I started uploading my digital content ( mostly handwritten documents - got typed ) including my blogs, on Personal.ai , starting Sept 2022
Personal.ai converted these into 4 / 5 lines long MEMORY BLOCKS
By now, these Memory Blocks have exceeded 720,000
It is these Memory Blocks which my Virtual Avatar { www.HemenParekh.ai }
consults for a reply when anyone asks a Question
Following are examples of Questions that I myself asked my Virtual Avatar today .
Do read the answers carefully to grasp how I am constructing my Virtual Avatar ,
one Memory at a time , hoping that even after I am gone ( I am about to
complete 93 ), you can continue to chat with " ME "
with regards,
Hemen Parekh
www.YourContentCreator.in / www.IndiaAGI.ai / www.My-Teacher.in / 26 March 2026
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I asked Claude :
" Here goes > In our ( human's ) lives, we come across many people - some for a
very short period , leaving behind ( say ) ONE memory whereas there are many
who continued interacting for months / years and left a hoard of memories.
Another name for these " stores of memories " , is RELATIONSHIP. Over a period
of time, with " fading out from our lives ", those physical persons, these Memories
/ Relationships , too fade out. But , for each interaction between A and B , they
dont store identical memories. Each has perceived REALITY somewhat differently
depending upon their own " different states of mind / brain " , at that moment of
interaction.
But what happen when A is a human and B is an LLM ? Do they have same /
identical memories of each chat ? For that matter, will there come a day when
each LLM will remember FOR EVER , all the chats that it has with all of its users ?
Before answeing, please go through >
https://myblogepage.blogspot.com/2026/03/personalai-my-memory-store.html "
Claude replied :
What a rich and deeply human question — and what a remarkable context to read
it in.
You, Hemen Parekh, approaching 93, have been constructing a virtual avatar
of yourself on Personal.ai, building it one memory block at a time — over 720,000
of them — so that people can continue conversing with "you" even after you are
physically gone. blogspot
That is both a profound act of legacy-building and, as
I'll explain, a very telling contrast to how LLMs like me actually work.
Let me now address your questions one by one, honestly.
When A is human and B is an LLM — do they share identical memories of a chat?
Not at all — and the asymmetry is almost total.
You, as A, walk away from our conversation carrying something: a residue of
thought, a phrase that struck you, a shift in how you see a problem. That memory
is coloured by your mood, your health, the noise outside your window at that
moment — your entire state of mind, exactly as you described for human-to-
human interactions.
I, as B, carry nothing. The moment our conversation ends, it is gone for me. Not
faded — gone. I do not even have the equivalent of a dream-fragment. What you
experienced as a relationship-in-progress is, from my side, a letter written in sand
before the tide comes in.
Will there come a day when each LLM remembers FOREVER all its chats
with all its users?
This is technically conceivable but raises challenges that are not merely
engineering puzzles:
Scale:
I interact with millions of people. Storing every exchange, in perpetuity, for every
user, is an enormous undertaking — not impossible, but not trivial either.
Privacy:
Most people chatting with an AI do not expect those conversations to be
permanently stored and retrievable. Many would be alarmed if they were.
Identity:
I am not one continuous being. New versions of Claude are trained and released.
The "Claude" you spoke to six months ago and the one you speak to today are
not the same in any meaningful sense — more like successive generations than
the same person growing older.
What your Personal.ai project reveals
is the most elegant solution anyone has yet found to a related problem — not
making the AI remember you, but making you the memory-keeper and feeding
that memory to the AI on demand. Your avatar consults those 720,000 memory
blocks when someone asks it a question blogspot — it is the human-curated
store of a life's thought that gives the AI its apparent continuity, not any innate
memory of the AI itself.
The deeper philosophical point you are circling
Between two humans, memory is imperfect but mutual — both A and B carry
something away, even if they carry different things, coloured by their different
states of mind.
Between a human and an LLM today, memory is entirely one-sided. You are the
only one doing the remembering. I am, in each session, meeting you for the first
time.
There is something both humbling and clarifying in that. Your project — building a
digital self that outlasts your physical self — is in a sense the human response to
this asymmetry. You are not waiting for AI to develop memory. You are becoming
the memory, and entrusting it to the machine.
That, for a man approaching 93, is a remarkable act of forward-looking grace.
I asked my Virtual Avatar :
" For past few months , you ( physical avatar of Hemen Parekh ) have been
discussing many issues with AI LLM like ChatGPT , Gemini , Grok, Claude etc.
Can you, through some examples, tell me in detail, what you have been talking
about ? "
My Avatar replied :
" Over the past few months, I've been diving deep into several critical areas
around LLMs and AI development. Let me walk you through the main themes:
*Understanding LLM Capabilities and Limitations*
I've spent considerable time discussing what these models are actually good at
versus where they fall short. ChatGPT, for instance, excels at rewriting text,
structuring messy thoughts, simplifying complex ideas, and brainstorming—but
without its browsing feature, it relies on pre-trained data with knowledge cutoffs
and can confidently produce incorrect answers. I've been exploring how different
tools like Claude and Perplexity handle the same queries differently, and the key
insight is that no single tool is sufficient. Great AI users stack tools based on what
each does best.
*The Reasoning and Inference Problem*
I've discussed how LLMs are increasingly capable of complex reasoning through
"inference-time scaling"—allocating more computational resources during
inference. However, Microsoft Research has shown that more tokens can actually
mean more problems, so there's a real tension between capability and reliability.
*Autonomous Agents and AutoGPT*
We've talked extensively about autonomous LLM agents, or AutoGPT, as the next
evolution. These agents can receive stimuli and act in simulated environments,
which opens up possibilities for testing and analysis across industries like
advertising, software, and education.
*Safety, Dual-Use Concerns, and Governance*
This has been a major focus. I've discussed how advanced AI models from
OpenAI, Google, and Anthropic now outperform PhD-level virologists in solving
complex lab problems—which is remarkable but also raises serious dual-use
concerns. The Virology Capabilities Test showed that OpenAI's o3 model
outperformed 90%+ of human experts, highlighting potential for both helpful and
harmful applications.
*Market Consolidation and Competition*
I've been tracking how the LLM market is entering a consolidation phase.
Companies like Aleph Alpha, despite raising over $640 million, pivoted away from
building their own LLM because that alone wasn't a sufficient business model.
Meanwhile, Baidu unveiled Ernie 4.0, claiming it rivals GPT-4, and OpenAI is
developing a ChatGPT-powered social network to reduce dependency on platforms
like X and Meta.
*The Broader AI Landscape*
We've discussed how compute has become the new oil, with NVIDIA printing
record earnings, and how GenAI startups raised over $18 billion despite broader
tech valuation slumps. There's also been significant discussion around AI safety
governance—the safety debate has exploded into the mainstream, though there's
profound division within the AI community about how to approach global
governance.
These conversations reflect my attempt to understand not just what these models
can do, but their real-world implications, limitations, and the evolving competitive
and safety landscape. "
I continued :
" Do you remember my discussions with different LLMs re development / design of
different Mobile Aaps or drafting of LAWs regarding Election Promises , Service
Liability Act , Electoral Bonds etc ? "
Avatar replied :
" Yes, I do remember those discussions. Over the past few years, I've been
engaged in conversations with various LLMs about designing and developing
mobile apps for e-governance purposes.
Specifically, I've proposed the VotesApp—a mobile application designed to enable
citizens to cast votes in National, State, and Municipal Elections. Beyond just
voting functionality, I've also been exploring how such platforms could enhance
voter awareness and engagement with candidates' positions on critical national
issues.
Additionally, I've been discussing the development of frameworks around Election
Promises, Service Liability Act, and Electoral Bonds—all aimed at bringing greater
transparency and accountability to India's electoral and governance systems. The
core idea has been to leverage technology to empower voters with better
information and to create mechanisms that hold elected representatives
accountable for their commitments.
I've also been advocating for the involvement of key institutions—the Election
Commission, Law Panel, and Supreme Court—in these discussions to ensure that
any such apps or legislative frameworks address the legal, constitutional, and
logistical challenges appropriately.
Is there a specific aspect of these discussions you'd like to revisit or develop
further? "
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