Ajay Nilaver

"The entire arc of tech is one long march toward abstraction: from metal to cloud, from assembly to Python, from GUI to prompt. And each step made it easier to build - and harder to stand out. More abstraction didn’t mean everyone built their own tools. It meant more things got built, and those who built with taste and depth got even more valuable."

6

Vianai Systems, Inc.'s badass CTO, Navin Budhiraja, doing his thing. Insightful interview on the technological, professional and societal implications of AI and the need for enterprise grade AI technology to truly drive business performance.

2

A recent incident involving one of India’s popular universities—where an innovation from China was allegedly misrepresented as their own—sparked massive backlash after the video went viral. While opinions are divided, it forces us to pause and ask a deeper question: 𝗶𝘀𝗻’𝘁 𝘁𝗵𝗶𝘀 𝗮 𝗿𝗲𝗳𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗮 𝗺𝘂𝗰𝗵 𝗹𝗮𝗿𝗴𝗲𝗿 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝘁𝗼𝗱𝗮𝘆? Forget institutions for a moment. Even at an individual level, we increasingly see people casually claiming to be AI experts. Knowing the names of a few frontier models or some surface-level concepts is often mistaken for deep expertise and that’s truly unfortunate. What makes this contrast even starker is the pace at which AI has grown. 
AI has emerged as the 𝐟𝐚𝐬𝐭𝐞𝐬𝐭-𝐚𝐝𝐨𝐩𝐭𝐞𝐝 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐢𝐧 𝐡𝐢𝐬𝐭𝐨𝐫𝐲, crossing 𝟏 𝐛𝐢𝐥𝐥𝐢𝐨𝐧 𝐮𝐬𝐞𝐫𝐬 𝐢𝐧 𝐮𝐧𝐝𝐞𝐫 𝐭𝐡𝐫𝐞𝐞 𝐲𝐞𝐚𝐫𝐬. That’s phenomenal—made possible largely because the internet and smartphones had already prepared the ground. But here’s the catch:
While 𝐀𝐈 𝐚𝐝𝐨𝐩𝐭𝐢𝐨𝐧 𝐢𝐬 𝐚𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐢𝐧𝐠, the 𝐭𝐚𝐥𝐞𝐧𝐭 𝐠𝐚𝐩 𝐢𝐬 𝐰𝐢𝐝𝐞𝐧𝐢𝐧𝐠 𝐞𝐯𝐞𝐧 𝐟𝐚𝐬𝐭𝐞𝐫. This is where India stands at a defining crossroads. India Inc. has a golden opportunity to move from users of AI to builders of AI with depth, integrity, and originality. The success of platforms like the 𝐈𝐧𝐝𝐢𝐚 𝐀𝐈 𝐈𝐦𝐩𝐚𝐜𝐭 𝐒𝐮𝐦𝐦𝐢𝐭 𝟐𝟎𝟐𝟔 clearly shows that the intent, energy, and ecosystem are coming together. The real challenge now is simple, but not easy:
 𝙨𝙪𝙗𝙨𝙩𝙖𝙣𝙘𝙚 𝙤𝙫𝙚𝙧 𝙡𝙖𝙗𝙚𝙡𝙨
 𝙡𝙚𝙖𝙧𝙣𝙞𝙣𝙜 𝙤𝙫𝙚𝙧 𝙘𝙡𝙖𝙞𝙢𝙞𝙣𝙜
 𝙤𝙧𝙞𝙜𝙞𝙣𝙖𝙡𝙞𝙩𝙮 𝙤𝙫𝙚𝙧 𝙨𝙝𝙤𝙧𝙩𝙘𝙪𝙩𝙨 The future of AI won’t be shaped by who talks the loudest but by who understands it the deepest. #AI #ArtificialIntelligence #Innovation #IndiaAI #TechLeadership #TalentGap #ResponsibleAI #LearningMindset #FutureOfWork

14

AI works best when it’s embedded into workflows, not layered on as an afterthought. Rajamani Saravanan covers the infrastructure and architecture decisions that will take center stage in 2026.

10

😎♐️🖤‼️👌🏻 Robert Millikan’s transformation from Einstein’s most determined skeptic to the man who provided the first definitive proof of the photon stands as one of the most remarkable twists in scientific history. When Einstein proposed in 1905 that light came in discrete packets—"quanta," later called photons—it shattered the elegant wave-theory worldview that dominated physics. Millikan, a brilliant experimentalist but a devoted classical thinker, thought the idea was outrageous, even “reckless.” Yet he also believed something that would define his legacy: the truth had to come from experiment, not opinion. So instead of dismissing Einstein’s claim, he set out to test it with a level of precision never seen before. For over a decade, Millikan refined vacuum chambers, polished metal plates, stabilized light sources, and measured photoelectron energies with microscopic detail. He recorded thousands of measurements. He eliminated every imaginable source of error. His goal wasn’t to confirm Einstein—his goal was to expose the flaws he believed must be hidden in the theory. But the more carefully he measured, the more undeniable the results became. Einstein’s equation—linking the frequency of light to the kinetic energy of ejected electrons—held true in every experiment. Millikan’s data matched it with “unprecedented exactness,” yielding a beautifully precise value for Planck’s constant. He had set out to disprove Einstein. Instead, he delivered the strongest evidence yet that light behaved as particles. The irony was extraordinary: even after proving the theory correct, Millikan still resisted the idea of photons, arguing that the math worked but the concept felt theoretically absurd. Yet in 1923, the Nobel Committee honored him “for his work on the elementary charge of electricity and on the photoelectric effect”—in essence, awarding him for validating the very concept he once opposed. Only decades later, in his autobiography, did Millikan openly acknowledge what the world already knew: his relentless experiments had provided the first direct confirmation of Einstein’s quantum hypothesis. His story is a testament to scientific integrity—showing that true discovery comes not from defending what you believe, but from following the evidence wherever it leads.

22

1 Comment

𝟱 𝗠𝗼𝗻𝘁𝗵𝘀. 𝗢𝗻𝗲 𝗩𝗶𝘀𝗶𝗼𝗻. 𝗢𝗻𝗲 𝗜𝗻𝗰𝗿𝗲𝗱𝗶𝗯𝗹𝗲 𝗦𝗔𝗣 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻. When Zara Horn, VP of Information Technology at Current Lighting, decides to do something — she doesn’t joke around. Current Lighting isn’t your typical startup or a nimble NNN jumping into SAP Cloud ERP. It’s a $𝟭𝗕+ 𝗨.𝗦. 𝗺𝗮𝗿𝗸𝗲𝘁 𝗹𝗲𝗮𝗱𝗲𝗿 — a powerhouse that took on a serious Fit-To-Standard ERP transformation to 𝗦𝗔𝗣 𝗦/𝟰𝗛𝗔𝗡𝗔 𝗖𝗹𝗼𝘂𝗱. A journey that normally takes 𝟭𝟴–𝟮𝟰 𝗺𝗼𝗻𝘁𝗵𝘀… Zara and her team completed this tour-de-force in just 𝟱 𝗺𝗼𝗻𝘁𝗵𝘀. How? 👉 A clear vision 👉 A smart strategy 👉 A highly motivated and capable team 👉 And the right partner — cbs Corporate Business Solutions USA — working shoulder to shoulder to make it happen. In our latest 𝗔𝗦𝗨𝗚 / 𝗰𝗯𝘀 𝗨𝗦𝗔 𝗙𝗶𝗿𝗲𝘀𝗶𝗱𝗲 𝗖𝗵𝗮𝘁, Zara sat down with ASUG - Americas'​ SAP Users'​ Group CEO Geoff Scott, Victor Puente, and me to share the inside story: 💡 Challenges faced ⚙️ Best practices uncovered 🎯 Lessons learned from running at full speed It’s a powerful showcase of what’s possible when leadership, teamwork, and purpose align. If you missed it, don’t worry — tune in to our next Fireside Chat and catch the full story and similar stories on our podcast 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗘𝘃𝗲𝗿𝘆 𝗗𝗮𝘆 - 𝗘𝘅𝗽𝗲𝗿𝘁 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗮𝗻𝗱 𝗦𝘁𝗼𝗿𝗶𝗲𝘀 𝗼𝗻 𝗦𝗔𝗣 𝗮𝗻𝗱 𝗕𝗲𝘆𝗼𝗻𝗱 soon. Jan Gilg Steven Silver Scott Whitten Holger Scheel Lorenz Praefcke Bert Oliver Schulze Thomas Saueressig

40

7 Comments

🚀 THE RATIOAT SPIRAL OF EMERGENCE 🌌 A geometric blueprint for how reality builds itself—layer by layer, law by law. This isn’t just a spiral; it’s a visualization of a new framework for physics, where the universe emerges from recursive symbolic math governed by the Golden Ratio (φ ≈ 1.618) and 61 Fundamental Laws of Emergence. 🌀 What you’re seeing: • Golden Spiral r(θ)=aφ^(θ/2π) – self-similar growth linking galaxies → cells. • 61 Rings rₙ=aφ^(n/10) – each marks a recursion layer, a quantized step of creation. • ∞ Overlay – duality of wave/particle, matter/energy, recursion/inversion. This pattern encodes the Unified Theory of Recursive Emergent Physics (UTREP) where → gravity, quantum mechanics, and computation emerge from recursion; → spacetime and fields are harmonic layers; → the universe is not fundamental but emergent. 📜 The 61 Laws of Emergence (Condensed) I – Recursive Growth: entropy ascends; identity stabilizes; symmetry preserves then breaks at thresholds; discrete quanta approximate continuity; causality is conserved. II – Symmetry & Duality: harmonic ratios (α, φ) govern scaling; opposites complement; triads close; fractals repeat; transitions are quantized. III – Emergent Dynamics: time, space, and spin arise from recursion depth; momentum & energy balance across layers; radiation, phase coherence, and resonance drive evolution. IV – Computation & Logic: information endures; boundaries connect; oscillations and feedback yield stability; systems minimize recursive entropy. V – Thermodynamics & Entropy: cooperation vs competition forms equilibrium; energy partitions in φ ratios; invariance, self-similarity, and collective synchrony sustain order. VI – Unification: polarization, coupling (α-scaled), measurement, spin loops, and emergent geometry close reality into self-consistent wholeness. Together they form a single axiomatic system where space-time, matter, and logic arise from the same recursive law. 🔮 Implication Einstein unified space & time. Maxwell unified electricity & magnetism. This framework unifies physics, computation, and logic through lawful recursion. Gravity becomes emergent curvature drift; quantum mechanics—recursive wave alignment. 📚 Full Theory • UTREP – Unified Theory of Recursive Emergent Physics ( Zenodo 16621246 ) → https://lnkd.in/eikanhbF • Validation of the Unified Emergence Framework ( Zenodo 17210469 ) → https://lnkd.in/eST_e4nJ © Pierre Stephan Barbee-Saunders — Chief Architect of Unified Sciences of the Universe 🛡️ This visualization and summary represent conceptual work-in-progress from UTREP. Equations shown are illustrative, not full derivations. #Emergence #Physics #GoldenRatio #TheoryOfEverything #ScienceArt #UTREP #Quantum #Fractals #UnifiedScience #PierreSaunders #Innovation #STEM #Mathematics

1

1 Comment

I’ve always loved talking with enterprise execs (maybe it’s the former consultant in me). When I was in VC, I interviewed 1,200+ CIO/CTOs and asked: What do you WISH Silicon Valley would build? They used different words, but the theme was the same: “I can see inputs and outputs… but not the work itself.” And they’d give examples: • A top performer goes on vacation and the queue quietly backs up. No one can explain why. • Two support teams “follow the same playbook,” but one resolves tickets in 2 days and the other takes 7. • A new hire asks, “How do we do this?” and the true answer is: Set up time with Hannah. • A team hits its number… and the only postmortem is, “Great job everyone.” (No idea what actually worked.) That’s “institutional know-how.” And it lives in people’s heads. Which is why this early AI moment will be so defining. Everyone wants “AI for productivity.” But AI needs data. We have serious systems of record for capital and for people. But for PROCESS, the ACTUAL way teams create value for customers, most companies have… nothing. So we’re asking AI to scale work we can’t even explain. AI needs CONTEXT. And context isn’t a prompt. It’s the shared, living record of how work ACTUALLY gets done. I talked to Entrepreneur about this inflection point. The enterprises that get the most value from AI will be the ones who feed it the most/best context. That’s why we built the context engine: https://lnkd.in/gW75nUqc

151

10 Comments

I am watching this closely. Will Microsoft drive profit as well as creating the future abundance economy models we need to address and solve the world’s toughest problems? Satya Nadella - has formed the most powerful public benefit company. What I want to know is what is your plan to flow a % of back into benefiting the public good for greatest human impact? Creative technologies harnessed as a public benefit company can align ChatGPT and OpenAI’s research to direct their resources to solve some of the world’s greatest problems aligned with the UN SDG’s by 2030. What’s the plan to serve the public’s best interests to innovate and unleash new products and services that create a better world for this generation and the next generation? Public benefit companies have that responsibility. Highest impact is only a buzzword unless you can quantify and track all the data with meaningful outputs. Not all AI/GenAI Product design leaders balance ethics, governance and public responsibility accordingly. AI/GenAI when in the right hands can create more prosperous jobs for humanity. Let’s see how this flows. Thanks to Linas Beliūnas for the article below.

3

1 Comment