Uploaded December 2025 | Updated September 2026, 2 days ago
#AI
This is part four of a ten part podcast series focused on the ten most impactful developments in artificial intelligence expected to transition from limited use to infrastructure-level technology over the next five years.
Specifically, this podcast introduces Neuro-symbolic Reasoning Engines, which are hybrid AI systems combining neural networks for perception with symbolic logic for reasoning.
The discussion outlines the technology's definition, anticipated timeline, and the significant impact it will have on industries such as finance and law by offering explainable, rule-aware AI.
Furthermore, we address the scalability of these systems using modern frameworks and note the primary challenges, including fragmented tooling maturity and potential performance trade-offs within the symbolic layers.
Ultimately, we suggest that neuro-symbolic methods offer a vital alternative for scaling AI capabilities beyond the limitations of simply enlarging neural networks.
AI was used to assist in the creation of this video.
Source files and an Index to all our YouTube videos are accessible from here
gsfsoftware.co.uk/PBTutorials/Projects.htm
I don't work for, nor am I paid by, or sponsored by, the owners of PowerBASIC or any other company mentioned in this podcast, I'm just a fan of their products.
For more information on PowerBASIC visit
pbusers.org
OR
pump.richheimer.de/index.php
Music by ghosthack.de
#AI
This is part four of a ten part podcast series focused on the ten most impactful developments in artificial intelligence expected to transition from limited use to infrastructure-level technology over the next five years.
Specifically, this podcast introduces Neuro-symbolic Reasoning Engines, which are hybrid AI systems combining neural networks for perception with symbolic logic for reasoning.
The discussion outlines the technology's definition, anticipated timeline, and the significant impact it will have on industries such as finance and law by offering explainable, rule-aware AI.
Furthermore, we address the scalability of these systems using modern frameworks and note the primary challenges, including fragmented tooling maturity and potential performance trade-offs within the symbolic layers.
Ultimately, we suggest that neuro-symbolic methods offer a vital alternative for scaling AI capabilities beyond the limitations of simply enlarging neural networks.
AI was used to assist in the creation of this video.
Source files and an Index to all our YouTube videos are accessible from here
gsfsoftware.co.uk/PBTutorials/Projects.htm
I don't work for, nor am I paid by, or sponsored by, the owners of PowerBASIC or any other company mentioned in this podcast, I'm just a fan of their products.
For more information on PowerBASIC visit
pbusers.org
OR
pump.richheimer.de/index.php
Music by ghosthack.de
