About Us
Scope AI Corp. is a Vancouver-based technology company specializing in artificial intelligence (‘AI’). Our flagship product, GEM - General Enterprise Machine Learning, is a proprietary cutting-edge recognition system powered by AI and designed for a wide range of visual recognition applications. Scope is dedicated to continuously enhancing GEM's capabilities, providing businesses of all sizes with a versatile solution to develop their own recognition and visual information systems.
Technology
Our proprietary platform GEM, is your AI Wizard now allowing businesses to create their own object detection, visual information systems and complete neural network.
Scope AI makes AI easy and open for everyone. With GEM available for others to use under their brand, entrepreneurs can build up their companies, sharing in the revenue. This model means any business can use AI without spending a lot. With our intuitive web-interface,a developer, detail user, entrepreneur or full-on enterprise could easily set up an object detection system to run advanced data inference, or build a completely new, never before seen neural network model in real-time.
Scope’s initial target market is the Advertising and gaming industry. Upon successful beta testing, the Company will expand to a number of other industries to meet the demands of businesses. Additional future features include not only the ability to render neural networks but also have the networks hosted by Scope’s SaaS infrastructure and have accessible via sophisticated globally available API’s.
In the future, we plan to expand GEM’s capabilities to include not only the ability to render neural networks but also to host these networks on Scope’s SaaS infrastructure, allowing for seamless access to inference tasks.
What is a Neural Network?
A neural network is a computational model inspired by the structure and functioning of the human brain’s interconnected neurons. It consists of interconnected nodes, called neurons or units, organized in layers. These layers typically include an input layer, one or more hidden layers, and an output layer.
Each neuron receives input signals, processes them through an activation function, and passes the result to the next layer. The connections between neurons have associated weights that adjust during training, allowing the network to learn from data and make predictions or classifications.
Neural networks are widely used in various fields, including machine learning, artificial intelligence, pattern recognition, image and speech recognition, natural language processing, and many others. They have shown remarkable effectiveness in tasks like image recognition, language translation, autonomous driving, and more.
Here is a more simple explanation
Think of a neural network like a sophisticated computer system that mimics how our brains work. It’s made up of interconnected nodes, or units, arranged in layers, similar to how our brain’s neurons are connected.
These layers process information in a step-by-step manner. The first layer takes in the input, like data or images. Then, the information flows through intermediate layers, where complex computations happen. Finally, the output layer gives us the result, whether it’s identifying objects in an image or understanding speech.
Each node in the network receives input, processes it using some rules, and passes it on to the next layer. As the network learns from examples, the connections between nodes adjust their strengths, improving the network’s ability to make accurate predictions or classifications.
Neural networks are incredibly versatile and find applications in various fields like machine learning, artificial intelligence, and pattern recognition. They’ve proven to be highly effective in tasks such as image recognition, language translation, and even autonomous driving.
Essentially, they’re powerful tools that help us tackle complex problems and make sense of vast amounts of data.
Initial Targeted Industries
Advertising
KNOW how well your ads will do before spending time and budget!
GEM can look at how people behave and use that to make ads more personal. This can change the way businesses connect with their audience. For example, GEM can analyze user engagement data to tailor ad content, resulting in more effective and resonant advertising campaigns.
Increase your ROAS!
Gaming
KNOW the best Layout, User flow and provide a custom look and journey for each users!
The online gambling industry is booming, expected to hit over US$107 billion by 2024 and US$138 billion by 2028. This fast-growing market is ready for innovation, and Scope’s GEM platform is here to shake things up. GEM’s AI capabilities can personalize game recommendations, enhance user experiences, and provide developers with valuable insights into player behavior.
How can a Neural Network help the Advertising Industry?
Neural networks can analyze vast amounts of user data, such as browsing history, purchase behavior, demographics, and interests, to create highly targeted advertising campaigns. By understanding individual preferences and behaviors, advertisers can deliver personalized ads that are more likely to resonate with the audience, leading to higher engagement and conversion rates.
Neural networks can forecast consumer trends and preferences based on historical data, allowing advertisers to anticipate future demand and adjust their marketing strategies accordingly. This predictive capability enables advertisers to stay ahead of market changes and optimize their advertising campaigns for maximum effectiveness.
Neural networks can analyze the performance of different ad creatives, such as images, videos, and copy, to determine which elements are most effective in driving user engagement and conversions. By continuously optimizing ad content based on real-time feedback, advertisers can improve the effectiveness of their campaigns and achieve better results.
Neural networks can detect fraudulent activities, such as click fraud and ad fraud, by analyzing patterns and anomalies in user behavior. By identifying and mitigating fraudulent activities, advertisers can ensure that their advertising budgets are spent efficiently and that their ads reach genuine potential customers.
Neural networks can segment the target audience into distinct groups based on their characteristics and behavior, allowing advertisers to tailor their advertising messages to specific customer segments. By delivering relevant and personalized ads to each segment, advertisers can increase the likelihood of conversion and improve the overall ROI of their advertising campaigns.
Overall, neural networks offer advertisers powerful tools for targeting the right audience, optimizing ad content, predicting market trends, detecting fraud, and improving the effectiveness of their advertising campaigns. Harness the power of your own neural network with Scope AI’s GEM.
Industry News
How can a Neural Network help the Gaming Industry?
Neural networks can power advanced artificial intelligence (AI) systems in games, making non-player characters (NPCs) more intelligent and responsive. These AI systems can learn from player behavior, adapt to different strategies, and provide more engaging and challenging gameplay experiences. Neural networks enable NPCs to exhibit complex behaviors, such as learning to navigate environments, solve puzzles, or compete with human players.
Neural networks can generate game content, such as levels, maps, characters, and items, using techniques like generative adversarial networks (GANs). By training on existing game assets, neural networks can create new content that matches the style and aesthetic of the game. This allows developers to generate endless variations of content, keeping the gameplay fresh and exciting for players.
Neural networks can analyze player behavior and preferences to personalize gaming experiences. By tracking player interactions, preferences, and performance metrics, neural networks can provide tailored recommendations, difficulty adjustments, and in-game assistance. This enhances player engagement and retention by delivering more relevant and enjoyable experiences.
Neural networks can accelerate real-time rendering and graphics processing in games. Techniques like deep learning-based denoising and super-resolution can improve the visual quality of game graphics while maintaining performance. Neural networks can also be used for tasks like texture synthesis, animation interpolation, and character animation, enhancing the realism and immersion of gaming environments.
Neural networks can automate game testing and quality assurance processes, helping developers identify bugs, glitches, and performance issues more efficiently. By training neural networks on large datasets of gameplay footage and bug reports, developers can build AI systems that can detect and diagnose problems in games, speeding up the debugging process and improving game quality.
Reasons You Should Incorporate GEM Into Your Business TODAY
By integrating GEM into your operations, you can unlock new opportunities, streamline processes, and stay at the forefront of technological innovation in your industry