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Z.ai Ships GLM-5.3 Without Retraining the Base Model: Better at Complex Coding and Long-Horizon Tasks

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Xiaomi Power Bank 5i 20000 67W Review

Add MobiGyaan as a preferred source on GoogleLast month, Xiaomi introduced its latest Xiaomi Power Bank 5i 20000 67W at ₹3,299, and it brings high-speed charging, multi-device support, and a built-in USB Type-C cable (also doubles as a carry loop) to the company’s portable power lineup. The power bank combines a high 20,000 mAh battery capacity, […]

Z.ai Ships GLM-5.3 Without Retraining the Base Model: Better at Complex Coding and Long-Horizon Tasks

Z.ai just released GLM-5.3. GLM-5.3 runs on the same 743B base model as GLM-5.2. Every reported gain comes from scaled post-training: more task environments, more environment types, longer training. The results land in two places. Coding jumps most on the longest-horizon benchmarks, with Terminal-Bench 3.0 moving from 4.6 to 28.3. Cybersecurity moved further than Z.ai […]

SEO Title:Mahindra Scorpio Classic Update Leaked

Mahindra appears to be preparing a significant update for the Scorpio Classic, with details of the refreshed SUV surfacing online ahead of an official announcement. While the mechanical package is expected to remain unchanged, the leaked information points towards a series of exterior styling revisions and the addition of new features, including a first-ever sunroof […]

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NVIDIA garak Tutorial: Build a Complete Defensive LLM Red-Teaming Workflow with Custom Probes and Detectors

print(“\n########## 5. ANALYSIS ##########”) import numpy as np, pandas as pd def find_latest_report(): cands = [] for base in [os.path.expanduser(“~/.local/share/garak/garak_runs”), os.path.expanduser(“~/.cache/garak”), “.”]: cands += glob.glob(os.path.join(base, “**”, “*report.jsonl”), recursive=True) cands = [c for c in cands if os.path.getsize(c) > 0] return max(cands, key=os.path.getmtime) if cands else None report_path = report_path or find_latest_report() print(“Analysing:”, report_path) evaluations = […]

Poetiq’s Meta-System Automatically Builds a Model-Agnostic Harness That Improved Every LLM Tested on LiveCodeBench Pro Without Fine-Tuning

Poetiq has just published some very interesting results showing its Meta-System reached a new state-of-the-art on LiveCodeBench Pro (LCB Pro), a competitive coding benchmark, by automatically building and optimizing its own inference harness — without fine-tuning any underlying model or accessing model internals. The result: GPT 5.5 High with Poetiq’s harness scores 93.9% on LCB […]