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Edge AI sounds like a way to save on cloud inference bills. In practice, it usually is not. The right reasons to go to the edge are latency, privacy, and bandwidth, in that order, and if your reason is not one of those three, stay in the cloud.
6 min readThe old Series A reflex was to raise the round and hire engineering up to twenty-five people. In 2026 that reflex is wrong. AI raises per-engineer output enough that you can stay lean far longer, but the organizational transition does not disappear. It relocates.
6 min readWhy now? 2023 is definitely a year of LLMs - GPT-4 and later on GPT-4-Turbo, LLaMA and LLaMA 2, Falcon, Mistral, Claude - a lot of different
4 min readThe increasing effects of climate change and the global population's growing demand for food have placed immense pressure on the agriculture industry.
2 min read