<p>Bengaluru: Deeptech startup Tattvam AI has raised $1.7 million in pre-seed funding led by Seedcamp, with participation from EWOR, Entropy Industrial Ventures, Concept Ventures, and semiconductor angel Stan Boland.</p><p>Founded by Bragadeesh Suresh Babu and Lannan Jiang, Tattvam AI is building the AI layer of chip design to cut years-long, manual semiconductor development cycles.</p>.Stalin creating 'artificial' narrative of rights deprivation in state: BJP leader Soundararajan.<p>Unlike general-purpose chips designed to handle a wide variety of tasks, custom silicon refers to specialised processors built and optimised for specific workloads — such as AI training or AI inference. These purpose-built chips can deliver up to 100x performance improvements over general-purpose hardware like GPUs for their targeted applications, while often consuming significantly less power.</p><p>Companies from tech giants to emerging startups are racing to build custom chips. Google has developed its own Tensor Processing Units (TPUs) optimised for AI workloads, Nvidia has partnered with Groq on specialised AI inference chips, and UK startups Fractile and Olix are building custom processors.</p><p>Bragadeesh Suresh Babu said, "Designing a chip is still one of the most manual, time-consuming endeavours in engineering. Even making a seemingly small change can take months of work. For the first time in history, we have a path towards changing that. That’s why we’re building Tattvam AI. We're building an AI system that deeply understands circuit structure and the design intent, reasoning from first principles to make the design decisions that today consume months of engineering time."</p><p>Babu added that chip design is fundamentally a reasoning problem over an enormous search space, not unlike the kind of reasoning that’s needed to solve hard problems in mathematics. Current AI tools, even the most advanced LLMs, struggle with the deep structural understanding that chip design demands. We're building a reasoning model that actually understands circuits from first principles - the constraints, the tradeoffs, the interdependencies - the same way a world-class engineer would and doing it in a fraction of the time.</p><p>Bragadeesh is an alumnus of IIT Madras. He was an early engineer at the UK-based brain-monitoring startup CoMind, which recently raised $100 million. He later became one of the earliest engineers at the UK-based chip startup Fractile. </p>
<p>Bengaluru: Deeptech startup Tattvam AI has raised $1.7 million in pre-seed funding led by Seedcamp, with participation from EWOR, Entropy Industrial Ventures, Concept Ventures, and semiconductor angel Stan Boland.</p><p>Founded by Bragadeesh Suresh Babu and Lannan Jiang, Tattvam AI is building the AI layer of chip design to cut years-long, manual semiconductor development cycles.</p>.Stalin creating 'artificial' narrative of rights deprivation in state: BJP leader Soundararajan.<p>Unlike general-purpose chips designed to handle a wide variety of tasks, custom silicon refers to specialised processors built and optimised for specific workloads — such as AI training or AI inference. These purpose-built chips can deliver up to 100x performance improvements over general-purpose hardware like GPUs for their targeted applications, while often consuming significantly less power.</p><p>Companies from tech giants to emerging startups are racing to build custom chips. Google has developed its own Tensor Processing Units (TPUs) optimised for AI workloads, Nvidia has partnered with Groq on specialised AI inference chips, and UK startups Fractile and Olix are building custom processors.</p><p>Bragadeesh Suresh Babu said, "Designing a chip is still one of the most manual, time-consuming endeavours in engineering. Even making a seemingly small change can take months of work. For the first time in history, we have a path towards changing that. That’s why we’re building Tattvam AI. We're building an AI system that deeply understands circuit structure and the design intent, reasoning from first principles to make the design decisions that today consume months of engineering time."</p><p>Babu added that chip design is fundamentally a reasoning problem over an enormous search space, not unlike the kind of reasoning that’s needed to solve hard problems in mathematics. Current AI tools, even the most advanced LLMs, struggle with the deep structural understanding that chip design demands. We're building a reasoning model that actually understands circuits from first principles - the constraints, the tradeoffs, the interdependencies - the same way a world-class engineer would and doing it in a fraction of the time.</p><p>Bragadeesh is an alumnus of IIT Madras. He was an early engineer at the UK-based brain-monitoring startup CoMind, which recently raised $100 million. He later became one of the earliest engineers at the UK-based chip startup Fractile. </p>
