Category: learning

Scientific understanding and AI

Let me draw attention, especially of those interested in scientific research, to a relevant review article in Nature Reviews Physics titled “On scientific understanding with artificial intelligence“

Below are a couple of paragraphs that caught my attention:

“Scientific understanding and scientific discovery are both important aims in science. The two are distinct in the sense that scientific discovery is possible without new scientific understanding….

…..to design new efficient molecules for organic laser diodes, a search space of 1.6 million was explored using ML and quantum chemistry insights. The top candidate was experimentally synthesized and investigated. Thereby, the authors of this study discovered new molecules with very high quantum efficiency. Whereas these discoveries could have important technological consequences, the results do not provide new scientific understanding.”

The authors provide two more examples of a similar kind, from different branches of science.

The authors conclude:

“Undoubtedly, advanced computational methods in general and in AI specifically will further revolutionize how scientists investigate the secrets of our world. We outline how these new methods can directly contribute to acquiring new scientific understanding. We suspect that significant future progress in the use of AI to acquire scientific understanding will require multidisciplinary collaborations between natural scientists, computer scientists and philosophers of science. Thus, we firmly believe that these research efforts can — within our lifetimes — transform AI into true agents of understanding that will directly contribute to one of the main goals of science, namely, scientific understanding.”

Worth reading the full article. Link here.

PS: Prof. Siddharth Tallur (IIT, Bombay) on LinkedIn raised an important question.

Nice.. thanks for sharing, will go through it. Although a lot of brute force seems to be passed off as understanding these days (brawn = brain?) I wonder if AI and ML of the varieties we have today are advancements in computing or intelligence?

My reply:

The computational capability is undoubtedly great, and probably the coding/software domain has been conquered, but there is a tendency to extrapolate the immediate impact of AI to every domain of human life, where even basic tech has not made an impact. That needs deeper knowledge of interfacing AI with other domains of engineering.
Embedding AI in the virtual domain is one thing, but to put it in the real world with noise is a different game altogether. That needs interfacing with the physical world, and there is also an energy expense that doesn’t get factored into the discussion. It has great potential, and I’m eager to see its impact on the physical infrastructure. Parallelly, it is interesting to see how it has been sold in the public domain.

made a video to explain the main blog:

AI hype..

A gentle reminder: Digital infrastructure is not equal to physical infrastructure.
The former is a smaller set of the four-dimensional space-time world we live in.
AI-based tech is fantastic for an upgrade in digital infrastructure and has already made tremendous progress. But the real deal is in the physical domain.
This also indicates where the future action is, and will be influenced by our understanding of physical sciences, including engineering domains beyond computer science.
What we are witnessing in AI is probably the peak of Gartner’s hype cycle.

C V Raman and long term thinking

A small sampling of Raman’s publication. These papers are related to light scattering and form the foundation on which he made his famous discovery. Raman wrote more than 400 research papers in his lifetime (apart from monographs, lectures and public talks). Writing such a series of papers on a particular topic can be observed throughout his career.

A note to young scholars: intellectual monuments are built this way: thought after thought, day after day, paper after paper. Never underestimate what can be achieved with consistent, honest effort.

Create to Understand

Below are two quotes on the blackboard of Feynman’s office in Caltech which were found just after his death.

 
The first of these quotes by Feynman is a guiding principle for anyone who wants to learn. The second quote is an idealistic one, but a good approach to becoming a ‘problem-solving’ researcher. Feynman was a master of this approach.
 
From a philosophy of science perspective, researchers can be both ‘problem creators’ and ‘problem solvers’. The latter ones are usually famous.
 
Michael Nielsen, a pioneer of quantum computing and champion of open science movement, has an essay titled: Principles of Effective Research, in which he explicitly identifies these two categories of researchers, and mentions that “they’re not really disjoint or exclusive styles of working, but rather idealizations which are useful ways of thinking about how people go about creative work.”.
 
He defines problem solvers as those “who works intensively on well-posed technical problems, often problems known (and sometimes well-known) to the entire research community in which they work.” Interesting, he connects this to sociology of researchers, and mentions that they “often attach great social cache to the level of difficulty of the problem they solve.”
 
On the other hand, problem creators, as Nielsen indicates, “ask an interesting new question, or pose an old problem in a new way, or demonstrate a simple but fruitful connection that no-one previously realized existed.”
 
He acknowledges that such bifurcation of researchers is an idealization, but a good model to “clarify our thinking about the creative process.”
 
Central to both of these processes is the problem itself, and what is a good research problem depends both on the taste of an individual and the consensus of a research community. This is one of the main reasons why researchers emphasize defining a problem so much. A counterintuitive aspect of the definition of the problem is that one does not know how good the ‘question’ is until one tries to answer and communicate it to others. This means feedback plays an important role in pursuing the problem further, and this aptly circles back to Feynman’s quote: “What I cannot create, I do not understand”.
 
 
 
 
 
 
 

Blog highlighted by SciRio

A nice article by @RutujaUgale in @Sci_Rio that discusses public engagement by scientists as influencers of scientific thought.

Thanks, Rutuja, for profiling my blog, ‘Vismaya’.

Here is my quote from the article:

“For me, there are two implications of doing science. One is that science is extremely useful to society, and the second is that it is a good, thoughtful way of living one’s life. Communicating the second implication is important to me, and I do this by researching, writing, and podcasting about the history and philosophy of science (physics in particular). This path helps people understand the human element of doing science and reveals a context. Some of my blogs (filtered here) discuss why I do science and how I do it. More than ‘influencing’ the audience, I am interested in inviting them to explore science by themselves via their own curiosity. That is one reason why my blog is called VISMAYA.”

Link to the full article.

THE DIARY AND OBSERVATIONS OF THOMAS ALVA EDISON

Thomas Alva Edison was one of the greatest inventors we know about. Sometime ago, I stumbled upon a book titled THE DIARY AND OBSERVATIONS OF THOMAS ALVA EDISON, and it was an interesting read. In there, we obtain an insight into Edison’s view on many different subjects, including education, work, religion, etc. Edison was a person with strong views. His working methods were unconventional. Here are a few interesting facts I learnt from this book:

1) Edison had to recruit many executives to his labs; he always emphasized on a memory test and gave them a questionnaire to answer. He insisted that memory is very important for decision making, and he usually employed those people who had very good memory. Edison wrote “…Certainly the brain should have the facts. If a brain possesses an enormous number of facts, those facts, through action of the subconscious mind, will automatically keep themselves available when needed and will automatically keep themselves out of the way, not interfering when not required.”

2) Edison’s view on education was interesting and bold for his times, and he believed that learning through movies would be vital for future education. As early as the 1890s, he said that the best way to teach geography is either by taking the student on a tour or by showing them a movie. Edison wrote

“…motion pictures can be applied to a scientific, systematic course of memory training in the schools, taking the children at an early age when the mind is plastic enough to adapt itself most readily to new habit of thought.

Most of our text books fail on two big counts. They are not sufficiently human, and their application is not sufficiently practical”

3) In the following lines, Edison gives an insight into how he worked: “When I want to discover something, I begin by reading up everything that has been done along that line in the past-that’s what all these books in the library are for. I see what has been accomplished at great labor and expense in the past. I gather the data of many thousands of experiments as a starting point, and then I make thousands more.”

“ …..The motive that I have for inventing is, I guess, like the motive of the billiard player, who always wants to do a little better-to add to his record. Under present conditions I use the reasonable profit which I derive from one invention to make experiments looking towards another invention…..”

4) Edison rates the phonograph as his greatest discovery. He writes, “Which do I consider my greatest invention ? Well, my reply to that would be that I like the phonograph best. Doubtless this is because I love music. And then it has brought so much joy into millions of homes all over this country, and , indeed, all over the world.”

5) The following quotation by Joshua Reynolds was hung in every room of Edison’s laboratory “ There is no expedient to which a man will not resort to avoid the real labor of thinking”

There are many more fascinating thoughts of Edison, many agreeable and a few disagreeable ones, in the above-mentioned book, and if you happen to find it, read it through…it’s a classic and insightful read.

The above text is from a 2011 post on my old blog.

15 years at IISER Pune – Journey so far

Today, I complete 15 years as a faculty member at IISER-Pune. I have attempted to put together a list of some lessons (based on my previous writings) that I have learnt so far. A disclaimer to note is that this list is by no means a comprehensive one, but a text of self-reflection from my viewpoint on Indian academia. Of course, I write this in my personal capacity. So here it is..

  1. People First, Infrastructure Next
    As an experimental physicist, people and infrastructure in the workplace are of paramount importance. When I am forced to prioritize between them, I have chosen people over infrastructure. I am extremely fortunate to have worked with, and continue to work with, excellent students, faculty colleagues, and administrative staff members. A good workplace is mainly defined by the people who occupy it. I do not neglect the role of infrastructure in academia, especially in a country like India, but people have a greater impact on academic life.
  2. Create Internal Standards
    In academia, there will always be evaluations and judgments on research, teaching, and beyond. Every academic ecosystem has its own standards, but they are generalized and not tailored to individuals. It was important for me to define what good work meant for myself. As long as internal standards are high and consistently met, external evaluation becomes secondary. This mindset frees the mind and allows for growth, without unnecessary comparisons.
  3. Compare with Yourself, Not Others
    The biggest stress in academic life often arises from comparison with peers. I’ve found peace and motivation in comparing my past with my present. Set internal benchmarks. Be skeptical of external metrics. Strive for a positive difference over time.
  4. Constancy and Moderation
    Intellectual work thrives not on intensity alone, but on constancy. Most research outcomes evolve over months and years. Constant effort with moderation keeps motivation high and the work enjoyable. Binge-working is tempting, but rarely effective for sustained intellectual output.
  5. Long-Term Work
    We often overestimate what we can do in a day or a week, and underestimate what we can do in a year. Sustained thought and work over time can build intellectual and technical monuments. Constancy is underrated.
  6. Self-Mentoring
    Much of the academic advice available is tailored for Western systems. Some of it is transferable to Indian contexts, but much of it is not. In such situations, I find it useful to mentor myself by learning from the lives and work of people who have done extraordinary science in India. I have been deeply inspired by many people, including M. Visvesvaraya, Ashoke Sen, R. Srinivasan, and Gagandeep Kang.
  7. Write Regularly—Writing Is Thinking
    Writing is a tool to think. Not just formal academic writing, but any articulation of thought, journals, blogs, drafts, clarifies and sharpens the mind. Many of my ideas have taken shape only after I started writing about them. Writing is part of the research process, not just a means of communicating its outcomes.
  8. Publication is an outcome, not a goal Publication is just one outcome of doing research. The act of doing the work itself is very important. It’s where the real intellectual engagement happens. Focus on the process, not just the destination.
  9. Importance of History and Philosophy of Physics
    Ever since my undergraduate days, I have been interested in the history and philosophy of science, especially physics. Although I never took a formal course, over time I have developed a deep appreciation for how historical and philosophical perspectives shape scientific understanding. They have helped me answer the fundamental question, “Why do I do what I do?” Reflecting on the evolution of ideas in physics—how they emerged, changed, and endured—has profoundly influenced both my teaching and research.
  10. Value of Curiosity-Driven Side Projects
    Some of the most fulfilling work I’ve done has emerged from side projects, not directly tied to funding deadlines or publication pressure, but driven by sheer curiosity. These projects, often small and exploratory, have helped me learn new tools, ask new questions, and sometimes even open up new directions in research. Curiosity, when protected from utilitarian pressures, can be deeply transformative.
  11. Professor as a Post-doc
    A strategy I found useful is to treat myself as a post-doc in my own lab. In India, retaining long-term post-docs is difficult. Hence, many hands-on skills and subtle knowledge are hard to transfer. During the lockdown, I was the only person in the lab for six months, doing experiments, rebuilding setups, and regaining technical depth. That experience was invaluable.
  12. Teaching as a Social Responsibility
    Scientific social responsibility is a buzzword, but for me, it finds its most meaningful expression in teaching. The impact of good teaching is often immeasurable and long-term. Watching students grow is among the most rewarding experiences in academia. Local, visible change matters.
  13. Teaching Informally Matters
    Teaching need not always be formal. Informal teaching, through conversations, mentoring, and public outreach, can be more effective and memorable. It is free of rigid expectations and evaluations. If possible, teach. And teach with joy. As Feynman showed us, it is a great way to learn.
  14. Foster Open Criticism
    In my group, anyone is free to critique my ideas, with reason. This open culture has been liberating and has helped me learn. It builds mutual respect and a more democratic intellectual space.
  15. Share Your Knowledge
    If possible, teach. Sharing knowledge is a fundamental part of academic life and enriches both the teacher and the learner. The joy of passing on what you know is priceless.
  16. Social Media: Effective If Used Properly
    Social media, if used responsibly, is a powerful tool, especially in India. It can bridge linguistic and geographical divides, connect scientists across the world, and communicate science to diverse audiences. For Indian scientists, it is a vital instrument of outreach and dialogue. My motivation to start the podcast was in this dialogue and self-reflection.
  17. Emphasis on Mental and Physical Health
    In my group, our foundational principle is clear: good health first, good work next. Mental and physical well-being are not optional; they are necessary conditions for a sustainable, meaningful academic life. There is no glory in research achieved at the cost of one’s health.
  18. Science, Sports, and Arts: A Trinity
    I enjoy outdoor sports like running, swimming, and cricket. Equally, I love music, poetry, and art from all cultures. This trinity of pursuits—science, sports, and the arts—makes us better human beings and enriches our intellectual and emotional lives. They complement and nourish each other.
  19. Build Compassion into Science
    None of this matters if the journey doesn’t make you a better human being. Be kind to students, collaborators, peers, and especially yourself. Scientific research, when done well, elevates both the individual and the collective. It has motivated me to humanize science.
  20. Academia Can Feed the Stomach, Brain, and Heart
    Academia, in its best form, can feed your stomach, brain and heart. Nurturing and enabling all three is the overarching goal of academics. And perhaps the goal of humanity.

My academic journey so far has given me plenty of reasons to love physics, India and humanity. Hopefully, it has made me a better human being.