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- The latest India Justice Report exposes persistent structural inefficiencies across the four pillars of the justice system—police, judiciary, prisons, and legal aid—that risk deepening inequality in access to justice.
- The police force faces a 23% overall vacancy rate, with forensic staff shortages exceeding 50%.
- Women remain underrepresented, holding only 8% of senior positions, well below the 33% benchmark.
- In the judiciary, India has just 15 judges per 10 lakh population, far short of the recommended 50.
- Diversity also lags, with women comprising only 14% of High Court judges, and only Karnataka meeting caste-based quotas.
- Prisons are 30% understaffed and overcrowded at 131% capacity, with undertrials making up 76% of inmates.
- Legal aid is also under pressure, as para-legal volunteer numbers have dropped by 38%.
- The report recommends incentivizing states to improve infrastructure, representation, and rehabilitation efforts to build a more equitable and sustainable justice system.
- QpiAI Launches India’s First Full-Stack Quantum Computer on World Quantum Day
- On April 14, World Quantum Day, QpiAI—a startup selected under the National Quantum Mission (NQM)—unveiled QpiAI-Indus, a 25-qubit superconducting quantum computer.
- This marks India’s first full-stack quantum computing system, integrating high-performance quantum hardware, scalable control mechanisms, and optimized hybrid software.
- Quantum computers harness the principles of quantum mechanics to tackle problems too complex for classical systems. Unlike classical bits, qubits can exist in multiple states at once (superposition), be deeply connected (entanglement), and use interference to improve accuracy.
- This breakthrough positions India alongside global leaders like the U.S., China, and France in the quantum technology space. It also lays the groundwork for quantum-secure communication, advanced molecular modeling for drug discovery, enhanced AI and machine learning capabilities, and smarter manufacturing with faster prototyping and reduced testing costs. QpiAI-Indus signals a major leap forward in India’s quantum technology ambitions.
- Google has recently introduced its 7th-generation Tensor Processing Unit (TPU), named Ironwood, designed to boost the performance of AI models.
- About TPU
- Developed by Google in 2015, the TPU (Tensor Processing Unit) is a specialized processor or Application-Specific Integrated Circuit (ASIC) optimized for machine learning and artificial intelligence (AI) tasks. TPUs excel in handling tensor operations, which are the core data structures used in ML models.
- Advantages of TPUs
- Optimized for AI: TPUs outperform traditional CPUs and GPUs when it comes to AI workloads, offering faster and more efficient processing.
- Faster Training: TPUs are capable of training complex neural networks in just a few hours, greatly reducing the time needed compared to other processors.
- About CPUs and GPUs
- CPU: A general-purpose processor that handles a wide range of tasks, with multitasking capabilities determined by the number of cores (typically 2 to 16).
- GPU: A specialized processor designed to handle multiple tasks in parallel, making it ideal for graphics rendering and AI computations.