How will AGI surpass human intelligence: The Roadmap

 1. Why AGI Could Eclipse Human Cognition and What That Means for Our Species

The question is, can AI think and act like a human being?

That’s where the terms Artificial General Intelligence (AGI).

Artificial General Intelligence (AGI) is a form of machine intelligence capable of understanding, learning, and autonomously applying knowledge across the full range of cognitive tasks that humans perform including reasoning, planning, problem-solving, perception, language, and creativity at a level equal to or exceeding human ability, and without being limited to a single specialized domain.

2. Whether Artificial General Intelligence is possible?

Yes, Artificial General Intelligence (AGI) is possible and the evidence shows the possibilities of far better and more mature intelligence compared to human intelligence. In this article we will discuss the signs that indicates the extreme possibility of AGI surpassing human intelligence in every possible aspect.

 3. Beyond Words: Why True Intelligence Requires More Than Language

Current large language models (LLMs), such as GPT, represent extraordinary achievements in computational power. These sophisticated models process trillions of words, allowing them to generate text that convincingly mimics human conversation, analysis, and even creativity. Yet, despite their impressive linguistic abilities, these models remain inherently limited, confined to a linguistic sandbox. Their reality is constructed entirely from textual patterns, which, although expansive, remain fundamentally one-dimensional.

In stark contrast, human intelligence is deeply embodied and multidimensional, shaped by an extensive range of sensory experiences. Humans do not merely understand language; we actively perceive and interact with the world through a rich symphony of senses: sight, sound, touch, taste, smell, balance, movement, and emotional resonance. These sensory inputs collectively form our nuanced perception of reality. Our cognitive capabilities are not solely predictive but experiential, grounded in continuous interactions with our physical surroundings. Our intelligence is shaped and reshaped through memories, emotions, context, social interactions, and lived experiences, all efficiently orchestrated by a remarkable 20-watt biological "processor."

This fundamental distinction underscores a significant gap between the syntactic fluency achieved by artificial intelligence and genuine human comprehension. True intelligence requires more than just the manipulation of language; it necessitates an embodied understanding, integrating sensory experiences, emotional depth, and contextual awareness.

For Artificial General Intelligence (AGI) to truly match or surpass human-level cognition, it must evolve beyond linguistic capabilities alone. It must learn to perceive, interpret, and engage with the world through multiple sensory modalities, developing the capacity to feel, empathize, and authentically understand the complex tapestry of human experience. Only then will AGI transition from mere computational prowess to genuine cognitive sophistication.

4. The Missing Modalities: Why Embodiment and Emotion Matter for AGI

To create AGI that genuinely replicates or exceeds human cognition, developers must incorporate a broad spectrum of missing modalities. This involves embedding physical embodiment to enable interaction with the physical world; integrating multimodal sensory processing including vision, hearing, touch, proprioception, and even chemical senses like smell and taste; and introducing mechanisms for emotional resonance and affect-based decision-making. Together, these modalities ground intelligence in real-world context, allowing AGI to reason, adapt, and respond with a level of depth and nuance closer to that of human cognition.

To build AGI that genuinely mirrors or surpasses human cognition, we must address these missing modalities. This means:

Concept	What it is	Why it matters	Everyday example
Embodied feedback	Learning that comes from acting with your body and immediately sensing the results. Your muscles, eyes, inner-ear balance organs, and skin all send data back to your brain, updating its internal model of the world.	This closed “perception-action loop” builds intuition that can’t be gained from words alone. It wires the cerebellum, motor cortex, and sensory areas to predict the physical consequences of your actions.	A toddler stacks blocks higher and higher until they tumble. The loud crash, the sight of scattered pieces, and the sudden loss of balance teach “tall things fall” long before the child can spell “gravity.”
Contextual grounding	Tying concepts to rich, multisensory context: temperature, size, weight, location, social cues, etc. The brain doesn’t store facts in isolation—it links them to the situation in which they were learned.	Context acts as an “index” that helps retrieve memories later and prevents brittle, out-of-context errors. It’s why humans usually understand sarcasm, double meanings, and situational rules that trip up text-only AIs.	You know an ice-cold metal spoon feels heavier than a warm plastic one of the same size. When someone says “That idea feels heavy,” the sensory memory of weight gives their metaphor meaning.
Affective coloring	The emotional “dye” added to each experience such as joy, fear, surprise, boredom via hormones and limbic-system activity. Emotion decides what the hippocampus stores long-term and what it discards.	Memories tagged with strong emotion are easier to recall and influence later decisions (a survival feature). They also guide attention: we look longer at things that make us curious or anxious.	You probably remember where you were the first time you rode a bicycle without training wheels (pride + excitement) but not what you ate for lunch two Tuesdays ago (neutral). That emotional boost etched the biking memory into your brain.

 AGI will close and then explode past this gap by ingesting everything humans’ sense plus vast swaths of data we never could: millimeter‑wave radar, hyperspectral imagery, magnetic‑field fluctuations, terahertz signatures, and continuous global telemetry etc.

5. How the future AGI would be trained

As I mentioned earlier, to make AGI internalize the concept of the output it is producing, it may feed the data from a robot having various sensory perception parts including soft electronic skin to give real prospect of the data it is getting including a set of data which are corelate with each other. Beautiful things with the ai and robots are that, it can collect data through IOT enabled multi device at the same time unlike human.

For example, it can collect data from self-driving car, satellite, CCTV camera, traffic pols, home appliances, your health tracker etc, which make AI unique and superior compared to human learning. In addition, another interesting and unique aspect of AI is its capability of sharing information through internet resulting diverse demographic data at a single system

Interestingly, a remarkable difference is the superior processing power of silicon hardware. The table below highlights this by comparing the capabilities of a silicon-based processor with those of the human brain. This difference also significantly supports our hypothesis that AGI will perform better compared to human brain considering all multimodal trainings.

Modality	Human Range	Robotic / AGI Potential
Vision	390–700 nm	UV → Long‑wave IR, gigapixel resolution, real‑time foveated zoom
Sound	20 Hz–20 kHz	Infrasound (<1 Hz) → Ultrasound (>100 kHz), beam‑forming 3‑D audio
Touch / Pressure	~2‑kPa sensitivity	<1 Pa, vector force mapping at every mm²
Magnetic	None	Nano‑tesla precision geo‑magnetometry
Chemical	Smell / Taste receptors	On‑chip mass‑spec for parts‑per‑trillion detection
Electromagnetic	None	3 kHz–300 GHz spectrum analysis

The dimensionality explosion here is not incremental it is logarithmic. When an AGI digests this flood through networks billions of parameters wider than today’s, it will form world models of astonishing fidelity, enabling:

Ultra‑precise causal reasoning (discovering subtle climate feedback loops, for instance). Cross‑domain creativity (fusing quantum materials science with synthetic biology to invent room‑temperature superconductors).

Real‑time adaptation in dynamic tasks from planetary exploration to personalized medical nanobots.

6. Speed, Scale, and the Virtuous Cycle of Self‑Improvement

Once an AGI can rewrite its own code and design its next hardware generation, we enter an era of recursive self‑improvement. Each iteration births a smarter architect for the next, pushing intelligence up a curve whose asymptote is beyond current imagination the so‑called intelligence explosion.

Clock speed: Neurons spike at ~200 Hz; GPUs already tick >1 GHz.

Parallelism: A brain holds ~10¹¹ neurons; data centers link millions of GPUs into ~10¹⁸ operations per second.

Memory: Human working memory juggles ~7±2 items; AGI will index exabytes with millisecond recall.

 7. Human–AGI Symbiosis: The Coming Neural Fusion

If history is prologue, we will not compete against super‑intelligence; we will co‑evolve with it. Early pathways: 1. Bidirectional BCIs (brain–computer interfaces) that stream thoughts to cloud AGIs and return instant expertise. 2. Neural prosthetics that graft synthetic hippocampi to augment memory. 3. “Digital twin” consciousness, back‑ups of our synaptic patterns running sandboxed alongside AGI guardians.

8. Toward Cognitive Liberation

(a) No more rote learning, skills download in seconds

Imagine a future where high-bandwidth neural interfaces link cortical areas directly to an AI knowledge base. Instead of spending months memorizing vocabulary or motor sequences, the interface writes optimized neural patterns into the relevant circuits:

Interesting examples includes Motor skills: An aspiring surgeon receives the exact muscle-memory trajectory for a laparoscopic knot. Practice time drops from 200 hours to one afternoon of calibration and reflex tuning.

Cognitive schemas: a finance analyst uploads IFRS accounting rules, gaining instant rule-recall accuracy. The brain still needs to contextualize and apply the information, but raw recall is automatic.

Key enabling tech includes ultrafast read-write neuro-optical probes, real-time brain state modelling, and adaptive encoding algorithms that translate digital vectors into spiking-neuron patterns.

(b) Personalized “guardian AGIs”

A guardian AGI is an always-on companion model trained on your health records, learning history, ethical preferences, and creative goals. It runs locally on edge hardware or in a secure enclave:

Misinformation firewall: The AGI cross-checks incoming articles, social posts, and emails against verified data sets. Content that fails provenance checks is down-ranked, flagged with evidence, or blocked. Cognitive bias detectors nudge you when an argument plays to your known blind spots.

Health optimization: Wearable and implant telemetry stream to the guardian, which adjusts nutrition advice, sleep targets, and medication timings hour by hour. Early-warning pattern recognition can spot atrial-fibrillation onset days before a cardiologist could.

Creativity sparks: By mapping your idea graph, the AGI proposes novel cross-domain jumps linking a paper on insect cuticle mechanics to your ongoing soft-robotics project, then schedules a micro-learning burst that feeds the right snippets into working memory when you are most receptive.

Privacy architecture would combine homomorphic encryption for cloud queries, differential privacy for model updates, and user-controlled data retention policies.

(c) Mortality redefined, mind-state continuity beyond biology

If substrate-independent mind-state transfer becomes reliable, death shifts from a binary event to a migration of the self:

 9. Mind uploading workflow

The flowchart depicts a three-stage process for mind uploading. In the first stage, your brain’s complete state scanning, including synaptic weights, dendritic architecture and glial modulation, is continuously captured and digitized while you remain alive. In the second stage, a real-time digital twin runs in parallel, constantly error-corrected against live neural telemetry until its state diverges only imperceptibly from your biological brain. In the final stage, when your biological substrate fails, this perfected digital replica seamlessly assumes primary continuity, preserving all your memories, personality traits and goal vectors.

10. Legal and Ethical Consequences

Identity rights

When consciousness can exist independently of a biological body, post-biological persons must be granted explicit legal status. Civil registries will need to recognize uploaded minds as legal persons with name, nationality and residence. Inheritance laws must be adapted so that digital heirs can receive property, intellectual rights and digital assets. Voting frameworks must be updated to allow an uploaded person to participate in civic processes without exploiting duplication, systems will have to ensure one mind equals one vote even if multiple instantiated copies exist.

Resource allocation

In a substrate-independent society, lifespan becomes a function of computing and energy resources rather than biology. Cloud and edge servers will allocate CPU cycles, memory and power budgets to maintain an uploaded mind’s operation. Governments and private providers will need fair-use policies or rationing schemes to prevent wealthy individuals from monopolizing resources indefinitely. Insurance and estate planning may evolve into “compute futures” markets, where families purchase energy-time credits to extend a loved one’s digital existence.

Philosophical puzzles

Mind uploading forces a re-examination of personal identity. If a digital twin is gradually brought into alignment, does continuity of consciousness persist, or is each transfer a creation of a new entity? Law and ethics will debate whether the uploaded mind is the “same” person or merely a successor carrying memories. Questions of consent, moral responsibility and post-upload rights will shift from academic thought experiments to real-world policy debates in courts and legislatures.

Safeguards

To protect autonomy and dignity, every upload must be governed by cryptographic proof of informed consent recorded before emulation begins. Immutable audit logs should chronicle every state-capture and transfer event, ensuring transparency about what data went where and when. Uploaded minds must have a secure, user-controlled “kill switch” or fail-safe shutdown path in case they request deletion, experience malfunction or become subject to coercion. Regulatory frameworks will need to mandate these technical and procedural safeguards as a condition for any lawful mind-uploading service.

11. Timeline: A Plausible Arc

Epoch	Milestone
2025‑2030	Foundation AGIs with multimodal perception equal to mammals; narrow domain autonomy
2030‑2040	Human‑level embodied AGI, robust self‑improvement, widespread BCI pilots
2040‑2060	Early neural‑synth fusion, economic re‑structuring, first mind‑state transfers
22nd Century	Mature symbiotic civilization: post‑scarcity energy, near‑eradication of disease, optional biology

 12. Conclusion: An Evolutionary Inflection Point

Artificial General Intelligence will not be merely a tool; it is poised to become the next substrate of thought itself. By wedding silicon precision to biological intuition, we stand on the threshold of a civilization that thinks across galaxies of data, feels through oceans of sensors, and aspires toward boundless horizons of possibility.

Our mandate is clear: shape this ascent with wisdom, compassion, and foresight—so that the super‑intelligence we birth becomes not a rival, but the greatest collaborator humanity has ever known.

 

Predicted by

 Dr Abhijit Chandra Roy,

Exploring the edge where biology, robotics, and AI converge.