#anti-hallucination training
6 related articles
·3 min
Which ML Projects Will Actually Help You Land a Job Offer?
Ditch overused tutorial projects. Learn what hiring managers actually look for in ML portfolios: LLM apps, Agent systems, MLOps practices, and real-world solutions.
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·3 min
AI Daily: Alibaba Open-Sources Dance Model, World Model Launches, First AI-Native Phone Debuts
Alibaba open-sources 14B dance model Wan-Dancer, AutoNavi launches World Studio, Stepfun debuts AI-native phone STEPS NEO; GPT-5.6 file deletion and AI companion shutdowns spark safety and regulation debates.
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·3 min
Tencent Hunyuan HY3 In-Depth Review: How a Small Open-Source Model Punches Above Its Weight
In-depth analysis of Tencent's open-source reasoning model Hunyuan HY3: MoE architecture, 295B total params, Apache 2.0 license, coding & front-end rivaling DeepSeek V4 Pro at 1/35 the cost.
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·2 min
Deep Dive into Tencent Hunyuan Hy3: How a 295B MoE Model Cracks the Agent Deployment Challenge
Tencent Hunyuan Hy3 launches with a 295B MoE architecture activating just 21B params and 256K context. Hallucination cut from 12.5% to 5.4%, MRCR nearly doubled, with MTP and EAGLE decoding and Day-0 SGLang support.
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·4 min
Deep Dive: How Palantir Agents Interact with the Ontology
A deep dive into Palantir's five-layer Agent-Ontology architecture: how Context, Query, Logic, Action, and Governance layers work together to enable governed enterprise AI Agents, with a live demo.
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·3 min
Fable 5 System Prompt Leak Analysis: The Core Design Logic Behind Nearly 100,000 Words of AI Behavioral Specifications
Deep analysis of Claude Code Fable 5's leaked 100K-word system prompt, covering Memory mechanisms, anti-hallucination strategies, Refusal Handling, and actionable prompt engineering practices.
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