Hardware & Computing
Chip architecture, GPUs, quantum computing, custom silicon, memory-centric computing, semiconductor supply chains
Realizing Lattice Surgery on Two Distance-Three Repetition Codes with Superconducting Qubits
First experimental demonstration of lattice surgery on superconducting qubits — merges two distance-three repetition-code qubits using fault-tolerant circuits, validating a core building block for scaling surface codes
Deep Neural Network Inference on an Integrated, Reconfigurable Photonic Tensor Processor
First production-ready photonic tensor processor for DNN inference — packaged in a 19-inch rack unit, PyTorch-integrated, MNIST + CIFAR-10 benchmarked. Runs pretrained networks without chip-specific retraining
Integrated Photonic Neural Network with On-Chip Backpropagation Training
First integrated photonic deep neural network with end-to-end on-chip gradient-descent backpropagation — all linear AND nonlinear computations on a single silicon photonic chip. 92.5% accuracy on 2D classification; automatically compensates for fabrication variations
Quantum Error Correction Below the Surface Code Threshold
Google Willow: distance-5 and distance-7 surface codes operate below threshold — logical error suppression factor Λ = 2.14 per 2 distance steps; distance-7 achieves 0.143% error per cycle; logical memory exceeds physical qubit lifetime by 2.4x
Inside the NVIDIA Vera Rubin Platform
Six-chip co-designed AI supercomputer platform: 50 PFLOPS FP4 inference, 288GB HBM4 at 22TB/s, 5x improvement over Blackwell
Quantinuum Demonstrates Quantum Computations With 94 Protected Logical Qubits
94 error-protected logical qubits running 'beyond break-even' on a trapped-ion processor using 98 physical qubits — iceberg codes dramatically reduce encoding overhead
IBM Delivers New Quantum Processors, Software, and Algorithm Breakthroughs on Path to Advantage and Fault Tolerance
IBM Quantum Nighthawk (120 qubits, 5000 two-qubit gates) ships end of 2025 with concrete path: verified quantum advantage by end-2026, fault-tolerant system by 2029
Lightmatter: A New Kind of Computer — Photonic Processor Running Production Transformers
First photonic processor to run unmodified transformers + CNNs + RL at near-32-bit-float accuracy — no fine-tuning, no quantization-aware training. 65.5 TOPS (ABFP16) at 78W electrical + 1.6W optical, with 3D-integrated six-chip design using ~1M photonic components
NVIDIA, ASML, TSMC and Synopsys Set Foundation for Next-Generation Chip Manufacturing
NVIDIA cuLitho computational-lithography library deepens integration with ASML, TSMC, and Synopsys. GPU-accelerated mask synthesis becomes a structural enabler for sub-2nm production and a softener for TSMC's deferral of high-NA EUV
Custom Silicon Inflection 2026: Hyperscaler ASICs vs NVIDIA GPU
Deep technical analysis arguing NVIDIA's rack-as-product co-design strategy deepens lock-in despite custom ASIC growth at 44.6% CAGR
The Angstrom Era Arrives: TSMC Enters 2nm Mass Production and Unveils 1.6nm Roadmap
TSMC N2 hit mass production Q4 2025 (65-75% yield, Apple got >50% of capacity); A16 (1.6nm) with backside-power Super Power Rail targets late 2026 volume — first departure from FinFET in a decade
HBM Architectural Shakeup: HBM4, HBM4E, C-HBM4E — 3nm Base Dies Enable 2.5x Performance
HBM base dies move from DRAM to 3nm logic (TSMC N3P) — enables 2.5x bandwidth (3 TB/s per stack), 2x channels, C-HBM4E adds custom base dies with near-memory compute
Memory-Centric Computing: A Paradigm Shift for Sustainable and Efficient Systems
Argues processor-centric computing is fundamentally broken: 60–90% of system energy is data movement, not compute; DRAM can compute (RowClone, Ambit); reliability threats (RowHammer, RowPress, column disturbance) force memory intelligence anyway; JEDEC + trillion-dollar incumbency is the bottleneck, not technology
TSMC to Quadruple Advanced Packaging Capacity: Reaching 130,000 CoWoS Wafers Monthly by Late 2026
TSMC CoWoS ramp: ~35K wafers/mo (late 2024) → 75K (end 2025) → 130K target (end 2026); NVIDIA secures ~60% of capacity.
SK hynix 2026 Outlook: HBM3E Dominates, HBM4 Dual Strategy Amid 3 Market Headwinds
HBM3E 12-Hi 36GB ≈ 2/3 of 2026 HBM shipments; HBM4 16-Hi 48GB targets Q4 2026; SK Hynix ~60% share, 2026 capacity pre-booked by NVIDIA + OpenAI.
U.S. AI Data Center Delays: 7 GW Capacity Crisis (2026)
12 GW announced 2026 vs 5 GW under construction = 7 GW shortfall; AI DC load ~10 GW by end-2026; AEP queue 190 GW raw / 24 GW committed.
Google Expands Quantum Efforts to Include Neutral Atom Systems
Google Quantum AI adopts a dual-modality strategy — adds neutral atom computing alongside Willow superconducting, via strategic investment in QuEra. Internal effort led by Adam Kaufman (CU Boulder). Signals that neutral atoms are now a peer architecture, not a challenger
TSMC Debuts A13 Technology at 2026 North America Technology Symposium
TSMC unveils A13 (1.3nm direct shrink of A14) and N2U process nodes at NA Tech Symposium — A13 production targeted for 2029 for AI/HPC, N2U a more affordable variant for phones/laptops/AI; Arizona advanced packaging facility announced
TSMC Delays Use of ASML's High-NA EUV Machines Over Cost Concerns
TSMC publicly defers high-NA EUV adoption until at least 2029, citing ~$400M per-machine cost (vs ~$200M for current EUV). Plans to squeeze more performance from existing EUV through process optimization (A13, N2U) — major signal for ASML revenue
NVIDIA Snaps Up AI Chip Packaging Capacity as TSMC Expands in U.S.
NVIDIA has reserved the majority of TSMC's most advanced packaging capacity (CoWoS), making advanced packaging — not fabrication — the next bottleneck for AI accelerator supply