ARC is a Vision Problem! (Paper Review)
Author(s): Hira Ahmad Originally published on Towards AI. ARC is a Vision Problem! (Paper Review) Non-members can read for review Source ImageThe article discusses the re-framing of the Abstraction and Reasoning Corpus (ARC) as a vision problem, advocating for the use of …
The Geometry of Learning: How Machines Understand the World Through Shape, Distance, and Meaning
Author(s): Hira Ahmad Originally published on Towards AI. Introduction: Why Geometry Is the True Language of AI Underneath the code and data, machine learning is essentially pure geometry, using concepts like shadows, angles, and spaces to determine various outcomes. This is the …
Exploring Cutting-Edge Alternatives to Transformer-Based LLMs
Author(s): Hira Ahmad Originally published on Towards AI. Exploring Cutting-Edge Alternatives to Transformer-Based LLMs Large language models, such as the prominent DeepSeek R1 and MiniMax-M2, have primarily utilized a specific type of AI architecture called autoregressive decoder-style transformers. Built on multi-head attention, …
The Rise of Generative AI Agents: From Concept to Enterprise-Grade Systems
Author(s): Hira Ahmad Originally published on Towards AI. Introduction: The Emergence of Agentic AI Generative AI has evolved beyond content generation. Modern AI agents are autonomous, collaborative, and continuously learning entities capable of reasoning, acting, and interacting with humans, other agents, and …
Agentic AI: How Intelligence Learns to Work, Decide, and Evolve on Its Own
Author(s): Hira Ahmad Originally published on Towards AI. Power: Doing More with Less Energy Artificial intelligence is moving beyond simple instructions and fixed responses. We’re now entering the age of agentic AI where systems that can think, plan, and act in dynamic …
Diffuse and Disperse: Image Generation with Representation Regularization (Paper Review)
Author(s): Hira Ahmad Originally published on Towards AI. Diffuse and Disperse: Image Generation with Representation Regularization (Paper Review) Diffusion models have redefined the frontiers of generative AI, capable of transforming noise into highly structured, realistic images. But as these models grow, a …
Continual Learning via Sparse Memory Finetuning (Paper Review)
Author(s): Hira Ahmad Originally published on Towards AI. Continual Learning via Sparse Memory Finetuning (Paper Review) Modern large language models learn vast amounts of knowledge; yet when we try to teach them something new, they tend to forget what they already know. …
DeepSeek-OCR: Contexts Optical Compression (Paper Review)
Author(s): Hira Ahmad Originally published on Towards AI. The Shift from Recognition to Understanding From recognizing letters to reasoning through meaning, DeepSeek-OCR redefines what it means for machines to read. Source ImageDeepSeek-OCR revolutionizes optical character recognition by integrating comprehension and contextual reasoning …
Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models (Paper Review)
Author(s): Hira Ahmad Originally published on Towards AI. Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models (Paper Review) Intelligence is not in thinking long, it’s in thinking right.In the race to make machines reason like humans, we’ve trained models …
Less is More: Recursive Reasoning with Tiny Networks (Paper Review)
Author(s): Hira Ahmad Originally published on Towards AI. Less is More: Recursive Reasoning with Tiny Networks (Paper Review) Modern AI often chases scale: deeper layers, more attention heads, and billions of parameters. But hidden beneath this race lies a quieter revolution: recursive …
The Evolving Vision: From Block World to Intelligent Perception
Author(s): Hira Ahmad Originally published on Towards AI. The Evolving Vision: From Block World to Intelligent Perception In the vast history of artificial intelligence, vision has remained one of its most profound and persistent pursuits not merely to capture what humans see, …
When Transformers Multiply Their Heads: What Increasing Multi-Head Attention Really Does
Author(s): Hira Ahmad Originally published on Towards AI. When Transformers Multiply Their Heads: What Increasing Multi-Head Attention Really Does Transformers have become the backbone of many AI breakthroughs, in NLP, vision, speech, etc. A central component is multi-head self-attention: the notion that …
LLM Evaluation Methods: Integrating Binary Evals with Score Evals
Author(s): Hira Ahmad Originally published on Towards AI. LLM Evaluation Methods: Integrating Binary Evals with Score Evals Evaluating large language models (LLMs) is a bit like checking a student’s exam paper, you can grade by impression or you can check each answer …
Deep Reflection: How Modern LLMs are Redefining The Meaning of Writing
Author(s): Hira Ahmad Originally published on Towards AI. Beyond Function: The Search for Understanding Sometimes I wonder if we truly understand what we’ve created. These language models, magnificent in design and frightening in consequence, have begun to speak like us, yet they …
AI Roadmap: Foundation Models and Beyond
Author(s): Hira Ahmad Originally published on Towards AI. AI Roadmap: Foundation Models and Beyond Artificial Intelligence has evolved into an ecosystem of frameworks, architectures, and methodologies that together define how we build and understand intelligent systems today. Whether you’re beginning your journey …
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