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Stop Hallucinations at the Source: Hybrid RAG That Checks Itself
Stop hallucinations. Validate every answer. Combine vector and graph search. We built DocuChat to solve real RAG problems in produ...
Ethos Ex Machina: How AI Creates Trust Without Truth
AI-generated texts gain trust not through evidence but through structure. Passive voice, fake balance, and false references simula...
A Quick Guide to Quantization for LLMs
Quantization is a technique that reduces the precision of a model’s weights and activations. Quantization helps by: Shrinking mode...
Re: Defeating Nondeterminism in LLM Inference, The Future is Predictable
Gemini generated reply to [Thinking Machine Labs'] first blog post. The post addresses the challenge of large language models (LLM...
What Will AI Make of Us Entrepreneurs?
Software engineers and entrepreneurs are on the cusp of a tech tsunami. This might be the last, and largest, 'clean up season' in...
Best Stock Market Data APIs For Algorithmic Traders (2025 Edition)
Alpha Vantage leads the best stock market data APIs followed by Xignite (QUODD), Intrinio, Barchart OnDemand, and QuoteMedia as s...
16 Failure Modes of RAG and LLM Agents and How to Fix Them With a Semantic Firew...
most RAG and agent bugs don’t throw errors—they drift. this article names 16 failure modes, gives one-screen repros, and shows min...
15 Core Ideas Shaping the Future of AI—and Why They Matter Today
Artificial Super-Intelligence (AGI) is not a single marvel, but a relay race of inter-locking technologies. Raw data and the right...
