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Tech companies have been caught up in a race to build the biggest large language models (LLMs). In April, for example, Meta announced the 400-billion-parameter Llama 3, which contains twice the number of parameters—or variables that determine how the model responds to queries—than OpenAI’s original ChatGPT model from 2022. Although not confirmed, GPT-4 is estimated to have about 1.8 trillion parameters.In the last few months, however, some of the largest tech companies, including Apple and Microsoft, have introduced small language models (SLMs). These models are a fraction of the size of their LLM counterparts and yet, on many benchmarks, c...... Read Full article on HadNews

Since ChatGPT dropped in the fall of 2022, everyone and their donkey has tried their hand at prompt engineering—finding a clever way to phrase your query to a large-language model (LLM) or AI art or video generator to get the best results or side-step protections. The internet is replete with prompt engineering guides, cheat sheets and advice threads to help you get the most out of an LLM.In the commercial sector, companies are now wrangling LLMs to build product co-pilots, automate tedious work, create personal assistants, and more, says Austin Henley, a former Microsoft employee who conducted a series of interviews with people developing L...... Read Full article on HadNews