Open source models will continue to grow in popularity. Small Language Models (SLMs) are smaller, faster to train with less compute. They can be used for tackling specific cases while being at a lower cost. Photo by Tobias Bjørkli via Pexels SLMs can be more efficient SLMs are faster in inference speed, and they also require less memory and storage. SLMs and cost Small Language models can run on less powerful machines, making them more affordable. This could be ideal for experimentation, startups and/or small size companies. Here is a short list Tiny Llama. The 1.1B parameters AI Model, trained on 3T Tokens. Microsoft’s Phi-2. The 2.7B parameters, trained on 1.4T tokens. Gemini Nano. The 6B parameters. Deepseek Coder
On this occasion we would like to present our take and summary about prompt engineering. Like everyone else, at Beolle we have been researching the AI space lately, running experiments. On this occasion, our investigation has made us present our take and summary about prompt engineering. ( Skip Ahead note : If you like to get right to it then skip to the section What are prompts .) Generated image with Microsoft Designer and DALL-E 3 + Modified by Beolle team (Parenthesis) AI has disrupted all industries, and it will continue to do so as we explore new territories. We are still in discovery mode. Sectors and industries are building their know-how, evolving and using this technology; determining the value it brings to the business. The investment by tech players and executives, in traditional and Gen AI (Generative AI) capabilities, continues rising. The consequence has been an accelerated growth in a short matter of time. Venture capital investment in AI has grown 13x over the las