instead of trying to fab one giant, ultra-expensive monolithic die on those crazy pricey cutting-edge nodes (like 2nm), the manufacturers just break the chip into smaller pieces called chiplets. The critical compute cores still get printed on the leading-edge stuff, while the secondary bits (I/O, power interfaces, etc.) get made on older, way cheaper mature nodes. Then they slap them all together on a single substrate. way less silicon waste and way lower total production costs. wafer are round but chiplets are rectangular so some wafer is guranteed to be wasted

**Bharat Semiconductor AI Mission (B-SAIM): AI for Aatmanirbhar Chip Innovation** I propose a national AI-powered platform—B-SAIM—to democratise semiconductor innovation in India. It will empower students, researchers, startups and MSMEs with AI-assisted chip design, virtual labs, simulation, verification, RTL/Verilog learning, open-source EDA tools and indigenous IP libraries. A multilingual AI mentor will make advanced semiconductor knowledge accessible in Indian languages. The platform will connect innovators with government and industry challenges, transforming ideas into prototypes and market-ready solutions through mentorship, incubation and funding. B-SAIM will create a national innovation marketplace where Indian talent solves critical technology problems. By integrating AI, indigenous chip design and skill development, India can reduce foreign dependence, create high-value jobs, strengthen national security and build a globally competitive semiconductor ecosystem.

The convergence of Artificial Intelligence and Semiconductors can become a defining force of India’s next technological revolution. AI can accelerate chip design, improve manufacturing precision, reduce energy consumption and enable smarter semiconductor ecosystems. At the same time, advanced and indigenous chips can make AI faster, more affordable, secure and accessible across healthcare, agriculture, education, defence and smart infrastructure. India should focus on R&D, semiconductor fabrication, AI-chip innovation, talent development and strong industry-academia collaboration. By combining our software strength with semiconductor capabilities, India can move from being a technology consumer to a global technology creator. This intersection can create high-value jobs, strengthen digital sovereignty and position India as a trusted hub for next-generation AI and semiconductor innovation.

The shift I have personally seen in practice isn't AI generating chips from start to finish but AI shortening the iteration cycle in analog and mixed-signal design especially using open chip-design flow in projects and taking designs through tapeout. Tasks such as tuning a circuit, checking stability or finding an outdated design file before it invalidates simulation can take significant engineering time. These tasks involve repeated checking, running tools, reviewing results and making changes. AI can help reduce this cycle by working with tools and their outputs. Concern is that we as a nation are training our students on proprietary EDA tools we do not control and whose access can be disrupted. We should move faster to build our own capabilities with open-source EDA and LLMs, keeping our tools and knowledge under control. Example of analog driven analog layout done in minutes which earlier used to take a day or two.

🇮🇳 CHIPSAARTHI CHIPSAARTHI is a proposed AI-powered platform to support Indian semiconductor and VLSI development. It can help students, researchers, engineers and startups with Verilog/RTL design, debugging, verification, circuit optimization and FPGA prototyping. It can also provide AI-based learning, simulations and virtual labs, helping develop skilled semiconductor talent while supporting India's indigenous EDA ecosystem. Vision: “CHIPSAARTHI — AI as the guide, Indian talent as the creator, and semiconductors as the foundation for a self-reliant digital India.”

India's chip manufacturing ambitions (Micron, Kaynes, domestic fabs) face a critical gap: we're building silicon but not the security verification IP to validate it post-silicon. Every chip leaving an Indian fab goes to market without indigenous runtime threat detection. SHATRU (Secure Hardware with Autonomous Threat Recognition Unit) is a lightweight, AI-trained hardware security monitor that embeds as minimal IP in any SoC to detect runtime threats—voltage anomalies, supply-chain tampering, unauthorized memory access—in real-time, operating completely offline (critical for mil/crit-infra chips). It learns India-specific threat signatures from domestic fab datasets and has minimal die footprint (~0.5-1% area overhead). The solution eliminates foreign audit dependencies, accelerates chip bring-up by 30-40%, and becomes a reference design for India's emerging SoC ecosystem. Implementation path: final-year thesis project with IEEE publication on hardware threat detection methodology and

To achieve true self-reliance in semiconductors, India must own the design software layer. Our spending on foreign software licenses is projected to double by 2030. We cannot secure our electronics ecosystem if our chip designs rely entirely on foreign geometry engines. As a solution, I am building "PurusKernel" from scratch—an indigenous geometric CAD kernel developed natively for Windows OS, with zero external dependencies. It currently powers PurusCAD (Architecture) and PurusMech (mechanical). By extending this Windows-native architecture to the semiconductor industry, we can disrupt the EDA space in two key areas: Advanced 3D-IC Packaging: Essential for modern AI chips that rely on complex 3D chip stacking. AI-Driven Layout Automation: An indigenous kernel allows local developers to build AI agents that auto-optimize chip geometries on standard workstations. We must back local inventors building bedrock software IP. x.com/purus_m

ai chat messaging system must be connected to all government online portals/websites.it would easy for users/clients to solve there general queries through ai.it would be very helpful to all.example-we can query about startups,make in india,connect through many other bodies properly.ai could help alot.lots of time would be saved.

Suggestion for using AI- -Minimum use of AI in personal life. -Maximum use in Industrial,Banking, and all other sectors. -AI is the best tool in Research -Maximum use of AI where humans have not capability to work e.g.Deserts,Deep sea exploration, Antarctic regions,Space exploration, Mining operations,Fire fighting equipments -

I WILL LIKE TO BRING THE SERIOUS ATTENTION TO PMO INDIA TO KINDLY BUILD THE PROPER INFRASTRUCTURE AND ECO SYSTEM OF STARTUP INDIA PORTAL.THE PORTAL SHOULD BE ACCESIBLE AND WE CAN EASILY WORK AND RESEARCH THE STARTUP INDIA POLICY.WE CAN GAIN AND DISCUSS THE IDEAS.AI SHOULD BE CONNECTED TO ALL OF BUSINESS PORTALS,LIKE, STARTUP INDIA,MAKE IN INDIA AND ANOTHERS.AI COULD HELP USERS TO REACH TO THE GOVERNMENT POLICIES.AI COULD HELP THAT WE ARE EASILY CONNECTED TO THEM.PURE PROFFESIONAL SYSTEM.I WILL EAGERLY WAIT FOR THE PROPERLY REPLY BY PMO INDIA