Samsung (005930.KS) challenges $TSM production with Panel-Level-Packaging Samsung plans to bring its 415×510mm FOPLP platform into mass production around 2028, sticking with a significantly larger panel format than TSMC’s 310×310mm standard The larger Samsung panel offers 2.2× the usable area of a 310×310mm panel, potentially providing meaningful unit-cost advantages. Samsung also already has high-volume PLP manufacturing experience from mobile and wearable chips, giving it existing infrastructure and expertise in warpage control The challenge is moving the technology into AI server packaging, where integrating logic dies and HBM is considerably more difficult. TSMC also has an established advantage because its 310×310mm format has already attracted a large equipment, materials and OSAT ecosystem Samsung is also targeting glass-substrate mass production in 2029–2030 as package sizes increase and conventional ABF substrates face growing technical and supply constraints Perhaps most interestingly, Samsung is aggressively using AI in packaging R&D. Physics-Informed Neural Networks are being applied to signal integrity, power integrity and thermal simulations, reportedly reducing some engineering workflows from one year to a single day

pump at 0.005 was major resistance and it's logical that this takes some time to consolidate here anything above 0.004 is good consolidation LTF structure is pretty ugly on this one but HTF is still pretty intact

Samsung Electronics (005930 KS) went from third place to No. 1 in global Mini LED TV shipments in Q2, taking 28.2% share, according to Omdia. Mini LED TVs made up 13% of global TV shipments during the quarter as Samsung and LG expanded their lineups and lowered entry prices.

GLM-5.2 is now just 0.005 away from Fable-5 in visual spec-to-app development. On VISTA’s latest C4 leaderboard: 🥇 Claude Code + Fable-5 — 0.274 🥈 Claude Code + GLM-5.2 — 0.269 🥉 Claude Code + Opus 4.8 — 0.263 　 Claude Code + Sonnet 4.6 — 0.248 　 Cursor + Composer 2.5 — 0.212 　 Codex + GPT-5.5 — 0.205 The story is no longer just “which model writes better code.” For real app-building agents, performance is increasingly shaped by the full stack: 🧠 model 🛠️ harness 🔁 tool loop 👁️ visual understanding ⚙️ reasoning setup The harness is becoming part of the model. 🔗