agent receives the prompt.
• 0:08–1:22: Agent uses google_serper and url_crawl_tool multiple times.
• 1:52: Final output is shown.

Analysis of the Agent’s Thought Process

• Understanding the Prompt: Correctly interprets the need to compare EVs and hydrogen-powered cars on energy production, lifecycle, and emissions.
• Information Gathering Strategy: Uses both broad and specific search tools.
• Tool Usage: Employs google_serper and url_crawl_tool appropriately.
• Focus on Key Factors: Output successfully addresses mentioned factors.

Analysis of the Output

• Well-Structured: Clear sections for Energy Production, Vehicle Lifecycle, Emissions, Other Factors, and Conclusion.
• Comprehensive: Covers electricity sources, hydrogen production, manufacturing, efficiency, and infrastructure.
• Clear and Concise: Writing is direct and avoids jargon.
• Balanced: Presents pros and cons of both technologies.
• Well-Researched: Draws from multiple sources.

Snippet of Bot Output

Energy Production:

• Electric Vehicles (EVs): EVs run on electricity, which can be generated from fossil fuels, nuclear power, or renewables. Environmental impact depends on electricity source. Renewables lower carbon footprint; fossil fuels reduce benefits.

• Hydrogen Fuel Cell Vehicles (FCVs): FCVs use hydrogen to produce electricity. “Grey hydrogen” from fossil fuels releases CO2, while “green hydrogen” from electrolysis using renewables lowers emissions. Most current hydrogen is fossil-based.

• Time Taken: 1 minute and 46 seconds

• Readability: 698 words

Conclusion:
The agent generates a comprehensive, well-structured, and balanced comparison, demonstrating strong information synthesis.

Task 5: Creative Writing

Prompt:
Write a futuristic story (500 words) set in a world where electric vehicles have fully replaced traditional combustion-engine vehicles. Describe the environmental changes and societal impact.

Initial Task Understanding and Information Gathering

• 0:04: Agent receives the prompt about environmental changes.
• 0:08: Provides its first output, then receives a prompt about societal impacts.
• 1:26–2:25: Provides outputs and final story.

Analysis of the Agent’s Thought Process

• Understanding the Prompt: Correctly understands the creative writing and the need to address both environmental and societal changes.
• Two-Part Prompt: Considers both aspects before merging into a narrative.
• Information Synthesis: Draws on training data for plausible scenarios.

Analysis of the Output

• Creative and Engaging: Narrative titled “Echoes of Tomorrow” paints a vivid future with EVs.
• Well-Structured: Progresses logically: environment, society, challenges, reflection.
• Comprehensive: Covers air quality, noise, energy, economy, social equity, wildlife.
• Balanced Perspective: Acknowledges both positive and negative aspects.
• Imaginative and Thought-Provoking: Explores utopian and challenging futures.

Snippet of Bot Output

In the year 2050, the world had finally turned a corner. The air was cleaner, skies clearer, and cities quieter. Electric vehicles, once a futuristic dream, had fully replaced their combustion-engine ancestors. Streets once choked with the fumes of gasoline engines now hummed softly with the gentle whir of electric motors, a testament to humanity’s shift towards a greener future.

• Time Taken: 2 minutes and 21 seconds
• Readability: 511 words

Conclusion:
The agent excels in creative writing, producing an imaginative and well-structured narrative.

Gemini 1.5 Flash 8B: A Promising but Imperfect AI Agent

Gemini 1.5 Flash 8B demonstrates significant potential as an AI agent, excelling in tasks involving information retrieval, structured summarization, and creative writing. It effectively utilizes tools like google_serper and wikipedia to generate well-organized, informative, and engaging content. Its strong performance in project management, environmental comparison, and creative writing tasks showcases its ability to synthesize information, produce clear outputs, and adapt to different writing styles.

However, the model’s performance in the calculation task reveals critical weaknesses. Its thought process is repetitive and inefficient, failing to utilize appropriate calculation tools and relying on manual, error-prone methods. This leads to excessive processing time and a lack of transparency in reasoning. While it eventually arrives at correct answers, the process is convoluted and lacks explanation or alternative strategies. In the summarization task, the agent also included information not requested in the prompt.

Overall Conclusion

Gemini 1.5 Flash 8B is a powerful tool for language understanding, information retrieval, and creative generation.
Its ability to produce well-structured, comprehensive, and engaging content is impressive. However, its current limitations in numerical reasoning and problem-solving indicate a need for significant improvement. Future development should enhance its mathematical capabilities, integrate appropriate tools, and refine its thought process for efficiency and transparency. Stronger adherence to instructions, especially regarding extra information, is also needed.

In its current state, Gemini 1.5 Flash 8B is best for language and creativity tasks, while caution is advised for complex calculations or intricate problem-solving. Future improvements will be crucial for unlocking its full potential as a versatile and reliable AI agent.