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MiniMax’s 229B-parameter MoE model delivers Claude-level coding performance at 8% the price, challenging the economics of agentic development.
Anthropic and OpenAI’s unprecedented transparency reveals the messy reality of large-scale AI system design, and why architects should pay attention.
Debunking the myth that Google’s Gemma models are lagging behind, and exploring how their multilingual capabilities are quietly dominating the AI landscape.
Why treating AI data as transactional tables beats unstructured blob chaos
Accenture’s AI rush and Deloitte’s hallucinated citations expose a dangerous trend, enterprises paying premium rates for Blackbox AI systems with zero accountability.
Sentient AI’s ROMA framework tackles hierarchical task decomposition with recursive planning, delivering SOTA performance on complex agent benchmarks
As venture capital fuels trillion-dollar AI valuations without profits, local and open-source models face an existential threat when the bubble bursts.
With 2.65x faster CPU inference, BitDistill signals a potential shift toward CPU-efficient AI deployment, reducing reliance on expensive GPU infrastructure.
M5’s 3.5x AI performance leap and 153GB/s memory bandwidth reshape local LLM economics, but is it enough to dethrone PC builds?
Software engineers confess that ‘vibe coding’ with AI assistants like Cursor is making programming tedious and creatively bankrupt, is technical craftsmanship dying?
Z.ai’s latest model pushes boundaries with 200K context and 15% efficiency gains, but can your rig handle the 204GB quant?
IBM’s Granite 4.0 Nano loads smarter AI onto your laptop, phone, or potato PC, banishing the cloud to the bargain bin of bad ideas.
