The Effortless Podcast

In this episode of The Effortless Podcast, host Amit Prakash sits down with Professor Debdeep Jena, a leading expert in semiconductors, superconductors, and quantum devices at Cornell University. They explore the fascinating world of quantum computing, from its early 20th-century origins to its transformative potential in modern technology.Professor Jena delves into key concepts of quantum physics and quantum computing, shedding light on quantum systems, qubits, and the challenges and promises of quantum hardware. With decades of experience in semiconductor research, he explains how quantum computing could revolutionize industries, from computational speed to energy efficiency.In this conversation, they discuss:The birth of quantum mechanics and its evolution into quantum computingThe role of qubits and superposition in quantum devicesHow quantum computing is tackling complex problems beyond classical computingCurrent advancements in quantum hardware and the roadblocks still aheadProfessor Jena's perspective on the future of quantum technology and its potential impact on industries like AI, communications, and beyondThis episode is a must-watch for anyone curious about the future of quantum technology and its applications in modern science and industry. Professor Jena provides unique insights into how quantum systems are poised to transform computing, energy efficiency, and even artificial intelligence. Whether you're a tech enthusiast, a student of physics, or a professional exploring the frontier of quantum technology, this conversation is packed with invaluable knowledge.Key Topics & Timestamps:00:00 – Introduction to Quantum Mechanics, Entanglement, and the Role of Information in Physics05:00 – Classical Computation vs. Quantum Computation: Understanding the Basics of Classical and Quantum Bits12:00 – The Role of Information Erasure and Its Link to Energy Loss in Classical Computing18:00 – Superposition and Entanglement: The Basis of Quantum Computation25:00 – Bell's Theorem and the EPR Paradox: Understanding Quantum Nonlocality32:00 – Quantum Measurement and the Challenge of Formulating the Right Questions in Quantum Computation40:00 – Shor's Algorithm and the Promise of Quantum Speedup for Prime Factorization45:00 – Practical Quantum Computing: Grover's Algorithm and the Search Problem52:00 – The Need for Quantum Error Correction and the Problem of Decoherence in Quantum Systems58:00 – Superconducting Qubits: The Technology Behind Quantum Hardware1:05:00 – The Challenges of Packing More Qubits: Coherence Time and Integration of Quantum Systems1:12:00 – Temperature and Cooling Requirements for Superconducting Qubits1:20:00 – Advances in Quantum Error Correction and Strategies for Scaling Quantum Devices1:28:00 – Future Directions for Quantum Computing: Materials Science, Algorithms, and Hardware Innovations1:35:00 – Schrödinger's Cat: Exploring Quantum Superposition in a Philosophical Context1:45:00 – The Double-Slit Experiment: Quantum Interference and the Nature of Quantum Systems1:50:00 – The Future of Quantum Computing: Overcoming Challenges and Expanding Practical Applications2:00:00 – Concluding Thoughts on the Impact of Quantum Mechanics on Modern Technology and the Future of ComputingHosts:Amit Prakash: Co-founder and CTO at ThoughtSpot, former engineer at Google and Microsoft, and expert in distributed systems and machine learning.Guest:Professor Debdeep Jena: David E. Burr Professor of Engineering at Cornell University, expert in semiconductors, superconductors, and quantum devices.Follow the Hosts and Guest:Amit Prakash: LinkedIn | XDebdeep Jena: LinkedInHave questions or thoughts on AI? Drop us a mail at effortlesspodcasthq@gmail.comDon't forget to like, comment, and subscribe for more insightful conversations on the future of technology and innovation!

Episode 14 | The Effortless PodcastIn this episode of The Effortless Podcast, hosts Dheeraj Pandey and Amit Prakash sit down with Harpinder "Happy" Singh, AI/ML Engineer at DevRev, to explore the future of AI and machine learning in business automation. Happy, who joined DevRev in 2021, shares his journey from computer science to AI, discussing how DevRev is leveraging cutting-edge technologies like large language models (LLMs) and function calling to streamline enterprise workflows.Happy breaks down the key concepts of AI-driven workflows, the debate between federated and integrated systems, and the growing importance of Python in AI. He also shares insights from the CodeAct paper, which proposes using Python code execution for more efficient and flexible LLMs. The conversation highlights the transformative potential of AI in enterprise automation and how it is reshaping industries.They also cover:The evolution of AI at DevRev: From workflows to AI-driven automationThe role of Python in executing complex tasks for LLMsUnderstanding the user-agent-environment model in AI systemsHow federated vs. integrated systems impact AI performanceThe future of AI in enterprise automation and DevRev's innovationsHappy's decision to stay in India and the growing tech ecosystem in IndiaThis episode provides valuable insights into how AI is transforming business operations, making complex workflows more efficient and accessible. Whether you're an AI enthusiast, a developer, or a business leader, this conversation is a must-listen for anyone interested in the next wave of AI-driven innovation.Key Topics & Timestamps:00:00 – Introduction to Harpinder "Happy" Singh & His Journey into AI03:00 – Happy's Early Background: From Shahjahanpur to BITS Pilani06:30 – Transition to AI at DevRev09:30 – Bangalore Life and Growing with DevRev13:00 – AI in India vs. the US18:00 – Federated vs. Integrated Systems: Which Approach Works Best for AI?25:00 – The Role of Python in AI32:00 – User, Agent, and Environment Model in AI39:30 – The CodeAct Paper: Replacing Tool Calls with Python Code Execution47:00 – AI in Enterprise Automation: How DevRev Uses AI to Streamline Workflows54:00 – Looking Ahead at DevRev's AI Innovations1:00:00 – Final Reflections: The Future of AI in Business and AutomationHosts:Dheeraj Pandey: Co-founder and CEO at DevRev, formerly CEO of Nutanix, a tech visionary passionate about AI and systems thinking.Amit Prakash: Co-founder and CTO at ThoughtSpot, former engineer at Google and Microsoft, and expert in distributed systems and machine learning.Guest:Harpinder Jot Singh: AI/ML Engineer at DevRev, working on the cutting edge of large language models (LLMs), AI-driven workflows, and integrating AI into enterprise systems.Follow the Host and the Guest:Dheeraj Pandey: LinkedIn | XAmit Prakash: LinkedIn | XHarpinder Singh: LinkedInHave questions or thoughts on AI? Drop us a mail at effortlesspodcasthq@gmail.comDon't forget to like, comment, and subscribe for more insights into the future of AI, business automation, and enterprise technology!

Episode 13 | The Effortless PodcastIn this episode of The Effortless Podcast, hosts Dheeraj Pandey and Amit Prakash sit down with Dr. Sonika Johri, Founder and CEO of Coherent Computing, to dive deep into the revolutionary world of quantum computing. Dr. Johri, a physicist with a PhD in condensed matter physics from Princeton University, takes us on her journey from engineering physics at IIT Delhi to becoming a leading figure in the quantum industry, having worked at Intel and IonQ.Sonika explains the core concepts of quantum computing—superposition, entanglement, and the quantum state space—and how they fundamentally change how we approach complex problems in fields like chemistry, material science, and AI. She discusses the future potential of quantum technologies, including the exciting prospects for Quantum AI and the shift in programming paradigms as we move from low-level machine code to higher-level abstractions.They also cover: The evolution of quantum hardware: From small qubits to scaling quantum systemsWhat makes quantum computing different from classical computingThe intersection of quantum computing and artificial intelligence Sonika's mission to democratize quantum through Coherent ComputingThe current state of quantum software and the tools that will shape the futureThis episode offers insights into quantum computing, AI, and how these emerging technologies will reshape the future of computing. Whether you're a tech enthusiast, developer, or entrepreneur, this conversation is a must-listen for anyone curious about the next frontier in technology.Key Topics & Timestamps:[00:00] – Introduction to Dr. Sonika Johri & Her Journey into Quantum Tech[03:00] – Sonika's early influences: Einstein and IIT Delhi[06:30] – Understanding Condensed Matter Physics[12:00] – Quantum Computing vs Classical Computing[20:00] – How Quantum Can Solve Complex Problems (Chemistry, Optimization, AI)[28:00] – Quantum Hardware: The Role of Qubits and Their Physical Realization[35:00] – Programming Quantum Computers: From Low-Level Gates to High-Level Abstractions[43:00] – Building Quantum Applications: Real-World Use Cases from IonQ and Coherent Computing[52:00] – The Future of Quantum AI: Machine Learning and Quantum Reasoning[1:00:00] – Quantum's Impact on Cryptography and Data Security[1:05:00] – The Mission of Coherent Computing: Making Quantum Accessible[1:12:00] – Looking Ahead: Future Episodes on Quantum Computing and AI[1:20:00] – Wrap-Up and Final ThoughtsHosts:Dheeraj Pandey: Co-founder and CEO at DevRev, formerly CEO of Nutanix, a tech visionary passionate about AI and systems thinking.Amit Prakash: Co-founder and CTO at ThoughtSpot, former engineer at Google and Microsoft, and expert in distributed systems and machine learning.Guest:Dr. Sonika Johri: Founder and CEO of Coherent Computing, a quantum software startup aiming to make quantum models accessible through developer-friendly tools. Formerly at Intel and IonQ, Sonika brings her experience in building quantum software and applications for industries like finance, chemistry, and optimization.Follow the Host and the Guest:Dheeraj Pandey: LinkedIn | XAmit Prakash: LinkedIn | XDr. Sonika Johri: LinkedIn | XHave questions or thoughts on quantum computing? Drop us a mail at EffortlessPodcastHQ@gmail.comDon't forget to like, comment, and subscribe for more deep dives into the future of technology, AI, and quantum computing!

In this episode of The Effortless Podcast, host Dheeraj Pandey sits down with Bipul Sinha, co-founder and CEO of Rubrik, to explore the power of relentless innovation, first-principles thinking, and continuous reinvention.Bipul shares his journey from Oracle to venture capital, his transition from investor to entrepreneur, and the bold thinking behind Rubrik's evolution from backup and recovery to cybersecurity and AI-driven data protection. He and Dheeraj reflect on lessons from Larry Ellison, the shifting tech landscape, and the importance of being non-consensus in building transformative businesses.They also discuss:

In this episode, Amit and Dheeraj dive deep into the world of AI reasoning models with Alex, an AI researcher involved in OpenThinker and OpenThoughts. They explore two recent groundbreaking papers—SkyT1 and S1 (Simple Test Time Scaling)—that showcase new insights into how large language models (LLMs) develop reasoning capabilities.From structured reasoning vs. content accuracy to fine-tuning efficiency and the role of active learning, this conversation highlights the shift from prompt engineering to structured supervised fine-tuning (SFT) and post-training techniques. The discussion also touches on open weights, open data, and open-source AI, revealing the evolving AI landscape and its impact on startups, research, and beyond.Key Topics & Chapter Markers[00:00] Introduction – Why reasoning models matter & today's agenda[05:15] Breaking Down SkyT1 – Structure vs. Content in reasoning[15:45] Open weights, open data, and open-source AI[22:30] Fine-tuning vs. RL – When do you need reinforcement learning?[30:10] S1 and the power of test-time scaling[40:25] Budget forcing – Making AI "think" more efficiently[50:50] RAG vs. SFT – What should startups use?[01:05:30] Active learning – AI asking the right questions[01:15:00] Final thoughts – Where AI reasoning is heading nextResources & Links

This is the second part of episode 10 of Effortless Podcast, hosts Dheeraj Pandey and Amit Prakash sit down with Alex Dimakis, a renowned AI researcher and professor, to discuss one of the biggest breakthroughs in open AI models—DeepSeek R1. They explore how DeepSeek's innovations in reasoning, reinforcement learning, and efficiency optimizations are reshaping the AI landscape.The conversation covers the shift from large, proprietary AI models to open-source alternatives, the role of post-training fine-tuning, and how reinforcement learning (GRPO) enables reasoning capabilities in LLMs. They also dive into KV caching, mixture of experts, multi-token prediction, and what this means for NVIDIA, hardware players, and AI startups.Key Topics & Timestamps:[00:00] - Introduction & Why DeepSeek Matters[01:30] - DeepSeek R1: Open-Source AI Disrupting the Industry[03:00] - Has China Become an AI Innovator?[07:30] - Open Weights vs. Open Data: What Really Matters?[10:00] - KV Caching, Mixture of Experts & Model Optimizations[21:00] - How Reinforcement Learning (GRPO) Enables Reasoning[32:00] - Why OpenAI is Keeping Its Reasoning Traces Hidden[45:00] - The Impact of AI on NVIDIA & Hardware Demand[1:02:00] - AGI: Language Models vs. Multimodal AI[1:15:00] - The Future of AI: Fine-Tuning, Open-Source & Specialized ModelsHosts:Dheeraj Pandey: Co-founder and CEO at DevRev, formerly Co-founder and CEO of Nutanix. A tech visionary with a deep interest in AI and systems thinking.Amit Prakash: Co-founder and CTO at ThoughtSpot, formerly at Google AdSense and Bing, with extensive expertise in analytics and large-scale systems.Guest:Alex Dimakis: Professor at UC Berkeley and co-founder of Bespoke Labs, Alex has made significant contributions to deep learning, machine learning infrastructure, and the development of AI reasoning frameworks.Follow the Hosts and the Guest:Dheeraj Pandey:LinkedIn - https://www.linkedin.com/in/dpandeyTwitter - https://x.com/dheerajAmit Prakash:LinkedIn - https://www.linkedin.com/in/amit-prak...Twitter - https://x.com/amitp42Alex Dimakis:LinkedIn - https://www.linkedin.com/in/alex-dima...Twitter - https://x.com/AlexGDimakisShare Your Thoughts:Have questions, comments, or ideas for future episodes? Email us at EffortlessPodcastHQ@gmail.comDon't forget to Like, Comment, and Subscribe for more in-depth discussions on AI, technology, and innovation!

In this episode of the Effortless Podcast, hosts Dheeraj Pandey and Amit Prakash sit down with Alex Dimakis, a renowned AI researcher and professor at UC Berkeley. With a background in deep learning, graphical models, and foundational AI frameworks, Alex provides unparalleled insights into the evolving landscape of AI.The discussion delves into the detailing of foundation models, modular AI architectures, fine-tuning, and the role of synthetic data in post-training. They also explore practical applications, challenges in creating reasoning frameworks, and the future of AI specialization and generalization.As Alex puts it, "To deep seek or not, that's the $1 trillion question." Tune in to hear his take on how companies can bridge the gap between large generalist models and smaller specialized agents to achieve meaningful AI outcomes.Key Topics and Chapter Markers:Introduction to Alex Dimakis & His Journey [0:00]From Foundation Models to Modular AI Systems [6:00]Fine-Tuning vs. Prompting: Understanding Post-Training [15:00]Synthetic Data in AI Development: Challenges and Solutions [25:00]The Role of Reasoning and Chain of Thought in AI [45:00]AI's Future: Specialized Models vs. General Systems [1:05:00]Alex's Reflections on AI Research and Innovation [1:20:00]Hosts:Dheeraj Pandey: Co-founder and CEO at DevRev, formerly Co-founder and CEO of Nutanix. A tech visionary with a deep interest in AI and systems thinking.Amit Prakash: Co-founder and CTO at ThoughtSpot, formerly at Google AdSense and Bing, with extensive expertise in analytics and large-scale systems.Guest:Alex Dimakis: Professor at UC Berkeley and co-founder of Bespoke Labs, Alex has made significant contributions to deep learning, machine learning infrastructure, and the development of AI reasoning frameworks.Follow the Hosts and the Guest:Dheeraj Pandey:LinkedIn: Dheeraj PandeyTwitter: @dheeraj Amit Prakash:LinkedIn: Amit PrakashTwitter: @amitp42 Alex Shtoyanov:LinkedIn: Alex DimakisTwitter: @AlexGDimakisShare Your Thoughts:Have questions, comments, or ideas for future episodes? Email us at EffortlessPodcastHQ@gmail.comDon't forget to Like, Comment, and Subscribe for more in-depth discussions on AI, technology, and innovation!

In this special guest episode of the Effortless Podcast, Amit Prakash sits down with Rajat Monga, the creator of TensorFlow and current Corporate Vice President of Engineering at Microsoft. With a career spanning Google Brain, founding Inference, and leading AI inferencing at Microsoft, Rajat offers a unique perspective on the evolution of AI. The conversation dives into TensorFlow's revolutionary impact, the challenges of building startups, the rise of PyTorch, the future of inferencing, and how transformative tools like GPT-4 and OpenAI's Gemini are reshaping the AI landscape.Key Topics and Chapter Markers:Introduction to Rajat Monga & TensorFlow Legacy [0:00]The inflection points in AI: TensorFlow's role and challenges [6:00]PyTorch vs. TensorFlow: A tale of shifting paradigms [16:00]The startup journey: Building Inference and lessons learned [27:00]Exploring O1 and advancements in reasoning frameworks [54:00]AI inference: Cost optimizations and hardware innovations [57:00]Agents, trust, and validation: AI in decision-making workflows [1:05:00]Rajat's personal journey: Tools for resilience and finding balance [1:20:00] Host:Amit Prakash: Co-founder and CTO at ThoughtSpot, formerly at Google AdSense and Bing, and a PhD in Computer Engineering. Amit has a strong track record in analytics, machine learning, and large-scale systems. Follow Amit on:LinkedIn - https://www.linkedin.com/in/amit-prakash-50719a2/  X (Twitter) - https://x.com/amitp42 Guest:Rajat Monga: He is a pioneer in the AI industry, best known as the co-creator of TensorFlow. He has held senior roles at Google Brain and Microsoft, shaping the foundational tools that power today's AI systems. Rajat also co-founded Inference, a startup focused on anomaly detection in data analytics. At Microsoft, he leads AI software engineering, advancing inferencing infrastructure for the next generation of AI applications. He holds a Btech Degree from IIT, Delhi. Follow Rajat on:LinkedIn - https://www.linkedin.com/in/rajatmonga/  X (Twitter) - https://twitter.com/rajatmonga Share Your Thoughts: Have questions or comments? Drop us a mail at EffortlessPodcastHQ@gmail.com Email: EffortlessPodcastHQ@gmail.com

In this episode, Amit and Dheeraj dive deep into the transformative world of AI agents and enterprise workflows. They explore the concept of “AgentOS”—a platform enabling modular agents, each equipped with specific skills to tackle distinct challenges within workflows. Drawing parallels between AI advancements and real-world enterprise needs, Amit and Dheeraj discuss the importance of balancing both probabilistic AI-driven nodes with deterministic workflows to enhance efficiency without losing context or accuracy. Together, they examine industry needs, like reducing redundancy in incident management through vector databases, and predict the impact of AI agents on collaboration platforms, employee workflows, and customer support. This episode is a rich, thought-provoking journey through the latest in AI, where Amit and Dheeraj also offer their insights into enterprise AI adoption, future trends, and their forecasts for the next decade of AI-driven business transformation.Key Topics and Timestamps:The Rise of AI Agents [0:14]System 1 and System 2 Thinking in AI [1:50]Workflows in Enterprise Automation [3:51]Handling Context and Intent in Workflows [10:32]Incident Management and Reducing Redundancy [43:57]Collaboration Platforms' Future [49:13]Optimizing Enterprise Workflows with Agentic Systems [1:03:46]The Enterprise AI Landscape and Predictions [1:13:18]Share Your Thoughts: Have questions or comments? Drop us a mail at EffortlessPodcastHQ@gmail.com

Key Topics and Chapter Markers:The Foundations of Modern Analytics [00:03:00]Cloud Computing's Impact on Analytics [00:15:30]Data Warehouse Wars: Snowflake vs. Databricks [00:26:15]AI, LLMs, and the Future of Analytics [00:41:10]Visualization as the Next Frontier in Analytics [00:45:00]Reflections on the Path to AI [00:52:30]Share Your Thoughts: Have questions or comments? Drop us a mail at EffortlessPodcastHQ@gmail.com

Key Topics & Chapter Markers:Recap from Part 1: The Early Years of AI [00:00:00]AI Architecture & Oracle's Innovation in Hash Joins [00:02:00]Impact of Nature in Creative and Collaborative Work [00:05:00]The Rise of Neural Networks: Language and Image Processing [00:10:00]Sparse and Dense Vectors Explained [00:15:00]Google Translate's Early Approaches & Statistical Methods [00:20:00]TensorFlow vs. PyTorch: Defining the Modern AI Framework [00:30:00]Dot Products, Similarity, and the Concept of Attention [00:35:00]Transformers & The Attention Mechanism Revolution [00:42:00]BERT, GPT, and the Dawn of Transfer Learning [01:00:00]The Road to ChatGPT and OpenAI's Innovations [01:10:00]The Future of AI and Computational Scaling [01:15:00]Share Your Thoughts: Have questions or comments? Drop us a mail at EffortlessPodcastHQ@gmail.com

Key Topics & Chapter Markers:AI's Evolutionary Journey & Key Challenges [00:00:00]Neural Networks: Inspiration from Biology [00:01:00]Weighted Sum, Inputs & Mathematical Functions [00:05:00]Gradient Descent & Optimization in Neural Nets [00:10:15]Computing Architecture: CPUs vs. GPUs [00:39:56]RNNs and Early Problems in Memory & Context [01:03:00]The Emergence of Convolutional Neural Networks (CNNs) [01:10:00]ImageNet, GPUs & Scaling Neural Networks [01:24:00]Share Your Thoughts: Have questions or comments? Drop us a mail at EffortlessPodcastHQ@gmail.com

Key Topics and Chapter Markers:Introduction and Catch-up [0:00]Yahoo vs. Google: Lessons from Deep Engineering [0:03:00]The Evolution of Essentialism in Company Building [0:10:00]Product Management: From Project Coordination to Deep Focus [0:16:00]AI and the Depth of Real-World Applications [0:21:00]Search, RAG, and Workflow Engines in AI [0:32:00]Analytics: Why Legacy Systems Still Matter in AI [0:44:00]The Power of Staying Financially Prudent Through Hype Cycles [0:55:00]Closing Thoughts: Sustaining Depth for Long-term Success [1:05:00]Share Your Thoughts: Have questions or comments? Drop us a mail at EffortlessPodcastHQ@gmail.com

In this episode, we talk about Product management from the lens of a startup

In this episode, we talk about how to build an early team that is set up for success. We also talk about the US-India corridor and how we have experienced building companies that take advantage of a significant talent pool in India and the large market in the US.

If you are looking at an early-stage startup to join, how do you tell the ones with high potential from the ones that may be doomed? We tackle this episode in the second episode of Effortless Podcast.

In this inaugural episode of the Effortless Podcast, Dheeraj and Amit introduce themselves and talk about the beginning of their entrepreneurial journey.