"As enterprises focus on the ROI of their AI spend, small language models (SLMs) — which have fewer parameters than LLMs, making them cheaper to train and easier to run — are becoming an attractive option. In the last year, a rising number of players — from big tech to startups — have emerged with SLM offerings. By training on narrow datasets, small models, also called lightweight models, can be honed for targeted applications — with even higher, accuracy and performance to larger models." Claro AI bridges the gap between the broad capabilities of Large Language Models and the need for tailor-made specialised Small Language Models.
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The Top 12 Small Language Model Startups | Many businesses don't need huge proprietary Large Language Models (LLMs) for the vast majority of their use cases. Small Language Models (SLMs) are less resource-intensive than LLMs (like GPT-4) and offer several advantages: 💸 Cost-effectiveness ⏱ Faster deployment times, and 💻 Reduced computational requirements. S/O to Adya Pandey, Intelligence Analyst at CB Insights for her recent 2Q24 State of AI presentation | | #genai #ai #generativeai #artificialintelligence #business #ceo #technology | Hugging Face Sakana AI Sarvam AI Predibase Arcee.ai Nomic AI PremAI Malted AI Argilla Nous Research Claro AI Glaive |