📰 Dev.to · AI Tech Connect

A $10.3B valuation for silicon that has given up the ability to run anything but a transformer. The bet, the trade-off, and why it moves your GPU bill.

Thinking Machines Lab's Inkling is a 975B-parameter MoE reasoning model under Apache 2.0 — and the lab says its 276B sibling keeps pace. The licence, not the si

Architecture guide to compliant LLM routing under India's DPDP Act, UK GDPR and EU rules: region-aware gateways, perimeter PII masking, hybrid local-plus-API se

Meta's Muse Spark 1.1 arrives with the company's first paid AI model API: $1.25/$4.25 per million tokens, a 1M context and dual OpenAI/Anthropic SDK compatibili

Reasoning models now plan their own chain of thought. Manual step-by-step prompts, few-shot scaffolds and 'be concise' waste tokens or degrade output — here is

Anthropic's Sonnet 5 closes most of the benchmark gap to Opus 4.8 at roughly 40% of the standard price. The buy-vs-build tier calculus for cost-sensitive teams

Sample sizing, sequential testing and guardrail metrics for comparing prompt and model rollouts without fooling yourself.

How to combine task-specific LoRA adapters into one stronger model with MergeKit, without retraining from scratch.

Build a document-extraction pipeline you can trust in production — schema-first VLM extraction, confidence gating, human-in-the-loop and evals.

Apache 2.0 MoE with 8B total / 760M active parameters, trained entirely on AMD Instinct hardware — the first credible no-NVIDIA frontier training story.

Alibaba's Qwen3.6-27B outperforms the 397B Qwen3.5 MoE on agentic coding benchmarks. Apache 2.0, fits on a single A100 — the self-hostable frontier coding agent

A three-tier caching stack — exact match, semantic similarity, provider-level prompt cache — that compounds to 70–90% spend reduction, with real production hit

Why 'lost in the middle' degrades recall past ~20k tokens and how to fight it with XML markers, hierarchical processing, and server-side compaction on Claude, G