Neural Networks
Neural networks applied to pattern recognition and prediction tasks, including market data analysis and telemetry-based modeling.
ABXK.AI designs, builds, and operates applied AI systems across different domains, with a focus on real-world use cases and evaluated outcomes.
Explore ProjectsNeural networks applied to pattern recognition and prediction tasks, including market data analysis and telemetry-based modeling.
Machine learning methods used to analyze historical data, test hypotheses, and improve models across different domains.
Automation of data pipelines, model evaluation, and monitoring workflows within applied AI systems.
Data analysis and evaluation used to assess model performance, system behavior, and decision-making processes.
ABXK.AI applies generative AI in real workflows. Under Showcases, we highlight how generative AI is used in practice across music, visuals, and creative systems.
Image generation used in creative workflows, prototyping, and visual experimentation within applied AI systems.
AI-based video generation for faceless content, internal demos, and workflow experimentation.
Speech synthesis and text-to-speech used for testing, automation, and applied content workflows.
Music and audio generation explored as part of creative AI workflows and system experiments.
Applied use of AI for DJ mixing, beat alignment, and creative audio experimentation.
Explore AI tools and platforms used and tested within ABXK.AI projects.
Explore Platforms & ToolsWe implemented a CI/CD pipeline for the AI Trading Platform. This post documents the approach, the types of bugs it catches, and why automated testing matters …
AI adoption in trading is accelerating. Learn why firms that act now gain an advantage, and how our AI trading platform validates this approach through real …
We tested our frozen v0.3 exit strategy across different markets and trading styles. Here is what we learned about CFDs, futures, stocks, and why swing trading …
ABXK.AI is a company focused on building and applying practical AI systems. The work centers on real-world workflows, where AI is used to solve concrete problems, test assumptions, and build systems that can be evaluated, repeated, and improved over time.
ABXK.AI operates across different applied AI domains, including generative AI, data-driven research, and experimental modeling. The focus is on how AI performs in practice — its limits, trade-offs, and measurable outcomes — rather than on trends or tool hype.