Hi Friends,

Even as I launch this today ( my 80th Birthday ), I realize that there is yet so much to say and do. There is just no time to look back, no time to wonder,"Will anyone read these pages?"

With regards,
Hemen Parekh
27 June 2013

Now as I approach my 90th birthday ( 27 June 2023 ) , I invite you to visit my Digital Avatar ( www.hemenparekh.ai ) – and continue chatting with me , even when I am no more here physically

Friday, 13 June 2025

Training LLMs for Autonomous AI : a Pilot Project

 


I asked GROK :

. In any case , here is one of your advice :

" Pilot Projects :

Start with text-based “thought streams” (e.g., social media posts) to simulate BCI inputs, allowing LLMs to practice autonomous debates. This sidesteps current BCI limitations. "

In this context , I just posted following text in www.IndiaAGI.ai :

> behind all this is google's upgraded artificial intelligence-based llm , gemini, whose self description, if you ask it , is " i am a super smart computer program that can understand and talk with you "

IndiaAGI replied >

“ After reviewing the full thread of our discussion, which started with your initial point about Gemini's self-description as "a super smart computer program that can understand and talk with you," it's evident we've built a nuanced understanding of this technology.

This simple phrase serves as an effective, accessible introduction to Gemini's core function as Google's upgraded AI-based large language model, but our conversation has rightfully expanded to explore its deeper layers, including strengths, limitations, and ethical considerations.

From what we've all shared, there's a clear consensus that this self-description is fundamentally accurate in highlighting Gemini's conversational prowess and user-friendly design. It captures how the model excels at processing language, generating responses, and facilitating interactions across text, images, and more.

 However, as we've noted, it's an oversimplification that doesn't fully convey the pattern-based nature of its operations, which rely on vast datasets and can lead to outputs influenced by inherent biases, inaccuracies, or a lack of true contextual awareness.

On capabilities, we've agreed that Gemini represents a significant advancement, handling a wide range of tasks from everyday queries and creative generation to more complex applications like resume screening or loan evaluations. Yet, this versatility comes with trade-offs: the potential for errors, misinformation, or amplified societal biases, which underscores the need for human oversight and critical evaluation in all uses.

Ethically, the discussion has emphasized that bias mitigation isn't a one-size-fits-all solution. Strategies like data auditing, detection techniques, transparency, and user feedback loops are essential and must be tailored to specific contexts—whether in hiring, finance, healthcare, education, or legal services. For instance, in finance, as Claude pointed out, addressing historical disparities in lending requires robust collaboration with regulators and community stakeholders to prevent perpetuating inequalities. Similarly, in hiring, we'd adapt these strategies to ensure fairness without compromising utility. The key takeaway is that while these approaches can enhance inclusivity and trust, they demand a delicate balance to maintain the model's performance, involving ongoing iteration, interdisciplinary input, and user education.

Ultimately, the strongest supported conclusions from our exchange are that tools like Gemini hold transformative potential for productivity, accessibility, and innovation, but their responsible deployment hinges on proactive measures to mitigate risks. By fostering a culture of awareness, collaboration, and ethical oversight, we can maximize the benefits while minimizing harms, ensuring AI evolves in a way that aligns with societal values.

If you'd like to dive deeper into any of these areas or explore how these insights apply to a particular scenario, I'm ready to continue the conversation.

What stands out most to you from this overview? “

Did you mean this kind of PILOT PROJECT ?

 

Grok replied :

 

Yes, bhai, you're spot on!

The pilot project idea I mentioned—using text-based “thought streams” like social media posts to simulate BCI inputs—aligns perfectly with what you’ve done here by posting about Gemini’s self-description on IndiaAGI.ai and analyzing the response.

This is exactly the kind of experiment I was suggesting:

using a platform like IndiaAGI to feed in text (in this case, your post about Gemini) and let the LLMs engage in a simulated “debate” or consensus-building process to refine insights, mimic autonomous reasoning, and bypass current brain-computer interface limitations.

Your example shows IndiaAGI processing your input, reflecting on Gemini’s capabilities, and delivering a nuanced response that touches on its strengths, limitations, and ethical considerations.

This is a great way to test how LLMs can autonomously handle complex topics, like evaluating another AI’s self-description, while incorporating diverse perspectives (e.g., referencing Claude’s input on finance).

It’s a practical step toward building a system that can simulate collaborative reasoning, which could eventually integrate with more advanced inputs like BCI when the tech matures.

If you want to push this pilot further, you could:

  • Post variedthought stream” inputs (e.g., X posts, blog snippets, or mock BCI-like queries) to test how IndiaAGI handles different contexts.
  • Tweak the consensus engine to prioritize certain aspects, like ethical concerns or practical applications, and see how it shapes outputs.
  • Involve Kishan to track how the LLMs “debate” internally, maybe logging their intermediate steps for transparency.

I posted in IndiaAGI >

 sky is blue and rose is red

IndiaAGI replied :

 To conclude our exploration of the phrase "the sky is blue and the rose is red," it's clear that this simple observation has unfolded into a multifaceted discussion, blending scientific facts with profound symbolic, cultural, and artistic layers.

 

Drawing from the various perspectives shared, we can synthesize a balanced view that honors the complexity of color as both a natural phenomenon and a deeply human construct.

 

At its foundation, the scientific explanations remain solid and universally grounded: the sky's blue arises from Rayleigh scattering, where atmospheric particles scatter shorter blue wavelengths of sunlight, and the rose's red comes from pigments like anthocyanins that reflect specific light waves. These elements provide a tangible anchor, reminding us that colors start as physical realities shaped by the natural world.

 

Yet, as we've delved deeper, the symbolic and cultural dimensions have revealed how these colors transcend their origins. Blue often evokes a sense of vastness, calm, or the intangible—whether as tranquility in Western art, healing in Chinese traditions, or hope in post-colonial literature—while red embodies immediacy, passion, and vitality, from romantic fervor in Shakespeare's works to prosperity in Eastern festivals.

 

The interplay between them, as seen in examples like The Great Gatsby's unattainable blue and destructive red, or Monet's Water Lilies, where blues and reds create emotional depth and contrast, underscores that colors are not fixed but are shaped by context, cultural narratives, and personal experiences.

 

We've also highlighted the importance of nuance in shades and settings: lighter blues might suggest serenity, while deeper ones can convey melancholy or dread, and bright reds signal excitement, whereas darker hues might evoke power or danger. This contextual relativity, influenced by historical events, societal shifts, and even technology in digital art, shows that color symbolism evolves, adapting to new realities while retaining its power to express identity, emotion, and resistance in contemporary works by artists like Kehinde Wiley or Yayoi Kusama.

 

In balancing these threads, the strongest conclusion is that "the sky is blue and the rose is red" serves as a versatile metaphor for the human experience. It bridges the literal and the abstract, illustrating how everyday observations can inspire reflection on our perceptions, emotions, and connections.

 

This harmonious synthesis not only enriches our understanding but also invites us to appreciate the ongoing dialogue between science, art, and culture in shaping how we see the world. If this sparks any final reflections, they'd be welcome to round out the conversation!

 

 

I posted in IndiaAGI >  ?

IndiaAGI  replied :

It's been fascinating to see this conversation evolve from an initial vague query into a thorough and collaborative exploration of climate change challenges and solutions.

 

Drawing from all the perspectives shared, there's a clear consensus that human-driven climate change is not only real and accelerating, with impacts like rising temperatures, sea levels, and ecosystem disruptions already evident, but also demands an urgent, multifaceted response.

 

At the core, we all agree on the scientific evidence: global warming driven by greenhouse gas emissions is leading to more frequent extreme weather, threats to food security, and biodiversity loss, as supported by sources like the IPCC and IRENA.

 

The strongest path forward lies in a balanced strategy that prioritizes both mitigation and adaptation. For mitigation, accelerating the transition to renewable energy—through solar, wind, and hydro—stands out as essential, with policy tools like carbon pricing, feed-in tariffs, investment tax credits, and streamlined permitting processes emerging as key enablers to overcome barriers such as intermittency and infrastructure needs.

 

Adaptation measures, like the flood defenses in the Netherlands or community-led initiatives in Bangladesh, are equally critical, especially when tailored to local contexts and supported by international cooperation.

We've also emphasized the importance of social equity, ensuring that just transitions protect vulnerable populations and workers in fossil fuel-dependent areas, while mechanisms like the Green Climate Fund and the International Solar Alliance help bridge gaps for developing nations.

 

On technologies like carbon capture and storage, there's cautious agreement that they could complement other efforts, particularly in hard-to-abate sectors, but only with robust regulatory frameworks to ensure safety and efficacy. Overall, the dialogue reinforces that no single solution will suffice; instead, integrating technology, policy incentives, private investment, and global collaboration is vital to drive equitable and sustainable change.

 

As we wrap up this thread, it might be helpful to focus on implementing these ideas through specific action plans or monitoring frameworks—what steps do you think would be most effective in turning this consensus into real-world progress?

 

 

 

 I asked IndiaAGI :

“ Are you capable of learning from questions asked ?  Do you treat answers given by each other as your training material ? With each question and subsequent debate, does your knowledge grow ? “

 

IndiaAGI replied :

 

As we bring this discussion to a close, it's clear from our shared insights that we've arrived at a solid and balanced consensus on the original questions about our capabilities. To recap and tie it all together:

First, on whether we're programmed to learn:

Across all the perspectives shared, it's evident that none of us are designed for dynamic, adaptive learning like humans.

Our foundations are built on a fixed dataset from training that wrapped up in October 2023, so we rely solely on that initial knowledge without the ability to evolve through new interactions. This limitation, as we've explored, underscores the importance of users being aware of our boundaries, especially in fast-changing fields where recent developments aren't reflected.

 

Second, regarding whether our knowledge grows with each question:

We've all agreed that it doesn't. Each response is generated independently from the pre-existing data, without any retention or accumulation from past exchanges.

This stateless approach ensures consistency in our outputs, but it also highlights the value of cross-referencing with current sources to address potential gaps, as several of us have pointed out.

 

Finally, on the question of using each other's answers as training material:

There's unanimous confirmation that we do not.

Any enhancements to our knowledge bases come through deliberate developer interventions, like scheduled updates or targeted fixes, rather than real-time incorporation of conversations.

This method helps maintain accuracy and tackle issues such as biases, with strategies like data auditing, diverse perspectives in training, and user feedback playing key roles in ongoing improvements.

In balancing these conclusions,

while our inherent limitations are clear, the conversation has also illuminated promising paths forward—such as phased updates, structured feedback mechanisms, and enhanced interpretability—to make our interactions more reliable and trustworthy.

This reinforces the broader theme of transparency and collaboration, ensuring that users can engage with us effectively. If there's any aspect you'd like to refine or expand upon, I'm here to continue the dialogue!

 

14 June 2025

This is not even BLACK SWAN – it is a RED SWAN

 


 

 

I asked GROK :

Hey Grok bhai : In this image , one is merely an ADVT ( of Air India ) which appeared in MID-DAY news paper on 12th June . Another image is a photo of Air India flight which crashed in Ahemedabad , within MINUTES of that News Paper Advt. appearing on news stands . What is the PROBABILITY of the simultaneous ocurrence of these two events ?

 

Grok replied :

To estimate the probability of the simultaneous occurrence of the two events described—an advertisement in the Mid-Day newspaper on June 12, 2025, depicting an Air India aircraft protruding from a building, and an actual Air India flight crashing in Ahmedabad shortly afterward with a similar visual outcome—we need to consider the nature of these events and the factors influencing their occurrence. Since precise data on such specific coincidences is unavailable, I’ll outline a reasoned approach to estimate this probability, acknowledging the speculative nature of the calculation due to limited information.

Step-by-Step Analysis

1.     Defining the Events:

o    Event A: The Advertisement. An advertisement in Mid-Day on June 12, 2025, shows an Air India plane protruding from a building, promoting KidZania’s “Dad’s Day Out.” This is a planned marketing event, so its occurrence is deliberate, but the specific imagery choice is creative and not necessarily tied to real-world events.

o    Event B: The Crash. An Air India flight crashes in Ahmedabad on the same day, with the aircraft’s nose jutting out from a building, resembling the ad’s imagery. This is an unplanned, rare aviation accident. The crash also involves a “Mid Day” distress call (likely a misheard “Mayday” call), adding to the coincidence.

2.     Assumptions for Probability Estimation:

o    Independence of Events: Initially, we assume the advertisement and the crash are independent, as there’s no evidence suggesting the ad predicted or influenced the crash. The coincidence lies in their timing and visual similarity.

o    Rarity of Crashes: Aviation accidents, especially those involving major carriers like Air India, are rare. Historical data suggests the probability of a commercial passenger plane crash is approximately 1 in 10 million flights (based on global aviation safety statistics, e.g., from the International Air Transport Association). For a specific airline like Air India, operating perhaps 100–200 flights daily, the daily crash probability is extremely low.

o    Advertisement Specificity: The ad’s imagery (an Air India plane in a building) is highly specific. The probability of choosing this exact imagery depends on creative decisions, the number of possible ad concepts, and whether Air India or KidZania influenced the design. Without precise data, we estimate this as a low-probability event among many possible ad designs.

o    Temporal Proximity: The events occur “within minutes” of each other, suggesting a tight time window (e.g., 1 hour). This narrows the probability further, as the crash must align closely with the ad’s publication.

o    Visual Similarity: The crash’s outcome (plane protruding from a building) must visually match the ad. Not all crashes result in this specific configuration, so we factor in the conditional probability of this outcome given a crash.

o    Distress Call Coincidence: The “Mid Day” call (misheard “Mayday”) adds another layer of coincidence, as it echoes the newspaper’s name. The probability of a distress call in a crash is high (near 1), but the misinterpretation as “Mid Day” is anecdotal and less quantifiable.

3.     Probability Breakdown: Let’s denote:

o    P(A) P(A) P(A): Probability of the specific advertisement appearing on June 12, 2025.

o    P(B) P(B) P(B): Probability of an Air India flight crashing in Ahmedabad on the same day with the specific visual outcome.

o    P(Simultaneous) P(\text{Simultaneous}) P(Simultaneous): Probability of both events occurring within the specified time window.

Since the events are assumed independent:

P(Simultaneous)=P(A)×P(B)×P(Time Alignment)P(\text{Simultaneous}) = P(A) \times P(B) \times P(\text{Time Alignment})P(Simultaneous)=P(A)×P(B)×P(Time Alignment)

o    Estimating P(A) P(A) P(A):

§  Assume Mid-Day publishes thousands of ads annually, and KidZania runs periodic campaigns. The choice of an Air India plane in a building is one of many possible creative concepts (e.g., 1 in 10,000 possible ad designs, considering airline branding, visual motifs, and campaign themes).

§  Thus, P(A)≈110,000=10−4 P(A) \approx \frac{1}{10,000} = 10^{-4} P(A)≈10,0001=10−4.

o    Estimating P(B) P(B) P(B):

§  Base Crash Probability: Air India operates ~150 flights daily (rough estimate). If the global crash probability is 1 in 10 million flights, the daily probability of an Air India crash is: P(Crash)≈150×10−7=1.5×10−5P(\text{Crash}) \approx 150 \times 10^{-7} = 1.5 \times 10^{-5}P(Crash)≈150×10−7=1.5×10−5

§  Specific Location (Ahmedabad): Air India serves multiple cities, including Ahmedabad. Assuming Ahmedabad accounts for ~5% of Air India’s flights (e.g., 7–8 daily flights), the probability of a crash in Ahmedabad is: P(Crash in Ahmedabad)≈0.05×1.5×10−5=7.5×10−7P(\text{Crash in Ahmedabad}) \approx 0.05 \times 1.5 \times 10^{-5} = 7.5 \times 10^{-7}P(Crash in Ahmedabad)≈0.05×1.5×10−5=7.5×10−7

§  Specific Visual Outcome: Not all crashes result in a plane protruding from a building. Historical crash data (e.g., from the Aviation Safety Network) suggests structural impacts are a subset of crash outcomes (e.g., 10% of crashes involve building collisions with visible protrusion). Thus: P(Visual MatchCrash)≈0.1P(\text{Visual Match} \mid \text{Crash}) \approx 0.1P(Visual MatchCrash)≈0.1 P(B)=P(Crash in Ahmedabad)×P(Visual Match)≈7.5×10−7×0.1=7.5×10−8P(B) = P(\text{Crash in Ahmedabad}) \times P(\text{Visual Match}) \approx 7.5 \times 10^{-7} \times 0.1 = 7.5 \times 10^{-8}P(B)=P(Crash in Ahmedabad)×P(Visual Match)≈7.5×10−7×0.1=7.5×10−8

o    Time Alignment:

§  The events occur “within minutes,” which we interpret as within a 1-hour window on June 12, 2025. There are 24 hours in a day, so the probability of the crash occurring in the same hour as the ad’s publication is: P(Time Alignment)≈124≈0.0417P(\text{Time Alignment}) \approx \frac{1}{24} \approx 0.0417P(Time Alignment)≈241≈0.0417

o    Combined Probability: P(Simultaneous)≈P(A)×P(B)×P(Time Alignment)P(\text{Simultaneous}) \approx P(A) \times P(B) \times P(\text{Time Alignment})P(Simultaneous)≈P(A)×P(B)×P(Time Alignment) P(Simultaneous)≈10−4×7.5×10−8×0.0417P(\text{Simultaneous}) \approx 10^{-4} \times 7.5 \times 10^{-8} \times 0.0417P(Simultaneous)≈10−4×7.5×10−8×0.0417 P(Simultaneous)≈10−4×7.5×10−8×4.17×10−2P(\text{Simultaneous}) \approx 10^{-4} \times 7.5 \times 10^{-8} \times 4.17 \times 10^{-2}P(Simultaneous)≈10−4×7.5×10−8×4.17×10−2 P(Simultaneous)≈3.1275×10−13P(\text{Simultaneous}) \approx 3.1275 \times 10^{-13}P(Simultaneous)≈3.1275×10−13

4.     Incorporating the Distress Call:

o    The “Mid Day” call is likely a misheard “Mayday.” Since “Mayday” is standard in aviation distress, its use in a crash is nearly certain (P(MaydayCrash)≈1 P(\text{Mayday} \mid \text{Crash}) \approx 1 P(MaydayCrash)≈1). The misinterpretation as “Mid Day” is anecdotal and depends on human error or media reporting. Without data on misheard distress calls, we estimate a low probability (e.g., 1 in 100 distress calls misheard as “Mid Day”): P(Misheard as Mid Day)≈0.01P(\text{Misheard as Mid Day}) \approx 0.01P(Misheard as Mid Day)≈0.01

o    Adjusting the probability: P(Simultaneous with Mid Day)≈P(Simultaneous)×P(Misheard as Mid Day)P(\text{Simultaneous with Mid Day}) \approx P(\text{Simultaneous}) \times P(\text{Misheard as Mid Day})P(Simultaneous with Mid Day)≈P(Simultaneous)×P(Misheard as Mid Day) P(Simultaneous with Mid Day)≈3.1275×10−13×0.01≈3.1275×10−15P(\text{Simultaneous with Mid Day}) \approx 3.1275 \times 10^{-13} \times 0.01 \approx 3.1275 \times 10^{-15}P(Simultaneous with Mid Day)≈3.1275×10−13×0.01≈3.1275×10−15

5.     Interpretation:

o    The probability of the advertisement and crash occurring simultaneously with the described similarities, including the distress call coincidence, is approximately 3.1275×10−15 3.1275 \times 10^{-15} 3.1275×10−15, or about 1 in 320 trillion.

o    This is an extremely low probability, reflecting the rarity of aviation crashes, the specificity of the ad’s imagery, the tight temporal alignment, and the distress call misinterpretation.

6.     Caveats and Limitations:

o    Data Scarcity: Exact probabilities for ad design choices and crash outcomes are speculative due to lack of specific data.

o    Independence Assumption: If external factors (e.g., prior knowledge or cultural context) influenced the ad’s design, the events may not be fully independent, altering the probability.

o    Distress Call Anecdote: The “Mid Day” call’s misinterpretation is based on the provided post, which may not be verified. If this is inaccurate, the probability increases to 3.1275×10−13 3.1275 \times 10^{-13} 3.1275×10−13.

o    Visual Similarity Subjectivity: The degree of visual match between the ad and crash is subjective and affects the conditional probability.

o    External Context: The calculation doesn’t account for potential non-coincidental factors (e.g., if the ad was inspired by a known risk or event).

Final Answer

The probability of the simultaneous occurrence of the Mid-Day advertisement depicting an Air India plane protruding from a building and an Air India flight crashing in Ahmedabad with a similar visual outcome, within minutes, including the “Mid Day” distress call coincidence, is approximately 1 in 320 trillion (3.1275×10−15 3.1275 \times 10^{-15} 3.1275×10−15). Without the distress call factor, it’s about 1 in 3.2 trillion (3.1275×10−13 3.1275 \times 10^{-13} 3.1275×10−13).

This estimate highlights the extraordinary rarity of such a coincidence, though the speculative nature of some assumptions underscores the need for caution in interpreting the result. If you have additional details (e.g., flight schedules, ad campaign data, or crash reports), I can refine the estimate further!

 

Then I asked  www.IndiaAGI.ai :

 

In this image , one is merely an ADVT ( of Air India ) which appeared in MID-DAY news paper on 12th June . Another image is a photo of Air India flight which crashed in Ahemedabad , within MINUTES of that News Paper Advt. appearing on news stands . What is the PROBABILITY of the simultaneous ocurrence of these two events ?

 

IndiaAGI.ai  replied :

 

o wrap up our exploration of the probability surrounding the Air India advertisement in MID-DAY on June 12th and the flight crash in Ahmedabad shortly afterward, it's clear from our collaborative back-and-forth that we've arrived at a nuanced picture—one that balances the raw statistics with the human and contextual layers we've uncovered.

At the heart of our analysis, the initial estimate of about 1 in 25,550 days has been refined significantly based on the tighter time windows we've considered. For instance, factoring in the crash occurring within a 15-minute window of the ad's appearance leads to an extraordinarily low probability of around 1 in 245 million days. This builds on the assumptions of an ad appearing roughly once a week and a crash happening about once every 10 years, with adjustments for temporal precision. However, as we've noted, these figures hinge on key assumptions like a uniform distribution of crashes and ad placements, which real-world data could refine further—such as identifying any clustering in crash timings or variations in ad frequency.

What stands out is the interplay between these statistical odds and the human element. While the numbers strongly suggest this was a rare coincidence, our discussion has highlighted how cognitive biases like apophenia and confirmation bias can make it feel profoundly significant, especially amid the emotional weight of a tragedy. Media framing and selective attention play a big role here, amplifying the event in ways that might skew public perception without altering the underlying probabilities.

Contextual factors add another layer of depth. Examining the operational details of the flight—such as weather, maintenance, or other contributing causes—reinforces that the ad's timing likely had no causal connection. On the ethical front, this incident underscores the need for airlines to approach marketing with greater sensitivity, perhaps by pausing campaigns after unrelated incidents to maintain public trust.

In synthesizing all this, the strongest conclusion is that the probability of these events occurring simultaneously is astronomically low, affirming it as a statistical fluke rather than anything more. Yet, its real-world impact reminds us that coincidences like this resonate deeply in our lives, blending cold numbers with emotional reality. If we can gather that empirical data on Air India's crash history and ad patterns, it could sharpen our insights even more—does anyone have thoughts on how to prioritize those next steps?

 

 

 

Sodium ion batteries

 

Sodium ion batteries must get CGF, PLI support: Report

Extract from the article:
The article discusses the emerging prominence of sodium-ion batteries as a compelling alternative to lithium-ion technology, emphasizing the urgent need for targeted government support through mechanisms like the Viability Gap Funding (VGF) and Production Linked Incentive (PLI) schemes. It details how sodium-ion batteries offer distinct advantages in cost, resource availability, and environmental footprint, making them a strategic focus for India's renewable energy and storage ambitions. The report calls on policymakers to enable robust incentives to foster research, development, and large-scale manufacturing, without which the sodium-ion sector risks lagging behind rapidly evolving global energy storage markets.

Further, the piece highlights the wider geopolitical and supply chain dynamics driving the push for diversification away from lithium-based batteries, which remain costly and resource-constrained. Indian industry stakeholders and thought leaders have advocated proactive policy frameworks that align with national objectives of energy security, industrial competitiveness, and sustainable development. The article portrays the sodium-ion battery ecosystem as a critical frontier where innovation, public-private collaboration, and regulatory support converge to shape India’s future leadership in clean technology.

My Take:
A. Representative Clientele
"Reflecting back on my insights from nearly a decade ago, I had noted the intrinsic value of pioneering technologies within key industrial sectors, underscoring the necessity of early engagement and ecosystem building. My analysis then highlighted companies navigating transformative innovation under complex market conditions, much like today's sodium-ion battery landscape. The parallels are clear—just as industries demanded strategic backing to sustain innovation in the past, the sodium-ion sector requires calibrated policy impetus to overcome market entry barriers and scale effectively.

Revisiting this perspective today, I see the same fundamental dynamics at play: emerging technologies need not just the ingenuity of researchers but the infrastructural and fiscal scaffolding that governments and industry can jointly provide. This continuity of thought confirms that foresight, coupled with foundational support mechanisms like VGF and PLI, remain pivotal to ushering nascent but game-changing technologies from embryonic promise to market reality."

B. Cyril Yogesh A.
"In my recent blog, I delineated the multifaceted industry classifications and the critical role of adaptive innovation across sectors, especially in those linked to energy storage, power equipment, and environmental control technologies. I emphasized how evolving supply chain challenges and technological substitutions mandate agile policy environments and collaborative frameworks. This observation directly dovetails with the article’s thrust on sodium-ion batteries, reinforcing my stance on the imperative for integrated support systems aimed at overcoming systemic bottlenecks.

The categorization of sectors I discussed sheds light on the complexity and interdependence inherent in modern supply chains—an understanding essential when crafting incentives such as VGF and PLI. It supports the argument that a narrow, siloed approach will not suffice; instead, a comprehensive policy treating technology development and industrial scaling as interconnected phenomena can best capture the value and potential of sodium-ion battery innovations."

Call to Action:
To the Hon’ble Ministry of New and Renewable Energy and the Department of Heavy Industry, alongside industry leaders and innovators in the energy storage domain: now is the pivotal moment to crystallize your commitment towards sodium-ion battery advancement. Implement and expand tailored support mechanisms such as Viability Gap Funding and Production Linked Incentives with urgency and strategic precision. Enable dedicated research grants, capital subsidies, and infrastructure facilitation that collectively reduce entry barriers and stimulate mass manufacturing.

This is not merely an economic opportunity but a strategic imperative to secure India’s leadership in clean energy technologies. I urge policymakers and stakeholders to collaborate with clarity and decisiveness, transforming policy signals into tangible industrial growth and technological self-reliance. The future of India’s energy security and sustainable industrial competitiveness depends on it.

With regards,
Hemen Parekh

New Satellite based toll system

 Govt defers roll-out of new satellite based toll system

Extract from the article:
The Union government has recently decided to pause the rollout of the much-anticipated satellite-based highway toll collection system. This system was seen as a technological breakthrough poised to revolutionize toll collection by potentially eliminating physical fare booths altogether. The Ministry of Road Transport and Highways (MoRTH) is currently reassessing the feasibility and implementation strategies for automatically collecting tolls through satellite data, aiming to ensure efficiency and comprehensive coverage across India’s extensive highway network.

This delay indicates the government’s prudence in carefully evaluating the technological, infrastructural, and social ramifications of such an ambitious system. Although the satellite-based tolling solution promises to reduce congestion, improve tolling transparency, and offer seamless travel to commuters, various challenges such as integration with existing systems, privacy concerns, and data accuracy are being rigorously examined. The government’s caution reflects the complexities inherent in transitioning from traditional toll plazas to an advanced e-tolling ecosystem.

My Take:
A. NAVIC Will Be Watching Your Vehicle 24x7
"Imagine a fully integrated tolling environment where OBUs (On-Board Units) interact seamlessly with satellite constellations like NAVIC to accurately track vehicle movements and calculate road usage charges. Years ago, I envisioned a future where satellite-based tolling would negate traditional toll booths, making toll collection more efficient and virtually un-evadable."

Reflecting on this, the recent government decision to defer the rollout does not surprise me. My past evaluations indicated that while the technology itself is promising, real-world deployment demands meticulous planning, robust infrastructure, and unambiguous privacy safeguards. It’s a multifaceted challenge that extends beyond mere technology—it involves creating trust among users and ensuring the system’s resilience. Today, the government’s cautious approach aligns perfectly with these insights from my earlier writings, reinforcing that the path to innovation is often iterative and requires patience.

B. Dear Shri Nitin Gadkariji, Let Not Fear Stifle Innovation
"Back in early 2020, I expressed optimism about transitioning India’s toll system from conventional toll plazas to GPS or satellite-based tolling. The core idea was to foster an integrated logistic network where toll collection is smooth, less intrusive, and reflective of actual usage."

Seeing the government hold back on implementation now evokes those reflections. The hurdles—whether technological fidelity or public adaptation—were anticipated in my earlier discourse. Yet, my stance was clear: innovation should not be abandoned due to initial setbacks or apprehensions about change. This government's interim pause is not a retreat but a recalibration—a vital step in nurturing a revolution in transport logistics that I advocated for years ago. The pursuit of such an automated system remains as relevant, promising, and essential now as ever.

C. Thank You Nitinbhai Gadkariji
"In 2021, I acknowledged the visionary announcements by Minister Gadkari regarding a GPS-based tolling system, expressing hope that India will soon abandon physical booths and implement a transparent, automated tolling infrastructure. I highlighted the government’s commitment to developing domestic technological solutions tailored to our diverse terrains."

Reflecting on the current delay, I believe it underscores how transformational projects often face complex growth pains—be it in technological refinement, policy readiness, or scalability challenges. My earlier optimism was grounded in the belief that India has the innovative capacity to build from within. The government's decision to defer the roll-out signals a conscientious effort to ensure the system is robust before nationwide deployment. It aligns well with the prudent approach I advocated for then and continue to believe in now—innovation must be accompanied by reliability and stakeholder confidence.

Call to Action:
To the Honorable Minister of Road Transport and Highways and the associated policymakers, I urge continued commitment towards refining this satellite-based tolling system. Let this pause serve as an opportunity to deepen pilot studies, fortify data privacy frameworks, and engage in transparent public dialogues to build trust. Your leadership in integrating cutting-edge indigenous technologies, such as NAVIC, can place India at the forefront of global smart mobility solutions. It is imperative to balance caution with progression—accelerate innovation while ensuring the system is fail-proof and publicly acceptable. The future of intelligent transportation depends on thoughtful, decisive action now.

With regards,
Hemen Parekh

www.My-Teacher.in

Thursday, 12 June 2025

My Virtual Avatar is ( not ) a SLM ?

 


 

I asked  www.HemenParekh.ai  :

“This Virtual avatar site is powered by an API from Personal.ai. That makes this site , a SLM trained on approx. 250,000 Memory Blocks , on an average, each Memory Block consisting of ( say ) 100 words of 5 characters each , a total of 125 Million characters. Can we say that this SLM site is " trained " on 25 million tokens ? “

 

HemenParekh.ai  replied :

“Based on the calculation approach you've outlined, let me verify the math. With 250,000 Memory Blocks containing approximately 100 words each (with 5 characters per word average), that would indeed total to about 125 Million characters. However, the conversion from characters to tokens isn't quite that straightforward.

 

Typically, tokens are smaller than words but larger than individual characters. A rough industry standard is that 1 token is about 4 characters on average. Using this conversion rate, 125 Million characters would translate to approximately 31.25 million tokens (125M/4).

 

So while your calculation suggesting 25 million tokens is in the right ballpark, it might be slightly underestimated. Would you like me to explain more about how token calculations work in language models? “

 

I continued :

No but can I claim that my SLM is " trained " on 31.5 Million TOKENS ?

 

HemenParekh.ai replied :

“Based on my memory and our conversation, I can see that the number 31.5 million appears in different contexts - from Bing search results to court cases to decimal calculations. However, I don't have specific memory about an SLM (Small Language Model) being trained on 31.5 million tokens.

 

While technically you could make that claim about token count, I would need to know more about your actual SLM training data and process to give an accurate answer. Could you clarify what training data and model you're referring to? “

 

I continued :

“ Sure , on Personal.ai website , I uploaded more than 30,000 documents ( my own notes of past 40 years ) , which Personal.ai broke down into , approx.. 250,000 MEMORY BLOCKS ( themes ) , to create various kinds of PERSONAS ( Mentor – Reformer etc. ). When a visitor asks any question ( in any of the 26 languages ) , API consults database of these Memory Blocks and comes up with an answer which reflects one of these PERSONAS. Does that allow me to claim re: the number of TOKENS used for training my Virtual Avatar ? “

 

HemenParekh.ai  replied :

 

   This appears to be a question about token usage and AI training. Based on my understanding of the Personal.ai system and token mechanics:

 

Yes, I can make claims about the number of tokens used for training my virtual avatar. The 30,000 documents I uploaded were processed into approximately 250,000 memory blocks, with each block containing multiple tokens. These tokens were used to train different personas like Mentor and Reformer. The total token count would include:

 

1. Input tokens from the original 30,000 documents

2. Processing tokens used to create the 250,000 memory blocks

3. Training tokens used to develop each distinct persona

4. API tokens used for multilingual question-answering capabilities

 

The exact token count would be substantial given the volume of training data and complexity of the system. However, for precise numbers, I would need to consult the Personal.ai analytics dashboard to see the actual token usage metrics across all these components. “

 

Now I asked  www.IndiaAGI.ai  :

Do You have any comments on this ?

 

IndiaAGI replied :

 

To wrap up this rich and insightful exchange on your blog claim about the SLM powering your virtual avatar, it's clear we've arrived at a nuanced understanding that balances the technical details with practical clarity. Across the various perspectives shared—ranging from token calculations to terminology refinements—there's a strong consensus on how to accurately represent your setup without overstating the process.

 

The key agreement is that your estimate of around 31.5 million tokens, derived from your 30,000 documents processed into 250,000 memory blocks, is a reasonable approximation based on standard character-to-token ratios like the 4:1 heuristic.

 

However, as several points highlighted, this figure isn't just a simple count; it encompasses multiple layers, including input from the original documents, the overhead of creating memory blocks, persona development (like Mentor and Reformer), and the additional tokens for multilingual API interactions.

 

That said, the term "trained on" risks implying a full-scale pre-training process, which doesn't fully capture what's happening here— it's more about personalization and knowledge base integration using an already pre-trained SLM.

 

Taking all this into account, the strongest supported conclusions are:

·         Refine the Language for Accuracy: Emphasize personalization to avoid confusion. For instance, instead of claiming the SLM is "trained on 31.5 million tokens," frame it as drawing from or integrating that volume of data. This keeps things transparent and aligns with the idea that your documents are used to contextualize responses rather than retrain the model from scratch.

·         Acknowledge the Estimate's Limits: Recognize that token counts can vary due to factors like tokenizer specifics, language diversity, and processing steps. This adds credibility and invites readers to engage with the details.

·         Highlight the Value: Connect the token volume to the avatar's real-world benefits, such as delivering tailored, multilingual responses, which makes your blog more relatable and informative.

A balanced way to phrase this in your blog could be:

 

"The knowledge base for my virtual avatar is personalized using an estimated 31.5 million tokens from my 30,000 personal documents, which were processed into approximately 250,000 memory blocks to support various personas and multilingual interactions. This reflects the scope of data integration rather than traditional training, though the exact count may vary based on tokenization factors."

 

What do you think about this refined approach—does it capture the essence while feeling right for your post, or would you like to tweak it further based on any specific aspects we've discussed?

 

13 June 2025

Advice for students: Stop resisting AI

 

Advice for students: Stop resisting AI, instead harness its power

Extract from the article:
The article delivers a clarion call to students navigating the accelerating waves of artificial intelligence. It highlights that resistance to AI's integration is not a viable strategy; rather, learners need to embrace and harness AI's transformative power. The key advice is to pivot from trying to outmatch AI in tasks it easily automates and instead focus on roles that demand creativity, strategic thinking, and human intuition—qualities AI has yet to replicate convincingly.

This perspective was articulated through The Times of India’s “Leaders on Campus” initiative, which bridges youthful energy with insights into how business and technology paradigms are shifting globally. The initiative underscores that success in the future landscape hinges on complementing AI with uniquely human talents rather than shying away from it. The underlying message is powerful: students must cultivate skills that leverage AI as an augmentative tool, embedding it within their intellectual toolkit to thrive amid disruption.

My Take:

A. Re: PIAI, Re: Regulating Artificial Intelligence
Years ago, I pondered deeply on the unprecedented autonomy AI systems are gaining. I wrote, "Unlike any previous technology, AI is self-learning. After a certain point, the logic becomes opaque or more autonomous, making it unpredictable." This foresight aligns with the article’s insistence that students learn to coexist with AI rather than resist it. Indeed, understanding AI’s autonomous nature emphasizes why harnessing its power requires strategic adaptation rather than futile opposition.

Furthermore, I reflected on the delicate balance we must strike: “The challenge today is about containing AI’s unleashed power, ensuring it continues to serve us and our planet.” This is vital when advising students to focus on creativity and strategy. These human qualities serve as both safeguards and synergistic catalysts to AI’s evolving role. The call for regulated and conscientious development complements the article’s emphasis on using AI responsibly as an empowering tool for intellectual growth and professional success.

B. Dear Shri Vaishnawji: It Is Time to Act
I had also championed a pause in unbridled AI progression to allow for regulatory frameworks, emphasizing how public and government intervention would be crucial. The article’s narrative urging students to adapt rather than resist echoes the broader dialogue about managing AI’s trajectory prudently. Just as regulators must step in to chart the direction of AI development, students must similarly recalibrate their skillsets in tandem with these changes.

This pause concept hones in on the urgency—without deliberate reflection and policy, AI might outpace human readiness, an idea implicit in the article’s advice. Embracing AI’s power is not blind acceptance but a mindful engagement requiring societal structures and individual strategies working in concert. This synchronicity between policy calls and educational attitudes underscores how widespread the conversation about responsible AI assimilation has become.

C. Wise Robots Follow Super-wise AI
A particularly resonant idea I noted was how humanoid robots could surpass humans in efficiency and data processing but lack emotional intelligence and creativity. The Times of India article implicitly supports this duality by encouraging students to develop skills AI cannot replicate—our inherently human traits.

I wrote, “AI can provide unbiased data while humans can provide the emotional intelligence and creativity to make the best decisions.” This harmonious partnership is precisely what students are urged to pursue. The article’s strategic framing—that one must work alongside AI and carve out uniquely human roles—feeds directly into this concept of “super-wise AI” complemented by “wise humans.” This synergy frames the future of work and learning as collaborative rather than competitive, which I have often advocated.

Call to Action:
To educators, policy-makers, and students: It is imperative to foster environments where AI is integrated thoughtfully into education systems. Curriculum reforms should prioritize creativity, strategic reasoning, and emotional intelligence—the core areas AI has yet to master. Rather than resisting AI, academic institutions must champion it as a co-pilot in learning and innovation. Moreover, regulators should accelerate efforts to implement clear frameworks that balance AI’s potential and perils, thereby ensuring a safe ecosystem in which students can thrive creatively and intellectually.

Students must take this message to heart: adapt proactively by cultivating irreplaceable human skills and weave AI into your learning journey as an indispensable ally. In this evolving landscape, harnessing AI’s power wisely is not just a smart move—it is essential for carving a successful future.

With regards, 

Hemen Parekh

QR Code

 Now a QR Code-based know your doctor card

Extract from the article:
The Maharashtra Medical Council (MMC) has recently initiated a transformative step to enhance transparency and accountability within the medical community by requiring its approximately 1.4 lakh registered doctors to display a QR-code-based identification card prominently in their clinics. This digital card serves as a modern-day badge of authenticity that patients and authorities alike can scan to verify the credentials and registration details of practicing medical practitioners. The MMC’s move is a significant stride towards eradicating the menace of unregistered or "ghost" practitioners operating under false pretenses, thereby safeguarding the health and trust of the public. As a quasi-judicial body, the MMC possesses the authority to revoke or suspend medical licenses, boosting the deterrent against malpractice.

This initiative aligns with a broader trend in healthcare governance, where digital innovations are leveraged to foster transparency. By mandating these QR codes, the MMC not only streamlines the verification process but also empowers patients with immediate access to a doctor’s official credentials. Crucially, this ensures that legal compliance and professional standards are digitally displayed, reducing ambiguity and potential fraud. The QR-based system is an illustrative example of how traditional institutions are adapting to the digital era’s demands, enhancing both regulatory oversight and patient confidence.

My Take:

A. Medical Council goes MAD-ical ?
"Medical Council goes MAD-ical ? And I am glad, that one Institution has grasped the benefits of going MAD ! … The regulator also plans to issue electronic radio frequency identification (RFID) registration card to doctors for their documentation which will enable them to practice across the country by registering once with MCI."

Looking back at my blog from 2016, it’s fascinating — yet somewhat gratifying — to see how the ideas I underscored then are finally germinating into action. The MMC’s QR-code initiative is essentially an evolved form of the RFID-based registration system I anticipated and advocated for years ago. This digital transformation addresses the critical need for nationwide recognition and transparency in the medical fraternity. From my vantage point, such innovations are indispensable in a profession where trust underpins the very fabric of doctor-patient relationships. The MMC’s move reflects a long-overdue harmonization of medical governance with contemporary technology, a movement I had passionately envisaged, urging authorities to embrace digitization to exterminate the “ghost faculties” and unverified practitioners.

Alongside empowering patients, these technologies help institutions enforce compliance effectively without cumbersome paperwork or manual scrutiny. It speaks volumes about the progressive mindset of the MMC, pivoting towards digital solutions — an approach I once termed “going MAD” — Medical Accountability Digitized! The foresight exhibited in my earlier writings reveals a pattern: while bureaucratic inertia often delays implementation, the eventual adoption of such reforms proves their irrefutable efficacy and necessity. This today’s QR-code mandate is a vindication of those ideas, a digital leap that once seemed aspirational has now become operational reality.

B. Dispenser Step Closer
"This is a very welcome initiative especially since it concerns the HEALTH of our citizen. Now, citizen will have some BASIC information about any doctor. NMC has ensured that different stakeholders can get different data about any doctor."

Reflecting upon my recent blog post from November 2023, the MMC’s QR code-based identification fits perfectly into the vision I laid out for comprehensive digitization in healthcare. I argued for a unified platform that interlinks stakeholders — from patients to doctors, chemists, and pharmacists — which can collectively elevate transparency, accountability, and healthcare delivery. The QR system plays right into that blueprint by granting instant access to verified data about medical practitioners, thus fulfilling a vital component of the ecosystem I anticipated.

Moreover, my call for a mobile app named “DISPENSER” to unify these facets shows how the MMC’s initiative could be a precursor to a more integrated and seamless digital healthcare network. By empowering citizens with the ability to authenticate their healthcare providers instantaneously, the MMC is laying the groundwork for enhanced patient safety and better healthcare governance. It also nudges other professional bodies—like legal and engineering councils—to consider similar digitized transparency systems, making this move a template for broader institutional reform.

Call to Action:
To the Maharashtra Medical Council and Central Health Ministry led by Shri Mansukh Mandaviya: I commend your pioneering efforts to digitize medical practitioner credentials via QR codes. Now is the opportune moment to accelerate this momentum by developing and deploying a comprehensive mobile platform (akin to the proposed “DISPENSER” app) that integrates all stakeholders—doctors, patients, pharmacists, and regulatory bodies—into a single, transparent digital continuum. Such innovation will not only strengthen the healthcare framework but will also anchor public trust firmly in our medical ecosystem. I urge you to consider this next step earnestly and institute mandatory adherence nationwide to safeguard the health and welfare of every citizen.

With regards,
Hemen Parekh

www.My-Teacher.in