IBM TechXchange Group

To All IBM Collaborative Team Members,

I am thrilled to share the latest developments in our collaborative project with IBM., made possible through the exceptional support and facilitation by Mrs. Olugbemisola Aruwayo-Obe, IBM Country General Manager for Nigeria. Our recent visit to the IBM office in Lagos was not only inspiring but also highly productive, strengthening our partnership and paving the way for groundbreaking advancements.

TopneunetAI's Breakthrough: Achieving 99.9% Time Series Prediction Accuracy in Key Domains

We are excited to announce that TopneunetAI has set a new industry benchmark to reach an unprecedented 99.9% prediction accuracy in critical fields such as financial forecasting, population dynamics, and weather signals. This success is part of our joint go-to-market strategy with IBM, integrating advanced technologies to transform predictive analytics.

Precision Across Eras of Time Series Predictive Analytics:

·         Early Era (1 < A ≤ 7.2%): Leveraging mathematical equations, differential equations, and dynamical systems for predictive analytics.

·         Current Trend (A ≥ 7.2%): Utilizing current IBM's machine learning algorithms with trial-and-error activation functions for enhanced predictive capabilities.

·         TopneunetAI's Breakthrough (7.2% ≤ A → 99.9%): Implementing our innovative solutions to achieve unparalleled accuracy.

 

Table of Summary:

Our Mission

TopneunetAI is committed to revolutionizing prediction accuracy, setting a new standard at 99.9% across vital domains. Our groundbreaking solutions enhance decision-making in areas such as:

·         Financial forecasting

·         Energy demand prediction

·         Stock and cryptocurrency market predictions

·         Weather (climate) forecasting

·         Healthcare forecasting

Overcoming Current Challenges

·         Managing high-dimensional data

·         Ensuring interpretability of machine learning models

·         Incorporating domain knowledge effectively

·         Addressing non-stationarity and seasonality in data

·         Enhancing accuracy, scalability, and computational efficiency

Value Add of TopneunetAI Models

Key value propositions include:

·         Data-driven activation function selection

·         Dynamic approach to model development

·         Diverse range of forecasting models

·         Robust solutions for complex challenges

·         Ethical and transparent forecasting practices

Results and Performance Metrics:

In the initial stages of prototype model development, we leveraged a span of historical data from Yahoo Finance, covering the period from March 31, 2021, to March 31, 2001 (roughly 20 years). To assess the performance of our solution, a comprehensive test was conducted, comparing Zaitun Time Series software's built-in activation functions (Sigmoid, Tanh, Semi Linear, and Bipolar Sigmoid - an industry benchmark) with the advanced activation functions of Topneunet (our proprietary algorithm) Time Series Software. Using the Microsoft Corporation Stock Prices data and applying a norm that prioritizes predictions with minimal error and Mean Absolute Error (MAE), the following results were obtained.

Results from Zaitun Time Series Software:

1.     Sigmoid: Error = 0.15312, MAE = 0.25340

2.     Tanh: Error = 0.28370, MAE = 0.21935

3.     Semi Linear: Error = 0.15002, MAE = 0.25991

4.     Bipolar Sigmoid: Error = 0.33859, MAE = 0.25753

Results from Topneunet Time Series Software:

1.     Cubic Logistic Logistic Logistic: Error = 0.0958, MAE = 0.2224

2.     Exponential Linear Logistic Logistic: Error = 0.0442, MAE = 0.1598

3.     Exponential Logistic Logistic Logistic: Error = 0.0652, MAE = 0.1915

4.     Gaussian Logistic Logistic Quadratic: Error = 0.0566, MAE = 0.1796

5.     Linear Logistic Logistic Logistic: Error = 0.0711, MAE = 0.2075

6.     Exponential Gaussian Gaussian Gaussian: Error = 0.0456, MAE = 0.1619

7.     Gaussian Gaussian Gaussian Logistic: Error = 0.0494, MAE = 0.1702

8.     Gaussian Logistic Logistic: Error = 0.0378, MAE = 0.1489

9.     Cubic Gaussian Gaussian Gaussian: Error = 0.0467, MAE = 0.1633

10.  Logistic Logistic Logistic: Error = 0.0655, MAE = 0.1970

11.  Gaussian Gaussian Quadratic: Error = 0.0528, MAE = 0.1753

12.  Gaussian Gaussian Gaussian Gaussian: Error = 0.0648, MAE = 0.1949

13.  Gaussian Gaussian Gaussian Linear: Error = 0.0526, MAE = 0.1769

14.  Cubic Exponential Gaussian Gaussian: Error = 0.0586, MAE = 0.1840

15.  Exponential Gaussian Gaussian Logistic: Error = 0.0617, MAE = 0.1801

16.  Constant Gaussian Logistic: Error = 0.0575, MAE = 0.1782

Comparative Analysis:

The forecast errors and Mean Absolute Errors (MAEs) produced by Zaitun Time Series Software are consistently larger across all of its activation functions compared to those generated by Topneunet Time Series Software. Consequently, the predictions of Topneunet outshine those of Zaitun in all 16 activation functions during the prototype stage, exhibiting a superior accuracy of at least 30%. This significant performance difference underscores the commercial viability and establishes the compelling commercial interests associated with Topneunet's predictive capabilities.

Strengthening Strategic IBM-TopneunetAI Partnership:

1.   Strategic Collaboration with IBM Nigeria:

Our interaction with Mrs. Aruwayo-Obe and her dedicated team, especially Mr. Adeyemi Ogunade, has been pivotal. Their gracious reception allowed us to present our innovative solutions and propose forward-thinking strategies. Mrs. Aruwayo-Obe's leadership in public relations, strategic direction, and problem-solving has been revitalizing for our collaboration.

2.   IBM Service Track Partner Benefits:

As an IBM Plus Partner under the New Service Track (Build Partner) Accelerator program, we have been promised significant support, including Cloud Credit, Technical Experts Engagement, and Market Demand Generation. However, these benefits are yet to be utilized due to technical gaps identified during our interactions with our key IBM contributors. Specifically, the scarcity of Technical Experts specializing in Time Series and Evolutionary Algorithms has hindered our progress. Consequently, the project is still ongoing with IBM teams, and we have no examples of success with clients to report at this stage.

3.   Addressing Technical Gaps:

Our discussions highlighted a critical gap: the scarcity of Technical Experts specializing in Time Series and Evolutionary Algorithms. To bridge this gap, we propose leveraging our partnership with Toptal LLC to recruit these experts, ensuring our project's success and furthering AI advancements.

4.   Proposed Key Actions:

·         Funding Acquisition: Collaborate with IBM Nigeria to secure funds from the $500 Million Enterprise AI Venture Fund, aimed at fostering innovation and strategic partnerships.

·         Expert Recruitment: Use the acquired funds to hire specialized Technical Experts in Time Series and Evolutionary Algorithms.

·         Supervision and Monitoring: Ensure ongoing supervision and support from IBM's esteemed Research Team and the IBM Country Office (Nigeria) to guarantee successful project completion.

Use cases with IBM technology 

Below are the use cases showcasing the integration of IBM technologies in our projects.

1.    Watsonx.ai: Enhancing Predictive Analytics:

Use Case: Financial Forecasting

Challenge: Financial institutions face challenges in predicting market trends, leading to inconsistent investment strategies and financial instability.

Solution:

·         Watsonx.ai provides advanced machine learning algorithms to analyze historical data and identify patterns.

·         Impact: TopneunetAI has achieved a 99.9% prediction accuracy, enabling financial institutions to make informed investment decisions, enhance investor confidence, and ensure consistent returns.

2.    Watsonx.data: Optimizing Data Management

Use Case: Energy Demand Prediction

Challenge: Energy companies need to predict demand accurately to avoid overproduction or shortages.

Solution:

·         Watsonx.data facilitates the integration and analysis of large datasets from various sources.

·         Impact: TopneunetAI's models, powered by Watsonx.data, optimize energy production, reduce waste, and ensure a stable supply, resulting in significant cost savings.

3.    Quantum System Two: Pioneering Advanced Research

Use Case: Climate Change Modeling

Challenge: Traditional computing methods are inadequate for the complex calculations required in climate change modeling.

Solution:

·         Quantum System Two offers unparalleled computational power to simulate climate models with high precision.

·         Impact: By leveraging quantum computing, TopneunetAI can provide highly accurate climate forecasts, aiding policymakers in making informed decisions to combat climate change.

4.    IBM Multivariate Time Series with AutoAI Platform

Use Case: Stock Market Predictions

Challenge: Predicting stock market trends involves analyzing multiple variables simultaneously, which is challenging with conventional methods.

Solution:

·         IBM Multivariate Time Series with AutoAI Platform automates the process of building and optimizing predictive models.

·         Impact: This platform has enabled TopneunetAI to achieve superior accuracy in stock market predictions, empowering investors to make strategic decisions and enhancing market stability.

5.    IBM Expertise

Use Case: Ongoing Project Supervision and Support

Challenge: Ensuring the successful completion of complex AI projects requires continuous expert supervision and support.

Solution:

·         IBM Expertise: We leverage IBM's esteemed research team, the masterminds behind the IBM Multiple Time Series AutoAI Platform, along with the ongoing support and supervision of the IBM Country Office in Nigeria.

·         Impact: This collaboration ensures the seamless execution of our projects, overcoming technical gaps and achieving significant milestones in AI innovation.

6.    Watsonx.ai: Enhancing Predictive Analytics

Use Case: Financial and Weather Earnings Trends Prediction

Stage 1: Crafting ChartMAE-Zero

·         Watsonx.ai powers AI-Driven Smart Insights and Creative Generative AI, enabling the platform to analyze vast datasets and provide accurate, actionable insights.

·         Impact: Achieves 99.9% prediction accuracy in financial forecasting and weather signals, setting new industry standards.

7.    Watson Assistant: Revolutionizing User Interaction

Use Case: Dynamic Visualization and Data Exploration

Stage 1: Natural Language to Vega-Lite Visualization

·         Watson Assistant facilitates conversational analysis, allowing users to interact with data through natural language queries.

·         Impact: Enhances user engagement and understanding by simplifying complex data into intuitive visualizations.

8.    Watsonx.data: Optimizing Data Management

Use Case: Energy Demand and Financial Forecasting

Stage 2: Pattern Recognition Algorithm and Neural Network Diagrams

·         Watsonx.data supports the integration and analysis of large datasets, enhancing the system's ability to detect and interpret complex patterns.

·         Impact: Enables precise energy demand predictions and accurate financial trend forecasting, optimizing resource allocation and investment strategies.

9.    Quantum System Two: Pioneering Advanced Research

Use Case: Climate Change Modeling and High-Dimensional Data Analysis

Stage 3: Harmonious Fusion of Elements

·         Quantum System Two provides unparalleled computational power for simulating complex models and handling high-dimensional data.

·         Impact: Offers unprecedented accuracy in climate change modeling and financial trend analysis, driving informed decision-making.

10. IBM Multivariate Time Series with AutoAI Platform

Use Case: Stock Market Predictions and Multimedia Transformation

Stage 4: Introducing ChartMAE-Zero

·         IBM Multivariate Time Series with AutoAI Platform automates the creation and optimization of predictive models, transforming rich analytics into text, audio, and video formats.

·         Impact: Ensures data insights are accessible and engaging across various media, enhancing user experience and comprehension.

11. Watson Assistant: Revolutionizing User Interaction

Use Case: Dynamic Visualization and Data Exploration

Stage 1: Natural Language to Vega-Lite Visualization

·         Watson Assistant facilitates conversational analysis, allowing users to interact with data through natural language queries.

·         Impact: Enhances user engagement and understanding by simplifying complex data into intuitive visualizations.

Users of IBM-TopneunetAI APIs and ChartMAE-Zero Interactive Platform

APIs Users:

1. Crypto-Currency Exchange Platforms: Enhance trading decisions with predictive crypto signals.
2. Stock Trading Signal Platforms: Offer predictive stock signals for informed trading.
3. Currency Signal Platforms: Navigate the forex market with predictive currency signals.
4. Climate Platforms: Manage assets better with predictive weather signals.
5. Data Scientists and Engineers: Utilize APIs for advanced data analysis and application development.

ChartMAE-Zero Platform Users:

1. Investors: Make informed investment decisions.
2. Brokers and Traders: Rely on real-time trading insights for stocks, currencies, ETFs, and crypto-currencies.
3. Financial Analysts: Conduct market analysis and forecasting.
4. Financial Planners: Implement strategic planning with the platform's insights.
5. Fund Managers: Optimize portfolio management.
6. Forecasters: Economic, financial, climate, and population forecasting.
7. Researchers, Teachers, and Students: Use the platform for educational and research purposes.
8. Modellers: Build and test predictive models.
9. Data Scientists and Engineers: Utilize the platform for data-driven decision-making and application development

Top Solution Areas Using IBM Technology

IBM's Cutting-Edge Research

IBM's distinguished research team has achieved a breakthrough in automating Multiple Time Series Forecasting by employing Trial-and-Error Activation Functions, along with hyperband/Bayesian optimization for hyperparameter search and hyperband/ENAS/DARTS for Neural Architecture Search. This endeavor has culminated in the development of IBM's AutoAI platform for multiple time series forecasting.

TopneunetAI's Strategic Objective

Collaborating with IBM's esteemed research team and leveraging the expertise of technical professionals in AI and ML, TopneunetAI sets out to automate Multiple Time Series Forecasting using Data-driven Activation Functions. This will be facilitated through the utilization of Advanced NAS, with the help of IBM's 'Service Track'.

Acknowledgments and Appreciation

Our collaboration with IBM has opened remarkable opportunities, and we extend our heartfelt gratitude to:

IBM Leadership: Under the visionary leadership of CEO Arvind Krishna, emphasizing Hybrid Cloud and facilitating work across various platforms.

Key IBM Contributors: Mrs. Aruwayo-Obe, Mr. Adeyemi Ogunade, Rani Patel, Ahmed Mohamed Abdel-Aziz, Brooks Brooks Barhydt, Grant Millar, Boakye Acheampong, Peter Redeky, Sumeet Kapoor, Deepa Manchikanti, Jean-Luc Collet, Abdelouahed El Marouani, Viviana Marin, Andrew Muwanga, and Velma Amondi.

Their unwavering support and collaboration have been instrumental in keeping our partnership vibrant and progressive. Special recognition goes to the IBM Research Team, whose innovative efforts have been crucial to our shared success.

Next Steps:

We are committed to leveraging these advancements to drive significant milestones in AI evolution, fostering innovation not only in Nigeria but across Africa.

Thank you once again for your support IBM, and we look forward to our continued collaboration.

Jamilu Adamu

Founder/CEO, Top Artificial Neural Network Ltd (10063p)

Mobile/Whatsapp: +2348038679094

------------------------------
Jamilu Adamu
CEO
Top Artificial Neutral Network Ltd (TopneunetAI)
Kano
+2348038679094
------------------------------

Thank you for the post. Especially looking forward to:
Quantum system 2
Climate change modeling and high dimensional data analysis


Original Message:
Sent: 7/21/2024 7:01:00 PM
From: Jamilu Adamu
Subject: Win Wire: IBM-TopneunetAI Partnership and Breakthrough Achievements

To All IBM Collaborative Team Members,

I am thrilled to share the latest developments in our collaborative project with IBM., made possible through the exceptional support and facilitation by Mrs. Olugbemisola Aruwayo-Obe, IBM Country General Manager for Nigeria. Our recent visit to the IBM office in Lagos was not only inspiring but also highly productive, strengthening our partnership and paving the way for groundbreaking advancements.

TopneunetAI's Breakthrough: Achieving 99.9% Time Series Prediction Accuracy in Key Domains

We are excited to announce that TopneunetAI has set a new industry benchmark to reach an unprecedented 99.9% prediction accuracy in critical fields such as financial forecasting, population dynamics, and weather signals. This success is part of our joint go-to-market strategy with IBM, integrating advanced technologies to transform predictive analytics.

Precision Across Eras of Time Series Predictive Analytics:

·         Early Era (1 < A ≤ 7.2%): Leveraging mathematical equations, differential equations, and dynamical systems for predictive analytics.

·         Current Trend (A ≥ 7.2%): Utilizing current IBM's machine learning algorithms with trial-and-error activation functions for enhanced predictive capabilities.

·         TopneunetAI's Breakthrough (7.2% ≤ A → 99.9%): Implementing our innovative solutions to achieve unparalleled accuracy.

 

Table of Summary:

Our Mission

TopneunetAI is committed to revolutionizing prediction accuracy, setting a new standard at 99.9% across vital domains. Our groundbreaking solutions enhance decision-making in areas such as:

·         Financial forecasting

·         Energy demand prediction

·         Stock and cryptocurrency market predictions

·         Weather (climate) forecasting

·         Healthcare forecasting

Overcoming Current Challenges

·         Managing high-dimensional data

·         Ensuring interpretability of machine learning models

·         Incorporating domain knowledge effectively

·         Addressing non-stationarity and seasonality in data

·         Enhancing accuracy, scalability, and computational efficiency

Value Add of TopneunetAI Models

Key value propositions include:

·         Data-driven activation function selection

·         Dynamic approach to model development

·         Diverse range of forecasting models

·         Robust solutions for complex challenges

·         Ethical and transparent forecasting practices

Results and Performance Metrics:

In the initial stages of prototype model development, we leveraged a span of historical data from Yahoo Finance, covering the period from March 31, 2021, to March 31, 2001 (roughly 20 years). To assess the performance of our solution, a comprehensive test was conducted, comparing Zaitun Time Series software's built-in activation functions (Sigmoid, Tanh, Semi Linear, and Bipolar Sigmoid - an industry benchmark) with the advanced activation functions of Topneunet (our proprietary algorithm) Time Series Software. Using the Microsoft Corporation Stock Prices data and applying a norm that prioritizes predictions with minimal error and Mean Absolute Error (MAE), the following results were obtained.

Results from Zaitun Time Series Software:

1.     Sigmoid: Error = 0.15312, MAE = 0.25340

2.     Tanh: Error = 0.28370, MAE = 0.21935

3.     Semi Linear: Error = 0.15002, MAE = 0.25991

4.     Bipolar Sigmoid: Error = 0.33859, MAE = 0.25753

Results from Topneunet Time Series Software:

1.     Cubic Logistic Logistic Logistic: Error = 0.0958, MAE = 0.2224

2.     Exponential Linear Logistic Logistic: Error = 0.0442, MAE = 0.1598

3.     Exponential Logistic Logistic Logistic: Error = 0.0652, MAE = 0.1915

4.     Gaussian Logistic Logistic Quadratic: Error = 0.0566, MAE = 0.1796

5.     Linear Logistic Logistic Logistic: Error = 0.0711, MAE = 0.2075

6.     Exponential Gaussian Gaussian Gaussian: Error = 0.0456, MAE = 0.1619

7.     Gaussian Gaussian Gaussian Logistic: Error = 0.0494, MAE = 0.1702

8.     Gaussian Logistic Logistic: Error = 0.0378, MAE = 0.1489

9.     Cubic Gaussian Gaussian Gaussian: Error = 0.0467, MAE = 0.1633

10.  Logistic Logistic Logistic: Error = 0.0655, MAE = 0.1970

11.  Gaussian Gaussian Quadratic: Error = 0.0528, MAE = 0.1753

12.  Gaussian Gaussian Gaussian Gaussian: Error = 0.0648, MAE = 0.1949

13.  Gaussian Gaussian Gaussian Linear: Error = 0.0526, MAE = 0.1769

14.  Cubic Exponential Gaussian Gaussian: Error = 0.0586, MAE = 0.1840

15.  Exponential Gaussian Gaussian Logistic: Error = 0.0617, MAE = 0.1801

16.  Constant Gaussian Logistic: Error = 0.0575, MAE = 0.1782

Comparative Analysis:

The forecast errors and Mean Absolute Errors (MAEs) produced by Zaitun Time Series Software are consistently larger across all of its activation functions compared to those generated by Topneunet Time Series Software. Consequently, the predictions of Topneunet outshine those of Zaitun in all 16 activation functions during the prototype stage, exhibiting a superior accuracy of at least 30%. This significant performance difference underscores the commercial viability and establishes the compelling commercial interests associated with Topneunet's predictive capabilities.

Strengthening Strategic IBM-TopneunetAI Partnership:

1.   Strategic Collaboration with IBM Nigeria:

Our interaction with Mrs. Aruwayo-Obe and her dedicated team, especially Mr. Adeyemi Ogunade, has been pivotal. Their gracious reception allowed us to present our innovative solutions and propose forward-thinking strategies. Mrs. Aruwayo-Obe's leadership in public relations, strategic direction, and problem-solving has been revitalizing for our collaboration.

2.   IBM Service Track Partner Benefits:

As an IBM Plus Partner under the New Service Track (Build Partner) Accelerator program, we have been promised significant support, including Cloud Credit, Technical Experts Engagement, and Market Demand Generation. However, these benefits are yet to be utilized due to technical gaps identified during our interactions with our key IBM contributors. Specifically, the scarcity of Technical Experts specializing in Time Series and Evolutionary Algorithms has hindered our progress. Consequently, the project is still ongoing with IBM teams, and we have no examples of success with clients to report at this stage.

3.   Addressing Technical Gaps:

Our discussions highlighted a critical gap: the scarcity of Technical Experts specializing in Time Series and Evolutionary Algorithms. To bridge this gap, we propose leveraging our partnership with Toptal LLC to recruit these experts, ensuring our project's success and furthering AI advancements.

4.   Proposed Key Actions:

·         Funding Acquisition: Collaborate with IBM Nigeria to secure funds from the $500 Million Enterprise AI Venture Fund, aimed at fostering innovation and strategic partnerships.

·         Expert Recruitment: Use the acquired funds to hire specialized Technical Experts in Time Series and Evolutionary Algorithms.

·         Supervision and Monitoring: Ensure ongoing supervision and support from IBM's esteemed Research Team and the IBM Country Office (Nigeria) to guarantee successful project completion.

Use cases with IBM technology 

Below are the use cases showcasing the integration of IBM technologies in our projects.

1.    Watsonx.ai: Enhancing Predictive Analytics:

Use Case: Financial Forecasting

Challenge: Financial institutions face challenges in predicting market trends, leading to inconsistent investment strategies and financial instability.

Solution:

·         Watsonx.ai provides advanced machine learning algorithms to analyze historical data and identify patterns.

·         Impact: TopneunetAI has achieved a 99.9% prediction accuracy, enabling financial institutions to make informed investment decisions, enhance investor confidence, and ensure consistent returns.

2.    Watsonx.data: Optimizing Data Management

Use Case: Energy Demand Prediction

Challenge: Energy companies need to predict demand accurately to avoid overproduction or shortages.

Solution:

·         Watsonx.data facilitates the integration and analysis of large datasets from various sources.

·         Impact: TopneunetAI's models, powered by Watsonx.data, optimize energy production, reduce waste, and ensure a stable supply, resulting in significant cost savings.

3.    Quantum System Two: Pioneering Advanced Research

Use Case: Climate Change Modeling

Challenge: Traditional computing methods are inadequate for the complex calculations required in climate change modeling.

Solution:

·         Quantum System Two offers unparalleled computational power to simulate climate models with high precision.

·         Impact: By leveraging quantum computing, TopneunetAI can provide highly accurate climate forecasts, aiding policymakers in making informed decisions to combat climate change.

4.    IBM Multivariate Time Series with AutoAI Platform

Use Case: Stock Market Predictions

Challenge: Predicting stock market trends involves analyzing multiple variables simultaneously, which is challenging with conventional methods.

Solution:

·         IBM Multivariate Time Series with AutoAI Platform automates the process of building and optimizing predictive models.

·         Impact: This platform has enabled TopneunetAI to achieve superior accuracy in stock market predictions, empowering investors to make strategic decisions and enhancing market stability.

5.    IBM Expertise

Use Case: Ongoing Project Supervision and Support

Challenge: Ensuring the successful completion of complex AI projects requires continuous expert supervision and support.

Solution:

·         IBM Expertise: We leverage IBM's esteemed research team, the masterminds behind the IBM Multiple Time Series AutoAI Platform, along with the ongoing support and supervision of the IBM Country Office in Nigeria.

·         Impact: This collaboration ensures the seamless execution of our projects, overcoming technical gaps and achieving significant milestones in AI innovation.

6.    Watsonx.ai: Enhancing Predictive Analytics

Use Case: Financial and Weather Earnings Trends Prediction

Stage 1: Crafting ChartMAE-Zero

·         Watsonx.ai powers AI-Driven Smart Insights and Creative Generative AI, enabling the platform to analyze vast datasets and provide accurate, actionable insights.

·         Impact: Achieves 99.9% prediction accuracy in financial forecasting and weather signals, setting new industry standards.

7.    Watson Assistant: Revolutionizing User Interaction

Use Case: Dynamic Visualization and Data Exploration

Stage 1: Natural Language to Vega-Lite Visualization

·         Watson Assistant facilitates conversational analysis, allowing users to interact with data through natural language queries.

·         Impact: Enhances user engagement and understanding by simplifying complex data into intuitive visualizations.

8.    Watsonx.data: Optimizing Data Management

Use Case: Energy Demand and Financial Forecasting

Stage 2: Pattern Recognition Algorithm and Neural Network Diagrams

·         Watsonx.data supports the integration and analysis of large datasets, enhancing the system's ability to detect and interpret complex patterns.

·         Impact: Enables precise energy demand predictions and accurate financial trend forecasting, optimizing resource allocation and investment strategies.

9.    Quantum System Two: Pioneering Advanced Research

Use Case: Climate Change Modeling and High-Dimensional Data Analysis

Stage 3: Harmonious Fusion of Elements

·         Quantum System Two provides unparalleled computational power for simulating complex models and handling high-dimensional data.

·         Impact: Offers unprecedented accuracy in climate change modeling and financial trend analysis, driving informed decision-making.

10. IBM Multivariate Time Series with AutoAI Platform

Use Case: Stock Market Predictions and Multimedia Transformation

Stage 4: Introducing ChartMAE-Zero

·         IBM Multivariate Time Series with AutoAI Platform automates the creation and optimization of predictive models, transforming rich analytics into text, audio, and video formats.

·         Impact: Ensures data insights are accessible and engaging across various media, enhancing user experience and comprehension.

11. Watson Assistant: Revolutionizing User Interaction

Use Case: Dynamic Visualization and Data Exploration

Stage 1: Natural Language to Vega-Lite Visualization

·         Watson Assistant facilitates conversational analysis, allowing users to interact with data through natural language queries.

·         Impact: Enhances user engagement and understanding by simplifying complex data into intuitive visualizations.

Users of IBM-TopneunetAI APIs and ChartMAE-Zero Interactive Platform

APIs Users:

1. Crypto-Currency Exchange Platforms: Enhance trading decisions with predictive crypto signals.
2. Stock Trading Signal Platforms: Offer predictive stock signals for informed trading.
3. Currency Signal Platforms: Navigate the forex market with predictive currency signals.
4. Climate Platforms: Manage assets better with predictive weather signals.
5. Data Scientists and Engineers: Utilize APIs for advanced data analysis and application development.

ChartMAE-Zero Platform Users:

1. Investors: Make informed investment decisions.
2. Brokers and Traders: Rely on real-time trading insights for stocks, currencies, ETFs, and crypto-currencies.
3. Financial Analysts: Conduct market analysis and forecasting.
4. Financial Planners: Implement strategic planning with the platform's insights.
5. Fund Managers: Optimize portfolio management.
6. Forecasters: Economic, financial, climate, and population forecasting.
7. Researchers, Teachers, and Students: Use the platform for educational and research purposes.
8. Modellers: Build and test predictive models.
9. Data Scientists and Engineers: Utilize the platform for data-driven decision-making and application development

Top Solution Areas Using IBM Technology

IBM's Cutting-Edge Research

IBM's distinguished research team has achieved a breakthrough in automating Multiple Time Series Forecasting by employing Trial-and-Error Activation Functions, along with hyperband/Bayesian optimization for hyperparameter search and hyperband/ENAS/DARTS for Neural Architecture Search. This endeavor has culminated in the development of IBM's AutoAI platform for multiple time series forecasting.

TopneunetAI's Strategic Objective

Collaborating with IBM's esteemed research team and leveraging the expertise of technical professionals in AI and ML, TopneunetAI sets out to automate Multiple Time Series Forecasting using Data-driven Activation Functions. This will be facilitated through the utilization of Advanced NAS, with the help of IBM's 'Service Track'.

Acknowledgments and Appreciation

Our collaboration with IBM has opened remarkable opportunities, and we extend our heartfelt gratitude to:

IBM Leadership: Under the visionary leadership of CEO Arvind Krishna, emphasizing Hybrid Cloud and facilitating work across various platforms.

Key IBM Contributors: Mrs. Aruwayo-Obe, Mr. Adeyemi Ogunade, Rani Patel, Ahmed Mohamed Abdel-Aziz, Brooks Brooks Barhydt, Grant Millar, Boakye Acheampong, Peter Redeky, Sumeet Kapoor, Deepa Manchikanti, Jean-Luc Collet, Abdelouahed El Marouani, Viviana Marin, Andrew Muwanga, and Velma Amondi.

Their unwavering support and collaboration have been instrumental in keeping our partnership vibrant and progressive. Special recognition goes to the IBM Research Team, whose innovative efforts have been crucial to our shared success.

Next Steps:

We are committed to leveraging these advancements to drive significant milestones in AI evolution, fostering innovation not only in Nigeria but across Africa.

Thank you once again for your support IBM, and we look forward to our continued collaboration.

Jamilu Adamu

Founder/CEO, Top Artificial Neural Network Ltd (10063p)

Mobile/Whatsapp: +2348038679094

------------------------------
Jamilu Adamu
CEO
Top Artificial Neutral Network Ltd (TopneunetAI)
Kano
+2348038679094
------------------------------